diff --git a/.cspell.json b/.cspell.json index c3afe17698a6f..94b509370e688 100644 --- a/.cspell.json +++ b/.cspell.json @@ -1,5 +1,8 @@ { - "ignorePaths": ["perception/bytetrack/lib/**"], + "ignorePaths": [ + "perception/bytetrack/lib/**", + "planning/behavior_velocity_intersection_module/scripts/**" + ], "ignoreRegExpList": [], - "words": ["dltype", "tvmgen"] + "words": ["dltype", "tvmgen", "fromarray"] } diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index a6cdc58f03e94..dc745760cb7d0 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -4,7 +4,7 @@ common/autoware_auto_common/** opensource@apex.ai satoshi.ota@tier4.jp shumpei.w common/autoware_auto_geometry/** satoshi.ota@tier4.jp common/autoware_auto_perception_rviz_plugin/** opensource@apex.ai satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taiki.tanaka@tier4.jp takeshi.miura@tier4.jp yoshi.ri@tier4.jp common/autoware_auto_tf2/** jit.ray.c@gmail.com satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomoya.kimura@tier4.jp -common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/** team-spatzenhirn@uni-ulm.de +common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/** ahmed.ebrahim@leodrive.ai common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/** khalil@leodrive.ai common/autoware_point_types/** taichi.higashide@tier4.jp common/autoware_testing/** adam.dabrowski@robotec.ai satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomoya.kimura@tier4.jp @@ -45,7 +45,7 @@ common/tier4_localization_rviz_plugin/** isamu.takagi@tier4.jp takamasa.horibe@t common/tier4_logging_level_configure_rviz_plugin/** kosuke.takeuchi@tier4.jp satoshi.ota@tier4.jp takamasa.horibe@tier4.jp common/tier4_perception_rviz_plugin/** yukihiro.saito@tier4.jp common/tier4_planning_rviz_plugin/** takayuki.murooka@tier4.jp yukihiro.saito@tier4.jp -common/tier4_screen_capture_rviz_plugin/** taiki.tanaka@tier4.jp +common/tier4_screen_capture_rviz_plugin/** kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp taiki.tanaka@tier4.jp common/tier4_simulated_clock_rviz_plugin/** maxime.clement@tier4.jp common/tier4_state_rviz_plugin/** hiroki.ota@tier4.jp isamu.takagi@tier4.jp common/tier4_system_rviz_plugin/** koji.minoda@tier4.jp @@ -72,12 +72,12 @@ control/shift_decider/** takamasa.horibe@tier4.jp control/trajectory_follower_base/** takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp control/trajectory_follower_node/** takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp control/vehicle_cmd_gate/** takamasa.horibe@tier4.jp tomoya.kimura@tier4.jp +evaluator/control_evaluator/** daniel.sanchez@tier4.jp takayuki.murooka@tier4.jp evaluator/diagnostic_converter/** kyoichi.sugahara@tier4.jp maxime.clement@tier4.jp takamasa.horibe@tier4.jp evaluator/kinematic_evaluator/** dominik.jargot@robotec.ai fumiya.watanabe@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp evaluator/localization_evaluator/** dominik.jargot@robotec.ai koji.minoda@tier4.jp evaluator/perception_online_evaluator/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp kotaro.uetake@tier4.jp kyoichi.sugahara@tier4.jp shunsuke.miura@tier4.jp yoshi.ri@tier4.jp evaluator/planning_evaluator/** kyoichi.sugahara@tier4.jp maxime.clement@tier4.jp -evaluator/tier4_metrics_rviz_plugin/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp kyoichi.sugahara@tier4.jp maxime.clement@tier4.jp satoshi.ota@tier4.jp launch/tier4_autoware_api_launch/** isamu.takagi@tier4.jp ryohsuke.mitsudome@tier4.jp launch/tier4_control_launch/** takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp launch/tier4_localization_launch/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp @@ -88,6 +88,7 @@ launch/tier4_sensing_launch/** yukihiro.saito@tier4.jp launch/tier4_simulator_launch/** keisuke.shima@tier4.jp taiki.tanaka@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp launch/tier4_system_launch/** fumihito.ito@tier4.jp tetsuhiro.kawaguchi@tier4.jp launch/tier4_vehicle_launch/** yukihiro.saito@tier4.jp +localization/autoware_pose_covariance_modifier/** melike@leodrive.ai localization/ekf_localizer/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp takamasa.horibe@tier4.jp takeshi.ishita@tier4.jp yamato.ando@tier4.jp localization/geo_pose_projector/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp localization/gyro_odometer/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp @@ -113,26 +114,26 @@ map/map_loader/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@ti map/map_projection_loader/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp map/map_tf_generator/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp map/util/lanelet2_map_preprocessor/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp masahiro.sakamoto@tier4.jp ryohsuke.mitsudome@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp -perception/bytetrack/** manato.hirabayashi@tier4.jp +perception/bytetrack/** manato.hirabayashi@tier4.jp yoshi.ri@tier4.jp perception/cluster_merger/** dai.nguyen@tier4.jp shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp perception/compare_map_segmentation/** abrahammonrroy@yahoo.com dai.nguyen@tier4.jp yukihiro.saito@tier4.jp perception/crosswalk_traffic_light_estimator/** satoshi.ota@tier4.jp shunsuke.miura@tier4.jp tao.zhong@tier4.jp perception/detected_object_feature_remover/** tomoya.kimura@tier4.jp -perception/detected_object_validation/** dai.nguyen@tier4.jp shintaro.tomie@tier4.jp shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp +perception/detected_object_validation/** dai.nguyen@tier4.jp shintaro.tomie@tier4.jp shunsuke.miura@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/detection_by_tracker/** taekjin.lee@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/elevation_map_loader/** kosuke.takeuchi@tier4.jp shintaro.tomie@tier4.jp taichi.higashide@tier4.jp perception/euclidean_cluster/** dai.nguyen@tier4.jp yukihiro.saito@tier4.jp -perception/ground_segmentation/** abrahammonrroy@yahoo.com dai.nguyen@tier4.jp shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp +perception/ground_segmentation/** abrahammonrroy@yahoo.com dai.nguyen@tier4.jp shunsuke.miura@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/image_projection_based_fusion/** dai.nguyen@tier4.jp koji.minoda@tier4.jp kotaro.uetake@tier4.jp shunsuke.miura@tier4.jp tao.zhong@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/lidar_apollo_instance_segmentation/** yukihiro.saito@tier4.jp perception/lidar_apollo_segmentation_tvm/** ambroise.vincent@arm.com xinyu.wang@tier4.jp perception/lidar_apollo_segmentation_tvm_nodes/** ambroise.vincent@arm.com xinyu.wang@tier4.jp perception/lidar_centerpoint/** kenzo.lobos@tier4.jp koji.minoda@tier4.jp perception/lidar_centerpoint_tvm/** carl.liu@autocore.ai xinyu.wang@tier4.jp -perception/map_based_prediction/** kotaro.uetake@tier4.jp kyoichi.sugahara@tier4.jp shunsuke.miura@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp yoshi.ri@tier4.jp +perception/map_based_prediction/** kotaro.uetake@tier4.jp kyoichi.sugahara@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp yoshi.ri@tier4.jp perception/multi_object_tracker/** taekjin.lee@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/object_merger/** taekjin.lee@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp -perception/object_range_splitter/** yukihiro.saito@tier4.jp +perception/object_range_splitter/** yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/object_velocity_splitter/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp yoshi.ri@tier4.jp perception/occupancy_grid_map_outlier_filter/** abrahammonrroy@yahoo.com yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/probabilistic_occupancy_grid_map/** mamoru.sobue@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp @@ -141,26 +142,28 @@ perception/radar_fusion_to_detected_object/** satoshi.tanaka@tier4.jp shunsuke.m perception/radar_object_clustering/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp perception/radar_object_tracker/** satoshi.tanaka@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/radar_tracks_msgs_converter/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp +perception/raindrop_cluster_filter/** dai.nguyen@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/shape_estimation/** yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/simple_object_merger/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp yoshi.ri@tier4.jp perception/tensorrt_classifier/** kotaro.uetake@tier4.jp shunsuke.miura@tier4.jp perception/tensorrt_yolox/** dan.umeda@tier4.jp manato.hirabayashi@tier4.jp perception/tracking_object_merger/** taekjin.lee@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp perception/traffic_light_arbiter/** kenzo.lobos@tier4.jp shunsuke.miura@tier4.jp -perception/traffic_light_classifier/** shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp +perception/traffic_light_classifier/** shunsuke.miura@tier4.jp tao.zhong@tier4.jp yukihiro.saito@tier4.jp perception/traffic_light_fine_detector/** shintaro.tomie@tier4.jp shunsuke.miura@tier4.jp tao.zhong@tier4.jp -perception/traffic_light_map_based_detector/** shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp +perception/traffic_light_map_based_detector/** shunsuke.miura@tier4.jp tao.zhong@tier4.jp yukihiro.saito@tier4.jp perception/traffic_light_multi_camera_fusion/** shunsuke.miura@tier4.jp tao.zhong@tier4.jp perception/traffic_light_occlusion_predictor/** shunsuke.miura@tier4.jp tao.zhong@tier4.jp -perception/traffic_light_visualization/** yukihiro.saito@tier4.jp +perception/traffic_light_visualization/** tao.zhong@tier4.jp yukihiro.saito@tier4.jp +planning/autoware_remaining_distance_time_calculator/** ahmed.ebrahim@leodrive.ai planning/behavior_path_avoidance_by_lane_change_module/** fumiya.watanabe@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp -planning/behavior_path_avoidance_module/** fumiya.watanabe@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp +planning/behavior_path_avoidance_module/** fumiya.watanabe@tier4.jp go.sakayori@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp planning/behavior_path_dynamic_avoidance_module/** kosuke.takeuchi@tier4.jp satoshi.ota@tier4.jp takayuki.murooka@tier4.jp yuki.takagi@tier4.jp planning/behavior_path_external_request_lane_change_module/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp planning/behavior_path_goal_planner_module/** daniel.sanchez@tier4.jp kosuke.takeuchi@tier4.jp kyoichi.sugahara@tier4.jp mamoru.sobue@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp planning/behavior_path_lane_change_module/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp -planning/behavior_path_planner/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp -planning/behavior_path_planner_common/** daniel.sanchez@tier4.jp fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp mamoru.sobue@tier4.jp maxime.clement@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp +planning/behavior_path_planner/** fumiya.watanabe@tier4.jp go.sakayori@tier4.jp kosuke.takeuchi@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp +planning/behavior_path_planner_common/** daniel.sanchez@tier4.jp fumiya.watanabe@tier4.jp go.sakayori@tier4.jp kosuke.takeuchi@tier4.jp mamoru.sobue@tier4.jp maxime.clement@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp takamasa.horibe@tier4.jp takayuki.murooka@tier4.jp tomoya.kimura@tier4.jp zulfaqar.azmi@tier4.jp planning/behavior_path_sampling_planner_module/** daniel.sanchez@tier4.jp maxime.clement@tier4.jp planning/behavior_path_side_shift_module/** fumiya.watanabe@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp planning/behavior_path_start_planner_module/** daniel.sanchez@tier4.jp kosuke.takeuchi@tier4.jp kyoichi.sugahara@tier4.jp mamoru.sobue@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp tomohito.ando@tier4.jp tomoya.kimura@tier4.jp @@ -197,7 +200,7 @@ planning/path_smoother/** maxime.clement@tier4.jp takayuki.murooka@tier4.jp planning/planning_test_utils/** kyoichi.sugahara@tier4.jp takamasa.horibe@tier4.jp planning/planning_topic_converter/** kosuke.takeuchi@tier4.jp satoshi.ota@tier4.jp shumpei.wakabayashi@tier4.jp planning/planning_validator/** kosuke.takeuchi@tier4.jp takamasa.horibe@tier4.jp -planning/route_handler/** fumiya.watanabe@tier4.jp kosuke.takeuchi@tier4.jp mamoru.sobue@tier4.jp takayuki.murooka@tier4.jp zulfaqar.azmi@tier4.jp +planning/route_handler/** fumiya.watanabe@tier4.jp go.sakayori@tier4.jp kosuke.takeuchi@tier4.jp mamoru.sobue@tier4.jp takayuki.murooka@tier4.jp zulfaqar.azmi@tier4.jp planning/rtc_interface/** fumiya.watanabe@tier4.jp kyoichi.sugahara@tier4.jp satoshi.ota@tier4.jp taiki.tanaka@tier4.jp planning/rtc_replayer/** fumiya.watanabe@tier4.jp taiki.tanaka@tier4.jp planning/sampling_based_planner/bezier_sampler/** maxime.clement@tier4.jp @@ -208,11 +211,11 @@ planning/scenario_selector/** fumiya.watanabe@tier4.jp satoshi.ota@tier4.jp shum planning/static_centerline_generator/** kosuke.takeuchi@tier4.jp takayuki.murooka@tier4.jp planning/surround_obstacle_checker/** satoshi.ota@tier4.jp sensing/gnss_poser/** anh.nguyen.2@tier4.jp kento.yabuuchi.2@tier4.jp koji.minoda@tier4.jp masahiro.sakamoto@tier4.jp ryu.yamamoto@tier4.jp shintaro.sakoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp -sensing/image_diagnostics/** dai.nguyen@tier4.jp -sensing/image_transport_decompressor/** yukihiro.saito@tier4.jp +sensing/image_diagnostics/** dai.nguyen@tier4.jp yoshi.ri@tier4.jp +sensing/image_transport_decompressor/** kenzo.lobos@tier4.jp yukihiro.saito@tier4.jp sensing/imu_corrector/** koji.minoda@tier4.jp taiki.yamada@tier4.jp yamato.ando@tier4.jp -sensing/livox/livox_tag_filter/** ryohsuke.mitsudome@tier4.jp -sensing/pointcloud_preprocessor/** abrahammonrroy@yahoo.com dai.nguyen@tier4.jp kyoichi.sugahara@tier4.jp shunsuke.miura@tier4.jp yukihiro.saito@tier4.jp +sensing/livox/livox_tag_filter/** kenzo.lobos@tier4.jp ryohsuke.mitsudome@tier4.jp +sensing/pointcloud_preprocessor/** abrahammonrroy@yahoo.com dai.nguyen@tier4.jp kenzo.lobos@tier4.jp kyoichi.sugahara@tier4.jp shunsuke.miura@tier4.jp yihsiang.fang@tier4.jp yoshi.ri@tier4.jp yukihiro.saito@tier4.jp sensing/radar_scan_to_pointcloud2/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp sensing/radar_static_pointcloud_filter/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp sensing/radar_threshold_filter/** satoshi.tanaka@tier4.jp shunsuke.miura@tier4.jp taekjin.lee@tier4.jp yoshi.ri@tier4.jp @@ -221,7 +224,9 @@ sensing/tier4_pcl_extensions/** david.wong@tier4.jp kenzo.lobos@tier4.jp ryu.yam sensing/vehicle_velocity_converter/** ryu.yamamoto@tier4.jp simulator/dummy_perception_publisher/** yukihiro.saito@tier4.jp simulator/fault_injection/** keisuke.shima@tier4.jp +simulator/learning_based_vehicle_model/** maxime.clement@tier4.jp nagy.tomas@tier4.jp simulator/simple_planning_simulator/** takamasa.horibe@tier4.jp tomoya.kimura@tier4.jp +simulator/vehicle_door_simulator/** isamu.takagi@tier4.jp system/autoware_auto_msgs_adapter/** isamu.takagi@tier4.jp mfc@leodrive.ai system/bluetooth_monitor/** fumihito.ito@tier4.jp system/component_state_monitor/** isamu.takagi@tier4.jp @@ -230,6 +235,7 @@ system/default_ad_api_helpers/ad_api_adaptors/** isamu.takagi@tier4.jp ryohsuke. system/default_ad_api_helpers/ad_api_visualizers/** isamu.takagi@tier4.jp ryohsuke.mitsudome@tier4.jp yukihiro.saito@tier4.jp system/default_ad_api_helpers/automatic_pose_initializer/** isamu.takagi@tier4.jp ryohsuke.mitsudome@tier4.jp yukihiro.saito@tier4.jp system/diagnostic_graph_aggregator/** isamu.takagi@tier4.jp +system/diagnostic_graph_utils/** isamu.takagi@tier4.jp system/dummy_diag_publisher/** fumihito.ito@tier4.jp tetsuhiro.kawaguchi@tier4.jp system/dummy_infrastructure/** ryohsuke.mitsudome@tier4.jp system/duplicated_node_checker/** mamoru.sobue@tier4.jp shumpei.wakabayashi@tier4.jp uken.ryu@tier4.jp @@ -238,6 +244,7 @@ system/hazard_status_converter/** isamu.takagi@tier4.jp system/mrm_comfortable_stop_operator/** makoto.kurihara@tier4.jp tomohito.ando@tier4.jp system/mrm_emergency_stop_operator/** makoto.kurihara@tier4.jp tomohito.ando@tier4.jp system/mrm_handler/** makoto.kurihara@tier4.jp ryuta.kambe@tier4.jp tetsuhiro.kawaguchi@tier4.jp +system/system_diagnostic_monitor/** isamu.takagi@tier4.jp system/system_error_monitor/** fumihito.ito@tier4.jp system/system_monitor/** fumihito.ito@tier4.jp tetsuhiro.kawaguchi@tier4.jp system/topic_state_monitor/** ryohsuke.mitsudome@tier4.jp diff --git a/.github/PULL_REQUEST_TEMPLATE/small-change.md b/.github/PULL_REQUEST_TEMPLATE/small-change.md index 2ff933c43a349..e15fdd992d114 100644 --- a/.github/PULL_REQUEST_TEMPLATE/small-change.md +++ b/.github/PULL_REQUEST_TEMPLATE/small-change.md @@ -15,6 +15,10 @@ Not applicable. Not applicable. +## Interface changes + + + ## Pre-review checklist for the PR author The PR author **must** check the checkboxes below when creating the PR. diff --git a/.github/PULL_REQUEST_TEMPLATE/standard-change.md b/.github/PULL_REQUEST_TEMPLATE/standard-change.md index 7aedefd0a7bf1..391af629751e0 100644 --- a/.github/PULL_REQUEST_TEMPLATE/standard-change.md +++ b/.github/PULL_REQUEST_TEMPLATE/standard-change.md @@ -18,6 +18,19 @@ +### ROS Topic Changes + + + + + + +### ROS Parameter Changes + + + + + ## Effects on system behavior diff --git a/.github/workflows/build-and-test-arm64.yaml b/.github/workflows/build-and-test-arm64.yaml index 932c15d27b05f..a5e00496cc50a 100644 --- a/.github/workflows/build-and-test-arm64.yaml +++ b/.github/workflows/build-and-test-arm64.yaml @@ -23,7 +23,7 @@ jobs: build-depends-repos: build_depends.repos steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Show disk space before the tasks run: df -h diff --git a/.github/workflows/build-and-test-differential-arm64.yaml b/.github/workflows/build-and-test-differential-arm64.yaml index f742dedcf0b89..bd422af46bc4d 100644 --- a/.github/workflows/build-and-test-differential-arm64.yaml +++ b/.github/workflows/build-and-test-differential-arm64.yaml @@ -33,7 +33,7 @@ jobs: build-depends-repos: build_depends.repos steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 0 diff --git a/.github/workflows/build-and-test-differential.yaml b/.github/workflows/build-and-test-differential.yaml index 0e759fe47630b..3ad7b6d434f33 100644 --- a/.github/workflows/build-and-test-differential.yaml +++ b/.github/workflows/build-and-test-differential.yaml @@ -32,7 +32,7 @@ jobs: build-depends-repos: build_depends.repos steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 0 @@ -80,7 +80,7 @@ jobs: container: ghcr.io/autowarefoundation/autoware-openadk:latest-prebuilt-cuda steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 0 diff --git a/.github/workflows/build-and-test.yaml b/.github/workflows/build-and-test.yaml index 49e1c979928ad..520c2cb9983b0 100644 --- a/.github/workflows/build-and-test.yaml +++ b/.github/workflows/build-and-test.yaml @@ -25,7 +25,7 @@ jobs: build-depends-repos: build_depends.repos steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Show disk space before the tasks run: df -h diff --git a/.github/workflows/check-build-depends.yaml b/.github/workflows/check-build-depends.yaml index 81618a1db0eea..c790c2132d71e 100644 --- a/.github/workflows/check-build-depends.yaml +++ b/.github/workflows/check-build-depends.yaml @@ -20,7 +20,7 @@ jobs: build-depends-repos: build_depends.repos steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Remove exec_depend uses: autowarefoundation/autoware-github-actions/remove-exec-depend@v1 diff --git a/.github/workflows/clang-tidy-pr-comments-manually.yaml b/.github/workflows/clang-tidy-pr-comments-manually.yaml index 9bccd972becde..87f939fe8b72f 100644 --- a/.github/workflows/clang-tidy-pr-comments-manually.yaml +++ b/.github/workflows/clang-tidy-pr-comments-manually.yaml @@ -11,7 +11,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Download analysis results run: | @@ -36,7 +36,7 @@ jobs: - name: Check out PR head if: ${{ steps.check-fixes-yaml-existence.outputs.exists == 'true' }} - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: repository: ${{ steps.set-variables.outputs.pr-head-repo }} ref: ${{ steps.set-variables.outputs.pr-head-ref }} diff --git a/.github/workflows/clang-tidy-pr-comments.yaml b/.github/workflows/clang-tidy-pr-comments.yaml index baaa0fb8e7744..0f6db69dfedd4 100644 --- a/.github/workflows/clang-tidy-pr-comments.yaml +++ b/.github/workflows/clang-tidy-pr-comments.yaml @@ -13,7 +13,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Download analysis results run: | @@ -37,7 +37,7 @@ jobs: - name: Check out PR head if: ${{ steps.check-fixes-yaml-existence.outputs.exists == 'true' }} - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: repository: ${{ steps.set-variables.outputs.pr-head-repo }} ref: ${{ steps.set-variables.outputs.pr-head-ref }} diff --git a/.github/workflows/delete-closed-pr-docs.yaml b/.github/workflows/delete-closed-pr-docs.yaml index b7b009fb00263..eb211766c49dd 100644 --- a/.github/workflows/delete-closed-pr-docs.yaml +++ b/.github/workflows/delete-closed-pr-docs.yaml @@ -10,7 +10,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 0 diff --git a/.github/workflows/deploy-docs.yaml b/.github/workflows/deploy-docs.yaml index b48d70dbacb0c..e5967b0d50c67 100644 --- a/.github/workflows/deploy-docs.yaml +++ b/.github/workflows/deploy-docs.yaml @@ -30,7 +30,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 with: fetch-depth: 0 ref: ${{ github.event.pull_request.head.sha }} diff --git a/.github/workflows/json-schema-check.yaml b/.github/workflows/json-schema-check.yaml index 77ce4576b4952..5c223edf1eec2 100644 --- a/.github/workflows/json-schema-check.yaml +++ b/.github/workflows/json-schema-check.yaml @@ -10,7 +10,7 @@ jobs: outputs: run-check: ${{ steps.paths_filter.outputs.json_or_yaml }} steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - uses: dorny/paths-filter@v3 id: paths_filter with: @@ -25,7 +25,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Check out repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 - name: Run json-schema-check uses: autowarefoundation/autoware-github-actions/json-schema-check@v1 diff --git a/build_depends.repos b/build_depends.repos index f7b3f12484015..32854cc34e362 100644 --- a/build_depends.repos +++ b/build_depends.repos @@ -41,3 +41,7 @@ repositories: type: git url: https://github.com/MORAI-Autonomous/MORAI-ROS2_morai_msgs.git version: main + universe/external/glog: # TODO: to use isGoogleInitialized() API in v0.6.0. Remove when the rosdep glog version is updated to v0.6.0 (already updated in Ubuntu 24.04) + type: git + url: https://github.com/tier4/glog.git + version: v0.6.0_t4-ros diff --git a/common/autoware_auto_common/include/autoware_auto_common/common/types.hpp b/common/autoware_auto_common/include/autoware_auto_common/common/types.hpp index 1c7dfe48c7ec8..83b8287ff60d4 100644 --- a/common/autoware_auto_common/include/autoware_auto_common/common/types.hpp +++ b/common/autoware_auto_common/include/autoware_auto_common/common/types.hpp @@ -37,7 +37,9 @@ namespace types // We don't currently require code to comply to MISRA, but we should try to where it is // easily possible. using bool8_t = bool; +#if __cplusplus < 201811L || !__cpp_char8_t using char8_t = char; +#endif using uchar8_t = unsigned char; // If we ever compile on a platform where this is not true, float32_t and float64_t definitions // need to be adjusted. diff --git a/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_detail.hpp b/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_detail.hpp index 8c6ade475217a..4f545d194b2c2 100644 --- a/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_detail.hpp +++ b/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_detail.hpp @@ -57,6 +57,9 @@ struct ObjectPropertyValues float alpha{0.999F}; }; +// Control object marker visualization +enum class ObjectFillType { Skeleton, Fill }; + // Map defining colors according to value of label field in ObjectClassification msg const std::map< autoware_auto_perception_msgs::msg::ObjectClassification::_label_type, ObjectPropertyValues> @@ -87,7 +90,8 @@ get_shape_marker_ptr( const autoware_auto_perception_msgs::msg::Shape & shape_msg, const geometry_msgs::msg::Point & centroid, const geometry_msgs::msg::Quaternion & orientation, const std_msgs::msg::ColorRGBA & color_rgba, const double & line_width, - const bool & is_orientation_available = true); + const bool & is_orientation_available = true, + const ObjectFillType fill_type = ObjectFillType::Skeleton); AUTOWARE_AUTO_PERCEPTION_RVIZ_PLUGIN_PUBLIC visualization_msgs::msg::Marker::SharedPtr get_2d_shape_marker_ptr( diff --git a/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_display_base.hpp b/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_display_base.hpp index 4290fdff49bb3..1093f6e4f2414 100644 --- a/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_display_base.hpp +++ b/common/autoware_auto_perception_rviz_plugin/include/autoware_auto_perception_rviz_plugin/object_detection/object_polygon_display_base.hpp @@ -112,6 +112,12 @@ class AUTOWARE_AUTO_PERCEPTION_RVIZ_PLUGIN_PUBLIC ObjectPolygonDisplayBase m_confidence_interval_property->addOption("95%", 2); m_confidence_interval_property->addOption("99%", 3); + m_object_fill_type_property = new rviz_common::properties::EnumProperty( + "Object Fill Type", "skeleton", "Change object fill type in visualization", this); + m_object_fill_type_property->addOption( + "skeleton", static_cast(detail::ObjectFillType::Skeleton)); + m_object_fill_type_property->addOption("Fill", static_cast(detail::ObjectFillType::Fill)); + // iterate over default values to create and initialize the properties. for (const auto & map_property_it : detail::kDefaultObjectPropertyValues) { const auto & class_property_values = map_property_it.second; @@ -189,9 +195,13 @@ class AUTOWARE_AUTO_PERCEPTION_RVIZ_PLUGIN_PUBLIC ObjectPolygonDisplayBase const bool & is_orientation_available) const { const std_msgs::msg::ColorRGBA color_rgba = get_color_rgba(labels); + const auto fill_type = + static_cast(m_object_fill_type_property->getOptionInt()); + if (m_display_type_property->getOptionInt() == 0) { return detail::get_shape_marker_ptr( - shape_msg, centroid, orientation, color_rgba, line_width, is_orientation_available); + shape_msg, centroid, orientation, color_rgba, line_width, is_orientation_available, + fill_type); } else if (m_display_type_property->getOptionInt() == 1) { return detail::get_2d_shape_marker_ptr( shape_msg, centroid, orientation, color_rgba, line_width, is_orientation_available); @@ -526,6 +536,8 @@ class AUTOWARE_AUTO_PERCEPTION_RVIZ_PLUGIN_PUBLIC ObjectPolygonDisplayBase rviz_common::properties::EnumProperty * m_simple_visualize_mode_property; // Property to set confidence interval of state estimations rviz_common::properties::EnumProperty * m_confidence_interval_property; + // Property to set visualization type + rviz_common::properties::EnumProperty * m_object_fill_type_property; // Property to enable/disable label visualization rviz_common::properties::BoolProperty m_display_label_property; // Property to enable/disable uuid visualization diff --git a/common/autoware_auto_perception_rviz_plugin/src/object_detection/object_polygon_detail.cpp b/common/autoware_auto_perception_rviz_plugin/src/object_detection/object_polygon_detail.cpp index 8be9d1c01332e..7631acffafdf9 100644 --- a/common/autoware_auto_perception_rviz_plugin/src/object_detection/object_polygon_detail.cpp +++ b/common/autoware_auto_perception_rviz_plugin/src/object_detection/object_polygon_detail.cpp @@ -495,23 +495,37 @@ visualization_msgs::msg::Marker::SharedPtr get_shape_marker_ptr( const autoware_auto_perception_msgs::msg::Shape & shape_msg, const geometry_msgs::msg::Point & centroid, const geometry_msgs::msg::Quaternion & orientation, const std_msgs::msg::ColorRGBA & color_rgba, const double & line_width, - const bool & is_orientation_available) + const bool & is_orientation_available, const ObjectFillType fill_type) { auto marker_ptr = std::make_shared(); marker_ptr->ns = std::string("shape"); + marker_ptr->color = color_rgba; + marker_ptr->scale.x = line_width; using autoware_auto_perception_msgs::msg::Shape; if (shape_msg.type == Shape::BOUNDING_BOX) { - marker_ptr->type = visualization_msgs::msg::Marker::LINE_LIST; - calc_bounding_box_line_list(shape_msg, marker_ptr->points); + if (fill_type == ObjectFillType::Skeleton) { + marker_ptr->type = visualization_msgs::msg::Marker::LINE_LIST; + calc_bounding_box_line_list(shape_msg, marker_ptr->points); + } else if (fill_type == ObjectFillType::Fill) { + marker_ptr->type = visualization_msgs::msg::Marker::CUBE; + marker_ptr->scale = shape_msg.dimensions; + marker_ptr->color.a = 0.75f; + } if (is_orientation_available) { calc_bounding_box_direction_line_list(shape_msg, marker_ptr->points); } else { calc_bounding_box_orientation_line_list(shape_msg, marker_ptr->points); } } else if (shape_msg.type == Shape::CYLINDER) { - marker_ptr->type = visualization_msgs::msg::Marker::LINE_LIST; - calc_cylinder_line_list(shape_msg, marker_ptr->points); + if (fill_type == ObjectFillType::Skeleton) { + marker_ptr->type = visualization_msgs::msg::Marker::LINE_LIST; + calc_cylinder_line_list(shape_msg, marker_ptr->points); + } else if (fill_type == ObjectFillType::Fill) { + marker_ptr->type = visualization_msgs::msg::Marker::CYLINDER; + marker_ptr->scale = shape_msg.dimensions; + marker_ptr->color.a = 0.75f; + } } else if (shape_msg.type == Shape::POLYGON) { marker_ptr->type = visualization_msgs::msg::Marker::LINE_LIST; calc_polygon_line_list(shape_msg, marker_ptr->points); @@ -523,8 +537,6 @@ visualization_msgs::msg::Marker::SharedPtr get_shape_marker_ptr( marker_ptr->action = visualization_msgs::msg::Marker::MODIFY; marker_ptr->pose = to_pose(centroid, orientation); marker_ptr->lifetime = rclcpp::Duration::from_seconds(0.15); - marker_ptr->scale.x = line_width; - marker_ptr->color = color_rgba; return marker_ptr; } diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/CMakeLists.txt b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/CMakeLists.txt new file mode 100644 index 0000000000000..8692ea1bb152a --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/CMakeLists.txt @@ -0,0 +1,108 @@ +cmake_minimum_required(VERSION 3.8) +project(autoware_mission_details_overlay_rviz_plugin) + +find_package(ament_cmake_auto REQUIRED) +ament_auto_find_build_dependencies() + +set( + headers_to_moc + include/mission_details_display.hpp +) + +set( + headers_to_not_moc + include/remaining_distance_time_display.hpp +) + +foreach(header "${headers_to_moc}") + qt5_wrap_cpp(display_moc_files "${header}") +endforeach() + +set( + display_source_files + src/overlay_utils.cpp + src/mission_details_display.cpp + src/remaining_distance_time_display.cpp +) + +add_library( + ${PROJECT_NAME} SHARED + ${display_moc_files} + ${headers_to_not_moc} + ${display_source_files} +) + +set_property(TARGET ${PROJECT_NAME} PROPERTY CXX_STANDARD 17) +target_compile_options(${PROJECT_NAME} PRIVATE -Wall -Wextra -Wpedantic) + +target_include_directories( + ${PROJECT_NAME} PUBLIC + $ + $ + ${Qt5Widgets_INCLUDE_DIRS} + ${OpenCV_INCLUDE_DIRS} +) + +target_link_libraries( + ${PROJECT_NAME} PUBLIC + rviz_ogre_vendor::OgreMain + rviz_ogre_vendor::OgreOverlay +) + +target_compile_definitions(${PROJECT_NAME} PRIVATE "${PROJECT_NAME}_BUILDING_LIBRARY") + +# prevent pluginlib from using boost +target_compile_definitions(${PROJECT_NAME} PUBLIC "PLUGINLIB__DISABLE_BOOST_FUNCTIONS") + +pluginlib_export_plugin_description_file(rviz_common plugins_description.xml) + +ament_target_dependencies( + ${PROJECT_NAME} + PUBLIC + rviz_common + rviz_rendering + autoware_internal_msgs +) + +ament_export_include_directories(include) +ament_export_targets(${PROJECT_NAME} HAS_LIBRARY_TARGET) +ament_export_dependencies( + rviz_common + rviz_ogre_vendor +) + +if(BUILD_TESTING) + find_package(ament_lint_auto REQUIRED) + ament_lint_auto_find_test_dependencies() +endif() + +install( + TARGETS ${PROJECT_NAME} + EXPORT ${PROJECT_NAME} + ARCHIVE DESTINATION lib + LIBRARY DESTINATION lib + RUNTIME DESTINATION bin + INCLUDES DESTINATION include +) + +install( + DIRECTORY include/ + DESTINATION include +) + +install( + TARGETS + DESTINATION lib/${PROJECT_NAME} +) + +# Copy the assets directory to the installation directory +install( + DIRECTORY assets/ + DESTINATION share/${PROJECT_NAME}/assets +) + +add_definitions(-DQT_NO_KEYWORDS) + +ament_package( + CONFIG_EXTRAS "autoware_mission_details_overlay_rviz_plugin-extras.cmake" +) diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/LICENSE b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/LICENSE new file mode 100644 index 0000000000000..a2fe2d3d1c7ed --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/LICENSE @@ -0,0 +1,12 @@ +Copyright (c) 2022, Team Spatzenhirn +Copyright (c) 2014, JSK Lab + +Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/README.md b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/README.md new file mode 100644 index 0000000000000..3a4040a7065d0 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/README.md @@ -0,0 +1,35 @@ +# autoware_mission_details_overlay_rviz_plugin + +This RViz plugin displays the remaining distance and time for the current mission. + +## Inputs / Outputs + +### Input + +| Name | Type | Description | +| ------------------------------------------- | ----------------------------------------------------------- | ---------------------------------------------------- | +| `/planning/mission_remaining_distance_time` | `autoware_planning_msgs::msg::MissionRemainingDistanceTime` | The topic is for mission remaining distance and time | + +## Overlay Parameters + +| Name | Type | Default Value | Description | +| -------- | ---- | ------------- | --------------------------------- | +| `Width` | int | 170 | Width of the overlay [px] | +| `Height` | int | 100 | Height of the overlay [px] | +| `Right` | int | 10 | Margin from the right border [px] | +| `Top` | int | 10 | Margin from the top border [px] | + +The mission details display is aligned with top right corner of the screen. + +## Usage + +Similar to [autoware_overlay_rviz_plugin](../autoware_overlay_rviz_plugin/README.md) + +## Credits + +Based on the [jsk_visualization](https://github.com/jsk-ros-pkg/jsk_visualization) package. + +### Icons + +- +- diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/av_timer.png b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/av_timer.png new file mode 100644 index 0000000000000..f7f5db1249511 Binary files /dev/null and b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/av_timer.png differ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/LICENSE b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/LICENSE new file mode 100644 index 0000000000000..cc04d393573f0 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/LICENSE @@ -0,0 +1,93 @@ +Copyright 2011 The Quicksand Project Authors (https://github.com/andrew-paglinawan/QuicksandFamily), with Reserved Font Name “Quicksand”. + +This Font Software is licensed under the SIL Open Font License, Version 1.1. +This license is copied below, and is also available with a FAQ at: +http://scripts.sil.org/OFL + + +----------------------------------------------------------- +SIL OPEN FONT LICENSE Version 1.1 - 26 February 2007 +----------------------------------------------------------- + +PREAMBLE +The goals of the Open Font License (OFL) are to stimulate worldwide +development of collaborative font projects, to support the font creation +efforts of academic and linguistic communities, and to provide a free and +open framework in which fonts may be shared and improved in partnership +with others. + +The OFL allows the licensed fonts to be used, studied, modified and +redistributed freely as long as they are not sold by themselves. The +fonts, including any derivative works, can be bundled, embedded, +redistributed and/or sold with any software provided that any reserved +names are not used by derivative works. The fonts and derivatives, +however, cannot be released under any other type of license. The +requirement for fonts to remain under this license does not apply +to any document created using the fonts or their derivatives. + +DEFINITIONS +"Font Software" refers to the set of files released by the Copyright +Holder(s) under this license and clearly marked as such. This may +include source files, build scripts and documentation. + +"Reserved Font Name" refers to any names specified as such after the +copyright statement(s). + +"Original Version" refers to the collection of Font Software components as +distributed by the Copyright Holder(s). + +"Modified Version" refers to any derivative made by adding to, deleting, +or substituting -- in part or in whole -- any of the components of the +Original Version, by changing formats or by porting the Font Software to a +new environment. + +"Author" refers to any designer, engineer, programmer, technical +writer or other person who contributed to the Font Software. + +PERMISSION & CONDITIONS +Permission is hereby granted, free of charge, to any person obtaining +a copy of the Font Software, to use, study, copy, merge, embed, modify, +redistribute, and sell modified and unmodified copies of the Font +Software, subject to the following conditions: + +1) Neither the Font Software nor any of its individual components, +in Original or Modified Versions, may be sold by itself. + +2) Original or Modified Versions of the Font Software may be bundled, +redistributed and/or sold with any software, provided that each copy +contains the above copyright notice and this license. These can be +included either as stand-alone text files, human-readable headers or +in the appropriate machine-readable metadata fields within text or +binary files as long as those fields can be easily viewed by the user. + +3) No Modified Version of the Font Software may use the Reserved Font +Name(s) unless explicit written permission is granted by the corresponding +Copyright Holder. This restriction only applies to the primary font name as +presented to the users. + +4) The name(s) of the Copyright Holder(s) or the Author(s) of the Font +Software shall not be used to promote, endorse or advertise any +Modified Version, except to acknowledge the contribution(s) of the +Copyright Holder(s) and the Author(s) or with their explicit written +permission. + +5) The Font Software, modified or unmodified, in part or in whole, +must be distributed entirely under this license, and must not be +distributed under any other license. The requirement for fonts to +remain under this license does not apply to any document created +using the Font Software. + +TERMINATION +This license becomes null and void if any of the above conditions are +not met. + +DISCLAIMER +THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT +OF COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE +COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL +DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM +OTHER DEALINGS IN THE FONT SOFTWARE. diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Bold.ttf b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Bold.ttf new file mode 100644 index 0000000000000..07d5127c04b17 Binary files /dev/null and b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Bold.ttf differ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Regular.ttf b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Regular.ttf new file mode 100644 index 0000000000000..60323ed6abdf1 Binary files /dev/null and b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/font/Quicksand/static/Quicksand-Regular.ttf differ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/path.png b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/path.png new file mode 100644 index 0000000000000..62af338b8c053 Binary files /dev/null and b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/assets/path.png differ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin-extras.cmake b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin-extras.cmake new file mode 100644 index 0000000000000..9d6f156555e57 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin-extras.cmake @@ -0,0 +1,31 @@ +# Copyright (c) 2021, Open Source Robotics Foundation, Inc. All rights reserved. +# +# Redistribution and use in source and binary forms, with or without +# modification, are permitted provided that the following conditions are met: +# +# * Redistributions of source code must retain the above copyright +# notice, this list of conditions and the following disclaimer. +# +# * Redistributions in binary form must reproduce the above copyright +# notice, this list of conditions and the following disclaimer in the +# documentation and/or other materials provided with the distribution. +# +# * Neither the name of the copyright holder nor the names of its +# contributors may be used to endorse or promote products derived from +# this software without specific prior written permission. +# +# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +# POSSIBILITY OF SUCH DAMAGE. + +# find package Qt5 because otherwise using the rviz_default_plugins::rviz_default_plugins +# exported target will complain that the Qt5::Widgets target does not exist +find_package(Qt5 REQUIRED QUIET COMPONENTS Widgets) diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/mission_details_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/mission_details_display.hpp new file mode 100644 index 0000000000000..ab5abfe3c3d83 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/mission_details_display.hpp @@ -0,0 +1,83 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef MISSION_DETAILS_DISPLAY_HPP_ +#define MISSION_DETAILS_DISPLAY_HPP_ +#ifndef Q_MOC_RUN +#include "overlay_utils.hpp" +#include "remaining_distance_time_display.hpp" + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include + +#include +#include +#endif + +namespace autoware::mission_details_overlay_rviz_plugin +{ +class MissionDetailsDisplay : public rviz_common::Display +{ + Q_OBJECT +public: + MissionDetailsDisplay(); + ~MissionDetailsDisplay() override; + +protected: + void onInitialize() override; + void update(float wall_dt, float ros_dt) override; + void reset() override; + void onEnable() override; + void onDisable() override; + +private Q_SLOTS: + void update_size(); + void topic_updated_remaining_distance_time(); + +private: + std::mutex mutex_; + autoware::mission_details_overlay_rviz_plugin::OverlayObject::SharedPtr overlay_; + rviz_common::properties::IntProperty * property_width_; + rviz_common::properties::IntProperty * property_height_; + rviz_common::properties::IntProperty * property_right_; + rviz_common::properties::IntProperty * property_top_; + std::unique_ptr + remaining_distance_time_topic_property_; + + void draw_rounded_rect(QPainter & painter, const QRectF & backgroundRect); + void setupRosSubscriptions(); + + std::unique_ptr remaining_distance_time_display_; + + rclcpp::Subscription::SharedPtr + remaining_distance_time_sub_; + + std::mutex property_mutex_; + + void cb_remaining_distance_time( + const autoware_internal_msgs::msg::MissionRemainingDistanceTime::ConstSharedPtr & msg); + void draw_widget(QImage & hud); +}; +} // namespace autoware::mission_details_overlay_rviz_plugin + +#endif // MISSION_DETAILS_DISPLAY_HPP_ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/overlay_utils.hpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/overlay_utils.hpp new file mode 100644 index 0000000000000..a0344f872f524 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/overlay_utils.hpp @@ -0,0 +1,131 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +// -*- mode: c++ -*- +/********************************************************************* + * Software License Agreement (BSD License) + * + * Copyright (c) 2022, Team Spatzenhirn + * Copyright (c) 2014, JSK Lab + * All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * * Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * * Redistributions in binary form must reproduce the above + * copyright notice, this list of conditions and the following + * disclaimer in the documentation and/o2r other materials provided + * with the distribution. + * * Neither the name of the JSK Lab nor the names of its + * contributors may be used to endorse or promote products derived + * from this software without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS + * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE + * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, + * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER + * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT + * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN + * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + * POSSIBILITY OF SUCH DAMAGE. + *********************************************************************/ + +#ifndef OVERLAY_UTILS_HPP_ +#define OVERLAY_UTILS_HPP_ + +#include +#include + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include + +namespace autoware::mission_details_overlay_rviz_plugin +{ +class OverlayObject; + +class ScopedPixelBuffer +{ +public: + explicit ScopedPixelBuffer(Ogre::HardwarePixelBufferSharedPtr pixel_buffer); + virtual ~ScopedPixelBuffer(); + virtual Ogre::HardwarePixelBufferSharedPtr getPixelBuffer(); + virtual QImage getQImage(unsigned int width, unsigned int height); + virtual QImage getQImage(OverlayObject & overlay); + virtual QImage getQImage(unsigned int width, unsigned int height, QColor & bg_color); + virtual QImage getQImage(OverlayObject & overlay, QColor & bg_color); + +protected: + Ogre::HardwarePixelBufferSharedPtr pixel_buffer_; +}; + +enum class VerticalAlignment : uint8_t { CENTER, TOP, BOTTOM }; + +enum class HorizontalAlignment : uint8_t { LEFT, RIGHT, CENTER }; + +/** + * Helper class for realizing an overlay object on top of the rviz 3D panel. + * + * This class is supposed to be instantiated in the onInitialize method of the + * rviz_common::Display class. + */ +class OverlayObject +{ +public: + using SharedPtr = std::shared_ptr; + + explicit OverlayObject(const std::string & name); + virtual ~OverlayObject(); + + virtual std::string getName() const; + virtual void hide(); + virtual void show(); + virtual bool isTextureReady() const; + virtual void updateTextureSize(unsigned int width, unsigned int height); + virtual ScopedPixelBuffer getBuffer(); + virtual void setPosition( + double hor_dist, double ver_dist, HorizontalAlignment hor_alignment = HorizontalAlignment::LEFT, + VerticalAlignment ver_alignment = VerticalAlignment::TOP); + virtual void setDimensions(double width, double height); + virtual bool isVisible() const; + virtual unsigned int getTextureWidth() const; + virtual unsigned int getTextureHeight() const; + +protected: + const std::string name_; + Ogre::Overlay * overlay_; + Ogre::PanelOverlayElement * panel_; + Ogre::MaterialPtr panel_material_; + Ogre::TexturePtr texture_; +}; +} // namespace autoware::mission_details_overlay_rviz_plugin + +#endif // OVERLAY_UTILS_HPP_ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/remaining_distance_time_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/remaining_distance_time_display.hpp new file mode 100644 index 0000000000000..843b75e352648 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/include/remaining_distance_time_display.hpp @@ -0,0 +1,57 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef REMAINING_DISTANCE_TIME_DISPLAY_HPP_ +#define REMAINING_DISTANCE_TIME_DISPLAY_HPP_ +#include "overlay_utils.hpp" + +#include +#include +#include +#include +#include +#include + +#include + +#include +#include +#include + +namespace autoware::mission_details_overlay_rviz_plugin +{ + +class RemainingDistanceTimeDisplay +{ +public: + RemainingDistanceTimeDisplay(); + void drawRemainingDistanceTimeDisplay(QPainter & painter, const QRectF & backgroundRect); + void updateRemainingDistanceTimeData( + const autoware_internal_msgs::msg::MissionRemainingDistanceTime::ConstSharedPtr & msg); + +private: + double remaining_distance_; // Internal variable to store remaining distance + double remaining_time_; // Internal variable to store remaining time + + QColor gray = QColor(194, 194, 194); + + QImage icon_dist_; + QImage icon_dist_scaled_; + QImage icon_time_; + QImage icon_time_scaled_; +}; + +} // namespace autoware::mission_details_overlay_rviz_plugin + +#endif // REMAINING_DISTANCE_TIME_DISPLAY_HPP_ diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/package.xml b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/package.xml new file mode 100644 index 0000000000000..1054ac4f516bd --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/package.xml @@ -0,0 +1,28 @@ + + + + autoware_mission_details_overlay_rviz_plugin + 0.0.1 + + RViz2 plugin for 2D overlays for mission details in the 3D view. Mainly a port of the JSK overlay plugin + (https://github.com/jsk-ros-pkg/jsk_visualization). + + Ahmed Ebrahim + + BSD-3-Clause + + autoware_internal_msgs + boost + rviz_common + rviz_ogre_vendor + rviz_rendering + + ament_lint_auto + autoware_lint_common + + ament_cmake_auto + + + ament_cmake + + diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/plugins_description.xml b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/plugins_description.xml new file mode 100644 index 0000000000000..5177b10859704 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/plugins_description.xml @@ -0,0 +1,5 @@ + + + Mission Details overlay plugin for the 3D view. + + diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/mission_details_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/mission_details_display.cpp new file mode 100644 index 0000000000000..bafae1727b2f1 --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/mission_details_display.cpp @@ -0,0 +1,212 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "mission_details_display.hpp" + +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include + +namespace autoware::mission_details_overlay_rviz_plugin +{ + +MissionDetailsDisplay::MissionDetailsDisplay() +{ + property_width_ = new rviz_common::properties::IntProperty( + "Width", 170, "Width of the overlay", this, SLOT(update_size())); + property_height_ = new rviz_common::properties::IntProperty( + "Height", 100, "Height of the overlay", this, SLOT(update_size())); + property_right_ = new rviz_common::properties::IntProperty( + "Right", 10, "Margin from the right border", this, SLOT(update_size())); + property_top_ = new rviz_common::properties::IntProperty( + "Top", 10, "Margin from the top border", this, SLOT(update_size())); + + // Initialize the component displays + remaining_distance_time_display_ = std::make_unique(); +} + +void MissionDetailsDisplay::onInitialize() +{ + std::lock_guard lock(property_mutex_); + + rviz_common::Display::onInitialize(); + rviz_rendering::RenderSystem::get()->prepareOverlays(scene_manager_); + static int count = 0; + std::stringstream ss; + ss << "MissionDetailsDisplay" << count++; + overlay_ = + std::make_shared(ss.str()); + overlay_->show(); + update_size(); + + auto rviz_ros_node = context_->getRosNodeAbstraction(); + + remaining_distance_time_topic_property_ = + std::make_unique( + "Remaining Distance and Time Topic", "/planning/mission_remaining_distance_time", + "autoware_internal_msgs/msg/MissionRemainingDistanceTime", + "Topic for Mission Remaining Distance and Time Data", this, + SLOT(topic_updated_remaining_distance_time())); + remaining_distance_time_topic_property_->initialize(rviz_ros_node); +} + +void MissionDetailsDisplay::setupRosSubscriptions() +{ + // Don't create a node, just use the one from the parent class + auto rviz_node_ = context_->getRosNodeAbstraction().lock()->get_raw_node(); + + remaining_distance_time_sub_ = + rviz_node_->create_subscription( + remaining_distance_time_topic_property_->getTopicStd(), + rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + [this](const autoware_internal_msgs::msg::MissionRemainingDistanceTime::SharedPtr msg) { + cb_remaining_distance_time(msg); + }); +} + +MissionDetailsDisplay::~MissionDetailsDisplay() +{ + std::lock_guard lock(property_mutex_); + overlay_.reset(); + + remaining_distance_time_sub_.reset(); + remaining_distance_time_display_.reset(); + remaining_distance_time_topic_property_.reset(); +} + +// mark maybe unused +void MissionDetailsDisplay::update(float wall_dt, float ros_dt) +{ + (void)wall_dt; // Mark as unused + (void)ros_dt; // Mark as unused + + if (!overlay_) { + return; + } + autoware::mission_details_overlay_rviz_plugin::ScopedPixelBuffer buffer = overlay_->getBuffer(); + QImage hud = buffer.getQImage(*overlay_); + hud.fill(Qt::transparent); + draw_widget(hud); +} + +void MissionDetailsDisplay::onEnable() +{ + std::lock_guard lock(property_mutex_); + if (overlay_) { + overlay_->show(); + } + setupRosSubscriptions(); +} + +void MissionDetailsDisplay::onDisable() +{ + std::lock_guard lock(property_mutex_); + + remaining_distance_time_sub_.reset(); + + if (overlay_) { + overlay_->hide(); + } +} + +void MissionDetailsDisplay::cb_remaining_distance_time( + const autoware_internal_msgs::msg::MissionRemainingDistanceTime::ConstSharedPtr & msg) +{ + std::lock_guard lock(property_mutex_); + + if (remaining_distance_time_display_) { + remaining_distance_time_display_->updateRemainingDistanceTimeData(msg); + queueRender(); + } +} + +void MissionDetailsDisplay::draw_widget(QImage & hud) +{ + std::lock_guard lock(property_mutex_); + + if (!overlay_->isVisible()) { + return; + } + + QPainter painter(&hud); + painter.setRenderHint(QPainter::Antialiasing, true); + + QRectF backgroundRect(0, 0, qreal(property_width_->getInt()), qreal(property_height_->getInt())); + draw_rounded_rect(painter, backgroundRect); + + if (remaining_distance_time_display_) { + remaining_distance_time_display_->drawRemainingDistanceTimeDisplay(painter, backgroundRect); + } + + painter.end(); +} + +void MissionDetailsDisplay::draw_rounded_rect(QPainter & painter, const QRectF & backgroundRect) +{ + painter.setRenderHint(QPainter::Antialiasing, true); + QColor colorFromHSV; + colorFromHSV.setHsv(0, 0, 29); + colorFromHSV.setAlphaF(0.60); + + painter.setBrush(colorFromHSV); + + painter.setPen(Qt::NoPen); + painter.drawRoundedRect(backgroundRect, backgroundRect.height() / 2, backgroundRect.height() / 2); +} + +void MissionDetailsDisplay::reset() +{ + rviz_common::Display::reset(); + overlay_->hide(); +} + +void MissionDetailsDisplay::update_size() +{ + std::lock_guard lock(mutex_); + overlay_->updateTextureSize(property_width_->getInt(), property_height_->getInt()); + overlay_->setDimensions(overlay_->getTextureWidth(), overlay_->getTextureHeight()); + overlay_->setPosition( + property_right_->getInt(), property_top_->getInt(), HorizontalAlignment::RIGHT, + VerticalAlignment::TOP); + queueRender(); +} + +void MissionDetailsDisplay::topic_updated_remaining_distance_time() +{ + // resubscribe to the topic + remaining_distance_time_sub_.reset(); + auto rviz_ros_node = context_->getRosNodeAbstraction().lock(); + remaining_distance_time_sub_ = + rviz_ros_node->get_raw_node() + ->create_subscription( + remaining_distance_time_topic_property_->getTopicStd(), + rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + [this](const autoware_internal_msgs::msg::MissionRemainingDistanceTime::SharedPtr msg) { + cb_remaining_distance_time(msg); + }); +} + +} // namespace autoware::mission_details_overlay_rviz_plugin + +#include +PLUGINLIB_EXPORT_CLASS( + autoware::mission_details_overlay_rviz_plugin::MissionDetailsDisplay, rviz_common::Display) diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/overlay_utils.cpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/overlay_utils.cpp new file mode 100644 index 0000000000000..68813a5f1140f --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/overlay_utils.cpp @@ -0,0 +1,267 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +// -*- mode: c++ -*- +/********************************************************************* + * Software License Agreement (BSD License) + * + * Copyright (c) 2022, Team Spatzenhirn + * Copyright (c) 2014, JSK Lab + * All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * * Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * * Redistributions in binary form must reproduce the above + * copyright notice, this list of conditions and the following + * disclaimer in the documentation and/o2r other materials provided + * with the distribution. + * * Neither the name of the JSK Lab nor the names of its + * contributors may be used to endorse or promote products derived + * from this software without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS + * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE + * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, + * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, + * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER + * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT + * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN + * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + * POSSIBILITY OF SUCH DAMAGE. + *********************************************************************/ + +#include "overlay_utils.hpp" + +#include + +namespace autoware::mission_details_overlay_rviz_plugin +{ +ScopedPixelBuffer::ScopedPixelBuffer(Ogre::HardwarePixelBufferSharedPtr pixel_buffer) +: pixel_buffer_(pixel_buffer) +{ + pixel_buffer_->lock(Ogre::HardwareBuffer::HBL_NORMAL); +} + +ScopedPixelBuffer::~ScopedPixelBuffer() +{ + pixel_buffer_->unlock(); +} + +Ogre::HardwarePixelBufferSharedPtr ScopedPixelBuffer::getPixelBuffer() +{ + return pixel_buffer_; +} + +QImage ScopedPixelBuffer::getQImage(unsigned int width, unsigned int height) +{ + const Ogre::PixelBox & pixelBox = pixel_buffer_->getCurrentLock(); + Ogre::uint8 * pDest = static_cast(pixelBox.data); + memset(pDest, 0, width * height); + return QImage(pDest, width, height, QImage::Format_ARGB32); +} + +QImage ScopedPixelBuffer::getQImage(unsigned int width, unsigned int height, QColor & bg_color) +{ + QImage Hud = getQImage(width, height); + for (unsigned int i = 0; i < width; i++) { + for (unsigned int j = 0; j < height; j++) { + Hud.setPixel(i, j, bg_color.rgba()); + } + } + return Hud; +} + +QImage ScopedPixelBuffer::getQImage(OverlayObject & overlay) +{ + return getQImage(overlay.getTextureWidth(), overlay.getTextureHeight()); +} + +QImage ScopedPixelBuffer::getQImage(OverlayObject & overlay, QColor & bg_color) +{ + return getQImage(overlay.getTextureWidth(), overlay.getTextureHeight(), bg_color); +} + +OverlayObject::OverlayObject(const std::string & name) : name_(name) +{ + std::string material_name = name_ + "Material"; + Ogre::OverlayManager * mOverlayMgr = Ogre::OverlayManager::getSingletonPtr(); + overlay_ = mOverlayMgr->create(name_); + panel_ = static_cast( + mOverlayMgr->createOverlayElement("Panel", name_ + "Panel")); + panel_->setMetricsMode(Ogre::GMM_PIXELS); + + panel_material_ = Ogre::MaterialManager::getSingleton().create( + material_name, Ogre::ResourceGroupManager::DEFAULT_RESOURCE_GROUP_NAME); + panel_->setMaterialName(panel_material_->getName()); + overlay_->add2D(panel_); +} + +OverlayObject::~OverlayObject() +{ + Ogre::OverlayManager * mOverlayMgr = Ogre::OverlayManager::getSingletonPtr(); + if (mOverlayMgr) { + mOverlayMgr->destroyOverlayElement(panel_); + mOverlayMgr->destroy(overlay_); + } + if (panel_material_) { + panel_material_->unload(); + Ogre::MaterialManager::getSingleton().remove(panel_material_->getName()); + } +} + +std::string OverlayObject::getName() const +{ + return name_; +} + +void OverlayObject::hide() +{ + if (overlay_->isVisible()) { + overlay_->hide(); + } +} + +void OverlayObject::show() +{ + if (!overlay_->isVisible()) { + overlay_->show(); + } +} + +bool OverlayObject::isTextureReady() const +{ + return texture_ != nullptr; +} + +void OverlayObject::updateTextureSize(unsigned int width, unsigned int height) +{ + const std::string texture_name = name_ + "Texture"; + if (width == 0) { + RVIZ_COMMON_LOG_WARNING_STREAM("[OverlayObject] width=0 is specified as texture size"); + width = 1; + } + + if (height == 0) { + RVIZ_COMMON_LOG_WARNING_STREAM("[OverlayObject] height=0 is specified as texture size"); + height = 1; + } + + if (!isTextureReady() || ((width != texture_->getWidth()) || (height != texture_->getHeight()))) { + if (isTextureReady()) { + Ogre::TextureManager::getSingleton().remove(texture_name); + panel_material_->getTechnique(0)->getPass(0)->removeAllTextureUnitStates(); + } + + texture_ = Ogre::TextureManager::getSingleton().createManual( + texture_name, // name + Ogre::ResourceGroupManager::DEFAULT_RESOURCE_GROUP_NAME, + Ogre::TEX_TYPE_2D, // type + width, height, // width & height of the render window + 0, // number of mipmaps + Ogre::PF_A8R8G8B8, // pixel format chosen to match a format Qt can use + Ogre::TU_DEFAULT // usage + ); + panel_material_->getTechnique(0)->getPass(0)->createTextureUnitState(texture_name); + + panel_material_->getTechnique(0)->getPass(0)->setSceneBlending(Ogre::SBT_TRANSPARENT_ALPHA); + } +} + +ScopedPixelBuffer OverlayObject::getBuffer() +{ + if (isTextureReady()) { + return ScopedPixelBuffer(texture_->getBuffer()); + } else { + return ScopedPixelBuffer(Ogre::HardwarePixelBufferSharedPtr()); + } +} + +void OverlayObject::setPosition( + double hor_dist, double ver_dist, HorizontalAlignment hor_alignment, + VerticalAlignment ver_alignment) +{ + // ogre position is always based on the top left corner of the panel, while our position input + // depends on the chosen alignment, i.e. if the horizontal alignment is right, increasing the + // horizontal dist moves the panel to the left (further away from the right border) + double left = 0; + double top = 0; + + switch (hor_alignment) { + case HorizontalAlignment::LEFT: + panel_->setHorizontalAlignment(Ogre::GuiHorizontalAlignment::GHA_LEFT); + left = hor_dist; + break; + case HorizontalAlignment::CENTER: + panel_->setHorizontalAlignment(Ogre::GuiHorizontalAlignment::GHA_CENTER); + left = hor_dist - panel_->getWidth() / 2; + break; + case HorizontalAlignment::RIGHT: + panel_->setHorizontalAlignment(Ogre::GuiHorizontalAlignment::GHA_RIGHT); + left = -hor_dist - panel_->getWidth(); + break; + } + + switch (ver_alignment) { + case VerticalAlignment::BOTTOM: + panel_->setVerticalAlignment(Ogre::GuiVerticalAlignment::GVA_BOTTOM); + top = -ver_dist - panel_->getHeight(); + break; + case VerticalAlignment::CENTER: + panel_->setVerticalAlignment(Ogre::GuiVerticalAlignment::GVA_CENTER); + top = ver_dist - panel_->getHeight() / 2; + break; + case VerticalAlignment::TOP: + panel_->setVerticalAlignment(Ogre::GuiVerticalAlignment::GVA_TOP); + top = ver_dist; + break; + } + + panel_->setPosition(left, top); +} + +void OverlayObject::setDimensions(double width, double height) +{ + panel_->setDimensions(width, height); +} + +bool OverlayObject::isVisible() const +{ + return overlay_->isVisible(); +} + +unsigned int OverlayObject::getTextureWidth() const +{ + if (isTextureReady()) { + return texture_->getWidth(); + } else { + return 0; + } +} + +unsigned int OverlayObject::getTextureHeight() const +{ + if (isTextureReady()) { + return texture_->getHeight(); + } else { + return 0; + } +} +} // namespace autoware::mission_details_overlay_rviz_plugin diff --git a/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/remaining_distance_time_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/remaining_distance_time_display.cpp new file mode 100644 index 0000000000000..86395ef1918bc --- /dev/null +++ b/common/autoware_overlay_rviz_plugin/autoware_mission_details_overlay_rviz_plugin/src/remaining_distance_time_display.cpp @@ -0,0 +1,157 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "remaining_distance_time_display.hpp" + +#include +#include +#include +#include + +#include + +#include +#include +#include +#include + +namespace autoware::mission_details_overlay_rviz_plugin +{ + +RemainingDistanceTimeDisplay::RemainingDistanceTimeDisplay() +: remaining_distance_(0.0), remaining_time_(0.0) +{ + std::string package_path = + ament_index_cpp::get_package_share_directory("autoware_mission_details_overlay_rviz_plugin"); + std::string font_path = package_path + "/assets/font/Quicksand/static/Quicksand-Regular.ttf"; + std::string font_path2 = package_path + "/assets/font/Quicksand/static/Quicksand-Bold.ttf"; + int fontId = QFontDatabase::addApplicationFont( + font_path.c_str()); // returns -1 on failure (see docs for more info) + int fontId2 = QFontDatabase::addApplicationFont( + font_path2.c_str()); // returns -1 on failure (see docs for more info) + if (fontId == -1 || fontId2 == -1) { + std::cout << "Failed to load the Quicksand font."; + } + + std::string dist_image = package_path + "/assets/path.png"; + std::string time_image = package_path + "/assets/av_timer.png"; + icon_dist_.load(dist_image.c_str()); + icon_time_.load(time_image.c_str()); + icon_dist_scaled_ = icon_dist_.scaled(28, 28, Qt::KeepAspectRatio, Qt::SmoothTransformation); + icon_time_scaled_ = icon_time_.scaled(28, 28, Qt::KeepAspectRatio, Qt::SmoothTransformation); +} + +void RemainingDistanceTimeDisplay::updateRemainingDistanceTimeData( + const autoware_internal_msgs::msg::MissionRemainingDistanceTime::ConstSharedPtr & msg) +{ + remaining_distance_ = msg->remaining_distance; + remaining_time_ = msg->remaining_time; +} + +void RemainingDistanceTimeDisplay::drawRemainingDistanceTimeDisplay( + QPainter & painter, const QRectF & backgroundRect) +{ + const QFont font("Quicksand", 15, QFont::Bold); + painter.setFont(font); + + // We'll display the distance and time in two rows + + auto calculate_inner_rect = [](const QRectF & outer_rect, double ratio_x, double ratio_y) { + QSizeF size_inner(outer_rect.width() * ratio_x, outer_rect.height() * ratio_y); + QPointF top_left_inner = QPointF( + outer_rect.center().x() - size_inner.width() / 2, + outer_rect.center().y() - size_inner.height() / 2); + return QRectF(top_left_inner, size_inner); + }; + + QRectF rect_inner = calculate_inner_rect(backgroundRect, 0.7, 0.7); + // Proportionally extend the rect to the right to account for visual icon distance to the left + rect_inner.setWidth(rect_inner.width() * 1.08); + + // Calculate distance row rectangle + const QSizeF distance_row_size(rect_inner.width(), rect_inner.height() / 2); + const QPointF distance_row_top_left(rect_inner.topLeft()); + const QRectF distance_row_rect_outer(distance_row_top_left, distance_row_size); + + // Calculate time row rectangle + const QSizeF time_row_size(rect_inner.width(), rect_inner.height() / 2); + const QPointF time_row_top_left( + rect_inner.topLeft().x(), rect_inner.topLeft().y() + rect_inner.height() / 2); + const QRectF time_row_rect_outer(time_row_top_left, time_row_size); + + const auto rect_time = calculate_inner_rect(time_row_rect_outer, 1.0, 0.9); + const auto rect_dist = calculate_inner_rect(distance_row_rect_outer, 1.0, 0.9); + + auto place_row = [&, this]( + const QRectF & rect, const QImage & icon, const QString & str_value, + const QString & str_unit) { + // order: icon, value, unit + + // place the icon + QPointF icon_top_left(rect.topLeft().x(), rect.center().y() - icon.height() / 2.0); + painter.drawImage(icon_top_left, icon); + + // place the unit text + const float unit_width = 40.0; + QRectF rect_text_unit( + rect.topRight().x() - unit_width, rect.topRight().y(), unit_width, rect.height()); + + painter.setPen(gray); + painter.drawText(rect_text_unit, Qt::AlignLeft | Qt::AlignVCenter, str_unit); + + // place the value text + const double margin_x = 5.0; // margin around the text + + const double used_width = icon.width() + rect_text_unit.width() + margin_x * 2.0; + + QRectF rect_text( + rect.topLeft().x() + icon.width() + margin_x, rect.topLeft().y(), rect.width() - used_width, + rect.height()); + + painter.drawText(rect_text, Qt::AlignRight | Qt::AlignVCenter, str_value); + }; + + // remaining_time_ is in seconds + if (remaining_time_ <= 60) { + place_row(rect_time, icon_time_scaled_, QString::number(remaining_time_, 'f', 0), "sec"); + } else if (remaining_time_ <= 600) { + place_row(rect_time, icon_time_scaled_, QString::number(remaining_time_ / 60.0, 'f', 1), "min"); + } else if (remaining_time_ <= 3600) { + place_row(rect_time, icon_time_scaled_, QString::number(remaining_time_ / 60.0, 'f', 0), "min"); + } else if (remaining_time_ <= 36000) { + place_row( + rect_time, icon_time_scaled_, QString::number(remaining_time_ / 3600.0, 'f', 1), "hrs"); + } else { + place_row( + rect_time, icon_time_scaled_, QString::number(remaining_time_ / 3600.0, 'f', 0), "hrs"); + } + + // remaining_distance_ is in meters + if (remaining_distance_ <= 10) { + place_row(rect_dist, icon_dist_scaled_, QString::number(remaining_distance_, 'f', 1), "m"); + } else if (remaining_distance_ <= 1000) { + place_row(rect_dist, icon_dist_scaled_, QString::number(remaining_distance_, 'f', 0), "m"); + } else if (remaining_distance_ <= 10000) { + place_row( + rect_dist, icon_dist_scaled_, QString::number(remaining_distance_ / 1000.0, 'f', 2), "km"); + } else if (remaining_distance_ <= 100000) { + place_row( + rect_dist, icon_dist_scaled_, QString::number(remaining_distance_ / 1000.0, 'f', 1), "km"); + } else { + place_row( + rect_dist, icon_dist_scaled_, QString::number(remaining_distance_ / 1000.0, 'f', 0), "km"); + } +} + +} // namespace autoware::mission_details_overlay_rviz_plugin diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CHANGELOG.rst b/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CHANGELOG.rst deleted file mode 100644 index e7672ee001955..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CHANGELOG.rst +++ /dev/null @@ -1,24 +0,0 @@ -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -Changelog for package rviz_2d_overlay_msgs -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -1.3.0 (2023-05-18) ------------------- -* Removed old position message fields -* Contributors: Dominik, Jonas Otto - -1.2.1 (2022-09-30) ------------------- - -1.2.0 (2022-09-27) ------------------- -* Rename package from overlay_rviz_msgs to rviz_2d_overlay_msgs -* Contributors: Jonas Otto - -1.1.0 (2022-09-11) ------------------- - -1.0.0 (2022-08-30) ------------------- -* Create OverlayText message (currently same as jsk_rviz_plugins) -* Contributors: Jonas Otto, Dominik Authaler diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CMakeLists.txt b/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CMakeLists.txt deleted file mode 100644 index e23a4e755cbc4..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/CMakeLists.txt +++ /dev/null @@ -1,19 +0,0 @@ -cmake_minimum_required(VERSION 3.5) -project(autoware_overlay_msgs) - -if (NOT CMAKE_CXX_STANDARD) - set(CMAKE_CXX_STANDARD 17) -endif () - - -# find dependencies -find_package(ament_cmake REQUIRED) -find_package(rosidl_default_generators REQUIRED) -find_package(std_msgs REQUIRED) -rosidl_generate_interfaces(${PROJECT_NAME} - "msg/OverlayText.msg" - DEPENDENCIES - std_msgs -) - -ament_package() diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/msg/OverlayText.msg b/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/msg/OverlayText.msg deleted file mode 100644 index db3cf628b895b..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/msg/OverlayText.msg +++ /dev/null @@ -1,31 +0,0 @@ -uint8 ADD = 0 -uint8 DELETE = 1 - -# constants for the horizontal and vertical alignment -uint8 LEFT = 0 -uint8 RIGHT = 1 -uint8 CENTER = 2 -uint8 TOP = 3 -uint8 BOTTOM = 4 - -uint8 action - -int32 width -int32 height -# Position: Positive values move the overlay towards the center of the window, -# for center alignment positive values move the overlay towards the bottom right -int32 horizontal_distance # Horizontal distance from left/right border or center, depending on alignment -int32 vertical_distance # Vertical distance between from top/bottom border or center, depending on alignment - -# Alignment of the overlay withing RVIZ -uint8 horizontal_alignment # one of LEFT, CENTER, RIGHT -uint8 vertical_alignment # one of TOP, CENTER, BOTTOM - -std_msgs/ColorRGBA bg_color - -int32 line_width -float32 text_size -string font -std_msgs/ColorRGBA fg_color - -string text diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/package.xml b/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/package.xml deleted file mode 100644 index 4881b126ffffb..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_msgs/package.xml +++ /dev/null @@ -1,24 +0,0 @@ - - - - autoware_overlay_msgs - 1.3.0 - Messages describing 2D overlays for RVIZ, extracted/derived from the jsk_visualization package. - Team Spatzenhirn - BSD-3-Clause - - ament_cmake - rosidl_default_generators - - autoware_auto_vehicle_msgs - autoware_perception_msgs - std_msgs - unique_identifier_msgs - rosidl_default_runtime - - rosidl_interface_packages - - - ament_cmake - - diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/CMakeLists.txt b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/CMakeLists.txt index afb12bffeeaa7..aafc62fc90d25 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/CMakeLists.txt +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/CMakeLists.txt @@ -3,28 +3,13 @@ project(autoware_overlay_rviz_plugin) # find dependencies find_package(ament_cmake_auto REQUIRED) -find_package(ament_cmake REQUIRED) -find_package(autoware_auto_vehicle_msgs REQUIRED) -find_package(tier4_planning_msgs REQUIRED) -find_package(autoware_perception_msgs REQUIRED) ament_auto_find_build_dependencies() -find_package(autoware_overlay_msgs REQUIRED) - -find_package(rviz_common REQUIRED) -find_package(rviz_rendering REQUIRED) -find_package(rviz_ogre_vendor REQUIRED) -find_package(std_msgs REQUIRED) - -set( - headers_to_moc - include/overlay_text_display.hpp - include/signal_display.hpp - +set(headers_to_moc + include/signal_display.hpp ) -set( - headers_to_not_moc +set(headers_to_not_moc include/steering_wheel_display.hpp include/gear_display.hpp include/speed_display.hpp @@ -34,47 +19,42 @@ set( ) - foreach(header "${headers_to_moc}") - qt5_wrap_cpp(display_moc_files "${header}") + qt5_wrap_cpp(display_moc_files "${header}") endforeach() -set( - display_source_files - src/overlay_text_display.cpp - src/overlay_utils.cpp - src/signal_display.cpp - src/steering_wheel_display.cpp - src/gear_display.cpp - src/speed_display.cpp - src/turn_signals_display.cpp - src/traffic_display.cpp - src/speed_limit_display.cpp - +set(display_source_files + src/overlay_utils.cpp + src/signal_display.cpp + src/steering_wheel_display.cpp + src/gear_display.cpp + src/speed_display.cpp + src/turn_signals_display.cpp + src/traffic_display.cpp + src/speed_limit_display.cpp ) -add_library( - ${PROJECT_NAME} SHARED - ${display_moc_files} - ${headers_to_not_moc} - ${display_source_files} +add_library(${PROJECT_NAME} SHARED + ${display_moc_files} + ${headers_to_not_moc} + ${display_source_files} ) set_property(TARGET ${PROJECT_NAME} PROPERTY CXX_STANDARD 17) target_compile_options(${PROJECT_NAME} PRIVATE -Wall -Wextra -Wpedantic) target_include_directories( - ${PROJECT_NAME} PUBLIC - $ - $ - ${Qt5Widgets_INCLUDE_DIRS} - ${OpenCV_INCLUDE_DIRS} + ${PROJECT_NAME} PUBLIC + $ + $ + ${Qt5Widgets_INCLUDE_DIRS} + ${OpenCV_INCLUDE_DIRS} ) target_link_libraries( - ${PROJECT_NAME} PUBLIC - rviz_ogre_vendor::OgreMain - rviz_ogre_vendor::OgreOverlay + ${PROJECT_NAME} PUBLIC + rviz_ogre_vendor::OgreMain + rviz_ogre_vendor::OgreOverlay ) @@ -85,22 +65,19 @@ target_compile_definitions(${PROJECT_NAME} PUBLIC "PLUGINLIB__DISABLE_BOOST_FUNC pluginlib_export_plugin_description_file(rviz_common plugins_description.xml) -ament_target_dependencies( - ${PROJECT_NAME} - PUBLIC - rviz_common - rviz_rendering - autoware_overlay_msgs - autoware_auto_vehicle_msgs - tier4_planning_msgs - autoware_perception_msgs +ament_target_dependencies(${PROJECT_NAME} PUBLIC + rviz_common + rviz_rendering + autoware_auto_vehicle_msgs + tier4_planning_msgs + autoware_perception_msgs ) ament_export_include_directories(include) ament_export_targets(${PROJECT_NAME} HAS_LIBRARY_TARGET) ament_export_dependencies( - rviz_common - rviz_ogre_vendor + rviz_common + rviz_ogre_vendor ) if(BUILD_TESTING) @@ -109,32 +86,32 @@ if(BUILD_TESTING) endif() install( - TARGETS ${PROJECT_NAME} - EXPORT ${PROJECT_NAME} - ARCHIVE DESTINATION lib - LIBRARY DESTINATION lib - RUNTIME DESTINATION bin - INCLUDES DESTINATION include + TARGETS ${PROJECT_NAME} + EXPORT ${PROJECT_NAME} + ARCHIVE DESTINATION lib + LIBRARY DESTINATION lib + RUNTIME DESTINATION bin + INCLUDES DESTINATION include ) install( - DIRECTORY include/ - DESTINATION include + DIRECTORY include/ + DESTINATION include ) install( - TARGETS - DESTINATION lib/${PROJECT_NAME} + TARGETS + DESTINATION lib/${PROJECT_NAME} ) # Copy the assets directory to the installation directory install( - DIRECTORY assets/ - DESTINATION share/${PROJECT_NAME}/assets + DIRECTORY assets/ + DESTINATION share/${PROJECT_NAME}/assets ) add_definitions(-DQT_NO_KEYWORDS) ament_package( - CONFIG_EXTRAS "autoware_overlay_rviz_plugin-extras.cmake" + CONFIG_EXTRAS "autoware_overlay_rviz_plugin-extras.cmake" ) diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_text_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_text_display.hpp deleted file mode 100644 index ccea51b9a5349..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_text_display.hpp +++ /dev/null @@ -1,157 +0,0 @@ -// Copyright 2024 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -// -*- mode: c++; -*- -/********************************************************************* - * Software License Agreement (BSD License) - * - * Copyright (c) 2022, Team Spatzenhirn - * Copyright (c) 2014, JSK Lab - * All rights reserved. - * - * Redistribution and use in source and binary forms, with or without - * modification, are permitted provided that the following conditions - * are met: - * - * * Redistributions of source code must retain the above copyright - * notice, this list of conditions and the following disclaimer. - * * Redistributions in binary form must reproduce the above - * copyright notice, this list of conditions and the following - * disclaimer in the documentation and/o2r other materials provided - * with the distribution. - * * Neither the name of the JSK Lab nor the names of its - * contributors may be used to endorse or promote products derived - * from this software without specific prior written permission. - * - * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS - * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT - * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS - * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE - * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, - * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, - * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; - * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER - * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT - * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN - * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE - * POSSIBILITY OF SUCH DAMAGE. - *********************************************************************/ -#ifndef OVERLAY_TEXT_DISPLAY_HPP_ -#define OVERLAY_TEXT_DISPLAY_HPP_ - -#include "autoware_overlay_msgs/msg/overlay_text.hpp" -#ifndef Q_MOC_RUN -#include "overlay_utils.hpp" - -#include -#include -#include -#include -#include -#include -#include - -#include -#include -#include - -#include -#endif - -namespace autoware_overlay_rviz_plugin -{ -class OverlayTextDisplay -: public rviz_common::RosTopicDisplay -{ - Q_OBJECT -public: - OverlayTextDisplay(); - virtual ~OverlayTextDisplay(); - -protected: - autoware_overlay_rviz_plugin::OverlayObject::SharedPtr overlay_; - - int texture_width_; - int texture_height_; - - bool overtake_fg_color_properties_; - bool overtake_bg_color_properties_; - bool overtake_position_properties_; - bool align_bottom_; - bool invert_shadow_; - QColor bg_color_; - QColor fg_color_; - int text_size_; - int line_width_; - std::string text_; - QStringList font_families_; - std::string font_; - int horizontal_dist_; - int vertical_dist_; - HorizontalAlignment horizontal_alignment_; - VerticalAlignment vertical_alignment_; - - void onInitialize() override; - void onEnable() override; - void onDisable() override; - void update(float wall_dt, float ros_dt) override; - void reset() override; - - bool require_update_texture_; - // properties are raw pointers since they are owned by Qt - rviz_common::properties::BoolProperty * overtake_position_properties_property_; - rviz_common::properties::BoolProperty * overtake_fg_color_properties_property_; - rviz_common::properties::BoolProperty * overtake_bg_color_properties_property_; - rviz_common::properties::BoolProperty * align_bottom_property_; - rviz_common::properties::BoolProperty * invert_shadow_property_; - rviz_common::properties::IntProperty * hor_dist_property_; - rviz_common::properties::IntProperty * ver_dist_property_; - rviz_common::properties::EnumProperty * hor_alignment_property_; - rviz_common::properties::EnumProperty * ver_alignment_property_; - rviz_common::properties::IntProperty * width_property_; - rviz_common::properties::IntProperty * height_property_; - rviz_common::properties::IntProperty * text_size_property_; - rviz_common::properties::IntProperty * line_width_property_; - rviz_common::properties::ColorProperty * bg_color_property_; - rviz_common::properties::FloatProperty * bg_alpha_property_; - rviz_common::properties::ColorProperty * fg_color_property_; - rviz_common::properties::FloatProperty * fg_alpha_property_; - rviz_common::properties::EnumProperty * font_property_; - -protected Q_SLOTS: - void updateOvertakePositionProperties(); - void updateOvertakeFGColorProperties(); - void updateOvertakeBGColorProperties(); - void updateAlignBottom(); - void updateInvertShadow(); - void updateHorizontalDistance(); - void updateVerticalDistance(); - void updateHorizontalAlignment(); - void updateVerticalAlignment(); - void updateWidth(); - void updateHeight(); - void updateTextSize(); - void updateFGColor(); - void updateFGAlpha(); - void updateBGColor(); - void updateBGAlpha(); - void updateFont(); - void updateLineWidth(); - -private: - void processMessage(autoware_overlay_msgs::msg::OverlayText::ConstSharedPtr msg) override; -}; -} // namespace autoware_overlay_rviz_plugin - -#endif // OVERLAY_TEXT_DISPLAY_HPP_ diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_utils.hpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_utils.hpp index 8581628ef0bce..b9c060899bace 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_utils.hpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/overlay_utils.hpp @@ -54,8 +54,6 @@ #include #include -#include "autoware_overlay_msgs/msg/overlay_text.hpp" - #include #include #include @@ -89,17 +87,9 @@ class ScopedPixelBuffer Ogre::HardwarePixelBufferSharedPtr pixel_buffer_; }; -enum class VerticalAlignment : uint8_t { - CENTER = autoware_overlay_msgs::msg::OverlayText::CENTER, - TOP = autoware_overlay_msgs::msg::OverlayText::TOP, - BOTTOM = autoware_overlay_msgs::msg::OverlayText::BOTTOM, -}; +enum class VerticalAlignment : uint8_t { CENTER, TOP, BOTTOM }; -enum class HorizontalAlignment : uint8_t { - LEFT = autoware_overlay_msgs::msg::OverlayText::LEFT, - RIGHT = autoware_overlay_msgs::msg::OverlayText::RIGHT, - CENTER = autoware_overlay_msgs::msg::OverlayText::CENTER -}; +enum class HorizontalAlignment : uint8_t { LEFT, RIGHT, CENTER }; /** * Helper class for realizing an overlay object on top of the rviz 3D panel. diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/signal_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/signal_display.hpp index 4fa39f2c5a903..ec1acb9a5dc68 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/signal_display.hpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/signal_display.hpp @@ -102,7 +102,7 @@ private Q_SLOTS: turn_signals_sub_; rclcpp::Subscription::SharedPtr hazard_lights_sub_; - rclcpp::Subscription::SharedPtr traffic_sub_; + rclcpp::Subscription::SharedPtr traffic_sub_; rclcpp::Subscription::SharedPtr speed_limit_sub_; std::mutex property_mutex_; @@ -117,7 +117,7 @@ private Q_SLOTS: const autoware_auto_vehicle_msgs::msg::HazardLightsReport::ConstSharedPtr & msg); void updateSpeedLimitData(const tier4_planning_msgs::msg::VelocityLimit::ConstSharedPtr msg); void updateTrafficLightData( - const autoware_perception_msgs::msg::TrafficSignalArray::ConstSharedPtr msg); + const autoware_perception_msgs::msg::TrafficSignal::ConstSharedPtr msg); void drawWidget(QImage & hud); }; } // namespace autoware_overlay_rviz_plugin diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/traffic_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/traffic_display.hpp index 20410a78edc44..efa30f37ccb3e 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/traffic_display.hpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/traffic_display.hpp @@ -24,7 +24,6 @@ #include #include -#include #include #include @@ -40,8 +39,8 @@ class TrafficDisplay TrafficDisplay(); void drawTrafficLightIndicator(QPainter & painter, const QRectF & backgroundRect); void updateTrafficLightData( - const autoware_perception_msgs::msg::TrafficSignalArray::ConstSharedPtr & msg); - autoware_perception_msgs::msg::TrafficSignalArray current_traffic_; + const autoware_perception_msgs::msg::TrafficSignal::ConstSharedPtr & msg); + autoware_perception_msgs::msg::TrafficSignal current_traffic_; private: QImage traffic_light_image_; diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/turn_signals_display.hpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/turn_signals_display.hpp index 87f141353d5b2..ca10c92c06a3e 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/turn_signals_display.hpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/include/turn_signals_display.hpp @@ -47,7 +47,7 @@ class TurnSignalsDisplay private: QImage arrowImage; - QColor gray = QColor(46, 46, 46); + QColor gray = QColor(79, 79, 79); int current_turn_signal_; // Internal variable to store turn signal state int current_hazard_lights_; // Internal variable to store hazard lights state diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/package.xml b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/package.xml index da075b2648937..4d2f53e1e27ed 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/package.xml +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/package.xml @@ -12,7 +12,6 @@ BSD-3-Clause autoware_auto_vehicle_msgs - autoware_overlay_msgs autoware_perception_msgs boost rviz_common diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/gear_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/gear_display.cpp index 8f05ce6fdce1c..825c7c1620e2c 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/gear_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/gear_display.cpp @@ -81,18 +81,19 @@ void GearDisplay::drawGearIndicator(QPainter & painter, const QRectF & backgroun break; } - QFont gearFont("Quicksand", 16, QFont::Bold); + QFont gearFont("Quicksand", 12, QFont::Bold); painter.setFont(gearFont); QPen borderPen(gray); - borderPen.setWidth(4); + borderPen.setWidth(1); painter.setPen(borderPen); - int gearBoxSize = 30; - int gearX = backgroundRect.left() + 30 + gearBoxSize; - int gearY = backgroundRect.height() - gearBoxSize - 20; + double gearBoxSize = 37.5; + double gearX = backgroundRect.left() + 54; + double gearY = backgroundRect.height() / 2 - gearBoxSize / 2; QRect gearRect(gearX, gearY, gearBoxSize, gearBoxSize); - painter.setBrush(QColor(0, 0, 0, 0)); + painter.setBrush(gray); painter.drawRoundedRect(gearRect, 10, 10); + painter.setPen(Qt::black); painter.drawText(gearRect, Qt::AlignCenter, QString::fromStdString(gearString)); } diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/overlay_text_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/overlay_text_display.cpp deleted file mode 100644 index b853e14a5858d..0000000000000 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/overlay_text_display.cpp +++ /dev/null @@ -1,556 +0,0 @@ -// Copyright 2024 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -// -*- mode: c++; -*- -/********************************************************************* - * Software License Agreement (BSD License) - * - * Copyright (c) 2022, Team Spatzenhirn - * Copyright (c) 2014, JSK Lab - * All rights reserved. - * - * Redistribution and use in source and binary forms, with or without - * modification, are permitted provided that the following conditions - * are met: - * - * * Redistributions of source code must retain the above copyright - * notice, this list of conditions and the following disclaimer. - * * Redistributions in binary form must reproduce the above - * copyright notice, this list of conditions and the following - * disclaimer in the documentation and/o2r other materials provided - * with the distribution. - * * Neither the name of the JSK Lab nor the names of its - * contributors may be used to endorse or promote products derived - * from this software without specific prior written permission. - * - * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS - * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT - * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS - * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE - * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, - * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, - * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; - * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER - * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT - * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN - * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE - * POSSIBILITY OF SUCH DAMAGE. - *********************************************************************/ - -#include "overlay_text_display.hpp" - -#include -#include -#include -#include -#include -#include - -#include -#include - -#include -#include -#include - -#include -#include - -namespace autoware_overlay_rviz_plugin -{ -OverlayTextDisplay::OverlayTextDisplay() -: texture_width_(0), - texture_height_(0), - bg_color_(0, 0, 0, 0), - fg_color_(255, 255, 255, 255.0), - text_size_(14), - line_width_(2), - text_(""), - font_(""), - require_update_texture_(false) -{ - overtake_position_properties_property_ = new rviz_common::properties::BoolProperty( - "Overtake Position Properties", false, - "overtake position properties specified by message such as left, top and font", this, - SLOT(updateOvertakePositionProperties())); - overtake_fg_color_properties_property_ = new rviz_common::properties::BoolProperty( - "Overtake FG Color Properties", false, - "overtake color properties specified by message such as foreground color and alpha", this, - SLOT(updateOvertakeFGColorProperties())); - overtake_bg_color_properties_property_ = new rviz_common::properties::BoolProperty( - "Overtake BG Color Properties", false, - "overtake color properties specified by message such as background color and alpha", this, - SLOT(updateOvertakeBGColorProperties())); - align_bottom_property_ = new rviz_common::properties::BoolProperty( - "Align Bottom", false, "align text with the bottom of the overlay region", this, - SLOT(updateAlignBottom())); - invert_shadow_property_ = new rviz_common::properties::BoolProperty( - "Invert Shadow", false, "make shadow lighter than original text", this, - SLOT(updateInvertShadow())); - hor_dist_property_ = new rviz_common::properties::IntProperty( - "hor_dist", 0, "horizontal distance to anchor", this, SLOT(updateHorizontalDistance())); - ver_dist_property_ = new rviz_common::properties::IntProperty( - "ver_dist", 0, "vertical distance to anchor", this, SLOT(updateVerticalDistance())); - hor_alignment_property_ = new rviz_common::properties::EnumProperty( - "hor_alignment", "left", "horizontal alignment of the overlay", this, - SLOT(updateHorizontalAlignment())); - hor_alignment_property_->addOption("left", autoware_overlay_msgs::msg::OverlayText::LEFT); - hor_alignment_property_->addOption("center", autoware_overlay_msgs::msg::OverlayText::CENTER); - hor_alignment_property_->addOption("right", autoware_overlay_msgs::msg::OverlayText::RIGHT); - ver_alignment_property_ = new rviz_common::properties::EnumProperty( - "ver_alignment", "top", "vertical alignment of the overlay", this, - SLOT(updateVerticalAlignment())); - ver_alignment_property_->addOption("top", autoware_overlay_msgs::msg::OverlayText::TOP); - ver_alignment_property_->addOption("center", autoware_overlay_msgs::msg::OverlayText::CENTER); - ver_alignment_property_->addOption("bottom", autoware_overlay_msgs::msg::OverlayText::BOTTOM); - width_property_ = new rviz_common::properties::IntProperty( - "width", 128, "width position", this, SLOT(updateWidth())); - width_property_->setMin(0); - height_property_ = new rviz_common::properties::IntProperty( - "height", 128, "height position", this, SLOT(updateHeight())); - height_property_->setMin(0); - text_size_property_ = new rviz_common::properties::IntProperty( - "text size", 12, "text size", this, SLOT(updateTextSize())); - text_size_property_->setMin(0); - line_width_property_ = new rviz_common::properties::IntProperty( - "line width", 2, "line width", this, SLOT(updateLineWidth())); - line_width_property_->setMin(0); - fg_color_property_ = new rviz_common::properties::ColorProperty( - "Foreground Color", QColor(25, 255, 240), "Foreground Color", this, SLOT(updateFGColor())); - fg_alpha_property_ = new rviz_common::properties::FloatProperty( - "Foreground Alpha", 0.8, "Foreground Alpha", this, SLOT(updateFGAlpha())); - fg_alpha_property_->setMin(0.0); - fg_alpha_property_->setMax(1.0); - bg_color_property_ = new rviz_common::properties::ColorProperty( - "Background Color", QColor(0, 0, 0), "Background Color", this, SLOT(updateBGColor())); - bg_alpha_property_ = new rviz_common::properties::FloatProperty( - "Background Alpha", 0.8, "Background Alpha", this, SLOT(updateBGAlpha())); - bg_alpha_property_->setMin(0.0); - bg_alpha_property_->setMax(1.0); - - QFontDatabase database; - font_families_ = database.families(); - font_property_ = new rviz_common::properties::EnumProperty( - "font", "DejaVu Sans Mono", "font", this, SLOT(updateFont())); - for (ssize_t i = 0; i < font_families_.size(); i++) { - font_property_->addOption(font_families_[i], static_cast(i)); - } -} - -OverlayTextDisplay::~OverlayTextDisplay() -{ - onDisable(); -} - -void OverlayTextDisplay::onEnable() -{ - if (overlay_) { - overlay_->show(); - } - subscribe(); -} - -void OverlayTextDisplay::onDisable() -{ - if (overlay_) { - overlay_->hide(); - } - unsubscribe(); -} - -// only the first time -void OverlayTextDisplay::onInitialize() -{ - RTDClass::onInitialize(); - rviz_rendering::RenderSystem::get()->prepareOverlays(scene_manager_); - - onEnable(); - updateTopic(); - updateOvertakePositionProperties(); - updateOvertakeFGColorProperties(); - updateOvertakeBGColorProperties(); - updateAlignBottom(); - updateInvertShadow(); - updateHorizontalDistance(); - updateVerticalDistance(); - updateHorizontalAlignment(); - updateVerticalAlignment(); - updateWidth(); - updateHeight(); - updateTextSize(); - updateFGColor(); - updateFGAlpha(); - updateBGColor(); - updateBGAlpha(); - updateFont(); - updateLineWidth(); - require_update_texture_ = true; -} - -void OverlayTextDisplay::update(float /*wall_dt*/, float /*ros_dt*/) -{ - if (!require_update_texture_) { - return; - } - if (!isEnabled()) { - return; - } - if (!overlay_) { - return; - } - - overlay_->updateTextureSize(texture_width_, texture_height_); - { - autoware_overlay_rviz_plugin::ScopedPixelBuffer buffer = overlay_->getBuffer(); - QImage Hud = buffer.getQImage(*overlay_, bg_color_); - QPainter painter(&Hud); - painter.setRenderHint(QPainter::Antialiasing, true); - painter.setPen(QPen(fg_color_, std::max(line_width_, 1), Qt::SolidLine)); - uint16_t w = overlay_->getTextureWidth(); - uint16_t h = overlay_->getTextureHeight(); - - // font - if (text_size_ != 0) { - // QFont font = painter.font(); - QFont font(font_.length() > 0 ? font_.c_str() : "Liberation Sans"); - font.setPointSize(text_size_); - font.setBold(true); - painter.setFont(font); - } - if (text_.length() > 0) { - QColor shadow_color; - if (invert_shadow_) - shadow_color = Qt::white; // fg_color_.lighter(); - else - shadow_color = Qt::black; // fg_color_.darker(); - shadow_color.setAlpha(fg_color_.alpha()); - - std::string color_wrapped_text = - (boost::format("%1%") % text_ % - fg_color_.red() % fg_color_.green() % fg_color_.blue() % fg_color_.alpha()) - .str(); - - // find a remove "color: XXX;" regex match to generate a proper shadow - std::regex color_tag_re("color:.+?;"); - std::string null_char(""); - std::string formatted_text_ = std::regex_replace(text_, color_tag_re, null_char); - std::string color_wrapped_shadow = - (boost::format("%1%") % - formatted_text_ % shadow_color.red() % shadow_color.green() % shadow_color.blue() % - shadow_color.alpha()) - .str(); - - QStaticText static_text( - boost::algorithm::replace_all_copy(color_wrapped_text, "\n", "
").c_str()); - static_text.setTextWidth(w); - - painter.setPen(QPen(shadow_color, std::max(line_width_, 1), Qt::SolidLine)); - QStaticText static_shadow( - boost::algorithm::replace_all_copy(color_wrapped_shadow, "\n", "
").c_str()); - static_shadow.setTextWidth(w); - - if (!align_bottom_) { - painter.drawStaticText(1, 1, static_shadow); - painter.drawStaticText(0, 0, static_text); - } else { - QStaticText only_wrapped_text(color_wrapped_text.c_str()); - QFontMetrics fm(painter.fontMetrics()); - QRect text_rect = fm.boundingRect( - 0, 0, w, h, Qt::TextWordWrap | Qt::AlignLeft | Qt::AlignTop, - only_wrapped_text.text().remove(QRegExp("<[^>]*>"))); - painter.drawStaticText(1, h - text_rect.height() + 1, static_shadow); - painter.drawStaticText(0, h - text_rect.height(), static_text); - } - } - painter.end(); - } - overlay_->setDimensions(overlay_->getTextureWidth(), overlay_->getTextureHeight()); - require_update_texture_ = false; -} - -void OverlayTextDisplay::reset() -{ - RTDClass::reset(); - - if (overlay_) { - overlay_->hide(); - } -} - -void OverlayTextDisplay::processMessage(autoware_overlay_msgs::msg::OverlayText::ConstSharedPtr msg) -{ - if (!isEnabled()) { - return; - } - if (!overlay_) { - static int count = 0; - std::stringstream ss; - ss << "OverlayTextDisplayObject" << count++; - overlay_.reset(new autoware_overlay_rviz_plugin::OverlayObject(ss.str())); - overlay_->show(); - } - if (overlay_) { - if (msg->action == autoware_overlay_msgs::msg::OverlayText::DELETE) { - overlay_->hide(); - } else if (msg->action == autoware_overlay_msgs::msg::OverlayText::ADD) { - overlay_->show(); - } - } - - // store message for update method - text_ = msg->text; - - if (!overtake_position_properties_) { - texture_width_ = msg->width; - texture_height_ = msg->height; - text_size_ = msg->text_size; - horizontal_dist_ = msg->horizontal_distance; - vertical_dist_ = msg->vertical_distance; - - horizontal_alignment_ = HorizontalAlignment{msg->horizontal_alignment}; - vertical_alignment_ = VerticalAlignment{msg->vertical_alignment}; - } - if (!overtake_bg_color_properties_) - bg_color_ = QColor( - msg->bg_color.r * 255.0, msg->bg_color.g * 255.0, msg->bg_color.b * 255.0, - msg->bg_color.a * 255.0); - if (!overtake_fg_color_properties_) { - fg_color_ = QColor( - msg->fg_color.r * 255.0, msg->fg_color.g * 255.0, msg->fg_color.b * 255.0, - msg->fg_color.a * 255.0); - font_ = msg->font; - line_width_ = msg->line_width; - } - if (overlay_) { - overlay_->setPosition( - horizontal_dist_, vertical_dist_, horizontal_alignment_, vertical_alignment_); - } - require_update_texture_ = true; -} - -void OverlayTextDisplay::updateOvertakePositionProperties() -{ - if (!overtake_position_properties_ && overtake_position_properties_property_->getBool()) { - updateVerticalDistance(); - updateHorizontalDistance(); - updateVerticalAlignment(); - updateHorizontalAlignment(); - updateWidth(); - updateHeight(); - updateTextSize(); - require_update_texture_ = true; - } - - overtake_position_properties_ = overtake_position_properties_property_->getBool(); - if (overtake_position_properties_) { - hor_dist_property_->show(); - ver_dist_property_->show(); - hor_alignment_property_->show(); - ver_alignment_property_->show(); - width_property_->show(); - height_property_->show(); - text_size_property_->show(); - } else { - hor_dist_property_->hide(); - ver_dist_property_->hide(); - hor_alignment_property_->hide(); - ver_alignment_property_->hide(); - width_property_->hide(); - height_property_->hide(); - text_size_property_->hide(); - } -} - -void OverlayTextDisplay::updateOvertakeFGColorProperties() -{ - if (!overtake_fg_color_properties_ && overtake_fg_color_properties_property_->getBool()) { - // read all the parameters from properties - updateFGColor(); - updateFGAlpha(); - updateFont(); - updateLineWidth(); - require_update_texture_ = true; - } - overtake_fg_color_properties_ = overtake_fg_color_properties_property_->getBool(); - if (overtake_fg_color_properties_) { - fg_color_property_->show(); - fg_alpha_property_->show(); - line_width_property_->show(); - font_property_->show(); - } else { - fg_color_property_->hide(); - fg_alpha_property_->hide(); - line_width_property_->hide(); - font_property_->hide(); - } -} - -void OverlayTextDisplay::updateOvertakeBGColorProperties() -{ - if (!overtake_bg_color_properties_ && overtake_bg_color_properties_property_->getBool()) { - // read all the parameters from properties - updateBGColor(); - updateBGAlpha(); - require_update_texture_ = true; - } - overtake_bg_color_properties_ = overtake_bg_color_properties_property_->getBool(); - if (overtake_bg_color_properties_) { - bg_color_property_->show(); - bg_alpha_property_->show(); - } else { - bg_color_property_->hide(); - bg_alpha_property_->hide(); - } -} - -void OverlayTextDisplay::updateAlignBottom() -{ - if (align_bottom_ != align_bottom_property_->getBool()) { - require_update_texture_ = true; - } - align_bottom_ = align_bottom_property_->getBool(); -} - -void OverlayTextDisplay::updateInvertShadow() -{ - if (invert_shadow_ != invert_shadow_property_->getBool()) { - require_update_texture_ = true; - } - invert_shadow_ = invert_shadow_property_->getBool(); -} - -void OverlayTextDisplay::updateVerticalDistance() -{ - vertical_dist_ = ver_dist_property_->getInt(); - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateHorizontalDistance() -{ - horizontal_dist_ = hor_dist_property_->getInt(); - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateVerticalAlignment() -{ - vertical_alignment_ = - VerticalAlignment{static_cast(ver_alignment_property_->getOptionInt())}; - - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateHorizontalAlignment() -{ - horizontal_alignment_ = - HorizontalAlignment{static_cast(hor_alignment_property_->getOptionInt())}; - - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateWidth() -{ - texture_width_ = width_property_->getInt(); - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateHeight() -{ - texture_height_ = height_property_->getInt(); - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateTextSize() -{ - text_size_ = text_size_property_->getInt(); - if (overtake_position_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateBGColor() -{ - QColor c = bg_color_property_->getColor(); - bg_color_.setRed(c.red()); - bg_color_.setGreen(c.green()); - bg_color_.setBlue(c.blue()); - if (overtake_bg_color_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateBGAlpha() -{ - bg_color_.setAlpha(bg_alpha_property_->getFloat() * 255.0); - if (overtake_bg_color_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateFGColor() -{ - QColor c = fg_color_property_->getColor(); - fg_color_.setRed(c.red()); - fg_color_.setGreen(c.green()); - fg_color_.setBlue(c.blue()); - if (overtake_fg_color_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateFGAlpha() -{ - fg_color_.setAlpha(fg_alpha_property_->getFloat() * 255.0); - if (overtake_fg_color_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateFont() -{ - int font_index = font_property_->getOptionInt(); - if (font_index < font_families_.size()) { - font_ = font_families_[font_index].toStdString(); - } else { - RVIZ_COMMON_LOG_ERROR_STREAM("Unexpected error at selecting font index " << font_index); - return; - } - if (overtake_fg_color_properties_) { - require_update_texture_ = true; - } -} - -void OverlayTextDisplay::updateLineWidth() -{ - line_width_ = line_width_property_->getInt(); - if (overtake_fg_color_properties_) { - require_update_texture_ = true; - } -} - -} // namespace autoware_overlay_rviz_plugin - -#include -PLUGINLIB_EXPORT_CLASS(autoware_overlay_rviz_plugin::OverlayTextDisplay, rviz_common::Display) diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/signal_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/signal_display.cpp index b2995327eb472..9add6336ece46 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/signal_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/signal_display.cpp @@ -39,11 +39,11 @@ namespace autoware_overlay_rviz_plugin SignalDisplay::SignalDisplay() { property_width_ = new rviz_common::properties::IntProperty( - "Width", 517, "Width of the overlay", this, SLOT(updateOverlaySize())); + "Width", 550, "Width of the overlay", this, SLOT(updateOverlaySize())); property_height_ = new rviz_common::properties::IntProperty( - "Height", 175, "Height of the overlay", this, SLOT(updateOverlaySize())); + "Height", 100, "Height of the overlay", this, SLOT(updateOverlaySize())); property_left_ = new rviz_common::properties::IntProperty( - "Left", 10, "Left position of the overlay", this, SLOT(updateOverlayPosition())); + "Left", 0, "Left position of the overlay", this, SLOT(updateOverlayPosition())); property_top_ = new rviz_common::properties::IntProperty( "Top", 10, "Top position of the overlay", this, SLOT(updateOverlayPosition())); property_signal_color_ = new rviz_common::properties::ColorProperty( @@ -111,67 +111,22 @@ void SignalDisplay::onInitialize() speed_limit_topic_property_->initialize(rviz_ros_node); traffic_topic_property_ = std::make_unique( - "Traffic Topic", "/perception/traffic_light_recognition/traffic_signals", - "autoware_perception/msgs/msg/TrafficSignalArray", "Topic for Traffic Light Data", this, + "Traffic Topic", + "/planning/scenario_planning/lane_driving/behavior_planning/debug/traffic_signal", + "autoware_perception/msgs/msg/TrafficSignal", "Topic for Traffic Light Data", this, SLOT(topic_updated_traffic())); traffic_topic_property_->initialize(rviz_ros_node); } void SignalDisplay::setupRosSubscriptions() { - // Don't create a node, just use the one from the parent class - auto rviz_node_ = context_->getRosNodeAbstraction().lock()->get_raw_node(); - - gear_sub_ = rviz_node_->create_subscription( - gear_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_auto_vehicle_msgs::msg::GearReport::SharedPtr msg) { - updateGearData(msg); - }); - - steering_sub_ = rviz_node_->create_subscription( - steering_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_auto_vehicle_msgs::msg::SteeringReport::SharedPtr msg) { - updateSteeringData(msg); - }); - - speed_sub_ = rviz_node_->create_subscription( - speed_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_auto_vehicle_msgs::msg::VelocityReport::SharedPtr msg) { - updateSpeedData(msg); - }); - - turn_signals_sub_ = - rviz_node_->create_subscription( - turn_signals_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_auto_vehicle_msgs::msg::TurnIndicatorsReport::SharedPtr msg) { - updateTurnSignalsData(msg); - }); - - hazard_lights_sub_ = - rviz_node_->create_subscription( - hazard_lights_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_auto_vehicle_msgs::msg::HazardLightsReport::SharedPtr msg) { - updateHazardLightsData(msg); - }); - - traffic_sub_ = rviz_node_->create_subscription( - traffic_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_perception_msgs::msg::TrafficSignalArray::SharedPtr msg) { - updateTrafficLightData(msg); - }); - - speed_limit_sub_ = rviz_node_->create_subscription( - speed_limit_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const tier4_planning_msgs::msg::VelocityLimit::ConstSharedPtr msg) { - updateSpeedLimitData(msg); - }); + topic_updated_gear(); + topic_updated_steering(); + topic_updated_speed(); + topic_updated_speed_limit(); + topic_updated_turn_signals(); + topic_updated_hazard_lights(); + topic_updated_traffic(); } SignalDisplay::~SignalDisplay() @@ -237,7 +192,7 @@ void SignalDisplay::onDisable() } void SignalDisplay::updateTrafficLightData( - const autoware_perception_msgs::msg::TrafficSignalArray::ConstSharedPtr msg) + const autoware_perception_msgs::msg::TrafficSignal::ConstSharedPtr msg) { std::lock_guard lock(property_mutex_); @@ -324,16 +279,18 @@ void SignalDisplay::drawWidget(QImage & hud) QPainter painter(&hud); painter.setRenderHint(QPainter::Antialiasing, true); - QRectF backgroundRect(0, 0, 322, hud.height()); + QRectF backgroundRect(0, 0, 550, hud.height()); drawHorizontalRoundedRectangle(painter, backgroundRect); // Draw components - if (steering_wheel_display_) { - steering_wheel_display_->drawSteeringWheel(painter, backgroundRect); - } if (gear_display_) { gear_display_->drawGearIndicator(painter, backgroundRect); } + + if (steering_wheel_display_) { + steering_wheel_display_->drawSteeringWheel(painter, backgroundRect); + } + if (speed_display_) { speed_display_->drawSpeedDisplay(painter, backgroundRect); } @@ -341,18 +298,12 @@ void SignalDisplay::drawWidget(QImage & hud) turn_signals_display_->drawArrows(painter, backgroundRect, property_signal_color_->getColor()); } - // a 27px space between the two halves of the HUD - - QRectF smallerBackgroundRect(340, 0, 190.0 / 2, hud.height()); - - drawVerticalRoundedRectangle(painter, smallerBackgroundRect); - if (traffic_display_) { - traffic_display_->drawTrafficLightIndicator(painter, smallerBackgroundRect); + traffic_display_->drawTrafficLightIndicator(painter, backgroundRect); } if (speed_limit_display_) { - speed_limit_display_->drawSpeedLimitIndicator(painter, smallerBackgroundRect); + speed_limit_display_->drawSpeedLimitIndicator(painter, backgroundRect); } painter.end(); @@ -363,8 +314,8 @@ void SignalDisplay::drawHorizontalRoundedRectangle( { painter.setRenderHint(QPainter::Antialiasing, true); QColor colorFromHSV; - colorFromHSV.setHsv(0, 0, 0); // Hue, Saturation, Value - colorFromHSV.setAlphaF(0.65); // Transparency + colorFromHSV.setHsv(0, 0, 29); // Hue, Saturation, Value + colorFromHSV.setAlphaF(0.60); // Transparency painter.setBrush(colorFromHSV); @@ -403,7 +354,9 @@ void SignalDisplay::updateOverlaySize() void SignalDisplay::updateOverlayPosition() { std::lock_guard lock(mutex_); - overlay_->setPosition(property_left_->getInt(), property_top_->getInt()); + overlay_->setPosition( + property_left_->getInt(), property_top_->getInt(), HorizontalAlignment::CENTER, + VerticalAlignment::TOP); queueRender(); } @@ -420,8 +373,7 @@ void SignalDisplay::topic_updated_gear() auto rviz_ros_node = context_->getRosNodeAbstraction().lock(); gear_sub_ = rviz_ros_node->get_raw_node()->create_subscription( - gear_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + gear_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), [this](const autoware_auto_vehicle_msgs::msg::GearReport::SharedPtr msg) { updateGearData(msg); }); @@ -434,8 +386,7 @@ void SignalDisplay::topic_updated_steering() auto rviz_ros_node = context_->getRosNodeAbstraction().lock(); steering_sub_ = rviz_ros_node->get_raw_node() ->create_subscription( - steering_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + steering_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), [this](const autoware_auto_vehicle_msgs::msg::SteeringReport::SharedPtr msg) { updateSteeringData(msg); }); @@ -448,8 +399,7 @@ void SignalDisplay::topic_updated_speed() auto rviz_ros_node = context_->getRosNodeAbstraction().lock(); speed_sub_ = rviz_ros_node->get_raw_node() ->create_subscription( - speed_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + speed_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), [this](const autoware_auto_vehicle_msgs::msg::VelocityReport::SharedPtr msg) { updateSpeedData(msg); }); @@ -463,7 +413,7 @@ void SignalDisplay::topic_updated_speed_limit() speed_limit_sub_ = rviz_ros_node->get_raw_node()->create_subscription( speed_limit_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + rclcpp::QoS(rclcpp::KeepLast(10)).transient_local(), [this](const tier4_planning_msgs::msg::VelocityLimit::ConstSharedPtr msg) { updateSpeedLimitData(msg); }); @@ -478,8 +428,7 @@ void SignalDisplay::topic_updated_turn_signals() turn_signals_sub_ = rviz_ros_node->get_raw_node() ->create_subscription( - turn_signals_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + turn_signals_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), [this](const autoware_auto_vehicle_msgs::msg::TurnIndicatorsReport::SharedPtr msg) { updateTurnSignalsData(msg); }); @@ -494,8 +443,7 @@ void SignalDisplay::topic_updated_hazard_lights() hazard_lights_sub_ = rviz_ros_node->get_raw_node() ->create_subscription( - hazard_lights_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), + hazard_lights_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), [this](const autoware_auto_vehicle_msgs::msg::HazardLightsReport::SharedPtr msg) { updateHazardLightsData(msg); }); @@ -506,14 +454,12 @@ void SignalDisplay::topic_updated_traffic() // resubscribe to the topic traffic_sub_.reset(); auto rviz_ros_node = context_->getRosNodeAbstraction().lock(); - traffic_sub_ = - rviz_ros_node->get_raw_node() - ->create_subscription( - traffic_topic_property_->getTopicStd(), - rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable(), - [this](const autoware_perception_msgs::msg::TrafficSignalArray::SharedPtr msg) { - updateTrafficLightData(msg); - }); + traffic_sub_ = rviz_ros_node->get_raw_node() + ->create_subscription( + traffic_topic_property_->getTopicStd(), rclcpp::QoS(rclcpp::KeepLast(10)), + [this](const autoware_perception_msgs::msg::TrafficSignal::SharedPtr msg) { + updateTrafficLightData(msg); + }); } } // namespace autoware_overlay_rviz_plugin diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_display.cpp index b1df14956d16c..5c5342259005b 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_display.cpp @@ -85,7 +85,7 @@ void SpeedDisplay::drawSpeedDisplay(QPainter & painter, const QRectF & backgroun backgroundRect.width() / 2 - referenceRect.width() / 2 - 5, backgroundRect.height() / 2); QString speedNumber = QString::number(current_speed_, 'f', 0); - int fontSize = 60; + int fontSize = 40; QFont speedFont("Quicksand", fontSize); painter.setFont(speedFont); @@ -94,16 +94,17 @@ void SpeedDisplay::drawSpeedDisplay(QPainter & painter, const QRectF & backgroun // Center the speed number in the backgroundRect QPointF speedPos( - backgroundRect.center().x() - speedNumberRect.width() / 2, backgroundRect.center().y()); + backgroundRect.center().x() - speedNumberRect.width() / 2, + backgroundRect.center().y() + speedNumberRect.bottom()); painter.setPen(gray); painter.drawText(speedPos, speedNumber); - QFont unitFont("Quicksand", 14); + QFont unitFont("Quicksand", 8, QFont::DemiBold); painter.setFont(unitFont); QString speedUnit = "km/h"; QRect unitRect = painter.fontMetrics().boundingRect(speedUnit); QPointF unitPos( - (backgroundRect.width() / 2 - unitRect.width() / 2), referencePos.y() + unitRect.height()); + (backgroundRect.width() / 2 - unitRect.width() / 2), referencePos.y() + unitRect.height() + 15); painter.drawText(unitPos, speedUnit); } diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_limit_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_limit_display.cpp index 6913ef6a48ecd..4c83b4a73c0c2 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_limit_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/speed_limit_display.cpp @@ -24,6 +24,7 @@ #include #include #include +#include #include #include @@ -99,10 +100,9 @@ void SpeedLimitDisplay::drawSpeedLimitIndicator(QPainter & painter, const QRectF } // Define the area for the outer circle - QRectF outerCircleRect = backgroundRect; - outerCircleRect.setWidth(backgroundRect.width() - 30); - outerCircleRect.setHeight(backgroundRect.width() - 30); - outerCircleRect.moveTopLeft(QPointF(backgroundRect.left() + 15, backgroundRect.top() + 10)); + QRectF outerCircleRect = QRectF(45, 45, 45, 45); + outerCircleRect.moveTopRight( + QPointF(backgroundRect.right() - 44, backgroundRect.top() + outerCircleRect.height() / 2 + 5)); // Now use borderColor for drawing painter.setPen(QPen(borderColor, 2, Qt::SolidLine, Qt::RoundCap, Qt::RoundJoin)); @@ -112,24 +112,30 @@ void SpeedLimitDisplay::drawSpeedLimitIndicator(QPainter & painter, const QRectF // Define the area for the inner circle QRectF innerCircleRect = outerCircleRect; - innerCircleRect.setWidth(outerCircleRect.width() / 1.25); - innerCircleRect.setHeight(outerCircleRect.height() / 1.25); + innerCircleRect.setWidth(outerCircleRect.width() / 1.09); + innerCircleRect.setHeight(outerCircleRect.height() / 1.09); innerCircleRect.moveCenter(outerCircleRect.center()); + QRectF innerCircleRect2 = innerCircleRect; + painter.setRenderHint(QPainter::Antialiasing, true); QColor colorFromHSV; - colorFromHSV.setHsv(0, 0, 0); // Hue, Saturation, Value - + colorFromHSV.setHsv(0, 0, 29); // Hue, Saturation, Value + colorFromHSV.setAlphaF(0.60); // Transparency painter.setBrush(colorFromHSV); painter.drawEllipse(innerCircleRect); + // Add a second inner circle as a mask to make the speed limit indicator look like a ring + // and follow the rest of the background color as close as possible + painter.drawEllipse(innerCircleRect2); + int current_limit_int = std::round(current_limit * 3.6); // Define the text to be drawn QString text = QString::number(current_limit_int); // Set the font and color for the text - QFont font = QFont("Quicksand", 24, QFont::Bold); + QFont font = QFont("Quicksand", 16, QFont::Bold); painter.setFont(font); // #C2C2C2 diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/steering_wheel_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/steering_wheel_display.cpp index 5882d7780dc92..45ebcde086165 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/steering_wheel_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/steering_wheel_display.cpp @@ -82,8 +82,8 @@ void SteeringWheelDisplay::drawSteeringWheel(QPainter & painter, const QRectF & // Rotate the wheel float steeringAngle = steering_angle_; // No need to round here // Calculate the position - int wheelCenterX = backgroundRect.right() - wheel.width() - 17.5; - int wheelCenterY = backgroundRect.height() - wheel.height() + 15; + int wheelCenterX = backgroundRect.left() + wheel.width() + 54 + 54; + int wheelCenterY = backgroundRect.height() / 2; // Rotate the wheel image QTransform rotationTransform; diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/traffic_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/traffic_display.cpp index 4fea8f78b80da..f6d232709a333 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/traffic_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/traffic_display.cpp @@ -48,7 +48,7 @@ TrafficDisplay::TrafficDisplay() } void TrafficDisplay::updateTrafficLightData( - const autoware_perception_msgs::msg::TrafficSignalArray::ConstSharedPtr & msg) + const autoware_perception_msgs::msg::TrafficSignal::ConstSharedPtr & msg) { current_traffic_ = *msg; } @@ -62,16 +62,14 @@ void TrafficDisplay::drawTrafficLightIndicator(QPainter & painter, const QRectF painter.setBrush(QBrush(tl_gray_, Qt::SolidPattern)); painter.setPen(Qt::NoPen); // Define the area for the circle (background) - QRectF circleRect = backgroundRect; - circleRect.setWidth(backgroundRect.width() - 30); - circleRect.setHeight(backgroundRect.width() - 30); + QRectF circleRect = QRectF(50, 50, 50, 50); circleRect.moveTopRight(QPointF( - backgroundRect.left() + circleRect.width() + 15, - backgroundRect.top() + circleRect.height() + 30)); + backgroundRect.right() - circleRect.width() - 75, + backgroundRect.top() + circleRect.height() / 2)); painter.drawEllipse(circleRect); - if (!current_traffic_.signals.empty()) { - switch (current_traffic_.signals[0].elements[0].color) { + if (!current_traffic_.elements.empty()) { + switch (current_traffic_.elements[0].color) { case 1: painter.setBrush(QBrush(tl_red_)); painter.drawEllipse(circleRect); @@ -96,7 +94,7 @@ void TrafficDisplay::drawTrafficLightIndicator(QPainter & painter, const QRectF } // Scaling factor (e.g., 1.5 for 150% size) - float scaleFactor = 1.00; + float scaleFactor = 0.75; // Calculate the scaled size QSize scaledSize = traffic_light_image_.size() * scaleFactor; diff --git a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/turn_signals_display.cpp b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/turn_signals_display.cpp index b6d37062bf08b..1aaa5871015a8 100644 --- a/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/turn_signals_display.cpp +++ b/common/autoware_overlay_rviz_plugin/autoware_overlay_rviz_plugin/src/turn_signals_display.cpp @@ -72,12 +72,12 @@ void TurnSignalsDisplay::updateHazardLightsData( void TurnSignalsDisplay::drawArrows( QPainter & painter, const QRectF & backgroundRect, const QColor & color) { - QImage scaledLeftArrow = arrowImage.scaled(64, 43, Qt::KeepAspectRatio, Qt::SmoothTransformation); + QImage scaledLeftArrow = arrowImage.scaled(50, 32, Qt::KeepAspectRatio, Qt::SmoothTransformation); scaledLeftArrow = coloredImage(scaledLeftArrow, gray); QImage scaledRightArrow = scaledLeftArrow.mirrored(true, false); - int arrowYPos = (backgroundRect.height() / 3 - scaledLeftArrow.height() / 2); - int leftArrowXPos = backgroundRect.width() / 4 - scaledLeftArrow.width(); // Adjust as needed - int rightArrowXPos = backgroundRect.width() * 3 / 4; // Adjust as needed + int arrowYPos = (backgroundRect.height() / 2 - scaledLeftArrow.height() / 2 - 4); + int leftArrowXPos = backgroundRect.left() + scaledLeftArrow.width() * 2 + 180; + int rightArrowXPos = backgroundRect.right() - scaledRightArrow.width() * 3 - 175; bool leftActive = (current_turn_signal_ == autoware_auto_vehicle_msgs::msg::TurnIndicatorsReport::ENABLE_LEFT || diff --git a/common/glog_component/CMakeLists.txt b/common/glog_component/CMakeLists.txt index c2a68d0130b37..a233914cc1524 100644 --- a/common/glog_component/CMakeLists.txt +++ b/common/glog_component/CMakeLists.txt @@ -8,7 +8,7 @@ autoware_package() ament_auto_add_library(glog_component SHARED src/glog_component.cpp ) -target_link_libraries(glog_component glog) +target_link_libraries(glog_component glog::glog) rclcpp_components_register_node(glog_component PLUGIN "GlogComponent" diff --git a/common/glog_component/package.xml b/common/glog_component/package.xml index 0d6e7daac1de3..6feedd090f2c6 100644 --- a/common/glog_component/package.xml +++ b/common/glog_component/package.xml @@ -13,7 +13,7 @@ ament_cmake_auto autoware_cmake - libgoogle-glog-dev + glog rclcpp rclcpp_components diff --git a/common/glog_component/src/glog_component.cpp b/common/glog_component/src/glog_component.cpp index 9e7e70da6c884..7fd9c923d23c9 100644 --- a/common/glog_component/src/glog_component.cpp +++ b/common/glog_component/src/glog_component.cpp @@ -17,8 +17,10 @@ GlogComponent::GlogComponent(const rclcpp::NodeOptions & node_options) : Node("glog_component", node_options) { - google::InitGoogleLogging("glog_component"); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging("glog_component"); + google::InstallFailureSignalHandler(); + } } #include diff --git a/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.cpp b/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.cpp index 5c1c98488b0f6..d89f13ce74d02 100644 --- a/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.cpp +++ b/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.cpp @@ -34,13 +34,19 @@ namespace tier4_calibration_rviz_plugin AccelBrakeMapCalibratorButtonPanel::AccelBrakeMapCalibratorButtonPanel(QWidget * parent) : rviz_common::Panel(parent) { - topic_label_ = new QLabel("Topic name of update suggest "); + topic_label_ = new QLabel("topic: "); topic_label_->setAlignment(Qt::AlignCenter); topic_edit_ = new QLineEdit("/vehicle/calibration/accel_brake_map_calibrator/output/update_suggest"); connect(topic_edit_, SIGNAL(textEdited(QString)), SLOT(editTopic())); + service_label_ = new QLabel("service: "); + service_label_->setAlignment(Qt::AlignCenter); + + service_edit_ = new QLineEdit("/vehicle/calibration/accel_brake_map_calibrator/update_map_dir"); + connect(service_edit_, SIGNAL(textEdited(QString)), SLOT(editService())); + calibration_button_ = new QPushButton("Wait for subscribe topic"); calibration_button_->setEnabled(false); connect(calibration_button_, SIGNAL(clicked(bool)), SLOT(pushCalibrationButton())); @@ -56,8 +62,13 @@ AccelBrakeMapCalibratorButtonPanel::AccelBrakeMapCalibratorButtonPanel(QWidget * topic_layout->addWidget(topic_label_); topic_layout->addWidget(topic_edit_); + auto * service_layout = new QHBoxLayout; + service_layout->addWidget(service_label_); + service_layout->addWidget(service_edit_); + auto * v_layout = new QVBoxLayout; v_layout->addLayout(topic_layout); + v_layout->addLayout(service_layout); v_layout->addWidget(calibration_button_); v_layout->addWidget(status_label_); @@ -75,7 +86,7 @@ void AccelBrakeMapCalibratorButtonPanel::onInitialize() &AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest, this, std::placeholders::_1)); client_ = raw_node->create_client( - "/vehicle/calibration/accel_brake_map_calibrator/update_map_dir"); + service_edit_->text().toStdString()); } void AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest( @@ -85,6 +96,12 @@ void AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest( return; } + if (!client_ || !client_->service_is_ready()) { + calibration_button_->setText("wait for service"); + calibration_button_->setEnabled(false); + return; + } + if (msg->data) { status_label_->setText("Ready"); status_label_->setStyleSheet("QLabel { background-color : white;}"); @@ -98,17 +115,34 @@ void AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest( void AccelBrakeMapCalibratorButtonPanel::editTopic() { - update_suggest_sub_.reset(); rclcpp::Node::SharedPtr raw_node = this->getDisplayContext()->getRosNodeAbstraction().lock()->get_raw_node(); - update_suggest_sub_ = raw_node->create_subscription( - topic_edit_->text().toStdString(), 10, - std::bind( - &AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest, this, std::placeholders::_1)); + try { + update_suggest_sub_.reset(); + update_suggest_sub_ = raw_node->create_subscription( + topic_edit_->text().toStdString(), 10, + std::bind( + &AccelBrakeMapCalibratorButtonPanel::callbackUpdateSuggest, this, std::placeholders::_1)); + } catch (const rclcpp::exceptions::InvalidTopicNameError & e) { + RCLCPP_WARN_STREAM(raw_node->get_logger(), e.what()); + } calibration_button_->setText("Wait for subscribe topic"); calibration_button_->setEnabled(false); } +void AccelBrakeMapCalibratorButtonPanel::editService() +{ + rclcpp::Node::SharedPtr raw_node = + this->getDisplayContext()->getRosNodeAbstraction().lock()->get_raw_node(); + try { + client_.reset(); + client_ = raw_node->create_client( + service_edit_->text().toStdString()); + } catch (const rclcpp::exceptions::InvalidServiceNameError & e) { + RCLCPP_WARN_STREAM(raw_node->get_logger(), e.what()); + } +} + void AccelBrakeMapCalibratorButtonPanel::pushCalibrationButton() { // lock button diff --git a/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.hpp b/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.hpp index e26789c9f120f..70ebe0631fa21 100644 --- a/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.hpp +++ b/common/tier4_calibration_rviz_plugin/src/accel_brake_map_calibrator_button_panel.hpp @@ -46,6 +46,7 @@ class AccelBrakeMapCalibratorButtonPanel : public rviz_common::Panel public Q_SLOTS: // NOLINT for Qt void editTopic(); + void editService(); void pushCalibrationButton(); protected: @@ -56,6 +57,8 @@ public Q_SLOTS: // NOLINT for Qt QLabel * topic_label_; QLineEdit * topic_edit_; + QLabel * service_label_; + QLineEdit * service_edit_; QPushButton * calibration_button_; QLabel * status_label_; }; diff --git a/common/tier4_logging_level_configure_rviz_plugin/README.md b/common/tier4_logging_level_configure_rviz_plugin/README.md index 8df17a82e3de7..ed400e521e6aa 100644 --- a/common/tier4_logging_level_configure_rviz_plugin/README.md +++ b/common/tier4_logging_level_configure_rviz_plugin/README.md @@ -1,9 +1,72 @@ # tier4_logging_level_configure_rviz_plugin -This package provides an rviz_plugin that can easily change the logger level of each node +This package provides an rviz_plugin that can easily change the logger level of each node. ![tier4_logging_level_configure_rviz_plugin](tier4_logging_level_configure_rviz_plugin.png) This plugin dispatches services to the "logger name" associated with "nodes" specified in YAML, adjusting the logger level. -As of November 2023, in ROS 2 Humble, users are required to initiate a service server in the node to use this feature. (This might be integrated into ROS standards in the future.) For easy service server generation, you can use the [LoggerLevelConfigure](https://github.com/autowarefoundation/autoware.universe/blob/main/common/tier4_autoware_utils/include/tier4_autoware_utils/ros/logger_level_configure.hpp) utility. +!!! Warning + + It is highly recommended to use this plugin when you're attempting to print any debug information. Furthermore, it is strongly advised to avoid using the logging level INFO, as it might flood the terminal with your information, potentially causing other useful information to be missed. + +!!! note + + To add your logger to the list, simply include the `node_name` and `logger_name` in the [logger_config.yaml](https://github.com/autowarefoundation/autoware.universe/blob/main/common/tier4_logging_level_configure_rviz_plugin/config/logger_config.yaml) under the corresponding component or module. If the relevant component or module is not listed, you may add them yourself. + +!!! note + + As of November 2023, in ROS 2 Humble, users are required to initiate a service server in the node to use this feature. (This might be integrated into ROS standards in the future.) For easy service server generation, you can use the [LoggerLevelConfigure](https://github.com/autowarefoundation/autoware.universe/blob/main/common/tier4_autoware_utils/include/tier4_autoware_utils/ros/logger_level_configure.hpp) utility. + +## How to use the plugin + +In RVIZ2, go to Panels and add LoggingLevelConfigureRVizPlugin. Then, search for the node you're interested in and select the corresponding logging level to print the logs. + +## How to add or find your logger name + +Because there are no available ROS 2 CLI commands to list loggers, there isn't a straightforward way to check your logger name. Additionally, the following assumes that you already know which node you're working with. + +### For logger as a class member variable + +If your class doesn't have an `rclcpp::Logger` member variable, you can start by including one yourself: + +```c++ +mutable rclcpp::Logger logger_; +``` + +If your node already has a logger, it should, under normal circumstances, be similar to the node's name. + +For instance, if the node name is `/some_component/some_node/node_child`, the `logger_name` would be `some_component.some_node.node_child`. + +Should your log not print as expected, one approach is to initially set your logging level in the code to info, like so: + +```c++ +RCLCPP_INFO(logger_, "Print something here."); +``` + +This will result in something like the following being printed in the terminal: + +```shell +[component_container_mt-36] [INFO 1711949149.735437551] [logger_name]: Print something here. (func() at /path/to/code:line_number) +``` + +Afterward, you can simply copy the `logger_name`. + +!!! warning + + Remember to revert your code to the appropriate logging level after testing. + ```c++ + RCLCPP_DEBUG(logger_, "Print something here."); + ``` + +### For libraries + +When dealing with libraries, such as utility functions, you may need to add the logger manually. Here's an example: + +```c++ +RCLCPP_WARN( + rclcpp::get_logger("some_component").get_child("some_child").get_child("some_child2"), + "Print something here."); +``` + +In this scenario, the `logger_name` would be `some_component.some_child.some_child2`. diff --git a/common/tier4_logging_level_configure_rviz_plugin/config/logger_config.yaml b/common/tier4_logging_level_configure_rviz_plugin/config/logger_config.yaml index a298967a31af9..6b1214b133af4 100644 --- a/common/tier4_logging_level_configure_rviz_plugin/config/logger_config.yaml +++ b/common/tier4_logging_level_configure_rviz_plugin/config/logger_config.yaml @@ -33,10 +33,14 @@ Planning: logger_name: planning.scenario_planning.lane_driving.behavior_planning.behavior_path_planner - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner logger_name: tier4_autoware_utils + - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner + logger_name: behavior_path_planner.path_shifter behavior_path_planner_avoidance: - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner logger_name: planning.scenario_planning.lane_driving.behavior_planning.behavior_path_planner.avoidance + - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner + logger_name: planning.scenario_planning.lane_driving.behavior_planning.behavior_path_planner.avoidance.utils behavior_path_planner_goal_planner: - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner @@ -49,10 +53,14 @@ Planning: behavior_path_avoidance_by_lane_change: - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner logger_name: lane_change.AVOIDANCE_BY_LANE_CHANGE + - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner + logger_name: lane_change.utils behavior_path_lane_change: - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner logger_name: lane_change.NORMAL + - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner + logger_name: lane_change.utils behavior_velocity_planner: - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_velocity_planner @@ -76,6 +84,10 @@ Planning: - node_name: /planning/scenario_planning/motion_velocity_smoother logger_name: tier4_autoware_utils + route_handler: + - node_name: /planning/scenario_planning/lane_driving/behavior_planning/behavior_path_planner + logger_name: route_handler + # ============================================================ # control # ============================================================ diff --git a/common/tier4_screen_capture_rviz_plugin/README.md b/common/tier4_screen_capture_rviz_plugin/README.md index d108d43a5dc41..d16c19c343017 100644 --- a/common/tier4_screen_capture_rviz_plugin/README.md +++ b/common/tier4_screen_capture_rviz_plugin/README.md @@ -4,6 +4,13 @@ This plugin captures the screen of rviz. +## Interface + +| Name | Type | Description | +| ---------------------------- | ------------------------ | ---------------------------------- | +| `/debug/capture/video` | `std_srvs::srv::Trigger` | Trigger to start screen capturing. | +| `/debug/capture/screen_shot` | `std_srvs::srv::Trigger` | Trigger to capture screen shot. | + ## Assumptions / Known limits This is only for debug or analyze. diff --git a/common/tier4_screen_capture_rviz_plugin/package.xml b/common/tier4_screen_capture_rviz_plugin/package.xml index 38479dc3c38ee..180bf9eedc9ca 100644 --- a/common/tier4_screen_capture_rviz_plugin/package.xml +++ b/common/tier4_screen_capture_rviz_plugin/package.xml @@ -5,6 +5,8 @@ 0.0.0 The screen capture package Taiki, Tanaka + Satoshi Ota + Kyoichi Sugahara Apache License 2.0 ament_cmake_auto diff --git a/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.cpp b/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.cpp index 5ec8f9b02d0e8..cad828903e0d3 100644 --- a/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.cpp +++ b/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.cpp @@ -81,7 +81,7 @@ AutowareScreenCapturePanel::AutowareScreenCapturePanel(QWidget * parent) state_ = State::WAITING_FOR_CAPTURE; } -void AutowareScreenCapturePanel::onCaptureTrigger( +void AutowareScreenCapturePanel::onCaptureVideoTrigger( [[maybe_unused]] const std_srvs::srv::Trigger::Request::SharedPtr req, const std_srvs::srv::Trigger::Response::SharedPtr res) { @@ -90,12 +90,24 @@ void AutowareScreenCapturePanel::onCaptureTrigger( res->message = stateToString(state_); } +void AutowareScreenCapturePanel::onCaptureScreenShotTrigger( + [[maybe_unused]] const std_srvs::srv::Trigger::Request::SharedPtr req, + const std_srvs::srv::Trigger::Response::SharedPtr res) +{ + onClickScreenCapture(); + res->success = true; + res->message = stateToString(state_); +} + void AutowareScreenCapturePanel::onInitialize() { raw_node_ = this->getDisplayContext()->getRosNodeAbstraction().lock()->get_raw_node(); - capture_service_ = raw_node_->create_service( - "/debug/service/capture_screen", - std::bind(&AutowareScreenCapturePanel::onCaptureTrigger, this, _1, _2)); + capture_video_srv_ = raw_node_->create_service( + "/debug/capture/video", + std::bind(&AutowareScreenCapturePanel::onCaptureVideoTrigger, this, _1, _2)); + capture_screen_shot_srv_ = raw_node_->create_service( + "/debug/capture/screen_shot", + std::bind(&AutowareScreenCapturePanel::onCaptureScreenShotTrigger, this, _1, _2)); } void onPrefixChanged() diff --git a/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.hpp b/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.hpp index 8ddd390206b81..5c4d16f57da82 100644 --- a/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.hpp +++ b/common/tier4_screen_capture_rviz_plugin/src/screen_capture_panel.hpp @@ -60,7 +60,10 @@ class AutowareScreenCapturePanel : public rviz_common::Panel void onTimer(); void save(rviz_common::Config config) const override; void load(const rviz_common::Config & config) override; - void onCaptureTrigger( + void onCaptureVideoTrigger( + const std_srvs::srv::Trigger::Request::SharedPtr req, + const std_srvs::srv::Trigger::Response::SharedPtr res); + void onCaptureScreenShotTrigger( const std_srvs::srv::Trigger::Request::SharedPtr req, const std_srvs::srv::Trigger::Response::SharedPtr res); @@ -98,7 +101,8 @@ public Q_SLOTS: } protected: - rclcpp::Service::SharedPtr capture_service_; + rclcpp::Service::SharedPtr capture_video_srv_; + rclcpp::Service::SharedPtr capture_screen_shot_srv_; rclcpp::Node::SharedPtr raw_node_; }; diff --git a/common/tier4_simulated_clock_rviz_plugin/README.md b/common/tier4_simulated_clock_rviz_plugin/README.md index 73e53b69279ff..a6218f32b988c 100644 --- a/common/tier4_simulated_clock_rviz_plugin/README.md +++ b/common/tier4_simulated_clock_rviz_plugin/README.md @@ -10,18 +10,37 @@ This plugin allows publishing and controlling the simulated ROS time. | -------- | --------------------------- | -------------------------- | | `/clock` | `rosgraph_msgs::msg::Clock` | the current simulated time | -## HowToUse +## How to use the plugin + +1. Launch [planning simulator](https://autowarefoundation.github.io/autoware-documentation/main/tutorials/ad-hoc-simulation/planning-simulation/#1-launch-autoware) with `use_sim_time:=true`. + + ```shell + ros2 launch autoware_launch planning_simulator.launch.xml map_path:=$HOME/autoware_map/sample-map-planning vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit use_sim_time:=true + ``` + + > Warning + > If you launch the planning simulator without adding the `tier4_simulated_clock_rviz_plugin`, your simulation will not be running. You'll not even be able to place the initial and the goal poses. + +2. Start rviz and select panels/Add new panel. -1. Start rviz and select panels/Add new panel. ![select_panel](./images/select_panels.png) -2. Select tier4_clock_rviz_plugin/SimulatedClock and press OK. + +3. Select tier4_clock_rviz_plugin/SimulatedClock and press OK. + ![select_clock_plugin](./images/select_clock_plugin.png) -3. Use the added panel to control how the simulated clock is published. + +4. Use the added panel to control how the simulated clock is published. + ![use_clock_plugin](./images/use_clock_plugin.png) - - Pause button: pause/resume the clock. - - Speed: speed of the clock relative to the system clock. - - Rate: publishing rate of the clock. - - Step button: advance the clock by the specified time step. - - Time step: value used to advance the clock when pressing the step button d). - - Time unit: time unit associated with the value from e). +
    +
  1. Pause button: pause/resume the clock.
    2. +
  2. Speed: speed of the clock relative to the system clock.
    3. +
  3. Rate: publishing rate of the clock.
    4. +
  4. Step button: advance the clock by the specified time step.
    5. +
  5. Time step: value used to advance the clock when pressing the step button d).
    6. +
  6. Time unit: time unit associated with the value from e).
    7. +
+ + > Warning + > If you set the time step too large, your simulation will go haywire. diff --git a/common/tvm_utility/example/yolo_v2_tiny/main.cpp b/common/tvm_utility/example/yolo_v2_tiny/main.cpp index 8a89436170894..8fd0cde3c306d 100644 --- a/common/tvm_utility/example/yolo_v2_tiny/main.cpp +++ b/common/tvm_utility/example/yolo_v2_tiny/main.cpp @@ -200,6 +200,8 @@ class PostProcessorYoloV2Tiny : public tvm_utility::pipeline::PostProcessor class_probabilities{}; float p_total = 0; diff --git a/control/autonomous_emergency_braking/README.md b/control/autonomous_emergency_braking/README.md index 28b7636ba82ac..7a7bf212320e0 100644 --- a/control/autonomous_emergency_braking/README.md +++ b/control/autonomous_emergency_braking/README.md @@ -86,20 +86,55 @@ where $v$ and $\omega$ are current longitudinal velocity and angular velocity re ### 3. Get target obstacles from the input point cloud -After generating the ego predicted path, we select target obstacles from the input point cloud. This obstacle filtering has two major steps, which are rough filtering and rigorous filtering. +After generating the ego predicted path, we select target obstacles from the input point cloud. This obstacle filtering has three major steps, which are rough filtering, noise filtering with clustering and rigorous filtering. #### Rough filtering -In rough filtering step, we select target obstacle with simple filter. Create a search area up to a certain distance (default 5[m]) away from the predicted path of the ego vehicle and ignore the point cloud (obstacles) that are not within it. The image of the rough filtering is illustrated below. +In rough filtering step, we select target obstacle with simple filter. Create a search area up to a certain distance (default is half of the ego vehicle width plus the `path_footprint_extra_margin` parameter) away from the predicted path of the ego vehicle and ignore the point cloud that are not within it. The image of the rough filtering is illustrated below. ![rough_filtering](./image/obstacle_filtering_1.drawio.svg) +#### Noise filtering with clustering and convex hulls + +To prevent the AEB from considering noisy points, euclidean clustering is performed on the filtered point cloud. The points in the point cloud that are not close enough to other points to form a cluster are discarded. The parameters `cluster_tolerance`, `minimum_cluster_size` and `maximum_cluster_size` can be used to tune the clustering and the size of objects to be ignored, for more information about the clustering method used by the AEB module, please check the official documentation on euclidean clustering of the PCL library: . + +Furthermore, a 2D convex hull is created around each detected cluster, the vertices of each hull represent the most extreme/outside points of the cluster. These vertices are then checked in the next step. + #### Rigorous filtering -After rough filtering, it performs a geometric collision check to determine whether the filtered obstacles actually have possibility to collide with the ego vehicle. In this check, the ego vehicle is represented as a rectangle, and the point cloud obstacles are represented as points. +After Noise filtering, it performs a geometric collision check to determine whether the filtered obstacles/hull vertices actually have possibility to collide with the ego vehicle. In this check, the ego vehicle is represented as a rectangle, and the point cloud obstacles are represented as points. Only the vertices with a possibility of collision are kept. ![rigorous_filtering](./image/obstacle_filtering_2.drawio.svg) +Finally, the vertex that is closest to the ego vehicle is chosen as the candidate for collision checking: Since rss distance is used to judge if a collision will happen or not, if the closest vertex to the ego is deemed to be safe, the rest of the vertices (and the points in the clusters) will also be safe. + +#### Obstacle velocity estimation + +Once the position of the closest obstacle/point is determined, the AEB modules uses the history of previously detected objects to estimate the closest object speed using the following equations: + +$$ +d_{t} = o_{time stamp} - prev_{time stamp} +$$ + +$$ +d_{pos} = norm(o_{pos} - prev_{pos}) +$$ + +$$ +v_{norm} = d_{pos} / d_{t} +$$ + +Where $o_{time stamp}$ and $prev_{time stamp}$ are the timestamps of the point clouds used to detect the current closest object and the closest object of the previous point cloud frame, and $o_{pos}$ and $prev_{pos}$ are the positions of those objects, respectively. + +Finally, the velocity vector is compared against the ego's predicted path to get the longitudinal velocity $v_{obj}$: + +$$ +v_{obj} = v_{norm} * Cos(yaw_{diff}) + v_{ego} +$$ + +where $yaw_{diff}$ is the difference in yaw between the ego path and the displacement vector $$v_{pos} = o_{pos} - prev_{pos} $$ and $v_{ego}$ is the ego's speed, which accounts for the movement of points caused by the ego moving and not the object. +All these equations are performed disregarding the z axis (in 2D). + ### 4. Collision check with target obstacles In the fourth step, it checks the collision with filtered obstacles using RSS distance. RSS is formulated as: diff --git a/control/autonomous_emergency_braking/config/autonomous_emergency_braking.param.yaml b/control/autonomous_emergency_braking/config/autonomous_emergency_braking.param.yaml index 82d5a4f12e002..68a42383feb1f 100644 --- a/control/autonomous_emergency_braking/config/autonomous_emergency_braking.param.yaml +++ b/control/autonomous_emergency_braking/config/autonomous_emergency_braking.param.yaml @@ -1,22 +1,38 @@ /**: ros__parameters: - publish_debug_pointcloud: false + # Ego path calculation use_predicted_trajectory: true - use_imu_path: true + use_imu_path: false + min_generated_path_length: 0.5 + imu_prediction_time_horizon: 1.5 + imu_prediction_time_interval: 0.1 + mpc_prediction_time_horizon: 1.5 + mpc_prediction_time_interval: 0.1 + + # Debug + publish_debug_pointcloud: false + + # Point cloud partitioning detection_range_min_height: 0.0 detection_range_max_height_margin: 0.0 voxel_grid_x: 0.05 voxel_grid_y: 0.05 voxel_grid_z: 100000.0 - min_generated_path_length: 0.5 + + # Point cloud cropping expand_width: 0.1 + path_footprint_extra_margin: 4.0 + + # Point cloud clustering + cluster_tolerance: 0.1 #[m] + minimum_cluster_size: 10 + maximum_cluster_size: 10000 + + # RSS distance collision check longitudinal_offset: 2.0 t_response: 1.0 a_ego_min: -3.0 a_obj_min: -1.0 - imu_prediction_time_horizon: 1.5 - imu_prediction_time_interval: 0.1 - mpc_prediction_time_horizon: 1.5 - mpc_prediction_time_interval: 0.1 - collision_keeping_sec: 0.0 + collision_keeping_sec: 2.0 + previous_obstacle_keep_time: 1.0 aeb_hz: 10.0 diff --git a/control/autonomous_emergency_braking/include/autonomous_emergency_braking/node.hpp b/control/autonomous_emergency_braking/include/autonomous_emergency_braking/node.hpp index b8aad1c80dfea..43fb310b17416 100644 --- a/control/autonomous_emergency_braking/include/autonomous_emergency_braking/node.hpp +++ b/control/autonomous_emergency_braking/include/autonomous_emergency_braking/node.hpp @@ -16,8 +16,10 @@ #define AUTONOMOUS_EMERGENCY_BRAKING__NODE_HPP_ #include +#include #include #include +#include #include #include @@ -39,12 +41,13 @@ #include #include +#include +#include #include -#include #include #include +#include #include - namespace autoware::motion::control::autonomous_emergency_braking { @@ -64,7 +67,6 @@ using visualization_msgs::msg::Marker; using visualization_msgs::msg::MarkerArray; using Path = std::vector; using Vector3 = geometry_msgs::msg::Vector3; - struct ObjectData { rclcpp::Time stamp; @@ -79,30 +81,146 @@ class CollisionDataKeeper public: explicit CollisionDataKeeper(rclcpp::Clock::SharedPtr clock) { clock_ = clock; } - void setTimeout(const double timeout_sec) { timeout_sec_ = timeout_sec; } + void setTimeout(const double collision_keep_time, const double previous_obstacle_keep_time) + { + collision_keep_time_ = collision_keep_time; + previous_obstacle_keep_time_ = previous_obstacle_keep_time; + } + + std::pair getTimeout() + { + return {collision_keep_time_, previous_obstacle_keep_time_}; + } - bool checkExpired() + bool checkObjectDataExpired(std::optional & data, const double timeout) { - if (data_ && (clock_->now() - data_->stamp).seconds() > timeout_sec_) { - data_.reset(); + if (!data.has_value()) return true; + const auto now = clock_->now(); + const auto & prev_obj = data.value(); + const auto & data_time_stamp = prev_obj.stamp; + if ((now - data_time_stamp).nanoseconds() * 1e-9 > timeout) { + data = std::nullopt; + return true; } - return (data_ == nullptr); + return false; + } + + bool checkCollisionExpired() + { + return this->checkObjectDataExpired(closest_object_, collision_keep_time_); + } + + bool checkPreviousObjectDataExpired() + { + return this->checkObjectDataExpired(prev_closest_object_, previous_obstacle_keep_time_); + } + + ObjectData get() const + { + return (closest_object_.has_value()) ? closest_object_.value() : ObjectData(); + } + + ObjectData getPreviousObjectData() const + { + return (prev_closest_object_.has_value()) ? prev_closest_object_.value() : ObjectData(); + } + + void setCollisionData(const ObjectData & data) + { + closest_object_ = std::make_optional(data); + } + + void setPreviousObjectData(const ObjectData & data) + { + prev_closest_object_ = std::make_optional(data); } - void update(const ObjectData & data) { data_.reset(new ObjectData(data)); } + void resetVelocityHistory() { obstacle_velocity_history_.clear(); } + + void updateVelocityHistory( + const double current_object_velocity, const rclcpp::Time & current_object_velocity_time_stamp) + { + // remove old msg from deque + const auto now = clock_->now(); + obstacle_velocity_history_.erase( + std::remove_if( + obstacle_velocity_history_.begin(), obstacle_velocity_history_.end(), + [&](const auto & velocity_time_pair) { + const auto & vel_time = velocity_time_pair.second; + return ((now - vel_time).nanoseconds() * 1e-9 > previous_obstacle_keep_time_); + }), + obstacle_velocity_history_.end()); + obstacle_velocity_history_.emplace_back( + std::make_pair(current_object_velocity, current_object_velocity_time_stamp)); + } - ObjectData get() + std::optional getMedianObstacleVelocity() const { - if (data_) { - return *data_; - } else { - return ObjectData(); + if (obstacle_velocity_history_.empty()) return std::nullopt; + std::vector raw_velocities; + for (const auto & vel_time_pair : obstacle_velocity_history_) { + raw_velocities.emplace_back(vel_time_pair.first); } + + const size_t med1 = (raw_velocities.size() % 2 == 0) ? (raw_velocities.size()) / 2 - 1 + : (raw_velocities.size()) / 2.0; + const size_t med2 = (raw_velocities.size()) / 2.0; + std::nth_element(raw_velocities.begin(), raw_velocities.begin() + med1, raw_velocities.end()); + const double vel1 = raw_velocities.at(med1); + std::nth_element(raw_velocities.begin(), raw_velocities.begin() + med2, raw_velocities.end()); + const double vel2 = raw_velocities.at(med2); + return (vel1 + vel2) / 2.0; + } + + std::optional calcObjectSpeedFromHistory( + const ObjectData & closest_object, const Path & path, const double current_ego_speed) + { + if (this->checkPreviousObjectDataExpired()) { + this->setPreviousObjectData(closest_object); + this->resetVelocityHistory(); + return std::nullopt; + } + + const auto estimated_velocity_opt = std::invoke([&]() -> std::optional { + const auto & prev_object = this->getPreviousObjectData(); + const double p_dt = + (closest_object.stamp.nanoseconds() - prev_object.stamp.nanoseconds()) * 1e-9; + if (p_dt < std::numeric_limits::epsilon()) return std::nullopt; + const auto & nearest_collision_point = closest_object.position; + const auto & prev_collision_point = prev_object.position; + + const double p_dx = nearest_collision_point.x - prev_collision_point.x; + const double p_dy = nearest_collision_point.y - prev_collision_point.y; + const double p_dist = std::hypot(p_dx, p_dy); + const double p_yaw = std::atan2(p_dy, p_dx); + const double p_vel = p_dist / p_dt; + + const auto nearest_idx = motion_utils::findNearestIndex(path, nearest_collision_point); + const auto & nearest_path_pose = path.at(nearest_idx); + const auto & traj_yaw = tf2::getYaw(nearest_path_pose.orientation); + const auto estimated_velocity = p_vel * std::cos(p_yaw - traj_yaw) + current_ego_speed; + + // Current RSS distance calculation does not account for negative velocities + return (estimated_velocity > 0.0) ? estimated_velocity : 0.0; + }); + + if (!estimated_velocity_opt.has_value()) { + return std::nullopt; + } + + const auto & estimated_velocity = estimated_velocity_opt.value(); + this->setPreviousObjectData(closest_object); + this->updateVelocityHistory(estimated_velocity, closest_object.stamp); + return this->getMedianObstacleVelocity(); } private: - std::unique_ptr data_; - double timeout_sec_{0.0}; + std::optional prev_closest_object_{std::nullopt}; + std::optional closest_object_{std::nullopt}; + double collision_keep_time_{0.0}; + double previous_obstacle_keep_time_{0.0}; + + std::deque> obstacle_velocity_history_; rclcpp::Clock::SharedPtr clock_; }; @@ -132,30 +250,44 @@ class AEB : public rclcpp::Node void onTimer(); void onPredictedTrajectory(const Trajectory::ConstSharedPtr input_msg); void onAutowareState(const AutowareState::ConstSharedPtr input_msg); + rcl_interfaces::msg::SetParametersResult onParameter( + const std::vector & parameters); bool isDataReady(); // main function void onCheckCollision(DiagnosticStatusWrapper & stat); bool checkCollision(MarkerArray & debug_markers); - bool hasCollision( - const double current_v, const Path & ego_path, const std::vector & objects); + bool hasCollision(const double current_v, const ObjectData & closest_object); - Path generateEgoPath(const double curr_v, const double curr_w, std::vector & polygons); - std::optional generateEgoPath( - const Trajectory & predicted_traj, std::vector & polygons); - void createObjectData( + Path generateEgoPath(const double curr_v, const double curr_w); + std::optional generateEgoPath(const Trajectory & predicted_traj); + std::vector generatePathFootprint(const Path & path, const double extra_width_margin); + + void createObjectDataUsingPointCloudClusters( + const Path & ego_path, const std::vector & ego_polys, const rclcpp::Time & stamp, + std::vector & objects, + const pcl::PointCloud::Ptr obstacle_points_ptr); + + void cropPointCloudWithEgoFootprintPath( + const std::vector & ego_polys, pcl::PointCloud::Ptr filtered_objects); + + void createObjectDataUsingPointCloudClusters( const Path & ego_path, const std::vector & ego_polys, const rclcpp::Time & stamp, std::vector & objects); + void cropPointCloudWithEgoFootprintPath(const std::vector & ego_polys); void addMarker( const rclcpp::Time & current_time, const Path & path, const std::vector & polygons, - const std::vector & objects, const double color_r, const double color_g, - const double color_b, const double color_a, const std::string & ns, - MarkerArray & debug_markers); + const std::vector & objects, const std::optional & closest_object, + const double color_r, const double color_g, const double color_b, const double color_a, + const std::string & ns, MarkerArray & debug_markers); void addCollisionMarker(const ObjectData & data, MarkerArray & debug_markers); + std::optional calcObjectSpeedFromHistory( + const ObjectData & closest_object, const Path & path, const double current_ego_speed); + PointCloud2::SharedPtr obstacle_ros_pointcloud_ptr_{nullptr}; VelocityReport::ConstSharedPtr current_velocity_ptr_{nullptr}; Vector3::SharedPtr angular_velocity_ptr_{nullptr}; @@ -175,6 +307,7 @@ class AEB : public rclcpp::Node bool publish_debug_pointcloud_; bool use_predicted_trajectory_; bool use_imu_path_; + double path_footprint_extra_margin_; double detection_range_min_height_; double detection_range_max_height_margin_; double voxel_grid_x_; @@ -186,11 +319,16 @@ class AEB : public rclcpp::Node double t_response_; double a_ego_min_; double a_obj_min_; + double cluster_tolerance_; + int minimum_cluster_size_; + int maximum_cluster_size_; double imu_prediction_time_horizon_; double imu_prediction_time_interval_; double mpc_prediction_time_horizon_; double mpc_prediction_time_interval_; CollisionDataKeeper collision_data_keeper_; + // Parameter callback + OnSetParametersCallbackHandle::SharedPtr set_param_res_; }; } // namespace autoware::motion::control::autonomous_emergency_braking diff --git a/control/autonomous_emergency_braking/src/node.cpp b/control/autonomous_emergency_braking/src/node.cpp index 8c830812078b6..d8886672a8ecd 100644 --- a/control/autonomous_emergency_braking/src/node.cpp +++ b/control/autonomous_emergency_braking/src/node.cpp @@ -14,17 +14,27 @@ #include "autonomous_emergency_braking/node.hpp" -#include +#include +#include #include #include #include +#include +#include +#include #include +#include +#include +#include #include #include +#include +#include +#include +#include #include - #ifdef ROS_DISTRO_GALACTIC #include #include @@ -34,8 +44,6 @@ #include #endif -#include -#include namespace autoware::motion::control::autonomous_emergency_braking { using diagnostic_msgs::msg::DiagnosticStatus; @@ -98,37 +106,42 @@ AEB::AEB(const rclcpp::NodeOptions & node_options) collision_data_keeper_(this->get_clock()) { // Subscribers - sub_point_cloud_ = this->create_subscription( - "~/input/pointcloud", rclcpp::SensorDataQoS(), - std::bind(&AEB::onPointCloud, this, std::placeholders::_1)); + { + sub_point_cloud_ = this->create_subscription( + "~/input/pointcloud", rclcpp::SensorDataQoS(), + std::bind(&AEB::onPointCloud, this, std::placeholders::_1)); - sub_velocity_ = this->create_subscription( - "~/input/velocity", rclcpp::QoS{1}, std::bind(&AEB::onVelocity, this, std::placeholders::_1)); + sub_velocity_ = this->create_subscription( + "~/input/velocity", rclcpp::QoS{1}, std::bind(&AEB::onVelocity, this, std::placeholders::_1)); - sub_imu_ = this->create_subscription( - "~/input/imu", rclcpp::QoS{1}, std::bind(&AEB::onImu, this, std::placeholders::_1)); + sub_imu_ = this->create_subscription( + "~/input/imu", rclcpp::QoS{1}, std::bind(&AEB::onImu, this, std::placeholders::_1)); - sub_predicted_traj_ = this->create_subscription( - "~/input/predicted_trajectory", rclcpp::QoS{1}, - std::bind(&AEB::onPredictedTrajectory, this, std::placeholders::_1)); + sub_predicted_traj_ = this->create_subscription( + "~/input/predicted_trajectory", rclcpp::QoS{1}, + std::bind(&AEB::onPredictedTrajectory, this, std::placeholders::_1)); - sub_autoware_state_ = this->create_subscription( - "/autoware/state", rclcpp::QoS{1}, - std::bind(&AEB::onAutowareState, this, std::placeholders::_1)); + sub_autoware_state_ = this->create_subscription( + "/autoware/state", rclcpp::QoS{1}, + std::bind(&AEB::onAutowareState, this, std::placeholders::_1)); + } // Publisher - pub_obstacle_pointcloud_ = - this->create_publisher("~/debug/obstacle_pointcloud", 1); - debug_ego_path_publisher_ = this->create_publisher("~/debug/markers", 1); - + { + pub_obstacle_pointcloud_ = + this->create_publisher("~/debug/obstacle_pointcloud", 1); + debug_ego_path_publisher_ = this->create_publisher("~/debug/markers", 1); + } // Diagnostics - updater_.setHardwareID("autonomous_emergency_braking"); - updater_.add("aeb_emergency_stop", this, &AEB::onCheckCollision); - + { + updater_.setHardwareID("autonomous_emergency_braking"); + updater_.add("aeb_emergency_stop", this, &AEB::onCheckCollision); + } // parameter publish_debug_pointcloud_ = declare_parameter("publish_debug_pointcloud"); use_predicted_trajectory_ = declare_parameter("use_predicted_trajectory"); use_imu_path_ = declare_parameter("use_imu_path"); + path_footprint_extra_margin_ = declare_parameter("path_footprint_extra_margin"); detection_range_min_height_ = declare_parameter("detection_range_min_height"); detection_range_max_height_margin_ = declare_parameter("detection_range_max_height_margin"); @@ -141,18 +154,74 @@ AEB::AEB(const rclcpp::NodeOptions & node_options) t_response_ = declare_parameter("t_response"); a_ego_min_ = declare_parameter("a_ego_min"); a_obj_min_ = declare_parameter("a_obj_min"); + + cluster_tolerance_ = declare_parameter("cluster_tolerance"); + minimum_cluster_size_ = declare_parameter("minimum_cluster_size"); + maximum_cluster_size_ = declare_parameter("maximum_cluster_size"); + imu_prediction_time_horizon_ = declare_parameter("imu_prediction_time_horizon"); imu_prediction_time_interval_ = declare_parameter("imu_prediction_time_interval"); mpc_prediction_time_horizon_ = declare_parameter("mpc_prediction_time_horizon"); mpc_prediction_time_interval_ = declare_parameter("mpc_prediction_time_interval"); - const auto collision_keeping_sec = declare_parameter("collision_keeping_sec"); - collision_data_keeper_.setTimeout(collision_keeping_sec); + { // Object history data keeper setup + const auto previous_obstacle_keep_time = + declare_parameter("previous_obstacle_keep_time"); + const auto collision_keeping_sec = declare_parameter("collision_keeping_sec"); + collision_data_keeper_.setTimeout(collision_keeping_sec, previous_obstacle_keep_time); + } + + // Parameter Callback + set_param_res_ = + add_on_set_parameters_callback(std::bind(&AEB::onParameter, this, std::placeholders::_1)); // start time const double aeb_hz = declare_parameter("aeb_hz"); const auto period_ns = rclcpp::Rate(aeb_hz).period(); - timer_ = rclcpp::create_timer(this, get_clock(), period_ns, std::bind(&AEB::onTimer, this)); + timer_ = rclcpp::create_timer(this, this->get_clock(), period_ns, std::bind(&AEB::onTimer, this)); +} + +rcl_interfaces::msg::SetParametersResult AEB::onParameter( + const std::vector & parameters) +{ + using tier4_autoware_utils::updateParam; + updateParam(parameters, "publish_debug_pointcloud", publish_debug_pointcloud_); + updateParam(parameters, "use_predicted_trajectory", use_predicted_trajectory_); + updateParam(parameters, "use_imu_path", use_imu_path_); + updateParam(parameters, "path_footprint_extra_margin", path_footprint_extra_margin_); + updateParam(parameters, "detection_range_min_height", detection_range_min_height_); + updateParam( + parameters, "detection_range_max_height_margin", detection_range_max_height_margin_); + updateParam(parameters, "voxel_grid_x", voxel_grid_x_); + updateParam(parameters, "voxel_grid_y", voxel_grid_y_); + updateParam(parameters, "voxel_grid_z", voxel_grid_z_); + updateParam(parameters, "min_generated_path_length", min_generated_path_length_); + updateParam(parameters, "expand_width", expand_width_); + updateParam(parameters, "longitudinal_offset", longitudinal_offset_); + updateParam(parameters, "t_response", t_response_); + updateParam(parameters, "a_ego_min", a_ego_min_); + updateParam(parameters, "a_obj_min", a_obj_min_); + + updateParam(parameters, "cluster_tolerance", cluster_tolerance_); + updateParam(parameters, "minimum_cluster_size", minimum_cluster_size_); + updateParam(parameters, "maximum_cluster_size", maximum_cluster_size_); + + updateParam(parameters, "imu_prediction_time_horizon", imu_prediction_time_horizon_); + updateParam(parameters, "imu_prediction_time_interval", imu_prediction_time_interval_); + updateParam(parameters, "mpc_prediction_time_horizon", mpc_prediction_time_horizon_); + updateParam(parameters, "mpc_prediction_time_interval", mpc_prediction_time_interval_); + + { // Object history data keeper setup + auto [previous_obstacle_keep_time, collision_keeping_sec] = collision_data_keeper_.getTimeout(); + updateParam(parameters, "previous_obstacle_keep_time", previous_obstacle_keep_time); + updateParam(parameters, "collision_keeping_sec", collision_keeping_sec); + collision_data_keeper_.setTimeout(collision_keeping_sec, previous_obstacle_keep_time); + } + + rcl_interfaces::msg::SetParametersResult result; + result.successful = true; + result.reason = "success"; + return result; } void AEB::onTimer() @@ -242,11 +311,9 @@ void AEB::onPointCloud(const PointCloud2::ConstSharedPtr input_msg) filter.filter(*no_height_filtered_pointcloud_ptr); obstacle_ros_pointcloud_ptr_ = std::make_shared(); + pcl::toROSMsg(*no_height_filtered_pointcloud_ptr, *obstacle_ros_pointcloud_ptr_); obstacle_ros_pointcloud_ptr_->header = input_msg->header; - if (publish_debug_pointcloud_) { - pub_obstacle_pointcloud_->publish(*obstacle_ros_pointcloud_ptr_); - } } bool AEB::isDataReady() @@ -284,13 +351,14 @@ void AEB::onCheckCollision(DiagnosticStatusWrapper & stat) MarkerArray debug_markers; checkCollision(debug_markers); - if (!collision_data_keeper_.checkExpired()) { + if (!collision_data_keeper_.checkCollisionExpired()) { const std::string error_msg = "[AEB]: Emergency Brake"; const auto diag_level = DiagnosticStatus::ERROR; stat.summary(diag_level, error_msg); const auto & data = collision_data_keeper_.get(); stat.addf("RSS", "%.2f", data.rss); stat.addf("Distance", "%.2f", data.distance_to_object); + stat.addf("Object Speed", "%.2f", data.velocity); addCollisionMarker(data, debug_markers); } else { const std::string error_msg = "[AEB]: No Collision"; @@ -304,6 +372,8 @@ void AEB::onCheckCollision(DiagnosticStatusWrapper & stat) bool AEB::checkCollision(MarkerArray & debug_markers) { + using colorTuple = std::tuple; + // step1. check data if (!isDataReady()) { return false; @@ -320,86 +390,114 @@ bool AEB::checkCollision(MarkerArray & debug_markers) return false; } - // step3. create ego path based on sensor data - bool has_collision_ego = false; - if (use_imu_path_) { - std::vector ego_polys; - const double current_w = angular_velocity_ptr_->z; - constexpr double color_r = 0.0 / 256.0; - constexpr double color_g = 148.0 / 256.0; - constexpr double color_b = 205.0 / 256.0; - constexpr double color_a = 0.999; - const auto current_time = get_clock()->now(); - const auto ego_path = generateEgoPath(current_v, current_w, ego_polys); - std::vector objects; - createObjectData(ego_path, ego_polys, current_time, objects); - has_collision_ego = hasCollision(current_v, ego_path, objects); - - std::string ns = "ego"; - addMarker( - current_time, ego_path, ego_polys, objects, color_r, color_g, color_b, color_a, ns, - debug_markers); - } - - // step4. transform predicted trajectory from control module - bool has_collision_predicted = false; - if (use_predicted_trajectory_) { - std::vector predicted_polys; - const auto predicted_traj_ptr = predicted_traj_ptr_; - constexpr double color_r = 0.0; - constexpr double color_g = 100.0 / 256.0; - constexpr double color_b = 0.0; - constexpr double color_a = 0.999; - const auto current_time = predicted_traj_ptr->header.stamp; - const auto predicted_path_opt = generateEgoPath(*predicted_traj_ptr, predicted_polys); - if (predicted_path_opt) { - const auto & predicted_path = predicted_path_opt.value(); - std::vector objects; - createObjectData(predicted_path, predicted_polys, current_time, objects); - has_collision_predicted = hasCollision(current_v, predicted_path, objects); - - std::string ns = "predicted"; + auto check_collision = [&]( + const auto & path, const colorTuple & debug_colors, + const std::string & debug_ns, + pcl::PointCloud::Ptr filtered_objects) { + // Crop out Pointcloud using an extra wide ego path + const auto expanded_ego_polys = + generatePathFootprint(path, expand_width_ + path_footprint_extra_margin_); + cropPointCloudWithEgoFootprintPath(expanded_ego_polys, filtered_objects); + + // Check which points of the cropped point cloud are on the ego path, and get the closest one + std::vector objects_from_point_clusters; + const auto ego_polys = generatePathFootprint(path, expand_width_); + const auto current_time = obstacle_ros_pointcloud_ptr_->header.stamp; + createObjectDataUsingPointCloudClusters( + path, ego_polys, current_time, objects_from_point_clusters, filtered_objects); + + // Get only the closest object and calculate its speed + const auto closest_object_point = std::invoke([&]() -> std::optional { + const auto closest_object_point_itr = std::min_element( + objects_from_point_clusters.begin(), objects_from_point_clusters.end(), + [](const auto & o1, const auto & o2) { + return o1.distance_to_object < o2.distance_to_object; + }); + + if (closest_object_point_itr == objects_from_point_clusters.end()) { + return std::nullopt; + } + const auto closest_object_speed = collision_data_keeper_.calcObjectSpeedFromHistory( + *closest_object_point_itr, path, current_v); + if (!closest_object_speed.has_value()) { + return std::nullopt; + } + closest_object_point_itr->velocity = closest_object_speed.value(); + return std::make_optional(*closest_object_point_itr); + }); + + // Add debug markers + { + const auto [color_r, color_g, color_b, color_a] = debug_colors; addMarker( - current_time, predicted_path, predicted_polys, objects, color_r, color_g, color_b, color_a, - ns, debug_markers); + this->get_clock()->now(), path, ego_polys, objects_from_point_clusters, + closest_object_point, color_r, color_g, color_b, color_a, debug_ns, debug_markers); } - } + // check collision using rss distance + return (closest_object_point.has_value()) + ? hasCollision(current_v, closest_object_point.value()) + : false; + }; + + // step3. make function to check collision with ego path created with sensor data + const auto has_collision_ego = [&](pcl::PointCloud::Ptr filtered_objects) -> bool { + if (!use_imu_path_) return false; + const double current_w = angular_velocity_ptr_->z; + constexpr colorTuple debug_color = {0.0 / 256.0, 148.0 / 256.0, 205.0 / 256.0, 0.999}; + const std::string ns = "ego"; + const auto ego_path = generateEgoPath(current_v, current_w); + + return check_collision(ego_path, debug_color, ns, filtered_objects); + }; - return has_collision_ego || has_collision_predicted; + // step4. make function to check collision with predicted trajectory from control module + const auto has_collision_predicted = + [&](pcl::PointCloud::Ptr filtered_objects) -> bool { + if (!use_predicted_trajectory_ || !predicted_traj_ptr_) return false; + const auto predicted_traj_ptr = predicted_traj_ptr_; + const auto predicted_path_opt = generateEgoPath(*predicted_traj_ptr); + + if (!predicted_path_opt) return false; + constexpr colorTuple debug_color = {0.0 / 256.0, 100.0 / 256.0, 0.0 / 256.0, 0.999}; + const std::string ns = "predicted"; + const auto & predicted_path = predicted_path_opt.value(); + + return check_collision(predicted_path, debug_color, ns, filtered_objects); + }; + + // Data of filtered point cloud + pcl::PointCloud::Ptr filtered_objects(new PointCloud); + // evaluate if there is a collision for both paths + const bool has_collision = + has_collision_ego(filtered_objects) || has_collision_predicted(filtered_objects); + + // Debug print + if (!filtered_objects->empty() && publish_debug_pointcloud_) { + const auto filtered_objects_ros_pointcloud_ptr_ = std::make_shared(); + pcl::toROSMsg(*filtered_objects, *filtered_objects_ros_pointcloud_ptr_); + pub_obstacle_pointcloud_->publish(*filtered_objects_ros_pointcloud_ptr_); + } + return has_collision; } -bool AEB::hasCollision( - const double current_v, const Path & ego_path, const std::vector & objects) +bool AEB::hasCollision(const double current_v, const ObjectData & closest_object) { - // calculate RSS - const auto current_p = tier4_autoware_utils::createPoint( - ego_path[0].position.x, ego_path[0].position.y, ego_path[0].position.z); + const double & obj_v = closest_object.velocity; const double & t = t_response_; - for (const auto & obj : objects) { - const double & obj_v = obj.velocity; - const double rss_dist = current_v * t + (current_v * current_v) / (2 * std::fabs(a_ego_min_)) - - obj_v * obj_v / (2 * std::fabs(a_obj_min_)) + longitudinal_offset_; - - // check the object is front the ego or not - if ((obj.position.x - ego_path[0].position.x) > 0) { - const double dist_ego_to_object = - motion_utils::calcSignedArcLength(ego_path, current_p, obj.position) - - vehicle_info_.max_longitudinal_offset_m; - if (dist_ego_to_object < rss_dist) { - // collision happens - ObjectData collision_data = obj; - collision_data.rss = rss_dist; - collision_data.distance_to_object = dist_ego_to_object; - collision_data_keeper_.update(collision_data); - return true; - } - } + const double rss_dist = current_v * t + (current_v * current_v) / (2 * std::fabs(a_ego_min_)) - + obj_v * obj_v / (2 * std::fabs(a_obj_min_)) + longitudinal_offset_; + if (closest_object.distance_to_object < rss_dist) { + // collision happens + ObjectData collision_data = closest_object; + collision_data.rss = rss_dist; + collision_data.distance_to_object = closest_object.distance_to_object; + collision_data_keeper_.setCollisionData(collision_data); + return true; } return false; } -Path AEB::generateEgoPath( - const double curr_v, const double curr_w, std::vector & polygons) +Path AEB::generateEgoPath(const double curr_v, const double curr_w) { Path path; double curr_x = 0.0; @@ -444,17 +542,10 @@ Path AEB::generateEgoPath( } path.push_back(current_pose); } - - // generate ego polygons - polygons.resize(path.size() - 1); - for (size_t i = 0; i < path.size() - 1; ++i) { - polygons.at(i) = createPolygon(path.at(i), path.at(i + 1), vehicle_info_, expand_width_); - } return path; } -std::optional AEB::generateEgoPath( - const Trajectory & predicted_traj, std::vector & polygons) +std::optional AEB::generateEgoPath(const Trajectory & predicted_traj) { if (predicted_traj.points.empty()) { return std::nullopt; @@ -482,35 +573,82 @@ std::optional AEB::generateEgoPath( break; } } - // create polygon - polygons.resize(path.size()); + return path; +} + +std::vector AEB::generatePathFootprint( + const Path & path, const double extra_width_margin) +{ + std::vector polygons; for (size_t i = 0; i < path.size() - 1; ++i) { - polygons.at(i) = createPolygon(path.at(i), path.at(i + 1), vehicle_info_, expand_width_); + polygons.push_back( + createPolygon(path.at(i), path.at(i + 1), vehicle_info_, extra_width_margin)); } - return path; + return polygons; } -void AEB::createObjectData( - const Path & ego_path, const std::vector & ego_polys, - const rclcpp::Time & stamp, std::vector & objects) +void AEB::createObjectDataUsingPointCloudClusters( + const Path & ego_path, const std::vector & ego_polys, const rclcpp::Time & stamp, + std::vector & objects, const pcl::PointCloud::Ptr obstacle_points_ptr) { // check if the predicted path has valid number of points - if (ego_path.size() < 2 || ego_polys.empty()) { + if (ego_path.size() < 2 || ego_polys.empty() || obstacle_points_ptr->empty()) { return; } - PointCloud::Ptr obstacle_points_ptr(new PointCloud); - pcl::fromROSMsg(*obstacle_ros_pointcloud_ptr_, *obstacle_points_ptr); - for (const auto & point : obstacle_points_ptr->points) { + // eliminate noisy points by only considering points belonging to clusters of at least a certain + // size + const std::vector cluster_indices = std::invoke([&]() { + std::vector cluster_idx; + pcl::search::KdTree::Ptr tree(new pcl::search::KdTree); + tree->setInputCloud(obstacle_points_ptr); + pcl::EuclideanClusterExtraction ec; + ec.setClusterTolerance(cluster_tolerance_); + ec.setMinClusterSize(minimum_cluster_size_); + ec.setMaxClusterSize(maximum_cluster_size_); + ec.setSearchMethod(tree); + ec.setInputCloud(obstacle_points_ptr); + ec.extract(cluster_idx); + return cluster_idx; + }); + + PointCloud::Ptr points_belonging_to_cluster_hulls(new PointCloud); + for (const auto & indices : cluster_indices) { + PointCloud::Ptr cluster(new PointCloud); + for (const auto & index : indices.indices) { + cluster->push_back((*obstacle_points_ptr)[index]); + } + // Make a 2d convex hull for the objects + pcl::ConvexHull hull; + hull.setDimension(2); + hull.setInputCloud(cluster); + std::vector polygons; + PointCloud::Ptr surface_hull(new pcl::PointCloud); + hull.reconstruct(*surface_hull, polygons); + for (const auto & p : *surface_hull) { + points_belonging_to_cluster_hulls->push_back(p); + } + } + + // select points inside the ego footprint path + const auto current_p = tier4_autoware_utils::createPoint( + ego_path[0].position.x, ego_path[0].position.y, ego_path[0].position.z); + + for (const auto & p : *points_belonging_to_cluster_hulls) { + const auto obj_position = tier4_autoware_utils::createPoint(p.x, p.y, p.z); + const double dist_ego_to_object = + motion_utils::calcSignedArcLength(ego_path, current_p, obj_position) - + vehicle_info_.max_longitudinal_offset_m; + // objects behind ego are ignored + if (dist_ego_to_object < 0.0) continue; + ObjectData obj; obj.stamp = stamp; - obj.position = tier4_autoware_utils::createPoint(point.x, point.y, point.z); + obj.position = obj_position; obj.velocity = 0.0; - const Point2d obj_point(point.x, point.y); - const double lat_dist = motion_utils::calcLateralOffset(ego_path, obj.position); - if (lat_dist > 5.0) { - continue; - } + obj.distance_to_object = dist_ego_to_object; + + const Point2d obj_point(p.x, p.y); for (const auto & ego_poly : ego_polys) { if (bg::within(obj_point, ego_poly)) { objects.push_back(obj); @@ -520,10 +658,41 @@ void AEB::createObjectData( } } +void AEB::cropPointCloudWithEgoFootprintPath( + const std::vector & ego_polys, pcl::PointCloud::Ptr filtered_objects) +{ + PointCloud::Ptr full_points_ptr(new PointCloud); + pcl::fromROSMsg(*obstacle_ros_pointcloud_ptr_, *full_points_ptr); + // Create a Point cloud with the points of the ego footprint + PointCloud::Ptr path_polygon_points(new PointCloud); + std::for_each(ego_polys.begin(), ego_polys.end(), [&](const auto & poly) { + std::for_each(poly.outer().begin(), poly.outer().end(), [&](const auto & p) { + pcl::PointXYZ point(p.x(), p.y(), 0.0); + path_polygon_points->push_back(point); + }); + }); + // Make a surface hull with the ego footprint to filter out points + pcl::ConvexHull hull; + hull.setDimension(2); + hull.setInputCloud(path_polygon_points); + std::vector polygons; + pcl::PointCloud::Ptr surface_hull(new pcl::PointCloud); + hull.reconstruct(*surface_hull, polygons); + // Filter out points outside of the path's convex hull + pcl::CropHull path_polygon_hull_filter; + path_polygon_hull_filter.setDim(2); + path_polygon_hull_filter.setInputCloud(full_points_ptr); + path_polygon_hull_filter.setHullIndices(polygons); + path_polygon_hull_filter.setHullCloud(surface_hull); + path_polygon_hull_filter.filter(*filtered_objects); + filtered_objects->header.stamp = full_points_ptr->header.stamp; +} + void AEB::addMarker( const rclcpp::Time & current_time, const Path & path, const std::vector & polygons, - const std::vector & objects, const double color_r, const double color_g, - const double color_b, const double color_a, const std::string & ns, MarkerArray & debug_markers) + const std::vector & objects, const std::optional & closest_object, + const double color_r, const double color_g, const double color_b, const double color_a, + const std::string & ns, MarkerArray & debug_markers) { auto path_marker = tier4_autoware_utils::createDefaultMarker( "base_link", current_time, ns + "_path", 0L, Marker::LINE_STRIP, @@ -553,12 +722,29 @@ void AEB::addMarker( auto object_data_marker = tier4_autoware_utils::createDefaultMarker( "base_link", current_time, ns + "_objects", 0, Marker::SPHERE_LIST, - tier4_autoware_utils::createMarkerScale(0.05, 0.05, 0.05), + tier4_autoware_utils::createMarkerScale(0.5, 0.5, 0.5), tier4_autoware_utils::createMarkerColor(color_r, color_g, color_b, color_a)); for (const auto & e : objects) { object_data_marker.points.push_back(e.position); } debug_markers.markers.push_back(object_data_marker); + + // Visualize planner type text + if (closest_object.has_value()) { + const auto & obj = closest_object.value(); + const auto color = tier4_autoware_utils::createMarkerColor(0.95, 0.95, 0.95, 0.999); + auto closest_object_velocity_marker_array = tier4_autoware_utils::createDefaultMarker( + "base_link", obj.stamp, ns + "_closest_object_velocity", 0, + visualization_msgs::msg::Marker::TEXT_VIEW_FACING, + tier4_autoware_utils::createMarkerScale(0.0, 0.0, 0.7), color); + closest_object_velocity_marker_array.pose.position = obj.position; + const auto ego_velocity = current_velocity_ptr_->longitudinal_velocity; + closest_object_velocity_marker_array.text = + "Object velocity: " + std::to_string(obj.velocity) + " [m/s]\n"; + closest_object_velocity_marker_array.text += + "Object relative velocity to ego: " + std::to_string(obj.velocity - ego_velocity) + " [m/s]"; + debug_markers.markers.push_back(closest_object_velocity_marker_array); + } } void AEB::addCollisionMarker(const ObjectData & data, MarkerArray & debug_markers) diff --git a/control/control_performance_analysis/src/control_performance_analysis_core.cpp b/control/control_performance_analysis/src/control_performance_analysis_core.cpp index 1ceef81e10c56..f4ed125956bfa 100644 --- a/control/control_performance_analysis/src/control_performance_analysis_core.cpp +++ b/control/control_performance_analysis/src/control_performance_analysis_core.cpp @@ -401,7 +401,7 @@ std::pair ControlPerformanceAnalysisCore::calculateClosestPose() if ( !interpolated_pose_ptr_ || !interpolated_velocity_ptr_ || !interpolated_acceleration_ptr_ || !interpolated_steering_angle_ptr_) { - std::make_pair(false, interp_point.pose); + return std::make_pair(false, interp_point.pose); } return std::make_pair(true, interp_point.pose); diff --git a/control/smart_mpc_trajectory_follower/.gitignore b/control/smart_mpc_trajectory_follower/.gitignore new file mode 100644 index 0000000000000..d914a0aa99e5a --- /dev/null +++ b/control/smart_mpc_trajectory_follower/.gitignore @@ -0,0 +1,3 @@ +# Files generated when installing smart_mpc_trajectory_follower +build/ +*.egg-info/ diff --git a/control/smart_mpc_trajectory_follower/CMakeLists.txt b/control/smart_mpc_trajectory_follower/CMakeLists.txt new file mode 100644 index 0000000000000..7aecab2597dcd --- /dev/null +++ b/control/smart_mpc_trajectory_follower/CMakeLists.txt @@ -0,0 +1,13 @@ +cmake_minimum_required(VERSION 3.14) +project(smart_mpc_trajectory_follower) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +install(PROGRAMS + smart_mpc_trajectory_follower/scripts/pympc_trajectory_follower.py + DESTINATION lib/${PROJECT_NAME} +) +ament_auto_package( + INSTALL_TO_SHARE +) diff --git a/control/smart_mpc_trajectory_follower/README.md b/control/smart_mpc_trajectory_follower/README.md new file mode 100644 index 0000000000000..8fcc13142d68b --- /dev/null +++ b/control/smart_mpc_trajectory_follower/README.md @@ -0,0 +1,338 @@ +

+ + + +

+ + +# Smart MPC Trajectory Follower + +Smart MPC (Model Predictive Control) is a control algorithm that combines model predictive control and machine learning. While inheriting the advantages of model predictive control, it solves its disadvantage of modeling difficulty with a data-driven method using machine learning. + +This technology makes it relatively easy to operate model predictive control, which is expensive to implement, as long as an environment for collecting data can be prepared. + +

+ + + +

+ +## Setup + +After building autoware, move to `control/smart_mpc_trajectory_follower` and run the following command: + +```bash +pip3 install . +``` + +If you have already installed and want to update the package, run the following command instead: + +```bash +pip3 install -U . +``` + +## Provided features + +This package provides smart MPC logic for path-following control as well as mechanisms for learning and evaluation. These features are described below. + +### Trajectory following control based on iLQR/MPPI + +The control mode can be selected from "ilqr", "mppi", or "mppi_ilqr", and can be set as `mpc_parameter:system:mode` in [mpc_param.yaml](./smart_mpc_trajectory_follower/param/mpc_param.yaml). +In "mppi_ilqr" mode, the initial value of iLQR is given by the MPPI solution. + +> [!NOTE] +> With the default settings, the performance of "mppi" mode is limited due to an insufficient number of samples. This issue is being addressed with ongoing work to introduce GPU support. + +To perform a simulation, run the following command: + +```bash +ros2 launch autoware_launch planning_simulator.launch.xml map_path:=$HOME/autoware_map/sample-map-planning vehicle_model:=sample_vehicle sensor_model:=sample_sensor_kit trajectory_follower_mode:=smart_mpc_trajectory_follower +``` + +> [!NOTE] +> When running with the nominal model set in [nominal_param.yaml](./smart_mpc_trajectory_follower/param/nominal_param.yaml), set `trained_model_parameter:control_application:use_trained_model` to `false` in [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml). To run using the trained model, set `trained_model_parameter:control_application:use_trained_model` to `true`, but the trained model must have been generated according to the following procedure. + +### Training of model and reflection in control + +To obtain training data, start autoware, perform a drive, and record rosbag data with the following commands. + +```bash +ros2 bag record /localization/kinematic_state /localization/acceleration /vehicle/status/steering_status /control/command/control_cmd /control/trajectory_follower/control_cmd /control/trajectory_follower/lane_departure_checker_node/debug/deviation/lateral /control/trajectory_follower/lane_departure_checker_node/debug/deviation/yaw /system/operation_mode/state /vehicle/status/control_mode /sensing/imu/imu_data /debug_mpc_x_des /debug_mpc_y_des /debug_mpc_v_des /debug_mpc_yaw_des /debug_mpc_acc_des /debug_mpc_steer_des /debug_mpc_X_des_converted /debug_mpc_x_current /debug_mpc_error_prediction /debug_mpc_max_trajectory_err /debug_mpc_emergency_stop_mode /debug_mpc_goal_stop_mode /debug_mpc_total_ctrl_time /debug_mpc_calc_u_opt_time +``` + +Move [rosbag2.bash](./smart_mpc_trajectory_follower/training_and_data_check/rosbag2.bash) to the rosbag directory recorded above and execute the following command on the directory + +```bash +bash rosbag2.bash +``` + +This converts rosbag data into CSV format for training models. + +> [!NOTE] +> Note that a large number of terminals are automatically opened at runtime, but they are automatically closed after rosbag data conversion is completed. +> From the time you begin this process until all terminals are closed, autoware should not be running. + +Instead, the same result can be obtained by executing the following command in a python environment: + +```python +from smart_mpc_trajectory_follower.training_and_data_check import train_drive_NN_model +model_trainer = train_drive_NN_model.train_drive_NN_model() +model_trainer.transform_rosbag_to_csv(rosbag_dir) +``` + +Here, `rosbag_dir` represents the rosbag directory. +At this time, all CSV files in `rosbag_dir` are automatically deleted first. + +The paths of the rosbag directories used for training, `dir_0`, `dir_1`, `dir_2`,... and the directory `save_dir` where you save the models, the model can be saved in the python environment as follows: + +```python +from smart_mpc_trajectory_follower.training_and_data_check import train_drive_NN_model +model_trainer = train_drive_NN_model.train_drive_NN_model() +model_trainer.add_data_from_csv(dir_0) +model_trainer.add_data_from_csv(dir_1) +model_trainer.add_data_from_csv(dir_2) +... +model_trainer.get_trained_model() +model_trainer.save_models(save_dir) +``` + +After performing the polynomial regression, the NN can be trained on the residuals as follows: + +```python +model_trainer.get_trained_model(use_polynomial_reg=True) +``` + +> [!NOTE] +> In the default setting, regression is performed by several preselected polynomials. +> When `use_selected_polynomial=False` is set as the argument of get_trained_model, the `deg` argument allows setting the maximum degree of the polynomial to be used. + +If only polynomial regression is performed and no NN model is used, run the following command: + +```python +model_trainer.get_trained_model(use_polynomial_reg=True,force_NN_model_to_zero=True) +``` + +Move `model_for_test_drive.pth` and `polynomial_reg_info.npz` saved in `save_dir` to the home directory and set `trained_model_parameter:control_application:use_trained_model` in [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml) to `true` to reflect the trained model in the control. + +### Performance evaluation + +Here, as an example, we describe the verification of the adaptive performance when the wheel base of the sample_vehicle is 2.79 m, but an incorrect value of 2.0 m is given to the controller side. +To give the controller 2.0 m as the wheel base, set the value of `nominal_parameter:vehicle_info:wheel_base` in [nominal_param.yaml](./smart_mpc_trajectory_follower/param/nominal_param.yaml) to 2.0, and run the following command: + +```bash +python3 -m smart_mpc_trajectory_follower.clear_pycache +``` + +#### Test on autoware + +To perform a control test on autoware with the nominal model before training, make sure that `trained_model_parameter:control_application:use_trained_model` in [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml) is `false` and launch autoware in the manner described in "Trajectory following control based on iLQR/MPPI". This time, the following route will be used for the test: + +

+ +Record rosbag and train the model in the manner described in "Training of model and reflection in control", and move the generated files `model_for_test_drive.pth` and `polynomial_reg_info.npz` to the home directory. + +> [!NOTE] +> Although the data used for training is small, for the sake of simplicity, we will see how much performance can be improved with this amount of data. + +To control using the trained model obtained here, set `trained_model_parameter:control_application:use_trained_model` to `true`, start autoware in the same way, and drive the same route recording rosbag. +After the driving is complete, convert the rosbag file to CSV format using the method described in "Training of model and reflection in control". +A plot of the lateral deviation is obtained by running the `lateral_error_visualize` function in `control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/data_checker.ipynb` for the nominal and training model rosbag files `rosbag_nominal` and `rosbag_trained`, respectively, as follows: + +```python +lateral_error_visualize(dir_name=rosbag_nominal,ylim=[-1.2,1.2]) +lateral_error_visualize(dir_name=rosbag_trained,ylim=[-1.2,1.2]) +``` + +The following results were obtained. + +
+ + +
+ +#### Test on python simulator + +First, to give wheel base 2.79 m in the python simulator, create the following file and save it in `control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator` with the name `sim_setting.json`: + +```json +{ "wheel_base": 2.79 } +``` + +Next, run the following commands to test the slalom driving on the python simulator with the nominal model: + +```python +import python_simulator +from smart_mpc_trajectory_follower.training_and_data_check import train_drive_NN_model +initial_error = [0.0, 0.03, 0.01, -0.01, 0.0, 0.0] +save_dir = "test_python_sim" +python_simulator.slalom_drive(save_dir=save_dir,use_trained_model=False,initial_error=initial_error) +``` + +Here, `initial_error` is the initial error from the target trajectory, in the order of x-coordinate, y-coordinate, longitudinal velocity, yaw angle, longitudinal acceleration, and steer angle, +and `save_dir` is the directory where the driving test results are saved. + +> [!NOTE] +> The value of `use_trained_model` given as the argument of `python_simulator.slalom_drive` takes precedence over the value of `trained_model_parameter:control_application:use_trained_model` in [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml). + +Run the following commands to perform training using driving data of the nominal model. + +```python +model_trainer = train_drive_NN_model.train_drive_NN_model() +model_trainer.add_data_from_csv(save_dir) +model_trainer.save_train_data(save_dir) +model_trainer.get_trained_model(use_polynomial_reg=True) +model_trainer.save_models(save_dir=save_dir) +``` + +This way, files `model_for_test_drive.pth` and `polynomial_reg_info.npz` are saved in `save_dir`. +The following results were obtained. + +

+ +

+ +The center of the upper row represents the lateral deviation. + +Finally, to drive with the training model, run the following commands: + +```python +load_dir = save_dir +save_dir = "test_python_trained_sim" +python_simulator.slalom_drive(save_dir=save_dir,load_dir=load_dir,use_trained_model=True,initial_error=initial_error) +``` + +The following results were obtained. + +

+ +

+ +It can be seen that the lateral deviation has improved significantly. + +Here we have described wheel base, but the parameters that can be passed to the python simulator are as follows. + +| Parameter | Type | Description | +| ------------------------ | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| steer_bias | float | steer bias [rad] | +| steer_rate_lim | float | steer rate limit [rad/s] | +| vel_rate_lim | float | acceleration limit [m/s^2] | +| wheel_base | float | wheel base [m] | +| steer_dead_band | float | steer dead band [rad] | +| adaptive_gear_ratio_coef | list[float] | List of floats of length 6 specifying information on speed-dependent gear ratios from tire angle to steering wheel angle. | +| acc_time_delay | float | acceleration time delay [s] | +| steer_time_delay | float | steer time delay [s] | +| acc_time_constant | float | acceleration time constant [s] | +| steer_time_constant | float | steer time constant [s] | +| accel_map_scale | float | Parameter that magnifies the corresponding distortion from acceleration input values to actual acceleration realizations.
Correspondence information is kept in `control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/accel_map.csv`. | +| acc_scaling | float | acceleration scaling | +| steer_scaling | float | steer scaling | + +For example, to give the simulation side 0.01 [rad] of steer bias and 0.001 [rad] of steer dead band, edit the `sim_setting.json` as follows. + +```json +{ "steer_bias": 0.01, "steer_dead_band": 0.001 } +``` + +#### Auto test on python simulator + +Here, we describe a method for testing adaptive performance by giving the simulation side a predefined range of model parameters while the control side is given constant model parameters. + +First, to restore nominal model settings to default values, set the value of `nominal_parameter:vehicle_info:wheel_base` in [nominal_param.yaml](./smart_mpc_trajectory_follower/param/nominal_param.yaml) to 2.79, and run the following command: + +```bash +python3 -m smart_mpc_trajectory_follower.clear_pycache +``` + +To run a driving experiment within the parameter change range set in [run_sim.py](./smart_mpc_trajectory_follower/python_simulator/run_sim.py), for example, move to `control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator` and run the following command: + +```bash +python3 run_sim.py --param_name steer_bias +``` + +Here we described the experimental procedure for steer bias, and the same method can be used for other parameters. + +If you want to do it for all parameters at once, run the following command: + +```bash +yes | python3 run_sim.py +``` + +In `run_sim.py`, the following parameters can be set: + +| Parameter | Type | Description | +| ------------------------- | ---- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| USE_TRAINED_MODEL_DIFF | bool | Whether the derivative of the trained model is reflected in the control | +| DATA_COLLECTION_MODE | str | Which method will be used to collect the training data　
"ff": Straight line driving with feed-forward input
"pp": Figure eight driving with pure pursuit control
"mpc": Slalom driving with mpc | +| USE_POLYNOMIAL_REGRESSION | bool | Whether to perform polynomial regression before NN | +| USE_SELECTED_POLYNOMIAL | bool | When USE_POLYNOMIAL_REGRESSION is True, perform polynomial regression using only some preselected polynomials.
The choice of polynomials is intended to be able to absorb the contribution of some parameter shifts based on the nominal model of the vehicle. | +| FORCE_NN_MODEL_TO_ZERO | bool | Whether to force the NN model to zero (i.e., erase the contribution of the NN model).
When USE_POLYNOMIAL_REGRESSION is True, setting FORCE_MODEL_TO_ZERO to True allows the control to reflect the results of polynomial regression only, without using NN models. | +| FIT_INTERCEPT | bool | Whether to include bias in polynomial regression.
If it is False, perform the regression with a polynomial of the first degree or higher. | +| USE_INTERCEPT | bool | When a polynomial regression including bias is performed, whether to use or discard the resulting bias information.
It is meaningful only if FIT_INTERCEPT is True.
If it is False, discard the bias in the polynomial regression in the hope that the NN model can remove the bias term, even if the polynomial regression is performed with the bias included. | + +> [!NOTE] +> When `run_sim.py` is run, the `use_trained_model_diff` set in `run_sim.py` takes precedence over the `trained_model_parameter:control_application:use_trained_model_diff` set in [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml). + +## Change of nominal parameters and their reloading + +The nominal parameters of vehicle model can be changed by editing the file [nominal_param.yaml](./smart_mpc_trajectory_follower/param/nominal_param.yaml). +After changing the nominal parameters, the cache must be deleted by running the following command: + +```bash +python3 -m smart_mpc_trajectory_follower.clear_pycache +``` + +The nominal parameters include the following: + +| Parameter | Type | Description | +| ------------------------------------------------ | ----- | ------------------------------ | +| nominal_parameter:vehicle_info:wheel_base | float | wheel base [m] | +| nominal_parameter:acceleration:acc_time_delay | float | acceleration time delay [s] | +| nominal_parameter:acceleration:acc_time_constant | float | acceleration time constant [s] | +| nominal_parameter:steering:steer_time_delay | float | steer time delay [s] | +| nominal_parameter:steering:steer_time_constant | float | steer time constant [s] | + +## Change of control parameters and their reloading + +The control parameters can be changed by editing files [mpc_param.yaml](./smart_mpc_trajectory_follower/param/mpc_param.yaml) and [trained_model_param.yaml](./smart_mpc_trajectory_follower/param/trained_model_param.yaml). +Although it is possible to reflect parameter changes by restarting autoware, the following command allows us to do so without leaving autoware running: + +```bash +ros2 topic pub /pympc_reload_mpc_param_trigger std_msgs/msg/String "data: ''" --once +``` + +The main parameters among the control parameters are as follows. + +### `mpc_param.yaml` + +| Parameter | Type | Description | +| ------------------------------------ | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| mpc_parameter:system:mode | str | control mode
"ilqr": iLQR mode
"mppi": MPPI mode
"mppi_ilqr": the initial value of iLQR is given by the MPPI solution. | +| mpc_parameter:cost_parameters:Q | list[float] | Stage cost for states.
List of length 8, in order: straight deviation, lateral deviation, velocity deviation, yaw angle deviation, acceleration deviation, steer deviation, acceleration input deviation, steer input deviation cost weights. | +| mpc_parameter:cost_parameters:Q_c | list[float] | Cost in the horizon corresponding to the following timing_Q_c for the states.
The correspondence of the components of the list is the same as for Q. | +| mpc_parameter:cost_parameters:Q_f | list[float] | Termination cost for the states.
The correspondence of the components of the list is the same as for Q. | +| mpc_parameter:cost_parameters:R | list[float] | A list of length 2 where R[0] is weight of cost for the change rate of acceleration input value and R[1] is weight of cost for the change rate of steer input value. | +| mpc_parameter:mpc_setting:timing_Q_c | list[int] | Horizon numbers such that the stage cost for the states is set to Q_c. | + +### `trained_model_param.yaml` + +| Parameter | Type | Description | +| ------------------------------------------------------------------ | ---- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| trained_model_parameter:control_application:use_trained_model | bool | Whether the trained model is reflected in the control or not. | +| trained_model_parameter:control_application:use_trained_model_diff | bool | Whether the derivative of the trained model is reflected on the control or not.
It is meaningful only when use_trained_model is True, and if False, the nominal model is used for the derivative of the dynamics, and trained model is used only for prediction. | + +## Request to release the slow stop mode + +If the predicted trajectory deviates too far from the target trajectory, the system enters a slow stop mode and the vehicle stops moving. +To cancel the slow stop mode and make the vehicle ready to run again, run the following command: + +```bash +ros2 topic pub /pympc_stop_mode_reset_request std_msgs/msg/String "data: ''" --once +``` + +## Limitation + +- May not be able to start when initial position/posture is far from the target. + +- It may take some time until the end of the planning to compile numba functions at the start of the first control. + +- In the stopping action near the goal our control switches to another simple control law. As a result, the stopping action may not work except near the goal. Stopping is also difficult if the acceleration map is significantly shifted. diff --git a/control/smart_mpc_trajectory_follower/images/autoware_smart_mpc.png b/control/smart_mpc_trajectory_follower/images/autoware_smart_mpc.png new file mode 100644 index 0000000000000..0349948cf80dd Binary files /dev/null and b/control/smart_mpc_trajectory_follower/images/autoware_smart_mpc.png differ diff --git a/control/smart_mpc_trajectory_follower/images/lateral_error_nominal_model.png b/control/smart_mpc_trajectory_follower/images/lateral_error_nominal_model.png new file mode 100644 index 0000000000000..3a96faa8dcba1 Binary files /dev/null and b/control/smart_mpc_trajectory_follower/images/lateral_error_nominal_model.png differ diff --git a/control/smart_mpc_trajectory_follower/images/lateral_error_trained_model.png b/control/smart_mpc_trajectory_follower/images/lateral_error_trained_model.png new file mode 100644 index 0000000000000..3396b9e7dd444 Binary files /dev/null and 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Binary files /dev/null and b/control/smart_mpc_trajectory_follower/images/python_sim_lateral_error_trained_model.png differ diff --git a/control/smart_mpc_trajectory_follower/images/test_route.png b/control/smart_mpc_trajectory_follower/images/test_route.png new file mode 100644 index 0000000000000..1387776e1a046 Binary files /dev/null and b/control/smart_mpc_trajectory_follower/images/test_route.png differ diff --git a/control/smart_mpc_trajectory_follower/package.xml b/control/smart_mpc_trajectory_follower/package.xml new file mode 100644 index 0000000000000..70bd15f97d609 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/package.xml @@ -0,0 +1,43 @@ + + + + smart_mpc_trajectory_follower + 1.0.0 + Nodes to follow a trajectory by generating control commands using smart mpc + + + Masayuki Aino + + Apache License 2.0 + + Masayuki Aino + + ament_cmake_auto + ament_cmake_python + autoware_cmake + + autoware_adapi_v1_msgs + autoware_auto_control_msgs + autoware_auto_planning_msgs + autoware_auto_system_msgs + autoware_auto_vehicle_msgs + motion_utils + pybind11_vendor + python3-scipy + rclcpp + rclcpp_components + tier4_autoware_utils + + ros2launch + + ament_cmake_ros + ament_index_python + ament_lint_auto + autoware_lint_common + autoware_testing + ros_testing + + + ament_cmake + + diff --git a/control/smart_mpc_trajectory_follower/setup.py b/control/smart_mpc_trajectory_follower/setup.py new file mode 100644 index 0000000000000..4dca4d72929a8 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/setup.py @@ -0,0 +1,37 @@ +# cspell: ignore numba +import glob +import json +import os +from pathlib import Path + +from setuptools import find_packages +from setuptools import setup + +os.system("pip3 install numba==0.58.1 --force-reinstall") +os.system("pip3 install pybind11") +os.system("pip3 install GPy") +os.system("pip3 install torch") +package_path = {} +package_path["path"] = str(Path(__file__).parent) +with open("smart_mpc_trajectory_follower/package_path.json", "w") as f: + json.dump(package_path, f) +build_cpp_command = "g++ -Ofast -Wall -shared -std=c++11 -fPIC $(python3 -m pybind11 --includes) " +build_cpp_command += "smart_mpc_trajectory_follower/scripts/proxima_calc.cpp " +build_cpp_command += ( + "-o smart_mpc_trajectory_follower/scripts/proxima_calc$(python3-config --extension-suffix) " +) +build_cpp_command += "-lrt -I/usr/include/eigen3" +os.system(build_cpp_command) + +so_path = ( + "scripts/" + + glob.glob("smart_mpc_trajectory_follower/scripts/proxima_calc.*.so")[0].split("/")[-1] +) +setup( + name="smart_mpc_trajectory_follower", + version="1.0.0", + packages=find_packages(), + package_data={ + "smart_mpc_trajectory_follower": ["package_path.json", so_path], + }, +) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/.gitignore b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/.gitignore new file mode 100644 index 0000000000000..2d04606a236d6 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/.gitignore @@ -0,0 +1,2 @@ +__pycache__/ +*.json diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/__init__.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/clear_pycache.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/clear_pycache.py new file mode 100644 index 0000000000000..fafcb5bdecf05 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/clear_pycache.py @@ -0,0 +1,31 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +from pathlib import Path +import shutil + +import smart_mpc_trajectory_follower + +if __name__ == "__main__": + package_dir = str(Path(smart_mpc_trajectory_follower.__file__).parent) + + remove_dirs = [ + package_dir + "/__pycache__", + package_dir + "/scripts/__pycache__", + package_dir + "/training_and_data_check/__pycache__", + ] + for i in range(len(remove_dirs)): + if os.path.isdir(remove_dirs[i]): + shutil.rmtree(remove_dirs[i]) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/mpc_param.yaml b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/mpc_param.yaml new file mode 100644 index 0000000000000..710d1cc992949 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/mpc_param.yaml @@ -0,0 +1,56 @@ +mpc_parameter: + system: + mode: mppi_ilqr # option: ilqr, mppi, mppi_ilqr + mpc_setting: + ctrl_time_step: 0.03333 + mpc_freq: 3 + N: 50 + steer_ctrl_queue_size: 50 + steer_ctrl_queue_size_core: 15 + acc_ctrl_queue_size: 12 + nx_0: 6 + nu_0: 2 + timing_Q_c: [25] + cost_parameters: + Q: [0.0, 10.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] + Q_c: [1e+2, 1e+8, 1e+6, 1e+3, 1.0, 1.0, 1.0, 1.0] + Q_f: [1e+2, 1e+8, 1e+2, 1e+8, 1.0, 1.0, 1.0, 1.0] + R: [10.0, 1000.0] + acc_lim_weight: 100.0 + steer_lim_weight: 100.0 + acc_rate_lim_weight: 10000.0 + steer_rate_lim_weight: 10000.0 + min_steer_rate_transform_for_start: 0.01 + power_steer_rate_transform_for_start: 5 + coef_steer_rate_transform_for_start: 3.0 + min_loose_lateral_cost: 0.00001 + power_loose_lateral_cost: 10 + threshold_loose_lateral_cost: 0.2 + min_loose_yaw_cost: 0.00001 + power_loose_yaw_cost: 1 + threshold_loose_yaw_cost: 0.1 + ilqr: + ls_step: 0.9 + max_iter_ls: 10 + max_iter_ilqr: 1 + ilqr_tol: 0.01 + mppi: + lam: 1.0 + Sigma: [1e-15, 1e-2] + max_iter_mppi: 2 + sample_num: 100 + mppi_tol: 0.5 + mppi_step: 20 + preprocessing: + reference_horizon: 50 + cap_pred_error: [0.5, 2.0] + use_sg_for_nominal_inputs: true + sg_deg_for_nominal_inputs: 0 + sg_window_size_for_nominal_inputs: 10 + to_be_deprecated: + tighten_horizon: 20 + min_tighten_steer_rate: 1.0 + power_tighten_steer_rate_by_lateral_error: 1 + threshold_tighten_steer_rate_by_lateral_error: 0.05 + power_tighten_steer_rate_by_yaw_error: 1 + threshold_tighten_steer_rate_by_yaw_error: 0.05 diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/nominal_param.yaml b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/nominal_param.yaml new file mode 100644 index 0000000000000..aa61a25e9a0ac --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/nominal_param.yaml @@ -0,0 +1,10 @@ +# default parameter is set for sample_vehicle of AWF: https://github.com/autowarefoundation/sample_vehicle_launch/tree/main/sample_vehicle_description +nominal_parameter: + vehicle_info: + wheel_base: 2.79 + acceleration: + acc_time_delay: 0.1 + acc_time_constant: 0.1 + steering: + steer_time_delay: 0.27 + steer_time_constant: 0.24 diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/trained_model_param.yaml b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/trained_model_param.yaml new file mode 100644 index 0000000000000..6d1973586a5eb --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/param/trained_model_param.yaml @@ -0,0 +1,30 @@ +trained_model_parameter: + control_application: + use_trained_model: false + update_trained_model: false + max_train_data_size: 10000 + error_decay: [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] + use_trained_model_diff: true + use_sg_for_trained_model_diff: true + sg_deg_for_trained_model_diff: 0 + sg_window_size_for_trained_model_diff: 25 + use_sg_for_noise: true + sg_deg_for_noise: 0 + sg_window_size_for_noise: 15 + use_x_noise: false + use_y_noise: false + use_v_noise: false + use_theta_noise: false + use_acc_noise: false + use_steer_noise: false + smoothing: + acc_sigma_for_learning: 5.0 + steer_sigma_for_learning: 5.0 + acc_des_sigma_for_learning: 5.0 + steer_des_sigma_for_learning: 5.0 + x_out_sigma_for_learning: 30.0 + y_out_sigma_for_learning: 30.0 + v_out_sigma_for_learning: 30.0 + theta_out_sigma_for_learning: 10.0 + acc_out_sigma_for_learning: 5.0 + steer_out_sigma_for_learning: 5.0 diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/.gitignore b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/.gitignore new file mode 100644 index 0000000000000..9f6b19213255b --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/.gitignore @@ -0,0 +1,13 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# workspace specific settings +train_drive_*.png +test_feedforward_*/ +test_pure_pursuit_*/ +test_python_*/ +python_sim_log_*/ +sim_setting.json +auto_test_result_*.csv diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/accel_map.csv b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/accel_map.csv new file mode 100644 index 0000000000000..83fa1f2612704 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/accel_map.csv @@ -0,0 +1,20 @@ +default, 0.00, 1.39, 2.78, 4.17, 5.56, 6.94, 8.33, 9.72, 11.11, 12.50, 13.89, 15.28, 16.67 +-4.0, -4.40, -4.36, -4.38, -4.12, -4.20, -3.94, -3.98, -3.80, -3.77, -3.76, -3.59, -3.50, -3.40 +-3.5, -4.00, -3.91, -3.85, -3.64, -3.68, -3.55, -3.42, -3.24, -3.25, -3.00, -3.04, -2.93, -2.80 +-3.0, -3.40, -3.37, -3.33, -3.00, -3.00, -2.90, -2.88, -2.65, -2.43, -2.44, -2.43, -2.39, -2.30 +-2.5, -2.80, -2.72, -2.72, -2.62, -2.41, -2.43, -2.26, -2.18, -2.11, -2.03, -1.96, -1.91, -1.85 +-2.0, -2.30, -2.24, -2.12, -2.02, -1.92, -1.81, -1.67, -1.58, -1.51, -1.49, -1.40, -1.35, -1.30 +-1.5, -1.70, -1.61, -1.47, -1.46, -1.40, -1.37, -1.29, -1.24, -1.10, -0.99, -0.83, -0.80, -0.78 +-1.0, -1.30, -1.28, -1.10, -1.09, -1.04, -1.02, -0.98, -0.89, -0.82, -0.61, -0.52, -0.54, -0.56 +-0.8, -0.96, -0.90, -0.82, -0.74, -0.70, -0.65, -0.63, -0.59, -0.55, -0.44, -0.39, -0.39, -0.35 +-0.6, -0.77, -0.71, -0.67, -0.65, -0.58, -0.52, -0.51, -0.50, -0.40, -0.33, -0.30, -0.31, -0.30 +-0.4, -0.45, -0.40, -0.45, -0.44, -0.38, -0.35, -0.31, -0.30, -0.26, -0.30, -0.29, -0.31, -0.25 +-0.2, -0.24, -0.24, -0.25, -0.22, -0.23, -0.25, -0.27, -0.29, -0.24, -0.22, -0.17, -0.18, -0.12 + 0.0, 0.00, 0.00, -0.05, -0.05, -0.05, -0.05, -0.08, -0.08, -0.08, -0.08, -0.10, -0.10, -0.10 + 0.2, 0.16, 0.12, 0.02, 0.02, 0.00, 0.00, -0.05, -0.05, -0.05, -0.05, -0.08, -0.08, -0.08 + 0.4, 0.38, 0.30, 0.22, 0.25, 0.24, 0.23, 0.20, 0.16, 0.16, 0.14, 0.10, 0.05, 0.05 + 0.6, 0.52, 0.52, 0.51, 0.49, 0.43, 0.40, 0.35, 0.33, 0.33, 0.33, 0.32, 0.34, 0.34 + 0.8, 0.82, 0.81, 0.78, 0.68, 0.63, 0.56, 0.53, 0.48, 0.43, 0.41, 0.37, 0.38, 0.40 + 1.0, 1.00, 1.08, 1.01, 0.88, 0.76, 0.69, 0.66, 0.58, 0.54, 0.49, 0.45, 0.40, 0.40 + 1.5, 1.52, 1.50, 1.38, 1.26, 1.14, 1.03, 0.91, 0.82, 0.67, 0.61, 0.51, 0.41, 0.41 + 2.0, 1.80, 1.80, 1.64, 1.43, 1.25, 1.11, 0.96, 0.81, 0.70, 0.59, 0.51, 0.42, 0.42 diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/plot_auto_test_result.ipynb b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/plot_auto_test_result.ipynb new file mode 100644 index 0000000000000..dd4dc9ae25cb2 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/plot_auto_test_result.ipynb @@ -0,0 +1,180 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "e78db57e-3218-4515-9ae5-4458ea071a1c", + "metadata": {}, + "outputs": [], + "source": [ + "# cspell: ignore kernelspec ipykernel codemirror ipython nbconvert pygments nbformat \n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dacb0655-e173-483f-86ac-0f39520c66f7", + "metadata": {}, + "outputs": [], + "source": [ + "import python_simulator" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "03850f4f-99c4-4f1c-8673-8bbabddea001", + "metadata": {}, + "outputs": [], + "source": [ + "# header of auto_test_result_*.csv\n", + "header = [\n", + " \"param_name\", # 0\n", + " \"param_val\", # 1\n", + " \"max_abs_lateral_error\", # 2\n", + " \"max_abs_vel_error\", # 3\n", + " # \"max_abs_yaw_error\", # 4\n", + " # \"max_abs_acc_error\", # 5\n", + " # \"max_abs_steer_error\" # 6\n", + "]\n", + "\n", + "\n", + "plot_param_list = [\n", + " # [label, header_index, unit_for_plot, nominal_value]\n", + " [\"steer_bias\", 2, \"[deg]\", 0.0] ,\n", + " [\"steer_rate_lim\", 2, \"[rad/s]\", python_simulator.steer_rate_lim],\n", + " [\"vel_rate_lim\", 3, \"[m/ss]\", python_simulator.vel_rate_lim],\n", + " [\"steer_dead_band\", 2, \"[rad]\", python_simulator.steer_dead_band],\n", + " [\"wheel_base\",2, \"[m]\", python_simulator.L],\n", + " # [\"adaptive_gear_ratio_coef\", 2,\"[-]\", None],\n", + " [\"acc_time_delay\",3, \"[s]\", python_simulator.acc_time_delay],\n", + " [\"steer_time_delay\",2, \"[s]\", python_simulator.steer_time_delay],\n", + " [\"acc_time_constant\",3, \"[s]\", python_simulator.acc_time_constant],\n", + " [\"steer_time_constant\",2, \"[s]\", python_simulator.steer_time_constant],\n", + " [\"accel_map_scale\",3, \"[-]\", None],\n", + " [\"acc_scaling\",3, \"[-]\", 1],\n", + " [\"steer_scaling\",2, \"[-]\", 1],\n", + "]\n", + "print(plot_param_list)\n", + "print(\"len(plot_param_list)\",len(plot_param_list))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4e8af4e4-db9f-4ee9-b41e-690b74ae5cf7", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "fig = plt.figure(figsize=(30, 18), tight_layout=True)\n", + "\n", + "ax_list = []\n", + "for i in range(len(plot_param_list)):\n", + " ax_list.append(plt.subplot(4, 3, i+1))\n", + "\n", + "# ff_data_result_csv = \"auto_test_result_final_model_control_trained_with_data_collected_by_ff_control.csv\"\n", + "nominal_data_result_csv = \"auto_test_result_final_model_control_trained_with_data_collected_by_nominal_control.csv\"\n", + "\n", + "df_info_list = [ \n", + " {\"file_name\": \"nominal/auto_test_result_nominal_model_control.csv\", \n", + " \"label_name\": \"nominal\"},\n", + "\n", + " # {\"file_name\": \"poly(selected) (data using FF)/\"+ff_data_result_csv, \n", + " # \"label_name\" : \"poly(selected) (data using FF)\"}, \n", + " # # {\"file_name\": \"poly(full) (data using FF)/\"+ff_data_result_csv, \n", + " # # \"label_name\" : \"poly(full) (data using FF)\"}, \n", + " # {\"file_name\": \"poly(selected)+NN (data using FF)/\"+ff_data_result_csv, \n", + " # \"label_name\" : \"poly(selected)+NN (data using FF)\"}, \n", + " # # {\"file_name\": \"poly(full)+NN (data using FF)/\"ff_data_result_csv, \n", + " # # \"label_name\" : \"poly(full)+NN (data using FF)\"},\n", + " # {\"file_name\": \"NN (data using FF)/\"+ff_data_result_csv, \n", + " # \"label_name\" : \"NN (data using FF)\"},\n", + " \n", + " {\"file_name\": \"poly(selected) (nominal control data)/\"+nominal_data_result_csv, \n", + " \"label_name\" : \"poly(selected) (nominal control data)\"}, \n", + " # {\"file_name\": \"poly(full) (nominal control data)/\"+nominal_data_result_csv, \n", + " # \"label_name\" : \"poly(full) (nominal control data)\"},\n", + " {\"file_name\": \"poly(selected)+NN (nominal control data)/\"+nominal_data_result_csv, \n", + " \"label_name\" : \"poly(selected)+NN (nominal control data)\"}, \n", + " # {\"file_name\": \"poly(full)+NN (nominal control data)/\"+nominal_data_result_csv, \n", + " # \"label_name\" : \"poly(full)+NN (nominal control data)\"},\n", + " {\"file_name\": \"NN (nominal control data)/\"+nominal_data_result_csv, \n", + " \"label_name\" : \"NN (nominal control data)\"}, \n", + "]\n", + "\n", + "cmap = plt.get_cmap(\"tab10\") \n", + "for l in range(len(df_info_list)):\n", + " df = pd.read_csv(df_info_list[l][\"file_name\"], header=None,sep=\",\")\n", + " for i in range(len(plot_param_list)):\n", + " index_bool = df[0].values==plot_param_list[i][0]\n", + " if any(index_bool):\n", + " x = df[1].values[index_bool]\n", + " \n", + " if plot_param_list[i][0]==\"adaptive_gear_ratio_coef\":\n", + " x = np.array(range(len(x)))\n", + " x = np.array([float(x[j]) for j in range(len(x))])\n", + " if plot_param_list[i][0]==\"steer_bias\":\n", + " x *= 180.0/np.pi\n", + " \n", + " \n", + " y = df[plot_param_list[i][1]].values[index_bool]\n", + " ax_list[i].plot(x,y,\"o-\",label=df_info_list[l][\"label_name\"],color=cmap(l))\n", + " else:\n", + " pass\n", + " if i==0:\n", + " ax_list[i].plot([0],[0],\"o-\",label=df_info_list[l][\"label_name\"],color=cmap(l))\n", + "\n", + "\n", + "for i in range(len(plot_param_list)): \n", + " #ax_list[i].set_title(header[plot_param_list[i][1]]+\" / \"+plot_param_list[i][0], fontsize=16)\n", + " ax_list[i].set_xlabel(plot_param_list[i][0] + \" \" + plot_param_list[i][2],fontsize=20)\n", + " ax_list[i].set_ylabel(header[plot_param_list[i][1]],fontsize=20)\n", + " ax_list[i].grid()\n", + "\n", + " if plot_param_list[i][3] is not None:\n", + " ax_list[i].plot([plot_param_list[i][3],plot_param_list[i][3]],[-0.1,2],\"k--\")\n", + " \n", + " # lateral_error\n", + " if 2==plot_param_list[i][1]:\n", + " ax_list[i].set_ylim([-0.01,1.0])\n", + " # vel_error\n", + " if 3==plot_param_list[i][1]:\n", + " ax_list[i].set_ylim([-0.01,1.0])\n", + "\n", + " # if(y.max()>2.0):\n", + " # ax_list[i].set_ylim([-0.1,2.0])\n", + " if i==0:\n", + " ax_list[i].legend(fontsize=13)\n", + "plt.savefig(\"auto_test_result.png\")\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/python_simulator.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/python_simulator.py new file mode 100644 index 0000000000000..d706c342f04ec --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/python_simulator.py @@ -0,0 +1,1593 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore numba njit simplejson fastmath interp suptitle fftfreq basefmt markerfmt + +import csv +import datetime +import os + +import matplotlib.pyplot as plt +from numba import njit +import numpy as np +import pandas as pd +import scipy.interpolate +import simplejson as json +from smart_mpc_trajectory_follower.scripts import drive_controller +from smart_mpc_trajectory_follower.scripts import drive_functions + +print("\n\n### import python_simulator.py ###") + +ctrl_time_step = drive_functions.ctrl_time_step + +sim_dt = 0.003333 # Simulation time step +ctrl_freq = 10 # int, controlled once in 10 simulations. +acc_time_delay = drive_functions.acc_time_delay +steer_time_delay = drive_functions.steer_time_delay +acc_delay_step_sim = round(acc_time_delay / sim_dt) +steer_delay_step_sim = round(steer_time_delay / sim_dt) +acc_time_constant = drive_functions.acc_time_constant +steer_time_constant = drive_functions.steer_time_constant +steer_dead_band = 0.0012 +steer_scaling = 1.0 +acc_scaling = 1.0 +measurement_steer_bias = 0.00 +L = drive_functions.L +N = drive_functions.N + +steer_rate_lim = 0.35 +vel_rate_lim = 7.0 + +mpc_freq = drive_functions.mpc_freq + + +use_accel_map = False + +vgr_coef_a1 = 15.713 +vgr_coef_b1 = 0.053 +vgr_coef_c1 = 0.042 +vgr_coef_a2 = 15.713 +vgr_coef_b2 = 0.053 +vgr_coef_c2 = 0.042 + + +perturbed_sim_flag = False +if os.path.isfile("sim_setting.json"): + with open("sim_setting.json", "r") as file: + sim_setting_dict = json.load(file) + print("load sim_setting.json") + print("sim_setting_dict", sim_setting_dict) + perturbed_sim_flag = True +else: + print("sim_setting.json not found") + +# Rewriting for para-search +nominal_setting_dict_display = {} +if perturbed_sim_flag: + if "steer_bias" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_bias"] = 1 * measurement_steer_bias + measurement_steer_bias = sim_setting_dict["steer_bias"] + print("nominal steer_bias", nominal_setting_dict_display["steer_bias"]) + print("perturbed steer_bias", measurement_steer_bias) + print("perturbed steer_bias_deg", measurement_steer_bias * 180 / np.pi) + + if "steer_rate_lim" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_rate_lim"] = 1 * steer_rate_lim + steer_rate_lim = sim_setting_dict["steer_rate_lim"] + print("nominal steer_rate_lim", nominal_setting_dict_display["steer_rate_lim"]) + print("perturbed steer_rate_lim", steer_rate_lim) + + if "vel_rate_lim" in sim_setting_dict.keys(): + nominal_setting_dict_display["vel_rate_lim"] = 1 * vel_rate_lim + vel_rate_lim = sim_setting_dict["vel_rate_lim"] + print("nominal vel_rate_lim", nominal_setting_dict_display["vel_rate_lim"]) + print("perturbed vel_rate_lim", vel_rate_lim) + + if "wheel_base" in sim_setting_dict.keys(): + nominal_setting_dict_display["wheel_base"] = 1 * L + L = sim_setting_dict["wheel_base"] + print("nominal wheel_base", nominal_setting_dict_display["wheel_base"]) + print("perturbed wheel_base", L) + + if "steer_dead_band" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_dead_band"] = 1 * steer_dead_band + steer_dead_band = sim_setting_dict["steer_dead_band"] + print("nominal steer_dead_band", nominal_setting_dict_display["steer_dead_band"]) + print("perturbed steer_dead_band", steer_dead_band) + + if "adaptive_gear_ratio_coef" in sim_setting_dict.keys(): + nominal_setting_dict_display["adaptive_gear_ratio_coef"] = [ + 1 * vgr_coef_a1, + 1 * vgr_coef_b1, + 1 * vgr_coef_c1, + 1 * vgr_coef_a2, + 1 * vgr_coef_b2, + 1 * vgr_coef_c2, + ] + vgr_coef_a1 = sim_setting_dict["adaptive_gear_ratio_coef"][0] + vgr_coef_b1 = sim_setting_dict["adaptive_gear_ratio_coef"][1] + vgr_coef_c1 = sim_setting_dict["adaptive_gear_ratio_coef"][2] + vgr_coef_a2 = sim_setting_dict["adaptive_gear_ratio_coef"][3] + vgr_coef_b2 = sim_setting_dict["adaptive_gear_ratio_coef"][4] + vgr_coef_c2 = sim_setting_dict["adaptive_gear_ratio_coef"][5] + print( + "nominal adaptive_gear_ratio_coef", + nominal_setting_dict_display["adaptive_gear_ratio_coef"], + ) + print( + "perturbed: vgr_coef_a1", + vgr_coef_a1, + "vgr_coef_b1", + vgr_coef_b1, + "vgr_coef_c1", + vgr_coef_c1, + ) + print( + "perturbed: vgr_coef_a2", + vgr_coef_a2, + "vgr_coef_b2", + vgr_coef_b2, + "vgr_coef_c2", + vgr_coef_c2, + ) + + if "acc_time_delay" in sim_setting_dict.keys(): + nominal_setting_dict_display["acc_time_delay"] = sim_dt * acc_delay_step_sim + print("nominal acc_time_delay", nominal_setting_dict_display["acc_time_delay"]) + print("nominal acc_delay_step_sim", acc_delay_step_sim) + acc_delay_step_sim = round(sim_setting_dict["acc_time_delay"] / sim_dt) + print("perturbed acc_time_delay", sim_setting_dict["acc_time_delay"]) + print("perturbed acc_delay_step_sim", acc_delay_step_sim) + + if "steer_time_delay" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_time_delay"] = sim_dt * steer_delay_step_sim + print("nominal steer_time_delay", nominal_setting_dict_display["steer_time_delay"]) + print("nominal steer_delay_step_sim", steer_delay_step_sim) + steer_delay_step_sim = round(sim_setting_dict["steer_time_delay"] / sim_dt) + print("perturbed steer_time_delay", sim_setting_dict["steer_time_delay"]) + print("perturbed steer_delay_step_sim", steer_delay_step_sim) + + if "acc_time_constant" in sim_setting_dict.keys(): + nominal_setting_dict_display["acc_time_constant"] = 1 * acc_time_constant + acc_time_constant = sim_setting_dict["acc_time_constant"] + print("nominal acc_time_constant", nominal_setting_dict_display["acc_time_constant"]) + print("perturbed acc_time_constant", acc_time_constant) + + if "steer_time_constant" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_time_constant"] = 1 * steer_time_constant + steer_time_constant = sim_setting_dict["steer_time_constant"] + print("nominal steer_time_constant", nominal_setting_dict_display["steer_time_constant"]) + print("perturbed steer_time_constant", steer_time_constant) + + if "accel_map_scale" in sim_setting_dict.keys(): + nominal_setting_dict_display["accel_map_scale"] = None + use_accel_map = True + accel_map_scale = sim_setting_dict["accel_map_scale"] + df = pd.read_csv("accel_map.csv", header=None) + current_vel_axis = np.array( + [float(df.loc[0].values[1 + i]) for i in range(len(df.loc[0].values[1:]))] + ) + accel_cmd_axis = np.array( + [float(df[0].values[1 + i]) for i in range(len(df[0].values[1:]))] + ) + accel_map_data = np.zeros((len(accel_cmd_axis), len(current_vel_axis))) + for i in range(len(current_vel_axis)): + for j in range(len(accel_cmd_axis)): + accel_map_data[j, i] = float(df[1 + i].values[1 + j]) * ( + accel_map_scale ** (i * 1.0 / (len(current_vel_axis) - 1)) + ) + X1, X2 = np.meshgrid(current_vel_axis, accel_cmd_axis) + xy = [(x, y) for x in current_vel_axis for y in accel_cmd_axis] + z = [ + accel_map_data[j, i] + for i in range(len(current_vel_axis)) + for j in range(len(accel_cmd_axis)) + ] + accel_map_f_ = scipy.interpolate.LinearNDInterpolator(xy, z) + + def accel_map_f(x, y): + res = accel_map_f_( + [np.clip(x, a_min=current_vel_axis.min(), a_max=current_vel_axis.max())], + [np.clip(y, a_min=accel_cmd_axis.min(), a_max=accel_cmd_axis.max())], + ) + return [res] + + print("current_vel_axis", current_vel_axis) + print("accel_cmd_axis", accel_cmd_axis) + print( + "accel_map_f(current_vel_axis[-1],accel_cmd_axis[-1])", + accel_map_f(current_vel_axis[-1], accel_cmd_axis[-1]), + "accel_map_data[-1,-1]", + accel_map_data[-1, -1], + ) + print( + "accel_map_f(current_vel_axis[-1],accel_cmd_axis[-2])", + accel_map_f(current_vel_axis[-1], accel_cmd_axis[-2]), + "accel_map_data[-2,-1]", + accel_map_data[-2, -1], + ) + print("perturbed use_accel_map", use_accel_map) + + if "steer_scaling" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_scaling"] = 1 * steer_scaling + steer_scaling = sim_setting_dict["steer_scaling"] + print("nominal steer_scaling", nominal_setting_dict_display["steer_scaling"]) + print("perturbed steer_scaling", steer_scaling) + + if "acc_scaling" in sim_setting_dict.keys(): + nominal_setting_dict_display["acc_scaling"] = 1 * acc_scaling + acc_scaling = sim_setting_dict["acc_scaling"] + print("nominal acc_scaling", nominal_setting_dict_display["acc_scaling"]) + print("perturbed acc_scaling", acc_scaling) + + if "vehicle_type" in sim_setting_dict.keys(): + nominal_setting_dict_display["steer_rate_lim"] = 1 * steer_rate_lim + nominal_setting_dict_display["vel_rate_lim"] = 1 * vel_rate_lim + nominal_setting_dict_display["wheel_base"] = 1 * L + nominal_setting_dict_display["acc_time_delay"] = sim_dt * acc_delay_step_sim + nominal_setting_dict_display["steer_time_delay"] = sim_dt * steer_delay_step_sim + nominal_setting_dict_display["acc_time_constant"] = 1 * acc_time_constant + nominal_setting_dict_display["steer_time_constant"] = 1 * steer_time_constant + nominal_setting_dict_display["acc_scaling"] = 1 * acc_scaling + if sim_setting_dict["vehicle_type"] == 0: + pass + elif sim_setting_dict["vehicle_type"] == 1: + # heavy-weight bus + steer_rate_lim = 5.0 + vel_rate_lim = 7.0 + L = 4.76 + acc_delay_step_sim = round(1.0 / sim_dt) + steer_delay_step_sim = round(1.0 / sim_dt) + acc_time_constant = 1.0 + steer_time_constant = 1.0 + acc_scaling = 0.2 + elif sim_setting_dict["vehicle_type"] == 2: + # light-weight bus + steer_rate_lim = 5.0 + vel_rate_lim = 7.0 + L = 4.76 + acc_delay_step_sim = round(0.5 / sim_dt) + steer_delay_step_sim = round(0.5 / sim_dt) + acc_time_constant = 0.5 + steer_time_constant = 0.5 + acc_scaling = 0.5 + elif sim_setting_dict["vehicle_type"] == 3: + # small vehicle + steer_rate_lim = 5.0 + vel_rate_lim = 7.0 + L = 1.335 + acc_delay_step_sim = round(0.3 / sim_dt) + steer_delay_step_sim = round(0.3 / sim_dt) + acc_time_constant = 0.3 + steer_time_constant = 0.3 + acc_scaling = 1.5 + elif sim_setting_dict["vehicle_type"] == 4: + # small robot + steer_rate_lim = 60.0 * (np.pi / 180.0) + vel_rate_lim = 3.0 + L = 0.395 + acc_delay_step_sim = round(0.2 / sim_dt) + steer_delay_step_sim = round(0.2 / sim_dt) + acc_time_constant = 0.2 + steer_time_constant = 0.2 + acc_scaling = 3.0 + + print("steer_rate_lim", nominal_setting_dict_display["steer_rate_lim"], steer_rate_lim) + print("vel_rate_lim", nominal_setting_dict_display["vel_rate_lim"], vel_rate_lim) + print("wheel_base", nominal_setting_dict_display["wheel_base"], L) + print( + "acc_time_delay", + nominal_setting_dict_display["acc_time_delay"], + sim_dt * acc_delay_step_sim, + ) + print( + "steer_time_delay", + nominal_setting_dict_display["steer_time_delay"], + sim_dt * steer_delay_step_sim, + ) + print( + "acc_time_constant", + nominal_setting_dict_display["acc_time_constant"], + acc_time_constant, + ) + print( + "steer_time_constant", + nominal_setting_dict_display["steer_time_constant"], + steer_time_constant, + ) + print("acc_scaling", nominal_setting_dict_display["acc_scaling"], acc_scaling) + + +# dynamics +# @njit(cache=False, fastmath=True) # Commented out because we want to use scipy.interpolate2d +def f_sim( + states, + inputs, + L=L, + acc_time_constant=acc_time_constant, + steer_time_constant=steer_time_constant, + steer_dead_band=steer_dead_band, + steer_scaling=steer_scaling, + acc_scaling=acc_scaling, + measurement_steer_bias=measurement_steer_bias, +): + """Time derivative of sim model dynamics.""" + v = states[2] + theta = states[3] + alpha = states[4] + delta = states[5] + + delta_diff = steer_scaling * inputs[1] - delta + if delta_diff >= steer_dead_band: + delta_diff = delta_diff - steer_dead_band + elif delta_diff <= -steer_dead_band: + delta_diff = delta_diff + steer_dead_band + else: + delta_diff = 0.0 + + actual_alpha = alpha + actual_delta = delta - measurement_steer_bias + + # Acceleration input value -> Actual acceleration input value distortion applied + if use_accel_map: + if actual_alpha > 0: + actual_alpha = accel_map_f(v, actual_alpha)[0] # vel, acc_cmd + + # Tire angle input value -> Actual tire angle input value distortion application + steer_tire_angle_cmd = 1 * delta + coeff_from_tire_to_wheel = ( + 20.0 # Assuming a fixed gear ratio of 20 (moving in a range of roughly 15-30) + ) + steer_wheel = coeff_from_tire_to_wheel * steer_tire_angle_cmd + adaptive_gear_ratio1 = vgr_coef_a1 + vgr_coef_b1 * v * v - vgr_coef_c1 * abs(steer_wheel) + adaptive_gear_ratio2 = vgr_coef_a2 + vgr_coef_b2 * v * v - vgr_coef_c2 * abs(steer_wheel) + actual_delta = ( + steer_tire_angle_cmd * (adaptive_gear_ratio1 / adaptive_gear_ratio2) + - measurement_steer_bias + ) + + states_dot = np.zeros(6) + states_dot[0] = v * np.cos(theta) + states_dot[1] = v * np.sin(theta) + states_dot[2] = actual_alpha + states_dot[3] = v * np.tan(actual_delta) / L + states_dot[4] = (acc_scaling * inputs[0] - alpha) / acc_time_constant + states_dot[5] = delta_diff / steer_time_constant + return states_dot + + +def F_sim( + states, + inputs, + L=L, + acc_time_constant=acc_time_constant, + steer_time_constant=steer_time_constant, + steer_dead_band=steer_dead_band, +): + """Sim model dynamics based on the Euler method.""" + states_next = ( + states + + f_sim(states, inputs, L, acc_time_constant, steer_time_constant, steer_dead_band) * sim_dt + ) + return states_next + + +@njit(cache=False, fastmath=True) +def d_inputs_to_inputs(u_old, d_inputs): + """Compute the sequence of input values from the sequence of input change rates.""" + inputs = np.zeros((d_inputs.shape[0] * ctrl_freq * mpc_freq, 2)) + for j in range(mpc_freq): + inputs[ctrl_freq * j : ctrl_freq * (j + 1)] += ( + u_old + (j + 1) * d_inputs[0] * ctrl_time_step + ) + for i in range(1, d_inputs.shape[0]): + for j in range(mpc_freq): + inputs[ctrl_freq * (mpc_freq * i + j) : ctrl_freq * (mpc_freq * i + j + 1)] += ( + inputs[ctrl_freq * mpc_freq * i - 1] + (j + 1) * d_inputs[i] * ctrl_time_step + ) + return inputs + + +def F_true_predict( + x_current, + u_old, + d_inputs, + acc_des_queue, + steer_des_queue, + L=L, + acc_time_constant=acc_time_constant, + steer_time_constant=steer_time_constant, + steer_dead_band=steer_dead_band, +): + """Compute the true predicted trajectory based on simulator dynamics from the input values.""" + inputs = d_inputs_to_inputs(u_old, d_inputs) + predicted_traj = np.zeros((d_inputs.shape[0] + 1, x_current.shape[0])) + predicted_traj[0] += x_current + acc_queue = np.concatenate((np.array(acc_des_queue), inputs[:, 0])) + steer_queue = np.concatenate((np.array(steer_des_queue), inputs[:, 1])) + for i in range(d_inputs.shape[0]): + x_tmp = predicted_traj[i].copy() + for j in range(ctrl_freq * mpc_freq): + x_tmp = F_sim( + x_tmp, + np.array( + [ + acc_queue[ctrl_freq * mpc_freq * i + j], + steer_queue[ctrl_freq * mpc_freq * i + j], + ] + ), + L, + acc_time_constant, + steer_time_constant, + steer_dead_band, + ) + predicted_traj[i + 1] = x_tmp.copy() + return predicted_traj, inputs[:: ctrl_freq * mpc_freq] + + +def get_mpc_trajectory(x_current, trajectory_data, trajectory_interpolator_list): + """Calculate the target trajectory to be used in MPC from the given data.""" + nearest_index = np.argmin( + ((trajectory_data[:, 1:3] - x_current[:2].reshape(1, 2)) ** 2).sum(axis=1) + ) + timestamp_mpc_trajectory = ( + np.arange(N + 1) * mpc_freq * ctrl_freq * sim_dt + trajectory_data[nearest_index, 0] + ) + break_flag = False + if timestamp_mpc_trajectory[-1] >= trajectory_data[-1, 0]: + timestamp_mpc_trajectory -= timestamp_mpc_trajectory[-1] - trajectory_data[-1, 0] - 1e-16 + break_flag = True + + mpc_trajectory = np.array( + [ + trajectory_interpolator_list[i](timestamp_mpc_trajectory) + for i in range(trajectory_data.shape[1] - 1) + ] + ).T + mpc_trajectory = np.hstack( + [ + timestamp_mpc_trajectory.reshape(-1, 1) - trajectory_data[nearest_index, 0], + mpc_trajectory, + ] + ) + + X_des = np.zeros((N + 1, 8)) + X_des[:, :6] = mpc_trajectory[:, 1:7] + X_des[:, [6, 7]] = mpc_trajectory[:, [5, 6]] + U_des = np.zeros((N, 2)) + return X_des, U_des, x_current[:6] - trajectory_data[nearest_index, 1:7], break_flag + + +def get_feedforward_nominal_input(t, trajectory_data): + """Calculate the nominal input for feed-forward driving.""" + total_time = trajectory_data[-1, 0] + t_current = t - (t // total_time) * total_time + nearest_index = np.argmin(np.abs(trajectory_data[:, 0] - t_current)) + return trajectory_data[nearest_index, [5, 6]] + + +def create_additional_sine_data( + seed, + t_range, + acc_width_range, + acc_period_range, + steer_width_range, + steer_period_range, + large_steer_width_range, + large_steer_period_range, + start_large_steer_time, +): + """Create sine wave data to be added randomly to feed-forward runs.""" + np.random.seed(seed=seed) + t_acc = 0.0 + t_steer = 0.0 + t_large_steer = 0.0 + t_acc_list = [] + t_steer_list = [] + t_large_steer_list = [] + t_acc_list.append(t_acc) + t_steer_list.append(t_steer) + t_large_steer_list.append(t_large_steer) + t_large_steer += start_large_steer_time + t_large_steer_list.append(t_large_steer) + width_acc_list = [] + width_steer_list = [] + width_large_steer_list = [] + width_large_steer_list.append(0) + while True: + if max(t_acc, t_large_steer) >= t_steer: + period = ( + steer_period_range[1] - steer_period_range[0] + ) * np.random.uniform() + steer_period_range[0] + t_steer += period + t_steer_list.append(t_steer) + width_steer_list.append(steer_width_range * np.random.uniform()) + elif t_large_steer >= t_acc: + period = ( + acc_period_range[1] - acc_period_range[0] + ) * np.random.uniform() + acc_period_range[0] + t_acc += period + t_acc_list.append(t_acc) + width_acc_list.append(acc_width_range * np.random.uniform()) + else: + period = ( + large_steer_period_range[1] - large_steer_period_range[0] + ) * np.random.uniform() + large_steer_period_range[0] + t_large_steer += period + t_large_steer_list.append(t_large_steer) + width_large_steer_list.append(large_steer_width_range * np.random.uniform()) + if t_acc >= t_range[1] and t_steer >= t_range[1] and t_large_steer >= t_range[1]: + break + return ( + np.array(t_acc_list), + np.array(width_acc_list), + np.array(t_steer_list), + np.array(width_steer_list), + np.array(t_large_steer_list), + np.array(width_large_steer_list), + ) + + +@njit(cache=False, fastmath=True) +def get_current_additional_sine( + t, + t_acc_array, + width_acc_array, + t_steer_array, + width_steer_array, + t_large_steer_array, + width_large_steer_array, +): + """Calculate current values from already created sine wave data.""" + acc_index = 0 + steer_index = 0 + large_steer_index = 0 + for i in range(t_acc_array.shape[0] - 1): + if t < t_acc_array[i + 1]: + break + acc_index += 1 + for i in range(t_steer_array.shape[0] - 1): + if t < t_steer_array[i + 1]: + break + steer_index += 1 + for i in range(t_large_steer_array.shape[0] - 1): + if t < t_large_steer_array[i + 1]: + break + large_steer_index += 1 + acc = width_acc_array[acc_index] * np.sin( + 2 + * np.pi + * (t - t_acc_array[acc_index]) + / (t_acc_array[acc_index + 1] - t_acc_array[acc_index]) + ) + steer = width_steer_array[steer_index] * np.sin( + 2 + * np.pi + * (t - t_steer_array[steer_index]) + / (t_steer_array[steer_index + 1] - t_steer_array[steer_index]) + ) + steer += width_large_steer_array[large_steer_index] * np.sin( + 2 + * np.pi + * (t - t_large_steer_array[large_steer_index]) + / (t_large_steer_array[large_steer_index + 1] - t_large_steer_array[large_steer_index]) + ) + return np.array([acc, steer]) + + +def create_vel_sine_data(seed, t_range, vel_width_range, vel_period_range): + """Create sine wave data for target velocity.""" + np.random.seed(seed=seed) + t_vel = 0.0 + t_vel_list = [] + t_vel_list.append(t_vel) + width_vel_list = [] + while True: + period = ( + vel_period_range[1] - vel_period_range[0] + ) * np.random.uniform() + vel_period_range[0] + t_vel += period + t_vel_list.append(t_vel) + width_vel_list.append(vel_width_range * np.random.uniform()) + if t_vel >= t_range[1]: + break + return ( + np.array(t_vel_list), + np.array(width_vel_list), + ) + + +@njit(cache=False, fastmath=True) +def get_current_vel_sine(t, t_vel_array, width_vel_array, v_mid): + """Calculate current target velocity values from already created sine wave data.""" + vel_index = 0 + for i in range(t_vel_array.shape[0] - 1): + if t < t_vel_array[i + 1]: + break + vel_index += 1 + vel = v_mid + width_vel_array[vel_index] * np.sin( + 2 + * np.pi + * (t - t_vel_array[vel_index]) + / (t_vel_array[vel_index + 1] - t_vel_array[vel_index]) + ) + return vel + + +def get_figure_eight_point(t, circle_radius): + """ + Get the position and yaw angle in world coordinates of the figure eight given the circle radius. + + Here t is a 1-dimensional array of numpy and each t[i] represents the distance traveled. + The return value is a 2-dimensional array of positions and a 1-dimensional array of yaw angles corresponding to t. + """ + sign = -2 * (np.floor(t / (2 * np.pi * circle_radius)) % 2).astype(int) + 1 + x = circle_radius * np.sin(t / circle_radius) + y = sign * circle_radius * (1 - np.cos(t / circle_radius)) + yaw = ( + sign * ((t / circle_radius) % (2 * np.pi) - np.pi) + np.pi + ) # if sign == 1, then yaw = (t/circle_radius)%(2*np.pi). Else, yaw = 2*np.pi - (t/circle_radius)%(2*np.pi). + return np.array([x, y]).T, yaw + + +def pure_pursuit( + x_current, + target_position, + target_vel, + target_yaw, + acc_lim=7.0, + steer_lim=1.0, + wheel_base=drive_functions.L, + lookahead_time=3.0, + min_lookahead=3.0, + acc_kp=0.5, +): + """Calculate acceleration and steer angle input values based on pure pursuit.""" + present_position = x_current[:2] + present_longitudinal_velocity = x_current[2] + present_point_yaw = x_current[3] + longitudinal_vel_err = present_longitudinal_velocity - target_vel + acc_kp = 0.5 + acc_cmd = np.clip(-acc_kp * longitudinal_vel_err, -acc_lim, acc_lim) + + # compute steer cmd + cos_yaw = np.cos(target_yaw) + sin_yaw = np.sin(target_yaw) + diff_position = present_position - target_position + lat_err = -sin_yaw * diff_position[0] + cos_yaw * diff_position[1] + yaw_err = present_point_yaw - target_yaw + while True: + if yaw_err > np.pi: + yaw_err -= 2.0 * np.pi + if yaw_err < (-np.pi): + yaw_err += 2.0 * np.pi + if np.abs(yaw_err) < np.pi: + break + + lookahead = min_lookahead + lookahead_time * np.abs(present_longitudinal_velocity) + steer_kp = 2.0 * wheel_base / (lookahead * lookahead) + steer_kd = 2.0 * wheel_base / lookahead + steer_cmd = np.clip(-steer_kp * lat_err - steer_kd * yaw_err, -steer_lim, steer_lim) + return np.array([acc_cmd, steer_cmd]) + + +def get_pure_pursuit_info(x_current, trajectory_position_data, trajectory_yaw_data, previous_index): + """Calculate the target position and yaw angle required for pure pursuit.""" + search_range = ( + np.arange( + previous_index - trajectory_position_data.shape[0] // 4, + previous_index + trajectory_position_data.shape[0] // 4, + ) + % trajectory_position_data.shape[0] + ) + nearest_index = np.argmin( + ((trajectory_position_data[search_range] - x_current[:2].reshape(1, 2)) ** 2).sum(axis=1) + ) + return ( + trajectory_position_data[search_range[nearest_index]], + trajectory_yaw_data[search_range[nearest_index]], + search_range[nearest_index], + ) + + +class driving_log_updater: + """Class for updating logs when driving on the Python simulator.""" + + def __init__(self): + self.X_history = [] + self.U_history = [] + self.control_cmd_time_stamp_list = [] + self.control_cmd_steer_list = [] + self.control_cmd_acc_list = [] + self.kinematic_state_list = [] + self.acceleration_list = [] + self.steering_status_list = [] + self.control_cmd_orig_list = [] + self.operation_mode_list = [] + + def update(self, t_current, x_current, u_current): + """Update logs.""" + self.X_history.append(x_current) + self.U_history.append(u_current) + self.control_cmd_time_stamp_list.append(t_current) + self.control_cmd_steer_list.append(u_current[1]) + self.control_cmd_acc_list.append(u_current[0]) + if self.control_cmd_time_stamp_list[-1] - self.control_cmd_time_stamp_list[0] > 3.0: + self.control_cmd_time_stamp_list.pop(0) + self.control_cmd_steer_list.pop(0) + self.control_cmd_acc_list.pop(0) + t_sec = int(t_current) + t_n_sec = int(1e9 * (t_current - t_sec)) + kinematic_state = np.zeros(7) + acceleration = np.zeros(4) + steering_status = np.zeros(3) + control_cmd_orig = np.zeros(10) + operation_mode = np.zeros(3) + kinematic_state[0] = t_sec + kinematic_state[1] = t_n_sec + kinematic_state[2] = x_current[0] + kinematic_state[3] = x_current[1] + kinematic_state[4] = np.sin(0.5 * x_current[3]) + kinematic_state[5] = np.cos(0.5 * x_current[3]) + kinematic_state[6] = x_current[2] + self.kinematic_state_list.append(kinematic_state) + acceleration[0] = t_sec + acceleration[1] = t_n_sec + acceleration[3] = x_current[4] + self.acceleration_list.append(acceleration) + steering_status[0] = t_sec + steering_status[1] = t_n_sec + steering_status[2] = x_current[5] + self.steering_status_list.append(steering_status) + control_cmd_orig[0] = t_sec + control_cmd_orig[1] = t_n_sec + control_cmd_orig[4] = u_current[1] + control_cmd_orig[9] = u_current[0] + self.control_cmd_orig_list.append(control_cmd_orig) + operation_mode[0] = t_sec + operation_mode[1] = t_n_sec + operation_mode[2] = 2.0 + self.operation_mode_list.append(operation_mode) + + def save(self, save_dir): + """Save logs in csv format.""" + kinematic_states = np.zeros((len(self.kinematic_state_list), 48)) + kinematic_states[:, [0, 1, 4, 5, 9, 10, 47]] = np.array(self.kinematic_state_list) + np.savetxt(save_dir + "/kinematic_state.csv", kinematic_states, delimiter=",") + np.savetxt(save_dir + "/acceleration.csv", np.array(self.acceleration_list), delimiter=",") + np.savetxt( + save_dir + "/steering_status.csv", + np.array(self.steering_status_list), + delimiter=",", + ) + np.savetxt( + save_dir + "/control_cmd_orig.csv", + np.array(self.control_cmd_orig_list), + delimiter=",", + ) + np.savetxt( + save_dir + "/system_operation_mode_state.csv", + np.array(self.operation_mode_list), + delimiter=",", + ) + with open(save_dir + "/system_operation_mode_state.csv", "w") as f: + writer = csv.writer(f) + for i in range(len(self.operation_mode_list)): + operation_mode_plus_true = self.operation_mode_list[i].tolist() + operation_mode_plus_true.append("True") + writer.writerow(operation_mode_plus_true) + + +def slalom_drive( + save_file=True, + save_dir=None, + load_dir=drive_functions.load_dir, + visualize=True, + use_trained_model=False, + use_trained_model_diff=None, + control_type="mpc", # feedforward_test=False, + straight_line_test=False, + initial_error=np.zeros(6), + t_range=[0, 100], + seed=1, + acc_width_range=0.005, + acc_period_range=[5.0, 20.0], + steer_width_range=0.005, + steer_period_range=[5.0, 20.0], + large_steer_width_range=0.00, + large_steer_period_range=[5.0, 20.0], + start_large_steer_time=40.0, + vel_width_range=5.0, + vel_period_range=[5.0, 20.0], + v_mid=6.0, + circle_radius=30.0, +): + """Perform a slalom driving simulation.""" + if control_type == "pp": + print("\n[run figure_eight_drive]\n") + elif control_type == "ff": + print("\n[run feedforward_drive]\n") + else: + if not straight_line_test: + print("\n[run slalom_drive]\n") + else: + print("\n[straight_line_test]\n") + if save_file: + if save_dir is None: + save_dir_ = "python_sim_log_" + str(datetime.datetime.now()) + else: + save_dir_ = save_dir + if not os.path.isdir(save_dir_): + os.mkdir(save_dir_) + controller = drive_controller.drive_controller( + model_file_name=(load_dir + "/model_for_test_drive.pth"), + load_GP_dir=load_dir, + load_polynomial_reg_dir=load_dir, + use_trained_model=use_trained_model, + use_trained_model_diff=use_trained_model_diff, + load_train_data_dir=load_dir, + ) + mode = controller.mode + if control_type == "mpc": + print("mode:", mode) + + plt.rcParams["figure.figsize"] = (8, 8) + t_eval = np.arange(*t_range, sim_dt) + if not straight_line_test: + trajectory_data = np.loadtxt("slalom_course_data.csv", delimiter=",") + else: + # Test by straight_line. To run, the following create_straight_line_test_csv() must be executed + trajectory_data = np.loadtxt("straight_line.csv", delimiter=",") + trajectory_interpolator_list = [ + scipy.interpolate.interp1d(trajectory_data[:, 0], trajectory_data[:, 1 + i]) + for i in range(trajectory_data.shape[1] - 1) + ] + x_init = trajectory_data[0, 1:7] + initial_error + + x_current = x_init.copy() + + acc_des_queue = [0] * acc_delay_step_sim + steer_des_queue = [0] * steer_delay_step_sim + + calculated = 0 + break_flag = False + + tracking_error_list = [] + + total_abs_max_lateral_deviation = -1 + straight_line_abs_max_lateral_deviation = -1 + total_abs_max_velocity_error = -1 + total_abs_max_yaw_error = -1 + total_abs_max_acc_error = -1 + total_abs_max_steer_error = -1 + prev_u_actual_input = np.zeros(2) + log_updater = driving_log_updater() + + previous_pp_index = 0 + + if control_type != "mpc": # feedforward_test: + ( + t_acc_array, + width_acc_array, + t_steer_array, + width_steer_array, + t_large_steer_array, + width_large_steer_array, + ) = create_additional_sine_data( + seed, + t_range, + acc_width_range, + acc_period_range, + steer_width_range, + steer_period_range, + large_steer_width_range, + large_steer_period_range, + start_large_steer_time, + ) + if control_type == "pp": + t_figure_eight = np.arange(*[0, 4 * np.pi * circle_radius], 0.01) + trajectory_position_data, trajectory_yaw_data = get_figure_eight_point( + t_figure_eight, circle_radius + ) + # plt.plot(trajectory_position_data[:,0],trajectory_position_data[:,1]) + # plt.show() + t_vel_array, width_vel_array = create_vel_sine_data( + seed, t_range, vel_width_range, vel_period_range + ) + + for i in range(t_eval.size): + if i % ctrl_freq == 0: # update u_opt + if control_type == "mpc": # not feedforward_test: + X_des, U_des, tracking_error, break_flag = get_mpc_trajectory( + x_current, trajectory_data, trajectory_interpolator_list + ) + tracking_error_list.append(tracking_error.copy()) + + u_opt = controller.update_input_queue_and_get_optimal_control( + log_updater.control_cmd_time_stamp_list, + log_updater.control_cmd_acc_list, + log_updater.control_cmd_steer_list, + x_current, + X_des, + U_des, + ) + elif control_type == "ff": + u_opt = get_current_additional_sine( + t_eval[i], + t_acc_array, + width_acc_array, + t_steer_array, + width_steer_array, + t_large_steer_array, + width_large_steer_array, + ) + u_opt[0] += get_feedforward_nominal_input(t_eval[i], trajectory_data)[0] + elif control_type == "pp": + target_position, target_yaw, previous_pp_index = get_pure_pursuit_info( + x_current, trajectory_position_data, trajectory_yaw_data, previous_pp_index + ) + target_vel = get_current_vel_sine(t_eval[i], t_vel_array, width_vel_array, v_mid) + u_opt = pure_pursuit(x_current, target_position, target_vel, target_yaw) + u_opt += get_current_additional_sine( + t_eval[i], + t_acc_array, + width_acc_array, + t_steer_array, + width_steer_array, + t_large_steer_array, + width_large_steer_array, + ) + calculated += 1 + log_updater.update(t_eval[i], x_current, u_opt) + if ( + visualize and (control_type in ["ff", "pp"]) and (i == t_eval.size - 1 or break_flag) + ): # feedforward_test and (i == t_eval.size - 1 or break_flag): + X = np.array(log_updater.X_history) + U = np.array(log_updater.U_history) + + if not use_trained_model: + title_str = "control_using_nominal_model: " + else: + title_str = "control_using_trained_model: " + if perturbed_sim_flag: + title_str += ( + "perturbed_sim: " + + str(sim_setting_dict) + + ", nominal_model: " + + str(nominal_setting_dict_display) + ) + fig = plt.figure(figsize=(18, 12), tight_layout=True) + fig.suptitle(title_str) + plt.subplot(231) + + ax1 = plt.subplot(2, 3, 1) + ax1.plot(X[:, 0], X[:, 1], label="trajectory") + ax1.legend() + ax1.set_xlabel("x_position [m]") + ax1.set_ylabel("y_position [m]") + + time_normalize_1 = ctrl_freq * sim_dt + f_s = int(1.0 / time_normalize_1) + + ax2 = plt.subplot(2, 3, 2) + X_acc = np.fft.fft(U[:, 0]) / len(U[:, 0]) # Fourier transform of waveforms + freqs = np.fft.fftfreq(len(U[:, 0])) * f_s + ax2.stem( + freqs, + np.abs(X_acc), + use_line_collection=True, + basefmt="k-", + markerfmt="cx", + label="acc input", + ) + ax2.legend() + ax2.set_xlim([-1.0, 1.0]) + ax2.set_xlabel("freq") + ax2.set_ylabel("amplitude") + + ax3 = plt.subplot(2, 3, 3) + X_steer = np.fft.fft(U[:, 1]) / len(U[:, 1]) # Fourier transform of waveforms + freqs = np.fft.fftfreq(len(U[:, 1])) * f_s + ax3.stem( + freqs, + np.abs(X_steer), + use_line_collection=True, + basefmt="k-", + markerfmt="cx", + label="steer input", + ) + ax3.legend() + ax3.set_xlim([-1.0, 1.0]) + ax3.set_xlabel("freq") + ax3.set_ylabel("amplitude") + + ax5 = plt.subplot(2, 3, 5) + ax5.plot(time_normalize_1 * np.arange(U.shape[0]), U[:, 0], label="acc input") + ax5.legend() + + ax6 = plt.subplot(2, 3, 6) + ax6.plot(time_normalize_1 * np.arange(U.shape[0]), U[:, 1], label="steer input") + ax6.legend() + + if save_file: + png_save_dir = save_dir_ + else: + png_save_dir = "." + if control_type == "ff": + plt.savefig(png_save_dir + "/python_simulator_feedforward_drive.png") + elif control_type == "pp": + plt.savefig(png_save_dir + "/python_simulator_pure_pursuit_drive.png") + plt.close() + + if ( + visualize + and (control_type == "mpc") + and (i % 1000 * ctrl_freq == 999 * ctrl_freq or i == t_eval.size - 1 or break_flag) + ): + fig = plt.figure(figsize=(24, 15), tight_layout=True) + if not use_trained_model: + title_str = "control_using_nominal_model: " + else: + title_str = "control_using_trained_model: " + if perturbed_sim_flag: + title_str += ( + "perturbed_sim: " + + str(sim_setting_dict) + + ", nominal_model: " + + str(nominal_setting_dict_display) + ) + fig.suptitle(title_str) + + plt.subplot(331) + + ax1 = plt.subplot(3, 3, 1) + X = np.array(log_updater.X_history) + U = np.array(log_updater.U_history) + X_des_hist = np.array(controller.X_des_history) + time_normalize_1 = ctrl_freq * sim_dt + time_normalize_2 = ctrl_freq * mpc_freq * sim_dt + ax1.scatter( + trajectory_data[:, 1], + trajectory_data[:, 2], + s=4, + c="orange", + label="reference_trajectory", + ) + ax1.plot(X[:, 0], X[:, 1], label="trajectory") + if mode != "mppi": + ax1.scatter( + controller.nominal_traj_ilqr[:, 0], + controller.nominal_traj_ilqr[:, 1], + s=4, + c="red", + label="pred_trajectory_ilqr", + ) + true_prediction, nominal_inputs = F_true_predict( + x_current, + controller.u_old, + controller.nominal_inputs_ilqr, + acc_des_queue, + steer_des_queue, + ) + ax1.scatter( + true_prediction[:, 0], + true_prediction[:, 1], + s=4, + c="green", + label="true_prediction", + ) + if mode != "ilqr": + ax1.scatter( + controller.nominal_traj_mppi[:, 0], + controller.nominal_traj_mppi[:, 1], + s=4, + c="pink", + label="pred_trajectory_mppi", + ) + + ax1.legend() + ax1.set_xlabel("x_position [m]") + ax1.set_ylabel("y_position [m]") + + ax2 = plt.subplot(3, 3, 2) + tracking_error_array = np.array(tracking_error_list) + lateral_deviation = ( + -np.sin(X_des_hist[:, 3]) * tracking_error_array[:, 0] + + np.cos(X_des_hist[:, 3]) * tracking_error_array[:, 1] + ) + + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + lateral_deviation, + label="lateral_deviation", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + np.zeros(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + 0.05 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -0.05 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + 0.1 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -0.1 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + 0.15 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -0.15 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + 0.2 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -0.2 * np.ones(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax2.set_xlabel("Time [s]") + ax2.set_ylabel("Lateral deviation [m]") + ax2.legend() + + straight_line_index = np.where(X_des_hist[:, 0] < 250.0)[ + 0 + ].max() # Before 250 [m] is considered to be a straight run. + total_abs_max_lateral_deviation = np.abs(lateral_deviation).max() + total_abs_mean_lateral_deviation = np.abs(lateral_deviation).mean() + straight_line_abs_max_lateral_deviation = np.abs( + lateral_deviation[: straight_line_index + 1] + ).max() + ax2.set_title( + "abs_max(lateral_dev) = " + + str(total_abs_max_lateral_deviation) + + "\nabs_max(lateral_dev[straight_line]) = " + + str(straight_line_abs_max_lateral_deviation) + ) + + ax3 = plt.subplot(3, 3, 4) + ax3.plot(time_normalize_1 * np.arange(X.shape[0]), X[:, 2], label="velocity") + ax3.plot( + time_normalize_1 * np.arange(X.shape[0]), X_des_hist[:, 2], label="velocity_target" + ) + ax3.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -tracking_error_array[:, 2], + label="velocity_error", + ) + if mode != "mppi": + ax3.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(true_prediction.shape[0]), + true_prediction[:, 2], + s=4, + label="velocity_true_prediction", + ) + ax3.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(controller.nominal_traj_ilqr.shape[0]), + controller.nominal_traj_ilqr[:, 2], + s=4, + label="velocity_prediction_ilqr", + ) + ax3.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + np.zeros(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax3.set_xlabel("Time [s]") + ax3.set_ylabel("velocity [m/s]") + ax3.legend() + total_abs_max_velocity_error = np.abs(tracking_error_array[:, 2]).max() + total_abs_mean_velocity_error = np.abs(tracking_error_array[:, 2]).mean() + straight_line_abs_max_velocity_error = np.abs( + tracking_error_array[: straight_line_index + 1, 2] + ).max() + ax3.set_title( + "abs_max(velocity_error) = " + + str(total_abs_max_velocity_error) + + "\nabs_max(velocity_error[straight_line]) = " + + str(straight_line_abs_max_velocity_error) + ) + + ax4 = plt.subplot(3, 3, 5) + ax4.plot(time_normalize_1 * np.arange(X.shape[0]), X[:, 3], label="yaw") + ax4.plot(time_normalize_1 * np.arange(X.shape[0]), X_des_hist[:, 3], label="yaw_target") + ax4.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -tracking_error_array[:, 3], + label="yaw_error", + ) + if mode != "mppi": + ax4.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(true_prediction.shape[0]), + true_prediction[:, 3], + s=4, + label="yaw_true_prediction", + ) + ax4.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(controller.nominal_traj_ilqr.shape[0]), + controller.nominal_traj_ilqr[:, 3], + s=4, + label="yaw_prediction_ilqr", + ) + ax4.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + np.zeros(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax4.set_xlabel("Time [s]") + ax4.set_ylabel("yaw [rad]") + ax4.legend() + total_abs_max_yaw_error = np.abs(tracking_error_array[:, 3]).max() + total_abs_mean_yaw_error = np.abs(tracking_error_array[:, 3]).mean() + straight_line_abs_max_yaw_error = np.abs( + tracking_error_array[: straight_line_index + 1, 3] + ).max() + ax4.set_title( + "abs_max(yaw_error) = " + + str(total_abs_max_yaw_error) + + "\nabs_max(yaw_error[straight_line]) = " + + str(straight_line_abs_max_yaw_error) + ) + + ax5 = plt.subplot(3, 3, 7) + ax5.plot(time_normalize_1 * np.arange(X.shape[0]), X[:, 4], label="acc") + ax5.plot(time_normalize_1 * np.arange(X.shape[0]), U[:, 0], label="acc_input") + ax5.plot(time_normalize_1 * np.arange(X.shape[0]), X_des_hist[:, 4], label="acc_target") + ax5.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -tracking_error_array[:, 4], + label="acc_error", + ) + if mode != "mppi": + ax5.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(true_prediction.shape[0]), + true_prediction[:, 4], + s=4, + label="acc_true_prediction", + ) + ax5.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(controller.nominal_traj_ilqr.shape[0]), + controller.nominal_traj_ilqr[:, 4], + s=4, + label="acc_prediction_ilqr", + ) + ax5.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(nominal_inputs.shape[0]), + nominal_inputs[:, 0], + s=4, + label="acc_input_schedule", + ) + ax5.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + np.zeros(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax5.set_xlabel("Time [s]") + ax5.set_ylabel("acc [m/s^2]") + ax5.legend() + total_abs_max_acc_error = np.abs(tracking_error_array[:, 4]).max() + total_abs_mean_acc_error = np.abs(tracking_error_array[:, 4]).mean() + straight_line_abs_max_acc_error = np.abs( + tracking_error_array[: straight_line_index + 1, 4] + ).max() + ax5.set_title( + "abs_max(acc_error) = " + + str(total_abs_max_acc_error) + + "\nabs_max(acc_error[straight_line]) = " + + str(straight_line_abs_max_acc_error) + ) + + ax6 = plt.subplot(3, 3, 8) + ax6.plot(time_normalize_1 * np.arange(X.shape[0]), X[:, 5], label="steer") + ax6.plot(time_normalize_1 * np.arange(X.shape[0]), U[:, 1], label="steer_input") + ax6.plot( + time_normalize_1 * np.arange(X.shape[0]), X_des_hist[:, 7], label="steer_mpc_target" + ) + ax6.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + -tracking_error_array[:, 5], + label="steer_error", + ) + if mode != "mppi": + ax6.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(true_prediction.shape[0]), + true_prediction[:, 5], + s=4, + label="steer_true_prediction", + ) + ax6.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(controller.nominal_traj_ilqr.shape[0]), + controller.nominal_traj_ilqr[:, 5], + s=4, + label="steer_prediction_ilqr", + ) + ax6.scatter( + time_normalize_1 * (X.shape[0] - 1) + + time_normalize_2 * np.arange(nominal_inputs.shape[0]), + nominal_inputs[:, 1], + s=4, + label="steer_input_schedule", + ) + ax6.plot( + time_normalize_1 * np.arange(tracking_error_array.shape[0]), + np.zeros(tracking_error_array.shape[0]), + linestyle="dashed", + ) + ax6.set_xlabel("Time [s]") + ax6.set_ylabel("steer [rad]") + ax6.legend() + total_abs_max_steer_error = np.abs(tracking_error_array[:, 5]).max() + total_abs_mean_steer_error = np.abs(tracking_error_array[:, 5]).mean() + straight_line_abs_max_steer_error = np.abs( + tracking_error_array[: straight_line_index + 1, 5] + ).max() + ax6.set_title( + "abs_max(steer_error) = " + + str(total_abs_max_steer_error) + + "\nabs_max(steer_error[straight_line]) = " + + str(straight_line_abs_max_steer_error) + ) + + ax7 = plt.subplot(3, 3, 3) + f_s = int(1.0 / time_normalize_1) + + steer_state = X[:, 5] + X_steer = np.fft.fft(steer_state) # Fourier transform of waveforms + freqs = np.fft.fftfreq(len(steer_state)) * f_s + ax7.stem( + freqs, + np.abs(X_steer) / len(steer_state), + use_line_collection=True, + basefmt="k-", + markerfmt="rx", + label="steer_state", + ) + + lateral_acc = X[:, 2] * X[:, 2] * np.tan(X[:, 5]) / L + steer_dot = np.zeros(X.shape[0]) + steer_dot[0] = (X[1, 5] - X[0, 5]) / time_normalize_1 + steer_dot[-1] = (X[-1, 5] - X[-2, 5]) / time_normalize_1 + steer_dot[1:-1] = 0.5 * (X[2:, 5] - X[:-2, 5]) / time_normalize_1 + lateral_jerk = 2 * X[:, 2] * np.tan(X[:, 5]) * X[:, 4] / L + X[:, 2] * X[ + :, 2 + ] * steer_dot / (L * np.cos(X[:, 5]) * np.cos(X[:, 5])) + + X_lateral_acc = np.fft.fft(lateral_acc) # Fourier transform of waveforms + freqs = np.fft.fftfreq(len(lateral_acc)) * f_s + ax7.stem( + freqs, + np.abs(X_lateral_acc) / len(lateral_acc), + use_line_collection=True, + basefmt="k-", + markerfmt="gx", + label="lateral_acc", + ) + + X_lateral_jerk = np.fft.fft(lateral_jerk) # Fourier transform of waveforms + freqs = np.fft.fftfreq(len(lateral_jerk)) * f_s + ax7.stem( + freqs, + np.abs(X_lateral_jerk) / len(lateral_jerk), + use_line_collection=True, + basefmt="k-", + markerfmt="bx", + label="lateral_jerk", + ) + + ax7.set_xlabel("Frequency in Hertz[Hz]") + ax7.set_ylabel("Amplitude (normalized dividing by data length)") + ax7.set_xlim(-1, 1) + ax7.legend() + + if use_accel_map: + ax9 = plt.subplot(3, 3, 9, projection="3d") + X1, X2 = np.meshgrid(current_vel_axis, accel_cmd_axis) + ax9.plot_surface(X1, X2, accel_map_data) + + if save_file: + png_save_dir = save_dir_ + else: + png_save_dir = "." + if not use_trained_model: + plt.savefig(png_save_dir + "/python_simulator_nominal_model_fig_" + str(i) + ".png") + else: + plt.savefig(png_save_dir + "/python_simulator_trained_model_fig_" + str(i) + ".png") + plt.close() + + np.savetxt( + save_dir_ + "/lateral_deviation.csv", + np.hstack( + [time_normalize_1 * np.arange(tracking_error_array.shape[0]), lateral_deviation] + ), + delimiter=",", + ) + + np.savetxt( + save_dir_ + "/steer_state.csv", + np.hstack( + [time_normalize_1 * np.arange(tracking_error_array.shape[0]), steer_state] + ), + delimiter=",", + ) + + acc_des_queue.append(u_opt[0]) + steer_des_queue.append(u_opt[1]) + u_actual_input = np.array([acc_des_queue.pop(0), steer_des_queue.pop(0)]) + + # Logic-level restrictions on control inputs + delta_steer_max = steer_rate_lim * sim_dt + u_actual_input[0] = np.clip(u_actual_input[0], -vel_rate_lim, vel_rate_lim) + u_actual_input[1] = np.clip( + u_actual_input[1], + prev_u_actual_input[1] - delta_steer_max, + prev_u_actual_input[1] + delta_steer_max, + ) + + x_next = F_sim(x_current, u_actual_input) + x_current = x_next.copy() + prev_u_actual_input = u_actual_input.copy() + if break_flag: + controller.send_initialize_input_queue() + controller.stop_model_update() + break + if save_file: + log_updater.save(save_dir_) + + if control_type == "mpc" and perturbed_sim_flag: + auto_test_performance_result_dict = { + "total_abs_max_lateral_deviation": total_abs_max_lateral_deviation, + "straight_line_abs_max_lateral_deviation": straight_line_abs_max_lateral_deviation, + "total_abs_max_velocity_error": total_abs_max_velocity_error, + "total_abs_max_yaw_error": total_abs_max_yaw_error, + "total_abs_max_acc_error": total_abs_max_acc_error, + "total_abs_max_steer_error": total_abs_max_steer_error, + "use_trained_model": use_trained_model, + "sim_setting_dict": sim_setting_dict, + "nominal_setting_dict_display": nominal_setting_dict_display, + } + auto_test_performance_result_list = [ + total_abs_max_lateral_deviation, + total_abs_max_velocity_error, + total_abs_max_yaw_error, + total_abs_max_acc_error, + total_abs_max_steer_error, + total_abs_mean_lateral_deviation, + total_abs_mean_velocity_error, + total_abs_mean_yaw_error, + total_abs_mean_acc_error, + total_abs_mean_steer_error, + straight_line_abs_max_lateral_deviation, + ] + + if save_file: + with open(save_dir_ + "/auto_test_performance_result.json", "w") as json_f: + json.dump(auto_test_performance_result_dict, json_f) + print("how_many_time_controlled", calculated) + + return auto_test_performance_result_list + + +def create_straight_line_test_csv( + jerk=0.3, starting_vel=5.0, interval_1=2.0, interval_2=3.0, interval_3=10.0 +): + """Generate data for a straight line driving test.""" + t_1 = 10.0 + t_2 = t_1 + interval_1 # Increasing acceleration. + t_3 = t_2 + interval_2 # Constant acceleration + t_4 = t_3 + interval_1 # Decreasing acceleration. + t_5 = t_4 + interval_3 # acceleration = 0 + t_6 = t_5 + interval_1 # Decreasing acceleration. + t_7 = t_6 + interval_2 # Constant acceleration + t_8 = t_7 + interval_1 # Decreasing acceleration. + vel_t1 = starting_vel + x_t1 = starting_vel * t_1 + vel_t2 = vel_t1 + 0.5 * jerk * interval_1 * interval_1 + x_t2 = x_t1 + vel_t1 * interval_1 + 0.5 * jerk * interval_1 * interval_1 * interval_1 / 3 + vel_t3 = vel_t2 + jerk * interval_1 * interval_2 + x_t3 = x_t2 + vel_t2 * interval_2 + 0.5 * jerk * interval_1 * interval_2 * interval_2 + vel_t4 = vel_t3 + 0.5 * jerk * interval_1 * interval_1 + x_t4 = x_t3 + vel_t4 * interval_1 - 0.5 * jerk * interval_1 * interval_1 * interval_1 / 3 + vel_t5 = vel_t4 + x_t5 = x_t4 + vel_t4 * interval_3 + vel_t6 = vel_t5 - 0.5 * jerk * interval_1 * interval_1 + x_t6 = x_t5 + vel_t5 * interval_1 - 0.5 * jerk * interval_1 * interval_1 * interval_1 / 3 + vel_t7 = vel_t6 - jerk * interval_1 * interval_2 + x_t7 = x_t6 + vel_t6 * interval_2 - 0.5 * jerk * interval_1 * interval_2 * interval_2 + vel_t8 = vel_t7 - 0.5 * jerk * interval_1 * interval_1 + x_t8 = x_t7 + vel_t8 * interval_1 + 0.5 * jerk * interval_1 * interval_1 * interval_1 / 3 + + def calc_longitudinal_state(t): + if t < t_1: + return starting_vel * t, starting_vel, 0.0 + elif t < t_2: + return ( + x_t1 + vel_t1 * (t - t_1) + 0.5 * jerk * (t - t_1) * (t - t_1) * (t - t_1) / 3, + vel_t1 + 0.5 * jerk * (t - t_1) * (t - t_1), + jerk * (t - t_1), + ) + elif t < t_3: + return ( + x_t2 + vel_t2 * (t - t_2) + 0.5 * jerk * (t_2 - t_1) * (t - t_2) * (t - t_2), + vel_t2 + jerk * (t_2 - t_1) * (t - t_2), + jerk * (t_2 - t_1), + ) + elif t < t_4: + return ( + x_t4 - vel_t4 * (t_4 - t) + 0.5 * jerk * (t_4 - t) * (t_4 - t) * (t_4 - t) / 3, + vel_t4 - 0.5 * jerk * (t_4 - t) * (t_4 - t), + jerk * (t_4 - t), + ) + elif t < t_5: + return x_t4 + vel_t4 * (t - t_4), vel_t4, 0.0 + elif t < t_6: + return ( + x_t5 + vel_t5 * (t - t_5) - 0.5 * jerk * (t - t_5) * (t - t_5) * (t - t_5) / 3, + vel_t5 - 0.5 * jerk * (t - t_5) * (t - t_5), + -jerk * (t - t_5), + ) + elif t < t_7: + return ( + x_t6 + vel_t6 * (t - t_6) - 0.5 * jerk * (t_6 - t_5) * (t - t_6) * (t - t_6), + vel_t6 - jerk * (t_6 - t_5) * (t - t_6), + -jerk * (t_6 - t_5), + ) + elif t < t_8: + return ( + x_t8 - vel_t8 * (t_8 - t) - 0.5 * jerk * (t_8 - t) * (t_8 - t) * (t_8 - t) / 3, + vel_t8 + 0.5 * jerk * (t_8 - t) * (t_8 - t), + -jerk * (t_8 - t), + ) + else: + return x_t8 + vel_t8 * (t - t_8), vel_t8, 0.0 + + t_range = [0, 100] + time_stamps = np.arange(*t_range, 0.001) + trajectory_data = np.zeros((time_stamps.shape[0], 9)) + trajectory_data[:, 0] = time_stamps + for i in range(time_stamps.shape[0]): + ( + trajectory_data[i, 1], + trajectory_data[i, 3], + trajectory_data[i, 5], + ) = calc_longitudinal_state(time_stamps[i]) + np.savetxt("straight_line.csv", trajectory_data, delimiter=",") diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_python_simulator.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_python_simulator.py new file mode 100644 index 0000000000000..6b477bb804ac9 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_python_simulator.py @@ -0,0 +1,36 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import numpy as np +import python_simulator +from smart_mpc_trajectory_follower.training_and_data_check import train_drive_NN_model + +initial_error = np.array( + [0.001, 0.03, 0.01, -0.001, 0, 2 * python_simulator.measurement_steer_bias] +) + +save_dir = "test_python_sim" +python_simulator.slalom_drive(save_dir=save_dir, initial_error=initial_error) + +model_trainer = train_drive_NN_model.train_drive_NN_model() +model_trainer.add_data_from_csv(save_dir) +model_trainer.save_train_data(save_dir) +model_trainer.get_trained_model() +model_trainer.save_models(save_dir=save_dir) + +save_dir = "test_python_trained_sim" +load_dir = "test_python_sim" +python_simulator.slalom_drive( + save_dir=save_dir, load_dir=load_dir, use_trained_model=True, initial_error=initial_error +) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_sim.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_sim.py new file mode 100644 index 0000000000000..3125719556559 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/run_sim.py @@ -0,0 +1,392 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore oneline + +import argparse +from enum import Enum +from importlib import reload as ir +import json +import os +import time +import traceback +from typing import Dict + +import numpy as np +import python_simulator +from smart_mpc_trajectory_follower.training_and_data_check import train_drive_NN_model + +parser = argparse.ArgumentParser() +parser.add_argument("--param_name", default=None) +args = parser.parse_args() + +P1 = 0.8 +P2 = 1.2 + +USE_TRAINED_MODEL_DIFF = True +DATA_COLLECTION_MODE = "pp" # option: "pp": pure_pursuit, "ff": feed_forward, "mpc": smart_mpc +USE_POLYNOMIAL_REGRESSION = True +USE_SELECTED_POLYNOMIAL = True +FORCE_NN_MODEL_TO_ZERO = False + + +FIT_INTERCEPT = True # Should be True if FORCE_NN_MODEL_TO_ZERO is True +USE_INTERCEPT = False # Should be True if FORCE_NN_MODEL_TO_ZERO is True + + +class ChangeParam(Enum): + """Parameters to be changed when running the simulation.""" + + steer_bias = [ + -1.0 * np.pi / 180.0, + -0.8 * np.pi / 180.0, + -0.6 * np.pi / 180.0, + -0.4 * np.pi / 180.0, + -0.2 * np.pi / 180.0, + 0.0, + 0.2 * np.pi / 180.0, + 0.4 * np.pi / 180.0, + 0.6 * np.pi / 180.0, + 0.8 * np.pi / 180.0, + 1.0 * np.pi / 180.0, + ] + """steer midpoint (soft + hard)""" + + steer_rate_lim = [0.020, 0.050, 0.100, 0.150, 0.200, 0.300, 0.400, 0.500] + """Maximum steer angular velocity""" + + vel_rate_lim = [0.5, 1.0, 3.0, 5.0, 7.0, 9.0] + """Maximum acceleration/deceleration""" + + wheel_base = [0.5, 1.0, 1.5, 2.0, 3.0, 5.0, 7.0] + """wheel base""" + + steer_dead_band = [0.0000, 0.0012, 0.0025, 0.0050, 0.01] + """steer dead band""" + + adaptive_gear_ratio_coef = [ + [15.713, 0.053, 0.042, 15.713, 0.053, 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, 0.053, 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, 0.053, 0.042], + [15.713, 0.053, 0.042, 15.713, P1 * 0.053, 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P1 * 0.053, 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P1 * 0.053, 0.042], + [15.713, 0.053, 0.042, 15.713, P2 * 0.053, 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P2 * 0.053, 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P2 * 0.053, 0.042], + [15.713, 0.053, 0.042, 15.713, 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, 15.713, P1 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P1 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P1 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, 15.713, P2 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P2 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P2 * 0.053, P1 * 0.042], + [15.713, 0.053, 0.042, 15.713, 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, 15.713, P1 * 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P1 * 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P1 * 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, 15.713, P2 * 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P1 * 15.713, P2 * 0.053, P2 * 0.042], + [15.713, 0.053, 0.042, P2 * 15.713, P2 * 0.053, P2 * 0.042], + ] + """velocity-dependent gear ratio""" + + acc_time_delay = [0.00, 0.1, 0.27, 0.40, 0.60, 0.80, 1.01] + """acc time delay""" + + steer_time_delay = [0.00, 0.1, 0.27, 0.40, 0.60, 0.80, 1.02] + """steer time delay""" + + acc_time_constant = [0.01, 0.1, 0.20, 0.24, 0.40, 0.60, 0.80, 1.01] + """time constant""" + + steer_time_constant = [0.01, 0.1, 0.20, 0.24, 0.40, 0.60, 0.80, 1.02] + """time constant""" + + accel_map_scale = [0.2, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0] + """pedal - real acceleration correspondence""" + + acc_scaling = [0.2, 0.5, 1.0, 2.0, 3.0, 4.0, 5.01] + """Acceleration scaling coefficient""" + + steer_scaling = [0.2, 0.5, 1.0, 2.0, 3.0, 4.0, 5.02] + """Steer scaling coefficient""" + + vehicle_type = [1, 2, 3, 4] + """change to other vehicle parameters""" + + +def run_simulator(change_param: ChangeParam): + """Run the simulator.""" + # initialize parameters + print("reset sim_setting_json") + data: Dict[str, float] = {} + with open("sim_setting.json", "w") as f: + json.dump(data, f) + + param_val_list = change_param.value + start_time = time.time() + + for j in range(len(param_val_list)): + i = j + 0 + with open("sim_setting.json", "r") as f: + data = json.load(f) + + data[change_param.name] = param_val_list[j] + with open("sim_setting.json", "w") as f: + json.dump(data, f) + ir(python_simulator) + + try: + initial_error = np.array( + [0.001, 0.03, 0.01, -0.001, 0, 2 * python_simulator.measurement_steer_bias] + ) + if DATA_COLLECTION_MODE in ["ff", "pp"]: + if DATA_COLLECTION_MODE == "ff": + save_dir = "test_feedforward_sim" + change_param.name + str(i) + else: + save_dir = "test_pure_pursuit_sim" + change_param.name + str(i) + python_simulator.slalom_drive( + save_dir=save_dir, + control_type=DATA_COLLECTION_MODE, + t_range=[0, 200.0], + acc_width_range=0.005, + acc_period_range=[5.0, 20.0], + steer_width_range=0.005, + steer_period_range=[5.0, 20.0], + large_steer_width_range=0.05, + large_steer_period_range=[10.0, 20.0], + start_large_steer_time=150.0, + ) + if FORCE_NN_MODEL_TO_ZERO: + model_trainer = train_drive_NN_model.train_drive_NN_model() + else: + model_trainer = train_drive_NN_model.train_drive_NN_model( + alpha_1_for_polynomial_regression=0.1**5, + alpha_2_for_polynomial_regression=0.1**5, + ) + + model_trainer.add_data_from_csv(save_dir) + start_time_learning = time.time() + model_trainer.get_trained_model( + use_polynomial_reg=USE_POLYNOMIAL_REGRESSION, + use_selected_polynomial=USE_SELECTED_POLYNOMIAL, + force_NN_model_to_zero=FORCE_NN_MODEL_TO_ZERO, + fit_intercept=FIT_INTERCEPT, + use_intercept=USE_INTERCEPT, + ) + learning_computation_time = time.time() - start_time_learning + model_trainer.plot_trained_result(save_dir=save_dir) + model_trainer.save_models(save_dir=save_dir) + load_dir = save_dir + if DATA_COLLECTION_MODE == "ff": + save_dir = "test_python_ff_aided_sim_" + change_param.name + str(i) + elif DATA_COLLECTION_MODE == "pp": + save_dir = "test_python_pp_aided_sim_" + change_param.name + str(i) + auto_test_performance_result_list = python_simulator.slalom_drive( + load_dir=load_dir, + save_dir=save_dir, + use_trained_model=True, + use_trained_model_diff=USE_TRAINED_MODEL_DIFF, + initial_error=initial_error, + ) + + print("learning_computation_time:", learning_computation_time) + if DATA_COLLECTION_MODE == "ff": + f = open(save_dir + "/computational_time_learning_from_ff_data.txt", "w") + f.write(str(learning_computation_time)) + f.close() + f = open( + "auto_test_result_intermediate_model_control_trained_with_data_collected_by_ff_control.csv", + mode="a", + ) + elif DATA_COLLECTION_MODE == "pp": + f = open(save_dir + "/computational_time_learning_from_pp_data.txt", "w") + f.write(str(learning_computation_time)) + f.close() + f = open( + "auto_test_result_intermediate_model_control_trained_with_data_collected_by_pp_control.csv", + mode="a", + ) + else: + save_dir = "test_python_sim_" + change_param.name + str(i) + auto_test_performance_result_list = python_simulator.slalom_drive( + save_dir=save_dir, + initial_error=initial_error, + ) + f = open("auto_test_result_nominal_model_control.csv", mode="a") + + print( + change_param.name, + str(param_val_list[j]).replace(",", "_"), + *auto_test_performance_result_list, + sep=",", + file=f + ) + f.close() + + print(i, "auto_test_performance_result_list", auto_test_performance_result_list) + + skip_learning_for_developing_testcase = False + if not skip_learning_for_developing_testcase: + ir(train_drive_NN_model) + model_trainer = train_drive_NN_model.train_drive_NN_model() + learning_computation_time = None + if DATA_COLLECTION_MODE in ["ff", "pp"]: + model_trainer.add_data_from_csv(load_dir) + model_trainer.add_data_from_csv(save_dir) + start_time_learning = time.time() + model_trainer.update_saved_trained_model( + path=load_dir + "/model_for_test_drive.pth", + use_polynomial_reg=USE_POLYNOMIAL_REGRESSION, + use_selected_polynomial=USE_SELECTED_POLYNOMIAL, + force_NN_model_to_zero=FORCE_NN_MODEL_TO_ZERO, + fit_intercept=FIT_INTERCEPT, + use_intercept=USE_INTERCEPT, + ) + learning_computation_time = time.time() - start_time_learning + model_trainer.plot_trained_result(save_dir=save_dir) + model_trainer.save_models(save_dir=save_dir) + if DATA_COLLECTION_MODE == "ff": + load_dir = "test_python_ff_aided_sim_" + change_param.name + str(i) + save_dir = "test_python_ff_aided_sim_trained_" + change_param.name + str(i) + elif DATA_COLLECTION_MODE == "pp": + load_dir = "test_python_pp_aided_sim_" + change_param.name + str(i) + save_dir = "test_python_pp_aided_sim_trained_" + change_param.name + str(i) + else: + model_trainer.add_data_from_csv(save_dir) + start_time_learning = time.time() + model_trainer.get_trained_model( + use_polynomial_reg=USE_POLYNOMIAL_REGRESSION, + use_selected_polynomial=USE_SELECTED_POLYNOMIAL, + force_NN_model_to_zero=FORCE_NN_MODEL_TO_ZERO, + fit_intercept=FIT_INTERCEPT, + use_intercept=USE_INTERCEPT, + ) + learning_computation_time = time.time() - start_time_learning + model_trainer.plot_trained_result(save_dir=save_dir) + model_trainer.save_models(save_dir=save_dir) + + load_dir = "test_python_sim_" + change_param.name + str(i) + save_dir = "test_python_sim_trained_" + change_param.name + str(i) + auto_test_performance_result_list = python_simulator.slalom_drive( + load_dir=load_dir, + use_trained_model=True, + use_trained_model_diff=USE_TRAINED_MODEL_DIFF, + save_dir=save_dir, + initial_error=initial_error, + ) + print("learning_computation_time: ", learning_computation_time) + f = open(save_dir + "/test_info.txt", "w") + f.write("commit id: " + str(os.popen("git log --oneline -1").read()) + "\n") + f.write( + "computational_time_learning_from_total_data: " + + str(learning_computation_time) + + "\n" + ) + f.write("USE_TRAINED_MODEL_DIFF: " + str(USE_TRAINED_MODEL_DIFF) + "\n") + f.write("USE_POLYNOMIAL_REGRESSION: " + str(USE_POLYNOMIAL_REGRESSION) + "\n") + f.write("USE_SELECTED_POLYNOMIAL: " + str(USE_SELECTED_POLYNOMIAL) + "\n") + f.write("FORCE_NN_MODEL_TO_ZERO: " + str(FORCE_NN_MODEL_TO_ZERO) + "\n") + f.write("FIT_INTERCEPT: " + str(FIT_INTERCEPT) + "\n") + f.write("USE_INTERCEPT: " + str(USE_INTERCEPT) + "\n") + f.close() + + if DATA_COLLECTION_MODE == "ff": + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_ff_control.csv", + mode="a", + ) + elif DATA_COLLECTION_MODE == "pp": + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_pp_control.csv", + mode="a", + ) + else: + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_nominal_control.csv", + mode="a", + ) + print( + change_param.name, + str(param_val_list[j]).replace(",", "_"), + *auto_test_performance_result_list, + sep=",", + file=f + ) + f.close() + print("experiment success") + except Exception: + print("# Catch Exception #") + print(traceback.print_exc()) + auto_test_performance_result_list = [1e16] * 11 + if DATA_COLLECTION_MODE == "ff": + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_ff_control.csv", + mode="a", + ) + elif DATA_COLLECTION_MODE == "pp": + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_pp_control.csv", + mode="a", + ) + else: + f = open( + "auto_test_result_final_model_control_trained_with_data_collected_by_nominal_control.csv", + mode="a", + ) + print( + change_param.name, + str(param_val_list[j]).replace(",", "_"), + *auto_test_performance_result_list, + sep=",", + file=f + ) + f.close() + print("experiment failure") + print("data:", data) + + print("total_time: ", time.time() - start_time) + + +def yes_no_input(): + """Let the user enter yes or no. Default is no.""" + choice = input("Please respond with 'yes' or 'no' [y/N]: ").lower() + if choice in ["y", "ye", "yes"]: + return True + return False + + +if __name__ == "__main__": + if args.param_name is None: + print("Do you want to run the simulation for all parameters at once?") + if yes_no_input(): + for _, change_param in ChangeParam.__members__.items(): + run_simulator(change_param) + else: + print("Enter the name of the parameter for which the simulation is to be run.") + input_string = input() + for name, change_param in ChangeParam.__members__.items(): + if name == input_string: + run_simulator(change_param) + break + else: + for name, change_param in ChangeParam.__members__.items(): + if name == args.param_name: + run_simulator(change_param) + break diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/python_simulator/slalom_course_data.csv 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b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/.gitignore @@ -0,0 +1,7 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/__init__.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_GP.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_GP.py new file mode 100644 index 0000000000000..e75eedcb4bf65 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_GP.py @@ -0,0 +1,110 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore numba njit fastmath + +from functools import partial + +from numba import njit +import numpy as np +from smart_mpc_trajectory_follower.scripts import drive_functions + +sqrt_mpc_time_step = np.sqrt(drive_functions.mpc_time_step) + + +@njit(cache=True, fastmath=True) +def get_pred(x_input, theta_1, theta_2, Z, mean_mtr, cov_mtr): + """Calculate the prediction and its derivative, the deviation and its derivative based on the Gaussian process.""" + Z_norm = (Z - x_input) * theta_2 + k_ast = theta_1 * np.exp(-0.5 * ((Z - x_input) * Z_norm).sum(axis=1)) + k_ = cov_mtr @ k_ast + Z_k = Z_norm.T * k_ast + deviation = np.sqrt(theta_1 - np.dot(k_ast, k_)) + return np.dot(mean_mtr, k_ast), deviation, Z_k @ mean_mtr, -Z_k @ k_ / deviation + + +@njit(cache=True, fastmath=True) +def get_pred_deviation(x_input, theta_1, theta_2, Z, cov_mtr): + """Calculate the deviation of the prediction and its derivative based on the Gaussian process.""" + coef = np.abs(x_input[0]) + coef = coef * coef * coef * coef * coef * coef * coef + if coef > 1.0: + coef = 1.0 + Z_norm = (Z - x_input) * theta_2 + k_ast = theta_1 * np.exp(-0.5 * ((Z - x_input) * Z_norm).sum(axis=1)) + k_ = cov_mtr @ k_ast + Z_k = Z_norm.T * k_ast + deviation = np.sqrt(theta_1 - np.dot(k_ast, k_)) + return coef * deviation, -coef * Z_k @ k_ / deviation + + +@njit(cache=True, fastmath=True) +def get_pred_deviations(x_inputs, theta_1, theta_2, Z, cov_mtr, indices): + """Calculate the deviation of the predictions and their derivatives for multiple inputs based on the Gaussian process.""" + deviation = np.zeros(x_inputs.shape[0]) + deviation_dot = np.zeros((x_inputs.shape[0], x_inputs.shape[1] + 3)) + for i in range(x_inputs.shape[0]): + deviation[i], deviation_dot[i, indices] = get_pred_deviation( + x_inputs[i], theta_1, theta_2, Z, cov_mtr + ) + return sqrt_mpc_time_step * deviation, sqrt_mpc_time_step * deviation_dot + + +class transform_GP_to_numba: + """Class for fast computation of necessary calculations based on Gaussian processes with numba.""" + + def __init__(self, i, dir_name="."): + indices = np.concatenate( + ( + np.array([2, 4, 5]), + np.arange( + drive_functions.acc_ctrl_queue_size + drive_functions.steer_ctrl_queue_size + ) + + 6, + ) + ) + file_names = [ + "/GP_x_info.npz", + "/GP_y_info.npz", + "/GP_v_info.npz", + "/GP_theta_info.npz", + "/GP_acc_info.npz", + "/GP_steer_info.npz", + ] + file_name = file_names[i] + GP_info = np.load(dir_name + file_name) + theta_1 = 1 * GP_info["theta_1"] + theta_2 = GP_info["theta_2"] + Z = GP_info["Z"] + mean_mtr = GP_info["mean_mtr"] + cov_mtr = GP_info["cov_mtr"] + self.get_pred = partial( + get_pred, + theta_1=theta_1, + theta_2=theta_2, + Z=Z, + mean_mtr=mean_mtr, + cov_mtr=cov_mtr, + ) + self.pred_deviation = partial( + get_pred_deviation, theta_1=theta_1, theta_2=theta_2, Z=Z, cov_mtr=cov_mtr + ) + self.pred_deviations = partial( + get_pred_deviations, + theta_1=theta_1, + theta_2=theta_2, + Z=Z, + cov_mtr=cov_mtr, + indices=indices, + ) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_NN.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_NN.py new file mode 100644 index 0000000000000..f35789ee39fd3 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_NN.py @@ -0,0 +1,247 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +import numpy as np +from smart_mpc_trajectory_follower.scripts import drive_functions +from smart_mpc_trajectory_follower.scripts import proxima_calc +import torch +from torch import nn + +dim_steer_layer_1_head = 32 +dim_steer_layer_1_tail = 16 +dim_steer_layer_2 = 8 +dim_acc_layer_1 = 16 +dim_acc_layer_2 = 16 + + +def nominal_model_input(Var, lam, step): + """Calculate prediction with nominal model that takes into account time constants for the first order and time delays related to the input.""" + nominal_pred = Var[:, 0] + nominal_pred = ( + nominal_pred + (Var[:, step] - nominal_pred) * drive_functions.ctrl_time_step / lam + ) + nominal_pred = ( + nominal_pred + (Var[:, step - 1] - nominal_pred) * drive_functions.ctrl_time_step / lam + ) + nominal_pred = ( + nominal_pred + (Var[:, step - 2] - nominal_pred) * drive_functions.ctrl_time_step / lam + ) + return nominal_pred + + +def loss_fn_plus_tanh(loss_fn, pred, Y, tanh_gain, tanh_weight): + """Compute the loss function to be used in the training.""" + loss = loss_fn(pred, Y) + loss += tanh_weight * loss_fn( + torch.tanh(tanh_gain * (pred[:, -1] - Y[:, -1])), torch.zeros(Y.shape[0]) + ) + return loss + + +# example usage: `model = DriveNeuralNetwork(params...).to("cpu")` +class DriveNeuralNetwork(nn.Module): + """Define the neural net model to be used in vehicle control.""" + + def __init__( + self, + hidden_layer_sizes=(32, 16), + randomize=0.01, + acc_drop_out=0.0, + steer_drop_out=0.0, + acc_delay_step=drive_functions.acc_delay_step, + steer_delay_step=drive_functions.steer_delay_step, + acc_time_constant_ctrl=drive_functions.acc_time_constant, + steer_time_constant_ctrl=drive_functions.steer_time_constant, + acc_queue_size=drive_functions.acc_ctrl_queue_size, + steer_queue_size=drive_functions.steer_ctrl_queue_size, + steer_queue_size_core=drive_functions.steer_ctrl_queue_size_core, + ): + super().__init__() + self.acc_time_constant_ctrl = acc_time_constant_ctrl + self.acc_delay_step = acc_delay_step + self.steer_time_constant_ctrl = steer_time_constant_ctrl + self.steer_delay_step = steer_delay_step + + lb = -randomize + ub = randomize + self.acc_input_index = np.concatenate(([1], np.arange(acc_queue_size) + 3)) + self.steer_input_index = np.concatenate( + ([2], np.arange(steer_queue_size_core) + acc_queue_size + 3) + ) + self.acc_input_index_ = np.arange(acc_queue_size) + 3 + self.steer_input_index_ = np.arange(steer_queue_size_core) + acc_queue_size + 3 + self.steer_input_index_full = np.arange(steer_queue_size) + acc_queue_size + 3 + self.acc_layer_1 = nn.Sequential( + nn.Linear(self.acc_input_index.shape[0], dim_acc_layer_1), + nn.ReLU(), + ) + nn.init.uniform_(self.acc_layer_1[0].weight, a=lb, b=ub) + nn.init.uniform_(self.acc_layer_1[0].bias, a=lb, b=ub) + self.steer_layer_1_head = nn.Sequential( + nn.Linear(self.steer_input_index.shape[0], dim_steer_layer_1_head), + nn.ReLU(), + ) + nn.init.uniform_(self.steer_layer_1_head[0].weight, a=lb, b=ub) + nn.init.uniform_(self.steer_layer_1_head[0].bias, a=lb, b=ub) + + self.steer_layer_1_tail = nn.Sequential( + nn.Linear(self.steer_input_index_full.shape[0], dim_steer_layer_1_tail), nn.ReLU() + ) + nn.init.uniform_(self.steer_layer_1_tail[0].weight, a=lb, b=ub) + nn.init.uniform_(self.steer_layer_1_tail[0].bias, a=lb, b=ub) + + self.acc_layer_2 = nn.Sequential(nn.Linear(dim_acc_layer_1, dim_acc_layer_2), nn.Tanh()) + nn.init.uniform_(self.acc_layer_2[0].weight, a=lb, b=ub) + nn.init.uniform_(self.acc_layer_2[0].bias, a=lb, b=ub) + + self.steer_layer_2 = nn.Sequential( + nn.Linear(dim_steer_layer_1_head + dim_steer_layer_1_tail, dim_steer_layer_2), nn.Tanh() + ) + nn.init.uniform_(self.steer_layer_2[0].weight, a=lb, b=ub) + nn.init.uniform_(self.steer_layer_2[0].bias, a=lb, b=ub) + + self.linear_relu_stack = nn.Sequential( + nn.Linear(1 + dim_acc_layer_2 + dim_steer_layer_2, hidden_layer_sizes[0]), + nn.ReLU(), + nn.Linear(hidden_layer_sizes[0], hidden_layer_sizes[1]), + nn.ReLU(), + ) + nn.init.uniform_(self.linear_relu_stack[0].weight, a=lb, b=ub) + nn.init.uniform_(self.linear_relu_stack[0].bias, a=lb, b=ub) + nn.init.uniform_(self.linear_relu_stack[2].weight, a=lb, b=ub) + nn.init.uniform_(self.linear_relu_stack[2].bias, a=lb, b=ub) + + self.finalize = nn.Linear(hidden_layer_sizes[1] + dim_acc_layer_2 + dim_steer_layer_2, 6) + + nn.init.uniform_(self.finalize.weight, a=lb, b=ub) + nn.init.uniform_(self.finalize.bias, a=lb, b=ub) + + self.acc_dropout = nn.Dropout(acc_drop_out) + self.steer_dropout = nn.Dropout(steer_drop_out) + + def forward(self, x): + acc_layer_1 = self.acc_layer_1(x[:, self.acc_input_index]) + steer_layer_1 = torch.cat( + ( + self.steer_layer_1_head(x[:, self.steer_input_index]), + self.steer_layer_1_tail(x[:, self.steer_input_index_full]), + ), + dim=1, + ) + acc_layer_2 = self.acc_layer_2(self.acc_dropout(acc_layer_1)) + steer_layer_2 = self.steer_layer_2(self.steer_dropout(steer_layer_1)) + + pre_pred = self.linear_relu_stack(torch.cat((x[:, [0]], acc_layer_2, steer_layer_2), dim=1)) + pred = self.finalize(torch.cat((pre_pred, acc_layer_2, steer_layer_2), dim=1)) + return pred + + +class EarlyStopping: + """Class for early stopping in NN training.""" + + def __init__(self, initial_loss, tol=0.01, patience=30): + self.epoch = 0 # Initialise the counter for the number of epochs being monitored. + self.best_loss = float("inf") # Initialise loss of comparison with infinity 'inf'. + self.patience = patience # Initialise the number of epochs to be monitored with a parameter + self.initial_loss = initial_loss.detach().item() + self.tol = tol + + def __call__(self, current_loss): + current_loss_num = current_loss.detach().item() + if current_loss_num + self.tol * self.initial_loss > self.best_loss: + self.epoch += 1 + else: + self.epoch = 0 + if current_loss_num < self.best_loss: + self.best_loss = current_loss_num + if self.epoch >= self.patience: + return True + return False + + +class transform_model_to_c: + """Pass the necessary information to the C++ program to call the trained model at high speed.""" + + def __init__( + self, + model, + A_for_linear_reg, + b_for_linear_reg, + deg, + acc_time_constant, + acc_delay_step, + steer_time_constant, + steer_delay_step, + acc_queue_size, + steer_queue_size, + steer_queue_size_core, + ): + transformer = proxima_calc.transform_model_to_eigen() + + numpy_weight_list = [] + numpy_bias_list = [] + for i, w in enumerate(model.parameters()): + if i % 2 == 0: + numpy_weight_list.append(w.detach().numpy().astype(np.float64)) + else: + numpy_bias_list.append(w.detach().numpy().astype(np.float64)) + array_weight_list_0 = numpy_weight_list[0] + array_bias_list_0 = numpy_bias_list[0] + array_weight_list_1 = numpy_weight_list[1] + array_bias_list_1 = numpy_bias_list[1] + array_weight_list_2 = numpy_weight_list[2] + array_bias_list_2 = numpy_bias_list[2] + array_weight_list_3 = numpy_weight_list[3] + array_bias_list_3 = numpy_bias_list[3] + array_weight_list_4 = numpy_weight_list[4] + array_bias_list_4 = numpy_bias_list[4] + array_weight_list_5 = numpy_weight_list[5] + array_bias_list_5 = numpy_bias_list[5] + array_weight_list_6 = numpy_weight_list[6] + array_bias_list_6 = numpy_bias_list[6] + array_weight_list_7 = numpy_weight_list[7] + array_bias_list_7 = numpy_bias_list[7] + + transformer.set_params( + array_weight_list_0, + array_weight_list_1, + array_weight_list_2, + array_weight_list_3, + array_weight_list_4, + array_weight_list_5, + array_weight_list_6, + array_weight_list_7, + array_bias_list_0, + array_bias_list_1, + array_bias_list_2, + array_bias_list_3, + array_bias_list_4, + array_bias_list_5, + array_bias_list_6, + array_bias_list_7, + A_for_linear_reg, + b_for_linear_reg, + deg, + acc_time_constant, + acc_delay_step, + steer_time_constant, + steer_delay_step, + acc_queue_size, + steer_queue_size, + steer_queue_size_core, + ) + self.pred = transformer.rot_and_d_rot_error_prediction + self.pred_with_diff = transformer.rot_and_d_rot_error_prediction_with_diff + self.Pred = transformer.Rotated_error_prediction diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_controller.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_controller.py new file mode 100644 index 0000000000000..b21fcf72da931 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_controller.py @@ -0,0 +1,943 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore optim numba interp + + +"""Define a drive_controller class that calculates the final input of the Proxima-side MPC.""" +from functools import partial +from importlib import reload as ir +import threading +import time + +import numpy as np +import scipy.interpolate # type: ignore +from sklearn.preprocessing import PolynomialFeatures +from smart_mpc_trajectory_follower.scripts import drive_GP +from smart_mpc_trajectory_follower.scripts import drive_NN +from smart_mpc_trajectory_follower.scripts import drive_functions +from smart_mpc_trajectory_follower.scripts import drive_iLQR +from smart_mpc_trajectory_follower.scripts import drive_mppi +import torch + +ctrl_index_for_polynomial_reg = np.concatenate( + ( + np.arange(3), + [3 + drive_functions.acc_delay_step], + [3 + drive_functions.acc_ctrl_queue_size + drive_functions.steer_delay_step], + ) +) + + +class drive_controller: + """Calculate the final input of the Proxima-side MPC. + + Fields that can take None follow these specifications unless otherwise noted. + * If None, read from drive_functions.py + * If Bool, the input value is used + """ + + use_trained_model: bool | None + """Whether to use trained models """ + + use_trained_model_diff: bool | None + """Assuming a trained model is used, whether or not to use even its derivatives.""" + + update_trained_model: bool | None + """Whether to update the model online with the data under control.""" + + mode: str | None + """which algorithm to use, "mppi", "ilqr", or "mppi_ilqr" """ + + use_x_noise: bool | None + """Whether to reflect the uncertainty of the straight-line position when performing iLQG""" + + use_y_noise: bool | None + """Whether to reflect the uncertainty of the lateral position when performing iLQG""" + + use_v_noise: bool | None + """ Whether to reflect the uncertainty of the straight-line velocity when performing iLQG""" + + use_theta_noise: bool | None + """ Whether to reflect the uncertainty of the yaw angle when performing iLQG""" + + use_acc_noise: bool | None + """ Whether to reflect the uncertainty of the straight-line acceleration when performing iLQG""" + + use_steer_noise: bool | None + """ Whether to reflect the uncertainty of the steer when performing iLQG""" + + tanh_gain: float + """ Gain of the tanh term in the loss function in learning. """ + + lam: float + """ Weight fir the tanh term in the loss function in learning.""" + + alpha_1: float + """ Coefficients of the L¹ regularization term in online learning.""" + + alpha_2: float + """ Coefficients of the L² regularization term in online learning.""" + + drive_batch_size: int + """ Online learning batch sizes """ + + drive_learning_rate: float + """ Learning rate for online learning """ + + model_file_name: str + """ file name of the trained model to be loaded """ + + load_train_data_dir: str + """ directory for training data to be loaded during online learning """ + + load_GP_dir: str | None + """ directory to load the GP (Gaussian process regression) models for iLQG. """ + + def __init__( + self, + use_trained_model: bool | None = None, + use_trained_model_diff=None, + update_trained_model=None, + mode=None, + use_x_noise=None, + use_y_noise=None, + use_v_noise=None, + use_theta_noise=None, + use_acc_noise=None, + use_steer_noise=None, + tanh_gain=10.0, + lam=0.1, + alpha_1=1e-7, + alpha_2=0.0, + drive_batch_size=200, + drive_learning_rate=1e-6, + model_file_name="model_for_test_drive.pth", + load_train_data_dir=".", + load_GP_dir=None, + load_polynomial_reg_dir=None, + ): + """Initialize. + + Some arguments have a default value of None in order to reload drive_functions and update the parameters. + """ + # reload drive_functions + ir(drive_functions) + ir(drive_NN) + ir(drive_iLQR) + ir(drive_mppi) + + if use_trained_model is None: + self.use_trained_model = drive_functions.use_trained_model + else: + self.use_trained_model = use_trained_model + if not self.use_trained_model: + self.use_trained_model_diff = False + self.update_trained_model = False + else: + if use_trained_model_diff is None: + self.use_trained_model_diff = drive_functions.use_trained_model_diff + else: + self.use_trained_model_diff = use_trained_model_diff + if update_trained_model is None: + self.update_trained_model = drive_functions.update_trained_model + else: + self.update_trained_model = update_trained_model + if mode is None: + self.mode = drive_functions.mode + else: + self.mode = mode + + self.acc_delay_step = drive_functions.acc_delay_step + self.steer_delay_step = drive_functions.steer_delay_step + self.acc_time_constant_ctrl = drive_functions.acc_time_constant + self.steer_time_constant_ctrl = drive_functions.steer_time_constant + + # Term to consider noise in iLQG + if use_x_noise is None: + self.use_x_noise = drive_functions.use_x_noise + else: + self.use_x_noise = use_x_noise + if use_y_noise is None: + self.use_y_noise = drive_functions.use_y_noise + else: + self.use_y_noise = use_y_noise + if use_v_noise is None: + self.use_v_noise = drive_functions.use_v_noise + else: + self.use_v_noise = use_v_noise + if use_theta_noise is None: + self.use_theta_noise = drive_functions.use_theta_noise + else: + self.use_theta_noise = use_theta_noise + if use_acc_noise is None: + self.use_acc_noise = drive_functions.use_acc_noise + else: + self.use_acc_noise = use_acc_noise + if use_steer_noise is None: + self.use_steer_noise = drive_functions.use_steer_noise + else: + self.use_steer_noise = use_steer_noise + if not self.use_trained_model: + self.use_x_noise = False + self.use_y_noise = False + self.use_v_noise = False + self.use_theta_noise = False + self.use_acc_noise = False + self.use_steer_noise = False + + if load_GP_dir is None: + self.load_GP_dir = drive_functions.load_dir + else: + self.load_GP_dir = load_GP_dir + if load_polynomial_reg_dir is None: + self.load_polynomial_reg_dir = drive_functions.load_dir + else: + self.load_polynomial_reg_dir = load_polynomial_reg_dir + + self.drive_batch_size = drive_batch_size + self.alpha_1 = alpha_1 + self.alpha_2 = alpha_2 + self.tanh_gain = tanh_gain + self.lam = lam + + self.init = True + self.initialize_input_queue = True + self.mppi = drive_mppi.drive_mppi( + drive_functions.lam, + drive_functions.Sigma, + drive_functions.max_iter_mppi, + drive_functions.sample_num, + drive_functions.mppi_tol, + drive_functions.mppi_step, + ) + self.ilqr = drive_iLQR.drive_iLQR( + drive_functions.ls_step, + drive_functions.max_iter_ls, + drive_functions.max_iter_ilqr, + drive_functions.ilqr_tol, + self.use_trained_model_diff, + ) + self.err = 0 + if self.use_trained_model: + self.model = torch.load(model_file_name) + polynomial_reg_info = np.load(self.load_polynomial_reg_dir + "/polynomial_reg_info.npz") + self.A_for_polynomial_reg = polynomial_reg_info["A"] + self.b_for_polynomial_reg = polynomial_reg_info["b"] + self.deg = int(polynomial_reg_info["deg"]) + self.polynomial_features = PolynomialFeatures(degree=self.deg, include_bias=False) + transform_model = drive_NN.transform_model_to_c( + self.model, + self.A_for_polynomial_reg, + self.b_for_polynomial_reg, + self.deg, + self.acc_time_constant_ctrl, + self.acc_delay_step, + self.steer_time_constant_ctrl, + self.steer_delay_step, + drive_functions.acc_ctrl_queue_size, + drive_functions.steer_ctrl_queue_size, + drive_functions.steer_ctrl_queue_size_core, + ) + pred = transform_model.pred + Pred = transform_model.Pred + self.pred = pred + self.pred_with_diff = transform_model.pred_with_diff + self.loss_fn = torch.nn.L1Loss() + self.drive_optimizer = torch.optim.Adam( + params=self.model.parameters(), lr=drive_learning_rate + ) + self.F_N_initial_diff = partial( + drive_functions.F_with_model_initial_diff, + pred=pred, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + + self.F_N_diff = partial( + drive_functions.F_with_model_diff, + pred=self.pred_with_diff, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + self.F_N_for_candidates = partial( + drive_functions.F_with_model_for_candidates, + Pred=Pred, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + else: + self.F_N_diff = partial( + drive_functions.F_with_history_and_diff, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + self.F_N_initial_diff = self.F_N_diff + self.F_N_for_candidates = partial( + drive_functions.F_with_history_for_candidates, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + + if self.use_x_noise: + self.x_noise = drive_GP.transform_GP_to_numba( + 0, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.x_noise = None + if self.use_y_noise: + self.y_noise = drive_GP.transform_GP_to_numba( + 1, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.y_noise = None + if self.use_v_noise: + self.v_noise = drive_GP.transform_GP_to_numba( + 2, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.v_noise = None + if self.use_theta_noise: + self.theta_noise = drive_GP.transform_GP_to_numba( + 3, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.theta_noise = None + if self.use_acc_noise: + self.acc_noise = drive_GP.transform_GP_to_numba( + 4, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.acc_noise = None + if self.use_steer_noise: + self.steer_noise = drive_GP.transform_GP_to_numba( + 5, dir_name=self.load_GP_dir + ).pred_deviations + else: + self.steer_noise = None + + self.X_des_history: list[np.ndarray] = [] + + self.X_input_list = [] + self.Y_output_list = [] + # Initial data during online training + + self.emergency = False + + self.counter = 0 + self.model_update_flag = True + if self.update_trained_model: + train_data = np.load(load_train_data_dir + "/train_data.npz") + self.X_input_list = train_data["X_input"][ + -drive_functions.max_train_data_size : + ].tolist() + self.Y_output_list = ( + train_data["Y_output"][-drive_functions.max_train_data_size :] + - self.polynomial_features.fit_transform( + train_data["X_input"][ + -drive_functions.max_train_data_size :, ctrl_index_for_polynomial_reg + ] + ) + @ (self.A_for_polynomial_reg).T + - self.b_for_polynomial_reg + ).tolist() + self.model_updater = threading.Thread(target=self.update_model) + self.model_updater.start() + + self.x_old = np.empty(6) + + def __del__(self): + print("control finished") + + def get_optimal_control( + self, + x_current_: np.ndarray, + X_des_: np.ndarray, + U_des: np.ndarray = np.zeros((drive_functions.N, drive_functions.nu_0)), + ) -> np.ndarray: + """Calculate the optimal control input from the current state, target trajectory, and target input trajectory. + + The return value is an np.ndarray of the form `(drive_functions.nu_0, )`. + """ + if self.initialize_input_queue: + x_current = x_current_.copy() + X_des, diff_delta = drive_functions.transform_yaw_for_X_des( + x_current, + X_des_, + ) + self.u_opt = X_des[0, drive_functions.nx_0 + np.arange(drive_functions.nu_0)] + self.u_old = self.u_opt.copy() + self.u_old2 = self.u_opt.copy() + self.acc_input_queue = self.u_opt[0] * np.ones(drive_functions.acc_ctrl_queue_size) + self.steer_input_queue = self.u_opt[1] * np.ones(drive_functions.steer_ctrl_queue_size) + self.nominal_inputs = drive_functions.U_des_from_X_des(self.u_old, X_des, diff_delta) + self.previous_error = np.zeros(8) + + self.X_queue_for_learning: list[np.ndarray] = [] + self.acc_input_queue_for_learning: list[np.ndarray] = [] + self.steer_input_queue_for_learning: list[np.ndarray] = [] + self.time_stamp_queue_for_learning: list[float] = [] + self.X_smoothed_queue: list[np.ndarray] = [] + + self.pre_X_input_list: list[np.ndarray] = [] + self.pre_Y_output_list: list[np.ndarray] = [] + + self.initialize_X_smoothing_time_stamp = True + else: + x_current = drive_functions.transform_yaw_for_x_current(self.x_old, x_current_) + X_des, diff_delta = drive_functions.transform_yaw_for_X_des( + x_current, + X_des_, + ) + self.u_old2 = self.u_old.copy() + self.u_old = self.u_opt.copy() + + if self.init: + self.X_current_queue = [] + self.init = False + self.X_des = X_des + + self.X_current = np.concatenate( + (x_current, self.acc_input_queue[::-1], self.steer_input_queue[::-1]) + ) + + self.X_current_queue.append(self.X_current.copy()) + if len(self.X_current_queue) > drive_functions.mpc_freq: + self.X_current_queue.pop(0) + if self.mode == "mppi": # Avoid duplicate filtering for "mppi_ilqr" mode + self.nominal_inputs = drive_functions.sg_filter_for_nominal_inputs(self.nominal_inputs) + if self.mode == "mppi" or self.mode == "mppi_ilqr": # Run mppi + self.start_mppi = time.time() + self.mppi.receive_model(self.F_N_for_candidates) + self.nominal_inputs, self.u_opt_dot, nominal_traj = (self.mppi).compute_optimal_control( + self.X_current, + self.nominal_inputs, + X_des, + U_des, + self.previous_error[:6], + ) + self.nominal_traj_mppi = nominal_traj.copy() + self.end_mppi = time.time() + if self.mode != "mppi": + self.start_ilqr = time.time() + proceed = True + for k in range(drive_functions.max_iter_ilqr): + if not proceed: + break + self.nominal_inputs = drive_functions.sg_filter_for_nominal_inputs( + self.nominal_inputs + ) + self.ilqr.receive_model( + self.F_N_initial_diff, self.F_N_diff, self.F_N_for_candidates + ) + self.nominal_inputs, self.u_opt_dot, nominal_traj, proceed = ( + self.ilqr + ).compute_optimal_control( + self.X_current, + self.nominal_inputs, + X_des, + U_des, + self.previous_error, + self.x_noise, + self.y_noise, + self.v_noise, + self.theta_noise, + self.acc_noise, + self.steer_noise, + ) + self.nominal_traj_ilqr = nominal_traj.copy() + self.nominal_inputs_ilqr = self.nominal_inputs.copy() + err = drive_functions.calc_maximum_trajectory_error(self.nominal_traj_ilqr, X_des) + if err > drive_functions.cap_pred_error[0]: + if err < drive_functions.cap_pred_error[1]: + mix_ratio = (drive_functions.cap_pred_error[1] - err) / ( + drive_functions.cap_pred_error[1] - drive_functions.cap_pred_error[0] + ) + else: + mix_ratio = 0.0 + self.nominal_inputs = mix_ratio * self.nominal_inputs + ( + 1 - mix_ratio + ) * drive_functions.U_des_from_X_des(self.u_old, X_des, diff_delta) + self.err = err + if err > 1.0: + self.emergency = True + + self.time_1 = self.ilqr.time_1 + self.time_2 = self.ilqr.time_2 + self.time_3 = self.ilqr.time_3 + self.time_4 = self.ilqr.time_4 + self.time_5 = self.ilqr.time_5 + self.end_ilqr = time.time() + + if self.use_trained_model: + self.previous_error = drive_functions.error_decay * self.previous_error + ( + 1 - drive_functions.error_decay + ) * self.pred(self.X_current) + + self.nominal_traj = nominal_traj + + self.u_opt = self.u_old + self.u_opt_dot * drive_functions.ctrl_time_step + ( + steer_lim, + steer_rate_lim_lb, + steer_rate_lim_ub, + acc_lim, + acc_rate_lim, + ) = drive_functions.calc_limits(x_current[2], x_current[4], x_current[5]) + + self.u_opt = drive_functions.u_cut_off( + self.u_opt, + self.u_old, + steer_lim, + steer_rate_lim_lb, + steer_rate_lim_ub, + acc_lim, + acc_rate_lim, + ) + + self.initialize_input_queue = False + self.X_des_history.append(X_des[0]) + self.initial_guess_for_debug = (self.nominal_inputs).copy() + + self.x_old = x_current + return self.u_opt + + def update_input_queue( + self, + time_stamp: list[float], + acc_history: list[float], + steer_history: list[float], + x_current_: np.ndarray, + ) -> None: + """Receives the history of the acceleration and steer inputs and their time stamps. + + And interpolates them to be the history of the time steps used by the controller. + The return value can be passed to get_optimal_control. + """ + if not self.initialize_input_queue: + if len(time_stamp) == 1: + self.acc_input_queue[-1] = acc_history[0] + self.steer_input_queue[-1] = steer_history[0] + elif len(time_stamp) > 1: + ctrl_num = int((time_stamp[-1] - time_stamp[0]) / drive_functions.ctrl_time_step) + acc_num = min(drive_functions.acc_ctrl_queue_size, ctrl_num) + steer_num = min(drive_functions.steer_ctrl_queue_size, ctrl_num) + time_stamp_acc = ( + drive_functions.ctrl_time_step * np.arange(acc_num) + - (acc_num - 1) * drive_functions.ctrl_time_step + + time_stamp[-1] + ) + time_stamp_steer = ( + drive_functions.ctrl_time_step * np.arange(steer_num) + - (steer_num - 1) * drive_functions.ctrl_time_step + + time_stamp[-1] + ) + acc_interpolate = scipy.interpolate.interp1d( + np.array(time_stamp), np.array(acc_history) + ) + steer_interpolate = scipy.interpolate.interp1d( + np.array(time_stamp), np.array(steer_history) + ) + + self.acc_input_queue[ + drive_functions.acc_ctrl_queue_size - acc_num : + ] = acc_interpolate(time_stamp_acc) + self.steer_input_queue[ + drive_functions.steer_ctrl_queue_size - steer_num : + ] = steer_interpolate(time_stamp_steer) + + if ( + acc_num == drive_functions.acc_ctrl_queue_size + and steer_num == drive_functions.steer_ctrl_queue_size + ): + self.X_queue_for_learning.append(x_current_) + self.acc_input_queue_for_learning.append(np.array(self.acc_input_queue)[::-1]) + self.steer_input_queue_for_learning.append( + np.array(self.steer_input_queue)[::-1] + ) + self.time_stamp_queue_for_learning.append(time_stamp[-1]) + if ( + self.initialize_X_smoothing_time_stamp + and self.time_stamp_queue_for_learning[-1] + - self.time_stamp_queue_for_learning[0] + > drive_functions.ctrl_time_step + * drive_functions.max_input_queue_size_for_learning + ): + self.initialize_X_smoothing_time_stamp = False + self.X_smoothing_time_stamp = ( + time_stamp[-1] - drive_functions.ctrl_time_step + ) + + if not self.initialize_X_smoothing_time_stamp: + while ( + self.time_stamp_queue_for_learning[-1] + > drive_functions.ctrl_time_step + self.X_smoothing_time_stamp + ): + self.X_smoothing_time_stamp += drive_functions.ctrl_time_step + time_stamp_smoothing = ( + drive_functions.ctrl_time_step + * np.arange(drive_functions.max_input_queue_size_for_learning) + - (drive_functions.max_input_queue_size_for_learning - 1) + * drive_functions.ctrl_time_step + + self.X_smoothing_time_stamp + ) + x_queue = scipy.interpolate.interp1d( + np.array(self.time_stamp_queue_for_learning), + np.array(self.X_queue_for_learning).T, + )(time_stamp_smoothing).T + acc_input_queue = scipy.interpolate.interp1d( + np.array(self.time_stamp_queue_for_learning), + np.array(self.acc_input_queue_for_learning).T, + )(time_stamp_smoothing).T + steer_input_queue = scipy.interpolate.interp1d( + np.array(self.time_stamp_queue_for_learning), + np.array(self.steer_input_queue_for_learning).T, + )(time_stamp_smoothing).T + X_smoothed = np.zeros( + drive_functions.nx_0 + + drive_functions.acc_ctrl_queue_size + + drive_functions.steer_ctrl_queue_size + ) + X_smoothed[0:4] = x_queue[ + drive_functions.max_input_queue_size_for_learning // 2, 0:4 + ] + X_smoothed[4] = np.dot( + x_queue[ + drive_functions.max_input_queue_size_for_learning // 2 + - drive_functions.kernel_acc_for_learning.shape[0] + // 2 : drive_functions.max_input_queue_size_for_learning + // 2 + + drive_functions.kernel_acc_for_learning.shape[0] // 2 + + 1, + 4, + ], + drive_functions.kernel_acc_for_learning, + ) + X_smoothed[5] = np.dot( + x_queue[ + drive_functions.max_input_queue_size_for_learning // 2 + - drive_functions.kernel_steer_for_learning.shape[0] + // 2 : drive_functions.max_input_queue_size_for_learning + // 2 + + drive_functions.kernel_steer_for_learning.shape[0] // 2 + + 1, + 5, + ], + drive_functions.kernel_steer_for_learning, + ) + X_smoothed[ + drive_functions.nx_0 : drive_functions.nx_0 + + drive_functions.acc_ctrl_queue_size + ] = ( + acc_input_queue[ + drive_functions.max_input_queue_size_for_learning // 2 + - drive_functions.kernel_acc_des_for_learning.shape[0] + // 2 : drive_functions.max_input_queue_size_for_learning + // 2 + + drive_functions.kernel_acc_des_for_learning.shape[0] // 2 + + 1 + ].T + * drive_functions.kernel_acc_des_for_learning + ).sum( + axis=1 + ) + X_smoothed[ + drive_functions.nx_0 + + drive_functions.acc_ctrl_queue_size : drive_functions.nx_0 + + drive_functions.acc_ctrl_queue_size + + drive_functions.steer_ctrl_queue_size + ] = ( + steer_input_queue[ + drive_functions.max_input_queue_size_for_learning // 2 + - drive_functions.kernel_steer_des_for_learning.shape[0] + // 2 : drive_functions.max_input_queue_size_for_learning + // 2 + + drive_functions.kernel_steer_des_for_learning.shape[0] // 2 + + 1 + ].T + * drive_functions.kernel_steer_des_for_learning + ).sum( + axis=1 + ) + self.X_smoothed_queue.append(X_smoothed) + if len(self.X_smoothed_queue) > drive_functions.mpc_freq + 1: + self.X_smoothed_queue.pop() + if len(self.X_smoothed_queue) == drive_functions.mpc_freq + 1: + acc_start = ( + drive_functions.acc_ctrl_queue_size + - drive_functions.acc_delay_step + ) + acc_end = ( + drive_functions.acc_ctrl_queue_size + - drive_functions.acc_delay_step + + drive_functions.mpc_freq + ) + steer_start = ( + drive_functions.steer_ctrl_queue_size + - drive_functions.steer_delay_step + ) + steer_end = ( + drive_functions.steer_ctrl_queue_size + - drive_functions.steer_delay_step + + drive_functions.mpc_freq + ) + + u_for_predict_x_current = np.zeros((drive_functions.mpc_freq, 2)) + u_for_predict_x_current[:, 0] = self.X_smoothed_queue[0][ + 6 : 6 + drive_functions.acc_ctrl_queue_size + ][::-1][acc_start:acc_end] + u_for_predict_x_current[:, 1] = self.X_smoothed_queue[0][ + 6 + drive_functions.acc_ctrl_queue_size : + ][::-1][steer_start:steer_end] + var_dot = self.X_smoothed_queue[-1][ + :6 + ] - drive_functions.F_multiple( + self.X_smoothed_queue[0][:6], + u_for_predict_x_current, + drive_functions.acc_time_constant, + drive_functions.steer_time_constant, + ) + var_dot /= drive_functions.mpc_time_step + + self.pre_X_input_list.append( + np.concatenate( + ( + self.X_smoothed_queue[0][[2, 4, 5]], + self.X_smoothed_queue[0][6:], + ) + ) + ) + self.pre_Y_output_list.append( + drive_functions.rotate_data( + self.X_smoothed_queue[0][:6], var_dot + ) + ) + if ( + len(self.pre_X_input_list) + > drive_functions.max_output_queue_size_for_learning + ): + self.pre_X_input_list.pop() + self.pre_Y_output_list.pop() + if ( + len(self.pre_X_input_list) + == drive_functions.max_output_queue_size_for_learning + and self.update_trained_model + ): + X_input = self.pre_X_input_list[ + drive_functions.max_output_queue_size_for_learning // 2 + ] + self.X_input_list.append(X_input) + pre_Y_output = np.array(np.array(self.pre_Y_output_list)) + Y_output = np.zeros(self.pre_Y_output_list[0].shape) + Y_output[0] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_x_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_x_out_for_learning.shape[0] + // 2 + + 1, + 0, + ], + drive_functions.kernel_x_out_for_learning, + ) + Y_output[1] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_y_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_y_out_for_learning.shape[0] + // 2 + + 1, + 1, + ], + drive_functions.kernel_y_out_for_learning, + ) + Y_output[2] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_v_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_v_out_for_learning.shape[0] + // 2 + + 1, + 2, + ], + drive_functions.kernel_v_out_for_learning, + ) + Y_output[3] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_theta_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_theta_out_for_learning.shape[0] + // 2 + + 1, + 3, + ], + drive_functions.kernel_theta_out_for_learning, + ) + Y_output[4] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_acc_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_acc_out_for_learning.shape[0] + // 2 + + 1, + 4, + ], + drive_functions.kernel_acc_out_for_learning, + ) + Y_output[5] = np.dot( + pre_Y_output[ + drive_functions.max_output_queue_size_for_learning // 2 + - drive_functions.kernel_steer_out_for_learning.shape[0] + // 2 : drive_functions.max_output_queue_size_for_learning + // 2 + + drive_functions.kernel_steer_out_for_learning.shape[0] + // 2 + + 1, + 5, + ], + drive_functions.kernel_steer_out_for_learning, + ) + self.Y_output_list.append( + Y_output + - self.A_for_polynomial_reg + @ self.polynomial_features.fit_transform( + X_input[ctrl_index_for_polynomial_reg].reshape(1, -1) + )[0] + - self.b_for_polynomial_reg + ) + if len(self.X_input_list) > drive_functions.max_train_data_size: + self.X_input_list.pop(0) + self.Y_output_list.pop(0) + while ( + self.X_smoothing_time_stamp - self.time_stamp_queue_for_learning[1] + > drive_functions.ctrl_time_step + * drive_functions.max_input_queue_size_for_learning + ): + self.X_queue_for_learning.pop(0) + self.acc_input_queue_for_learning.pop(0) + self.steer_input_queue_for_learning.pop(0) + self.time_stamp_queue_for_learning.pop(0) + + def update_input_queue_and_get_optimal_control( + self, + time_stamp, + acc_history, + steer_history, + x_current_, + X_des_, + U_des=np.zeros((drive_functions.N, drive_functions.nu_0)), + ): + """Run update_input_queue and get_optimal_control all at once.""" + self.update_input_queue(time_stamp, acc_history, steer_history, x_current_) + u_opt = self.get_optimal_control(x_current_, X_des_, U_des) + return u_opt + + def update_model(self): + """Update the learning model online.""" + while True: + if not self.model_update_flag: + break + if not self.initialize_input_queue and len(self.X_input_list) > self.drive_batch_size: + X_input = np.array(self.X_input_list) + Y_output = np.array(self.Y_output_list) + batch_index = np.random.choice( + X_input.shape[0], self.drive_batch_size, replace=False + ) + X_batch = torch.tensor(X_input[batch_index].astype(np.float32)).clone() + Y_batch = torch.tensor(Y_output[batch_index].astype(np.float32)).clone() + Y_pred = self.model(X_batch) + loss = drive_NN.loss_fn_plus_tanh( + self.loss_fn, Y_pred, Y_batch, self.tanh_gain, self.lam + ) + for w in self.model.parameters(): + loss = ( + loss + self.alpha_1 * torch.norm(w, p=1) + self.alpha_2 * torch.norm(w) ** 2 + ) + self.drive_optimizer.zero_grad() + loss.backward() + self.drive_optimizer.step() + + transform_model = drive_NN.transform_model_to_c( + self.model, + self.A_for_polynomial_reg, + self.b_for_polynomial_reg, + self.deg, + self.acc_time_constant_ctrl, + self.acc_delay_step, + self.steer_time_constant_ctrl, + self.steer_delay_step, + drive_functions.acc_ctrl_queue_size, + drive_functions.steer_ctrl_queue_size, + drive_functions.steer_ctrl_queue_size_core, + ) + self.pred = transform_model.pred + self.Pred = transform_model.Pred + self.pred_with_diff = transform_model.pred_with_diff + self.F_N_initial_diff = partial( + drive_functions.F_with_model_initial_diff, + pred=self.pred, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + self.F_N_diff = partial( + drive_functions.F_with_model_diff, + pred=self.pred_with_diff, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + self.F_N_for_candidates = partial( + drive_functions.F_with_model_for_candidates, + Pred=self.Pred, + i=self.acc_delay_step, + j=self.steer_delay_step, + acc_time_constant_ctrl=self.acc_time_constant_ctrl, + steer_time_constant_ctrl=self.steer_time_constant_ctrl, + ) + + print("updated!!!!!!!!!!!") + time.sleep(0.1) + + def send_initialize_input_queue(self): + """Flag initialization of the history of inputs passed to the control side.""" + self.initialize_input_queue = True + + def stop_model_update(self): + """Terminate the model update.""" + self.model_update_flag = False + if self.update_trained_model: + self.model_updater.join() diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_functions.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_functions.py new file mode 100644 index 0000000000000..c11b5c886b49a --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_functions.py @@ -0,0 +1,1540 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore numba njit fastmath ndim + + +"""Define primary parameters and functions to be used elsewhere.""" +from functools import partial +import json +import os +from pathlib import Path +import sys +from typing import Callable + +from numba import njit +import numpy as np +import yaml + +package_path_json = str(Path(__file__).parent.parent) + "/package_path.json" +with open(package_path_json, "r") as file: + package_path = json.load(file) + +mpc_param_path = package_path["path"] + "/smart_mpc_trajectory_follower/param/mpc_param.yaml" +with open(mpc_param_path, "r") as yml: + mpc_param = yaml.safe_load(yml) + +mpc_freq = int( + mpc_param["mpc_parameter"]["mpc_setting"]["mpc_freq"] +) # Int, mpc horizon interval/control interval + +# information on MPC +ctrl_time_step = float( + mpc_param["mpc_parameter"]["mpc_setting"]["ctrl_time_step"] +) # Time interval of control. +mpc_time_step = mpc_freq * ctrl_time_step # MPC Horizon interval. +N = int(mpc_param["mpc_parameter"]["mpc_setting"]["N"]) # Length of MPC Horizon. +steer_ctrl_queue_size = int( + mpc_param["mpc_parameter"]["mpc_setting"]["steer_ctrl_queue_size"] +) # Queue for training and control +steer_ctrl_queue_size_core = int( + mpc_param["mpc_parameter"]["mpc_setting"]["steer_ctrl_queue_size_core"] +) +acc_ctrl_queue_size = int(mpc_param["mpc_parameter"]["mpc_setting"]["acc_ctrl_queue_size"]) +nx_0 = int(mpc_param["mpc_parameter"]["mpc_setting"]["nx_0"]) # dimension of the state +nu_0 = int(mpc_param["mpc_parameter"]["mpc_setting"]["nu_0"]) # dimension of the input + +################################################################# + +# Control parameters that may be changed in the experiment## + +################################################################# +mode = str(mpc_param["mpc_parameter"]["system"]["mode"]) +# cost function weights +Q = np.diag(np.array(mpc_param["mpc_parameter"]["cost_parameters"]["Q"], dtype=float)) # stage cost +Q_c = np.diag( + np.array(mpc_param["mpc_parameter"]["cost_parameters"]["Q_c"], dtype=float) +) # Stage costs in MPC `timing_Q_c`th horizon. +Q_f = np.diag( + np.array(mpc_param["mpc_parameter"]["cost_parameters"]["Q_f"], dtype=float) +) # terminal cost +R = np.diag( + np.array(mpc_param["mpc_parameter"]["cost_parameters"]["R"], dtype=float) +) # Cost for control inputs. Here acceleration rate of change and steer rate of change. +timing_Q_c = np.array( + mpc_param["mpc_parameter"]["mpc_setting"]["timing_Q_c"], dtype=int +) # Horizon numbers to change stage costs. +reference_horizon = int(mpc_param["mpc_parameter"]["preprocessing"]["reference_horizon"]) # 50 + +acc_lim_weight = float(mpc_param["mpc_parameter"]["cost_parameters"]["acc_lim_weight"]) +steer_lim_weight = float(mpc_param["mpc_parameter"]["cost_parameters"]["steer_lim_weight"]) +acc_rate_lim_weight = float(mpc_param["mpc_parameter"]["cost_parameters"]["acc_rate_lim_weight"]) +steer_rate_lim_weight = float( + mpc_param["mpc_parameter"]["cost_parameters"]["steer_rate_lim_weight"] +) + +# iLQR parameters +ls_step = float(mpc_param["mpc_parameter"]["ilqr"]["ls_step"]) # 0.9 +max_iter_ls = int(mpc_param["mpc_parameter"]["ilqr"]["max_iter_ls"]) # 10 +max_iter_ilqr = int(mpc_param["mpc_parameter"]["ilqr"]["max_iter_ilqr"]) # 1 +ilqr_tol = float(mpc_param["mpc_parameter"]["ilqr"]["ilqr_tol"]) # 0.01 + +# MPPI parameters +lam = float(mpc_param["mpc_parameter"]["mppi"]["lam"]) # 0.1 +Sigma = np.array(mpc_param["mpc_parameter"]["mppi"]["Sigma"], dtype=float) +max_iter_mppi = int(mpc_param["mpc_parameter"]["mppi"]["max_iter_mppi"]) +sample_num = int(mpc_param["mpc_parameter"]["mppi"]["sample_num"]) +mppi_tol = float(mpc_param["mpc_parameter"]["mppi"]["mppi_tol"]) +mppi_step = int(mpc_param["mpc_parameter"]["mppi"]["mppi_step"]) + +cap_pred_error = np.array(mpc_param["mpc_parameter"]["preprocessing"]["cap_pred_error"]) + +nominal_param_path = ( + package_path["path"] + "/smart_mpc_trajectory_follower/param/nominal_param.yaml" +) +with open(nominal_param_path, "r") as yml: + nominal_param = yaml.safe_load(yml) +# Vehicle body information given by default. +L = float(nominal_param["nominal_parameter"]["vehicle_info"]["wheel_base"]) # Length of vehicle [m] +steer_dead_band_for_ctrl = 0.00 # Size of the steering dead band zone given to the control side. + +acc_time_delay = float(nominal_param["nominal_parameter"]["acceleration"]["acc_time_delay"]) +acc_delay_step = min(round(acc_time_delay / ctrl_time_step), acc_ctrl_queue_size - mpc_freq) +acc_time_constant = float(nominal_param["nominal_parameter"]["acceleration"]["acc_time_constant"]) + +steer_time_delay = float(nominal_param["nominal_parameter"]["steering"]["steer_time_delay"]) +steer_delay_step = min( + round(steer_time_delay / ctrl_time_step), steer_ctrl_queue_size_core - mpc_freq +) +steer_time_constant = float(nominal_param["nominal_parameter"]["steering"]["steer_time_constant"]) + +min_steer_rate_transform_for_start = float( + mpc_param["mpc_parameter"]["cost_parameters"]["min_steer_rate_transform_for_start"] +) +power_steer_rate_transform_for_start = int( + mpc_param["mpc_parameter"]["cost_parameters"]["power_steer_rate_transform_for_start"] +) +coef_steer_rate_transform_for_start = float( + mpc_param["mpc_parameter"]["cost_parameters"]["coef_steer_rate_transform_for_start"] +) + +min_tighten_steer_rate = float( + mpc_param["mpc_parameter"]["to_be_deprecated"]["min_tighten_steer_rate"] +) +power_tighten_steer_rate_by_lateral_error = int( + mpc_param["mpc_parameter"]["to_be_deprecated"]["power_tighten_steer_rate_by_lateral_error"] +) +threshold_tighten_steer_rate_by_lateral_error = float( + mpc_param["mpc_parameter"]["to_be_deprecated"]["threshold_tighten_steer_rate_by_lateral_error"] +) +power_tighten_steer_rate_by_yaw_error = int( + mpc_param["mpc_parameter"]["to_be_deprecated"]["power_tighten_steer_rate_by_yaw_error"] +) +threshold_tighten_steer_rate_by_yaw_error = float( + mpc_param["mpc_parameter"]["to_be_deprecated"]["threshold_tighten_steer_rate_by_yaw_error"] +) +tighten_horizon = int(mpc_param["mpc_parameter"]["to_be_deprecated"]["tighten_horizon"]) + +min_loose_lateral_cost = float( + mpc_param["mpc_parameter"]["cost_parameters"]["min_loose_lateral_cost"] +) +power_loose_lateral_cost = int( + mpc_param["mpc_parameter"]["cost_parameters"]["power_loose_lateral_cost"] +) +threshold_loose_lateral_cost = float( + mpc_param["mpc_parameter"]["cost_parameters"]["threshold_loose_lateral_cost"] +) + +min_loose_yaw_cost = float(mpc_param["mpc_parameter"]["cost_parameters"]["min_loose_yaw_cost"]) +power_loose_yaw_cost = int(mpc_param["mpc_parameter"]["cost_parameters"]["power_loose_yaw_cost"]) +threshold_loose_yaw_cost = float( + mpc_param["mpc_parameter"]["cost_parameters"]["threshold_loose_yaw_cost"] +) + +use_sg_for_nominal_inputs = bool( + mpc_param["mpc_parameter"]["preprocessing"]["use_sg_for_nominal_inputs"] +) +sg_deg_for_nominal_inputs = int( + mpc_param["mpc_parameter"]["preprocessing"]["sg_deg_for_nominal_inputs"] +) +sg_window_size_for_nominal_inputs = int( + mpc_param["mpc_parameter"]["preprocessing"]["sg_window_size_for_nominal_inputs"] +) +trained_model_param_path = ( + package_path["path"] + "/smart_mpc_trajectory_follower/param/trained_model_param.yaml" +) +with open(trained_model_param_path, "r") as yml: + trained_model_param = yaml.safe_load(yml) +use_trained_model_diff = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_trained_model_diff"] +) +use_sg_for_trained_model_diff = bool( + trained_model_param["trained_model_parameter"]["control_application"][ + "use_sg_for_trained_model_diff" + ] +) +sg_deg_for_trained_model_diff = int( + trained_model_param["trained_model_parameter"]["control_application"][ + "sg_deg_for_trained_model_diff" + ] +) +sg_window_size_for_trained_model_diff = int( + trained_model_param["trained_model_parameter"]["control_application"][ + "sg_window_size_for_trained_model_diff" + ] +) + +use_sg_for_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_sg_for_noise"] +) +sg_deg_for_noise = int( + trained_model_param["trained_model_parameter"]["control_application"]["sg_deg_for_noise"] +) +sg_window_size_for_noise = int( + trained_model_param["trained_model_parameter"]["control_application"][ + "sg_window_size_for_noise" + ] +) + + +load_dir = os.environ["HOME"] +save_dir = os.environ["HOME"] # +"/autoware" +use_trained_model = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_trained_model"] +) +update_trained_model = bool( + trained_model_param["trained_model_parameter"]["control_application"]["update_trained_model"] +) +max_train_data_size = int( + trained_model_param["trained_model_parameter"]["control_application"]["max_train_data_size"] +) + +error_decay = np.array( + trained_model_param["trained_model_parameter"]["control_application"]["error_decay"], + dtype=float, +) + +Error_decay = error_decay[:6] + +use_x_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_x_noise"] +) +use_y_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_y_noise"] +) +use_v_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_v_noise"] +) +use_theta_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_theta_noise"] +) +use_acc_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_acc_noise"] +) +use_steer_noise = bool( + trained_model_param["trained_model_parameter"]["control_application"]["use_steer_noise"] +) + +# smoothing parameter in training +acc_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["acc_sigma_for_learning"] +) +steer_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["steer_sigma_for_learning"] +) +acc_des_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["acc_des_sigma_for_learning"] +) +steer_des_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["steer_des_sigma_for_learning"] +) + +x_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["x_out_sigma_for_learning"] +) +y_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["y_out_sigma_for_learning"] +) +v_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["v_out_sigma_for_learning"] +) +theta_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["theta_out_sigma_for_learning"] +) +acc_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["acc_out_sigma_for_learning"] +) +steer_out_sigma_for_learning = float( + trained_model_param["trained_model_parameter"]["smoothing"]["steer_out_sigma_for_learning"] +) + + +# upper limit of input + + +package_path_split = str(package_path["path"]).split("/") +control_dir_path = "" +for i in range(len(package_path_split)): + control_dir_path += package_path_split[i] + if package_path_split[i] == "control": + break + control_dir_path += "/" + +limit_yaml_path = None +for curDir, dirs, files in os.walk(control_dir_path): + for name in files: + if name == "vehicle_cmd_gate.param.yaml": + if curDir.split("/")[-2] == "vehicle_cmd_gate": + limit_yaml_path = curDir + "/" + name + break + +limit_params = None +if limit_yaml_path is not None: + with open(limit_yaml_path, "r") as yml: + limit_params = yaml.safe_load(yml) +else: + print("Error: limit_yaml_path is None") + +if limit_params is not None: + reference_speed_points = np.array( + limit_params["/**"]["ros__parameters"]["nominal"]["reference_speed_points"] + ) + steer_lim_points = np.array(limit_params["/**"]["ros__parameters"]["nominal"]["steer_lim"]) + steer_rate_lim_points = np.array( + limit_params["/**"]["ros__parameters"]["nominal"]["steer_rate_lim"] + ) + acc_lim_points = np.array(limit_params["/**"]["ros__parameters"]["nominal"]["lon_acc_lim"]) + acc_rate_lim_points = np.array( + limit_params["/**"]["ros__parameters"]["nominal"]["lon_jerk_lim"] + ) + lat_acc_lim_points = np.array(limit_params["/**"]["ros__parameters"]["nominal"]["lat_acc_lim"]) + lat_jerk_lim_points = np.array( + limit_params["/**"]["ros__parameters"]["nominal"]["lat_jerk_lim"] + ) +else: + print("Error: limit_params is None") + sys.exit(1) + + +@njit(cache=True, fastmath=True) +def calc_limits( + vel: float, + acc: float, + steer: float, + reference_speed_points=reference_speed_points, + steer_lim_points=steer_lim_points, + steer_rate_lim_points=steer_rate_lim_points, + acc_lim_points=acc_lim_points, + lat_acc_lim_points=lat_acc_lim_points, + lat_jerk_lim_points=lat_jerk_lim_points, +) -> tuple[float, float, float, float, float]: + """Calculate the constraints according to the current velocity, acceleration and steer. + + Returns: + float: upper and lower limit of steer + float: upper limit of steer change rate + float: lower limit of steer change rate + float: upper and lower limit of acceleration + float: upper and lower limit of acceleration change rate + + However, we write the upper limit of the "upper and lower limits". lower limit is equal to `(-1) * upper limit`. + """ + interval_index = 0 + for i in range(reference_speed_points.shape[0]): + if np.abs(vel) > reference_speed_points[i]: + interval_index += 1 + else: + break + if interval_index == 0: + steer_lim = steer_lim_points[0] + steer_rate_lim = steer_rate_lim_points[0] + acc_lim = acc_lim_points[0] + acc_rate_lim = acc_rate_lim_points[0] + lat_acc_lim = lat_acc_lim_points[0] + lat_jerk_lim = lat_jerk_lim_points[0] + elif interval_index == reference_speed_points.shape[0]: + steer_lim = steer_lim_points[-1] + steer_rate_lim = steer_rate_lim_points[-1] + acc_lim = acc_lim_points[-1] + acc_rate_lim = acc_rate_lim_points[-1] + lat_acc_lim = lat_acc_lim_points[-1] + lat_jerk_lim = lat_jerk_lim_points[-1] + else: + r = (np.abs(vel) - reference_speed_points[interval_index - 1]) / ( + reference_speed_points[interval_index] - reference_speed_points[interval_index - 1] + ) + steer_lim = (1 - r) * steer_lim_points[interval_index - 1] + r * steer_lim_points[ + interval_index + ] + steer_rate_lim = (1 - r) * steer_rate_lim_points[ + interval_index - 1 + ] + r * steer_rate_lim_points[interval_index] + acc_lim = (1 - r) * acc_lim_points[interval_index - 1] + r * acc_lim_points[interval_index] + acc_rate_lim = (1 - r) * acc_rate_lim_points[interval_index - 1] + r * acc_rate_lim_points[ + interval_index + ] + lat_acc_lim = (1 - r) * lat_acc_lim_points[interval_index - 1] + r * lat_acc_lim_points[ + interval_index + ] + lat_jerk_lim = (1 - r) * lat_jerk_lim_points[interval_index - 1] + r * lat_jerk_lim_points[ + interval_index + ] + lat_jerk_lim_coef = L * np.cos(steer) * np.cos(steer) / (vel * vel + 1e-16) + lat_jerk_lim_const = vel * acc * np.sin(2 * steer) / (vel * vel + 1e-16) + steer_rate_lat_jerk_lim_lb = np.array( + [-lat_jerk_lim_coef * lat_jerk_lim - lat_jerk_lim_const, -0.01] + ).min() + steer_rate_lat_jerk_lim_ub = np.array( + [lat_jerk_lim_coef * lat_jerk_lim - lat_jerk_lim_const, 0.01] + ).max() + + steer_rate_lb = np.array([-steer_rate_lim, steer_rate_lat_jerk_lim_lb]).max() + steer_rate_ub = np.array([steer_rate_lim, steer_rate_lat_jerk_lim_ub]).min() + + return ( + np.array([steer_lim, np.arctan(lat_acc_lim * L / (vel * vel + 1e-16))]).min(), + steer_rate_lb, + steer_rate_ub, + acc_lim, + acc_rate_lim, + ) + + +@njit(cache=True, fastmath=True) +def transform_yaw(yaw_old: float, yaw_current_: float) -> float: + """Transform the yaw angle so that the difference in yaw angle is less than or equal to π.""" + rotate_num = (yaw_current_ - yaw_old) // (2 * np.pi) + if yaw_current_ - yaw_old - 2 * rotate_num * np.pi < np.pi: + return yaw_current_ - 2 * rotate_num * np.pi + else: + return yaw_current_ - 2 * (rotate_num + 1) * np.pi + + +@njit(cache=True, fastmath=True) +def transform_yaw_for_x_current(x_old: np.ndarray, x_current_: np.ndarray) -> np.ndarray: + """Apply `transform_yaw` to x_current_ and return the result.""" + x_current = x_current_.copy() + x_current[3] = transform_yaw(x_old[3], x_current_[3]) + return x_current + + +def transform_yaw_for_X_des(x_current: np.ndarray, X_des_: np.ndarray) -> np.ndarray: + """Transform the yaw angle with respect to the target trajectory. + + X_des[0] is set to the current state. + """ + X_des = X_des_.copy() + + initial_error = X_des[0, :3] - x_current[:3] + + len_journey = max(mpc_time_step * X_des[:, 2].sum(), 5.0) + theta_des = X_des[0, 3] + diff_position = -initial_error[:2] + signed_lat_err = -np.sin(theta_des) * diff_position[0] + np.cos(theta_des) * diff_position[1] + + X_des[: reference_horizon + 1, :3] -= ( + np.arange(reference_horizon + 1)[::-1].reshape(-1, 1) + @ initial_error.reshape(1, -1) + / reference_horizon + ) + X_des[0, 3] = transform_yaw(x_current[3], X_des[0, 3]) + yaw_initial_error = X_des[0, 3] - x_current[3] + X_des[0, 3] -= yaw_initial_error + + diff_theta = -yaw_initial_error + np.arctan(signed_lat_err / len_journey) + diff_delta = L * diff_theta / len_journey + + for i in range(X_des.shape[0] - 1): + if i < reference_horizon: + X_des[i + 1, 3] = ( + transform_yaw(X_des[i, 3], X_des[i + 1, 3]) + - yaw_initial_error * (reference_horizon - i - 1) / reference_horizon + ) + else: + X_des[i + 1, 3] = transform_yaw(X_des[i, 3], X_des[i + 1, 3]) + + return X_des, diff_delta + + +@njit(cache=True, fastmath=True) +def U_des_from_X_des(u_opt: np.ndarray, X_des: np.ndarray, diff_delta: float) -> np.ndarray: + """Calculate the initial value of the MPC from the target trajectory. + + This is used for the first control or when the error calculated by calc_maximum_trajectory_error is large. + """ + U_des = np.zeros((X_des.shape[0] - 1, nu_0)) + for i in range(U_des.shape[0]): + U_des[i] = (X_des[i + 1, 6:8] - X_des[i, 6:8]) / mpc_time_step + init_error = X_des[0, 6:8] - u_opt + U_des = U_des + init_error / ((X_des.shape[0] - 1) * mpc_time_step) - diff_delta + return U_des + + +@njit(cache=True, fastmath=True) +def calc_maximum_trajectory_error(traj: np.ndarray, X_des: np.ndarray) -> float: + """Calculate the maximum trajectory error. + + It calculates + * predicted trajectory produced by the MPC, + * the lateral error of the target trajectory + * the maximum value of the yaw error. + """ + err = 0.0 + for i in range(traj.shape[0]): + theta_des = X_des[i, 3] + diff_position = traj[i, 0:2] - X_des[i, 0:2] + lat_err = np.abs( + -np.sin(theta_des) * diff_position[0] + np.cos(theta_des) * diff_position[1] + ) + err = max(err, lat_err) + err = max(err, np.abs(theta_des - traj[i, 3])) + return err + + +@njit(cache=False, fastmath=True) +def transform_Q_R( + X_des: np.ndarray, U_des: np.ndarray, nominal_traj: np.ndarray, nominal_input: np.ndarray +) -> tuple: + """Calculate the MPC cost weight matrix from the current predicted trajectory and target trajectory. + + This calculates the information to add the constraints to the MPC cost. + """ + Q_total = np.zeros((X_des.shape[0], Q.shape[0], Q.shape[1])) + R_total = np.zeros((U_des.shape[0], R.shape[0], R.shape[1])) + acc_lim_weights = np.zeros(X_des.shape[0]) + acc_lim_center = np.zeros(X_des.shape[0]) + steer_lim_weights = np.zeros(X_des.shape[0]) + steer_lim_center = np.zeros(X_des.shape[0]) + acc_rate_lim_weights = np.zeros(U_des.shape[0]) + acc_rate_lim_center = np.zeros(U_des.shape[0]) + steer_rate_lim_weights = np.zeros(U_des.shape[0]) + steer_rate_lim_center = np.zeros(U_des.shape[0]) + for i in range(X_des.shape[0]): + if i == X_des.shape[0] - 1: + Q_ = Q_f.copy() + elif i in timing_Q_c: + Q_ = Q_c.copy() + else: + Q_ = Q.copy() + x_current = nominal_traj[i] + v = x_current[2] + acc = X_des[i, 4] + theta = X_des[i, 3] + + cos = np.cos(theta) + sin = np.sin(theta) + Rot = np.array([[cos, -sin], [sin, cos]]) + + lateral_error = np.abs((Rot.T @ (X_des[i, :2] - x_current[:2]))[1]) + yaw_error = np.abs(X_des[i, 3] - x_current[3]) + cost_tr_steer_rate_by_error = max( + min_tighten_steer_rate, + max( + (lateral_error / threshold_tighten_steer_rate_by_lateral_error) + ** power_tighten_steer_rate_by_lateral_error, + (yaw_error / threshold_tighten_steer_rate_by_yaw_error) + ** power_tighten_steer_rate_by_yaw_error, + ), + ) + cost_tr_steer_rate = 1 / ( + min( + max( + min_steer_rate_transform_for_start, + (coef_steer_rate_transform_for_start * np.abs(v)) + ** power_steer_rate_transform_for_start, + ), + 1.0, + ) + ) + if i >= tighten_horizon: + cost_tr_steer_rate = max(cost_tr_steer_rate, 1 / cost_tr_steer_rate_by_error) + if i in timing_Q_c or i == X_des.shape[0] - 1: + lateral_cost_coef = min( + max( + min_loose_lateral_cost, + (lateral_error / threshold_loose_lateral_cost) ** power_loose_lateral_cost, + ), + 1.0, + ) + Q_[1, 1] = lateral_cost_coef * Q_[1, 1] + yaw_cost_coef = min( + max( + min_loose_yaw_cost, + (yaw_error / threshold_loose_yaw_cost) ** power_loose_yaw_cost, + ), + 1.0, + ) + Q_[3, 3] = yaw_cost_coef * Q_[3, 3] + + Q_[:2, :2] = Rot @ Q_[:2, :2] @ Rot.T + Q_total[i] = Q_ + + steer_lim, steer_rate_lim_lb, steer_rate_lim_ub, acc_lim, acc_rate_lim = calc_limits( + v, x_current[4], x_current[5] + ) + + if x_current[2] <= 0.0 and x_current[nx_0] <= 0.0: + acc_lim_weights[i] = acc_lim_weight + acc_lim_center[i] = 0.0 + else: + if x_current[nx_0] > acc_lim: # acc inputs + acc_lim_weights[i] = acc_lim_weight + acc_lim_center[i] = acc_lim + elif x_current[nx_0] < -acc_lim: + acc_lim_weights[i] = acc_lim_weight + acc_lim_center[i] = -acc_lim + + if x_current[nx_0 + acc_ctrl_queue_size] > steer_lim: # steer inputs + steer_lim_weights[i] = steer_lim_weight + steer_lim_center[i] = steer_lim + elif x_current[nx_0 + acc_ctrl_queue_size] < -steer_lim: + steer_lim_weights[i] = steer_lim_weight + steer_lim_center[i] = -steer_lim + if i != X_des.shape[0] - 1: + R_ = R.copy() + if acc >= 0: + R_[1, 1] = cost_tr_steer_rate * R_[1, 1] + R_total[i] = R_ + + if nominal_input[i, 0] > acc_rate_lim: + acc_rate_lim_weights[i] = acc_rate_lim_weight + acc_rate_lim_center[i] = acc_rate_lim + elif nominal_input[i, 0] < -acc_rate_lim: + acc_rate_lim_weights[i] = acc_rate_lim_weight + acc_rate_lim_center[i] = -acc_rate_lim + + if nominal_input[i, 1] > steer_rate_lim_ub: + steer_rate_lim_weights[i] = steer_rate_lim_weight + steer_rate_lim_center[i] = steer_rate_lim_ub + elif nominal_input[i, 1] < steer_rate_lim_lb: + steer_rate_lim_weights[i] = steer_rate_lim_weight + steer_rate_lim_center[i] = steer_rate_lim_lb + + return ( + Q_total, + R_total, + acc_lim_weights, + acc_lim_center, + steer_lim_weights, + steer_lim_center, + acc_rate_lim_weights, + acc_rate_lim_center, + steer_rate_lim_weights, + steer_rate_lim_center, + ) + + +@njit(cache=False, fastmath=True) +def calc_cost( + X_des: np.ndarray, U_des: np.ndarray, Traj: np.ndarray, Inputs: np.ndarray, n: int +) -> np.ndarray: + """Calculate the MPC cost of the nth horizon from several candidate predicted trajectories and target trajectories.""" + Cost = np.zeros(Traj.shape[0]) + if n == N: + Q_ = Q_f.copy() + elif n in timing_Q_c: + Q_ = Q_c.copy() + else: + Q_ = Q.copy() + acc = X_des[4] + theta = X_des[3] + cos = np.cos(theta) + sin = np.sin(theta) + Rot = np.array([[cos, -sin], [sin, cos]]) + for i in range(Traj.shape[0]): + x_current = Traj[i] + v = x_current[2] + + Qi = Q_.copy() + lateral_error = np.abs((Rot.T @ (X_des[:2] - x_current[:2]))[1]) + yaw_error = np.abs(X_des[3] - x_current[3]) + cost_tr_steer_rate_by_error = max( + min_tighten_steer_rate, + max( + (lateral_error / threshold_tighten_steer_rate_by_lateral_error) + ** power_tighten_steer_rate_by_lateral_error, + (yaw_error / threshold_tighten_steer_rate_by_yaw_error) + ** power_tighten_steer_rate_by_yaw_error, + ), + ) + cost_tr_steer_rate = 1 / ( + min( + max( + min_steer_rate_transform_for_start, + (coef_steer_rate_transform_for_start * np.abs(v)) + ** power_steer_rate_transform_for_start, + ), + 1.0, + ) + ) + if n >= tighten_horizon: + cost_tr_steer_rate = max(cost_tr_steer_rate, 1 / cost_tr_steer_rate_by_error) + if n in timing_Q_c or n == N: + lateral_cost_coef = min( + max( + min_loose_lateral_cost, + (lateral_error / threshold_loose_lateral_cost) ** power_loose_lateral_cost, + ), + 1.0, + ) + Qi[1, 1] = lateral_cost_coef * Qi[1, 1] + yaw_cost_coef = min( + max( + min_loose_yaw_cost, + (yaw_error / threshold_loose_yaw_cost) ** power_loose_yaw_cost, + ), + 1.0, + ) + Qi[3, 3] = yaw_cost_coef * Qi[3, 3] + Qi[:2, :2] = Rot @ Qi[:2, :2] @ Rot.T + Cost[i] += 0.5 * np.dot(Qi @ (x_current - X_des), x_current - X_des) + + steer_lim, steer_rate_lim_lb, steer_rate_lim_ub, acc_lim, acc_rate_lim = calc_limits( + v, x_current[4], x_current[5] + ) + if x_current[2] <= 0.0 and x_current[nx_0] <= 0.0: + Cost[i] += 0.5 * acc_lim_weight * (x_current[nx_0] - 0.0) * (x_current[nx_0] - 0.0) + + else: + if x_current[nx_0] > acc_lim: + Cost[i] += ( + 0.5 * acc_lim_weight * (x_current[nx_0] - acc_lim) * (x_current[nx_0] - acc_lim) + ) + elif x_current[nx_0] < -acc_lim: + Cost[i] += ( + 0.5 * acc_lim_weight * (x_current[nx_0] + acc_lim) * (x_current[nx_0] + acc_lim) + ) + + if x_current[nx_0 + 1] > steer_lim: + Cost[i] += ( + 0.5 + * steer_lim_weight + * (x_current[nx_0 + 1] - steer_lim) + * (x_current[nx_0 + 1] - steer_lim) + ) + + elif x_current[nx_0 + 1] < -steer_lim: + Cost[i] += ( + 0.5 + * steer_lim_weight + * (x_current[nx_0 + 1] + steer_lim) + * (x_current[nx_0 + 1] + steer_lim) + ) + + if n != N: + R_ = R.copy() + if acc >= 0: + R_[1, 1] = cost_tr_steer_rate * R_[1, 1] + + Cost[i] += 0.5 * np.dot(R_ @ (Inputs[i] - U_des), Inputs[i] - U_des) + + if Inputs[i, 0] > acc_rate_lim: + Cost[i] += ( + 0.5 + * acc_rate_lim_weight + * (Inputs[i, 0] - acc_rate_lim) + * (Inputs[i, 0] - acc_rate_lim) + ) + elif Inputs[i, 0] < -acc_rate_lim: + Cost[i] += ( + 0.5 + * acc_rate_lim_weight + * (Inputs[i, 0] + acc_rate_lim) + * (Inputs[i, 0] + acc_rate_lim) + ) + + if Inputs[i, 1] > steer_rate_lim_ub: + Cost[i] += ( + 0.5 + * steer_rate_lim_weight + * (Inputs[i, 1] - steer_rate_lim_ub) + * (Inputs[i, 1] - steer_rate_lim_ub) + ) + elif Inputs[i, 1] < steer_rate_lim_lb: + Cost[i] += ( + 0.5 + * steer_rate_lim_weight + * (Inputs[i, 1] - steer_rate_lim_lb) + * (Inputs[i, 1] - steer_rate_lim_lb) + ) + + return Cost + + +@njit(cache=False, fastmath=True) +def calc_cost_only_for_states(X_des: np.ndarray, Traj: np.ndarray, n: int) -> np.ndarray: + """Calculate the MPC cost for states of the nth horizon from several candidate predicted trajectories and target trajectories.""" + Cost = np.zeros(Traj.shape[0]) + if n == N: + Q_ = Q_f.copy() + elif n in timing_Q_c: + Q_ = Q_c.copy() + else: + Q_ = Q.copy() + theta = X_des[3] + cos = np.cos(theta) + sin = np.sin(theta) + Rot = np.array([[cos, -sin], [sin, cos]]) + for i in range(Traj.shape[0]): + x_current = Traj[i] + v = x_current[2] + + Qi = Q_.copy() + if n in timing_Q_c or n == N: + lateral_error = np.abs((Rot.T @ (X_des[:2] - x_current[:2]))[1]) + lateral_cost_coef = min( + max( + min_loose_lateral_cost, + (lateral_error / threshold_loose_lateral_cost) ** power_loose_lateral_cost, + ), + 1.0, + ) + Qi[1, 1] = lateral_cost_coef * Qi[1, 1] + yaw_error = np.abs(X_des[3] - x_current[3]) + yaw_cost_coef = min( + max( + min_loose_yaw_cost, + (yaw_error / threshold_loose_yaw_cost) ** power_loose_yaw_cost, + ), + 1.0, + ) + Qi[3, 3] = yaw_cost_coef * Qi[3, 3] + Qi[:2, :2] = Rot @ Qi[:2, :2] @ Rot.T + Cost[i] += 0.5 * np.dot(Qi @ (x_current - X_des), x_current - X_des) + + steer_lim, _, _, acc_lim, _ = calc_limits(v, x_current[4], x_current[5]) + if x_current[2] <= 0.0 and x_current[nx_0] <= 0.0: + Cost[i] += 0.5 * acc_lim_weight * (x_current[nx_0] - 0.0) * (x_current[nx_0] - 0.0) + + else: + if x_current[nx_0] > acc_lim: + Cost[i] += ( + 0.5 * acc_lim_weight * (x_current[nx_0] - acc_lim) * (x_current[nx_0] - acc_lim) + ) + elif x_current[nx_0] < -acc_lim: + Cost[i] += ( + 0.5 * acc_lim_weight * (x_current[nx_0] + acc_lim) * (x_current[nx_0] + acc_lim) + ) + + if x_current[nx_0 + 1] > steer_lim: + Cost[i] += ( + 0.5 + * steer_lim_weight + * (x_current[nx_0 + 1] - steer_lim) + * (x_current[nx_0 + 1] - steer_lim) + ) + + elif x_current[nx_0 + 1] < -steer_lim: + Cost[i] += ( + 0.5 + * steer_lim_weight + * (x_current[nx_0 + 1] + steer_lim) + * (x_current[nx_0 + 1] + steer_lim) + ) + + return Cost + + +def rotate_data(x_old: np.ndarray, var_dot: np.ndarray) -> np.ndarray: + """Apply a rotation that converts the x, y velocity relative to the world to the x, y velocity relative to the vehicle body.""" + theta_old = x_old[3] + cos = np.cos(theta_old) + sin = np.sin(theta_old) + + var_dot_ = var_dot.copy() + var_dot_[:2] = np.array([[cos, sin], [-sin, cos]]) @ var_dot[:2] + + return var_dot_ + + +@njit(cache=True, fastmath=True) +def f_init( + states: np.ndarray, + inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Time derivative of nominal model dynamics.""" + v = states[2] + theta = states[3] + alpha = states[4] + delta = states[5] + + delta_diff = inputs[1] - delta + if delta_diff >= steer_dead_band_for_ctrl: + delta_diff = delta_diff - steer_dead_band_for_ctrl + elif delta_diff <= -steer_dead_band_for_ctrl: + delta_diff = delta_diff + steer_dead_band_for_ctrl + else: + delta_diff = 0.0 + + states_dot = np.zeros(nx_0) + states_dot[0] = v * np.cos(theta) + states_dot[1] = v * np.sin(theta) + states_dot[2] = alpha + states_dot[3] = v * np.tan(delta) / L + states_dot[4] = (inputs[0] - alpha) / acc_time_constant_ctrl + states_dot[5] = delta_diff / steer_time_constant_ctrl + return states_dot + + +@njit(cache=True, fastmath=True) +def F_init( + states: np.ndarray, + inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Nominal model dynamics.""" + states_next = ( + states + + f_init( + states, + inputs, + acc_time_constant_ctrl, + steer_time_constant_ctrl, + steer_dead_band_for_ctrl, + ) + * ctrl_time_step + ) + return states_next + + +@njit(cache=True, fastmath=True) +def F_multiple( + states: np.ndarray, + inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Discretize and integrate up to the MPC time width according to the nominal model dynamics.""" + states_next = states + for i in range(mpc_freq): + states_next = F_init( + states_next, + inputs[i], + acc_time_constant_ctrl, + steer_time_constant_ctrl, + steer_dead_band_for_ctrl, + ) + return states_next + + +@njit(cache=True, fastmath=True) +def F_init_with_diff( + states: np.ndarray, + inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Compute the dynamics of the nominal model while computing derivatives.""" + states_next = ( + states + + f_init( + states, + inputs, + acc_time_constant_ctrl, + steer_time_constant_ctrl, + steer_dead_band_for_ctrl, + ) + * ctrl_time_step + ) + dF_dx = np.eye(nx_0) + dF_du = np.zeros((nx_0, nu_0)) + v = states[2] + theta = states[3] + delta = states[5] + + dF_dx[0, 2] += np.cos(theta) * ctrl_time_step + dF_dx[0, 3] -= v * np.sin(theta) * ctrl_time_step + dF_dx[1, 2] += np.sin(theta) * ctrl_time_step + dF_dx[1, 3] += v * np.cos(theta) * ctrl_time_step + dF_dx[2, 4] += ctrl_time_step + dF_dx[3, 2] += np.tan(delta) * ctrl_time_step / L + dF_dx[3, 5] += v * ctrl_time_step / (L * np.cos(delta) * np.cos(delta)) + dF_dx[4, 4] -= ctrl_time_step / acc_time_constant_ctrl + + dF_du[4, 0] = ctrl_time_step / acc_time_constant_ctrl + if abs(inputs[1] - delta) >= steer_dead_band_for_ctrl: + dF_dx[5, 5] -= ctrl_time_step / steer_time_constant_ctrl + dF_du[5, 1] = ctrl_time_step / steer_time_constant_ctrl + return states_next, dF_dx, dF_du + + +@njit(cache=True, fastmath=True) +def F_multiple_with_diff( + states: np.ndarray, + inputs: np.ndarray, + acc_time_constant_ctrl: float = ctrl_time_step, + steer_time_constant_ctrl: float = ctrl_time_step, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Integrate up to the MPC time width according to the nominal model while calculating the derivative.""" + F_0, dFx_0, dFu_0 = F_init_with_diff( + states, + inputs[0], + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, + ) + F_1, dFx_1, dFu_1 = F_init_with_diff( + F_0, + inputs[1], + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, + ) + F_2, dFx_2, dFu_2 = F_init_with_diff( + F_1, + inputs[2], + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, + ) + dF_dx = dFx_2 @ dFx_1 @ dFx_0 + + dF_du = np.zeros((nx_0, 3 * nu_0)) + dF_du[:, :nu_0] = dFx_2 @ dFx_1 @ dFu_0 + dF_du[:, nu_0 : 2 * nu_0] = dFx_2 @ dFu_1 + dF_du[:, 2 * nu_0 : 3 * nu_0] = dFu_2 + return F_2, dF_dx, dF_du + + +@njit(cache=True, fastmath=True) +def f_init_for_candidates( + States: np.ndarray, + Inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Time derivative of nominal model dynamics for multiple candidates.""" + v = States[:, 2] + theta = States[:, 3] + alpha = States[:, 4] + delta = States[:, 5] + smaller_than_band = Inputs[:, 1] - delta < steer_dead_band_for_ctrl + larger_than_band = Inputs[:, 1] - delta > -steer_dead_band_for_ctrl + + delta_diff = (1 - smaller_than_band * larger_than_band) * ( + (Inputs[:, 1] - delta) + - (1 * larger_than_band - 1 * smaller_than_band) * steer_dead_band_for_ctrl + ) + States_dot = np.zeros(States.shape) + States_dot[:, 0] = v * np.cos(theta) + States_dot[:, 1] = v * np.sin(theta) + States_dot[:, 2] = alpha + States_dot[:, 3] = v * np.tan(delta) / L + States_dot[:, 4] = (Inputs[:, 0] - alpha) / acc_time_constant_ctrl + States_dot[:, 5] = delta_diff / steer_time_constant_ctrl + return States_dot + + +@njit(cache=True, fastmath=True) +def F_multiple_for_candidates( + States: np.ndarray, + Inputs: np.ndarray, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Discretize and integrate up to the MPC time width according to the nominal model dynamics for several candidates.""" + # Euler method + States_next = States.copy() + for i in range(mpc_freq): + States_next = ( + States_next + + f_init_for_candidates( + States_next, + Inputs[:, i, :], + acc_time_constant_ctrl, + steer_time_constant_ctrl, + steer_dead_band_for_ctrl, + ) + * ctrl_time_step + ) + return States_next + + +@njit(cache=True, fastmath=True) +def F_with_history( + states: np.ndarray, + inputs: np.ndarray, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, + steer_dead_band_for_ctrl=steer_dead_band_for_ctrl, +) -> np.ndarray: + """Integrate up to the MPC time width according to the nominal model. + + This includes the history of the input to the state. + """ + # Function from extended state + states_next = np.zeros(states.shape) + states_next[nx_0 + mpc_freq : nx_0 + acc_ctrl_queue_size] = states[ + nx_0 : nx_0 + acc_ctrl_queue_size - mpc_freq + ].copy() + states_next[ + nx_0 + acc_ctrl_queue_size + mpc_freq : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size + ] = states[ + nx_0 + acc_ctrl_queue_size : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size - mpc_freq + ].copy() + for k in range(mpc_freq): + states_next[nx_0 + mpc_freq - k - 1] = ( + states_next[nx_0 + mpc_freq - k] + ctrl_time_step * inputs[0] + ) + states_next[nx_0 + acc_ctrl_queue_size + mpc_freq - k - 1] = ( + states_next[nx_0 + acc_ctrl_queue_size + mpc_freq - k] + ctrl_time_step * inputs[1] + ) + + actual_inputs = np.zeros((mpc_freq, inputs.shape[0])) + actual_inputs[:, 0] = states_next[nx_0 + i + np.arange(mpc_freq)[::-1]] + actual_inputs[:, 1] = states_next[nx_0 + acc_ctrl_queue_size + j + np.arange(mpc_freq)[::-1]] + + states_next[:nx_0] = F_multiple( + states[:nx_0], + actual_inputs, + acc_time_constant_ctrl, + steer_time_constant_ctrl, + steer_dead_band_for_ctrl, + ) + + return states_next + + +def F_with_history_and_diff( + states: np.ndarray, + inputs: np.ndarray, + previous_error: None = None, + init: None = None, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, +) -> tuple[np.ndarray, np.ndarray, np.ndarray, None]: + """While computing the derivative, integrate up to the MPC time width according to the nominal model. + + This includes the history of the input to the state. + """ + nx = states.shape[0] + states_next = np.zeros(nx) + dF_dx = np.zeros((nx, nx)) + dF_du = np.zeros((nx, nu_0)) + + states_next[nx_0 + mpc_freq : nx_0 + acc_ctrl_queue_size] = states[ + nx_0 : nx_0 + acc_ctrl_queue_size - mpc_freq + ].copy() + states_next[ + nx_0 + acc_ctrl_queue_size + mpc_freq : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size + ] = states[ + nx_0 + acc_ctrl_queue_size : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size - mpc_freq + ].copy() + + dF_dx[ + nx_0 + mpc_freq : nx_0 + acc_ctrl_queue_size, nx_0 : nx_0 + acc_ctrl_queue_size - mpc_freq + ] = np.eye(acc_ctrl_queue_size - mpc_freq) + dF_dx[ + nx_0 + acc_ctrl_queue_size + mpc_freq : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size, + nx_0 + acc_ctrl_queue_size : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size - mpc_freq, + ] = np.eye(steer_ctrl_queue_size - mpc_freq) + + for k in range(mpc_freq): + states_next[nx_0 + mpc_freq - k - 1] = ( + states_next[nx_0 + mpc_freq - k] + ctrl_time_step * inputs[0] + ) + states_next[nx_0 + acc_ctrl_queue_size + mpc_freq - k - 1] = ( + states_next[nx_0 + acc_ctrl_queue_size + mpc_freq - k] + ctrl_time_step * inputs[1] + ) + dF_dx[nx_0 + mpc_freq - k - 1, nx_0] = 1 + dF_dx[nx_0 + acc_ctrl_queue_size + mpc_freq - k - 1, nx_0 + acc_ctrl_queue_size] = 1 + + dF_du[nx_0 + mpc_freq - k - 1, 0] = (k + 1) * ctrl_time_step + dF_du[nx_0 + acc_ctrl_queue_size + mpc_freq - k - 1, 1] = (k + 1) * ctrl_time_step + + actual_inputs = np.zeros((mpc_freq, inputs.shape[0])) + actual_inputs[:, 0] = states_next[nx_0 + i + np.arange(mpc_freq)[::-1]].copy() + + actual_inputs[:, 1] = states_next[ + nx_0 + acc_ctrl_queue_size + j + np.arange(mpc_freq)[::-1] + ].copy() + control_index = np.vstack( + ( + nx_0 + max(i - mpc_freq, 0) + np.arange(mpc_freq)[::-1], + nx_0 + acc_ctrl_queue_size + max(j - mpc_freq, 0) + np.arange(mpc_freq)[::-1], + ) + ).T.flatten() + states_next[:nx_0], dF_dx[:nx_0, :nx_0], dF_dx[:nx_0, control_index] = F_multiple_with_diff( + states[:nx_0], actual_inputs, acc_time_constant_ctrl, steer_time_constant_ctrl + ) + + return states_next, dF_dx, dF_du, None + + +@njit(cache=True, fastmath=True) +def F_with_history_for_candidates( + States: np.ndarray, + Inputs: np.ndarray, + Previous_error=None, + init=None, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, +) -> tuple[np.ndarray, None]: + """For several candidates, discretize and integrate up to the MPC time-width according to the nominal model dynamics. + + This includes the history of the input to the state. + """ + States_next = np.zeros(States.shape) + + States_next[:, nx_0 + mpc_freq : nx_0 + acc_ctrl_queue_size] = States[ + :, nx_0 : nx_0 + acc_ctrl_queue_size - mpc_freq + ].copy() + States_next[ + :, + nx_0 + acc_ctrl_queue_size + mpc_freq : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size, + ] = States[ + :, + nx_0 + acc_ctrl_queue_size : nx_0 + acc_ctrl_queue_size + steer_ctrl_queue_size - mpc_freq, + ].copy() + for k in range(mpc_freq): + States_next[:, nx_0 + mpc_freq - k - 1] = ( + States_next[:, nx_0 + mpc_freq - k] + ctrl_time_step * Inputs[:, 0] + ) + States_next[:, nx_0 + acc_ctrl_queue_size + mpc_freq - k - 1] = ( + States_next[:, nx_0 + acc_ctrl_queue_size + mpc_freq - k] + + ctrl_time_step * Inputs[:, 1] + ) + actual_Inputs = np.zeros((Inputs.shape[0], mpc_freq, nu_0)) + + actual_Inputs[:, :, 0] = States_next[:, nx_0 + i + np.arange(mpc_freq)[::-1]].copy() + actual_Inputs[:, :, 1] = States_next[ + :, nx_0 + acc_ctrl_queue_size + j + np.arange(mpc_freq)[::-1] + ].copy() + States_next[:, :nx_0] = F_multiple_for_candidates( + States[:, :nx_0], actual_Inputs, acc_time_constant_ctrl, steer_time_constant_ctrl + ) + return States_next, None + + +def F_with_model_initial_diff( + states: np.ndarray, + inputs: np.ndarray, + previous_error: np.ndarray, + k: int, + pred: Callable, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, +) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + """While computing the derivative, integrate up to the MPC time width according to the trained model. + + This includes the history of the input to the state. + The derivative follows the nominal model. + This verifies whether the learning is working on the predictions or on the derivatives. + """ + if k == 0: + error = error_decay * previous_error + (1 - error_decay) * pred(states) + else: + error = error_decay * error_decay * error_decay * previous_error + ( + 1 - error_decay * error_decay * error_decay + ) * pred(states) + previous_error_ = error + + rot_error, d_rot_error = np.split(error, [nx_0]) + states_next, dF_dx, dF_du, _ = F_with_history_and_diff( + states, + inputs, + i=i, + j=j, + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + ) + + dF_dx[:2, 3] += d_rot_error * mpc_time_step + states_next[:nx_0] += rot_error * mpc_time_step + + return states_next, dF_dx, dF_du, previous_error_ + + +def F_with_model_diff( + states: np.ndarray, + inputs: np.ndarray, + previous_error: np.ndarray, + k: int, + pred: Callable, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, +) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + """While computing the derivative, it integrates up to the MPC time width according to the trained model. + + This includes the history of the input to the state. + The derivatives also follow a trained model. + """ + pred_with_diff = pred(states) + + if k == 0: + rot_error = ( + error_decay[:nx_0] * previous_error[:nx_0] + + (1 - error_decay[:nx_0]) * pred_with_diff[:, 0] + ) + d_rot_error = ( + error_decay[nx_0:] * previous_error[nx_0:] + + (1 - error_decay[nx_0:]) * pred_with_diff[:2, 1] + ) + else: + rot_error = ( + error_decay[:nx_0] * error_decay[:nx_0] * error_decay[:nx_0] * previous_error[:nx_0] + + (1 - error_decay[:nx_0] * error_decay[:nx_0] * error_decay[:nx_0]) + * pred_with_diff[:, 0] + ) + d_rot_error = ( + error_decay[nx_0:] * error_decay[nx_0:] * error_decay[nx_0:] * previous_error[nx_0:] + + (1 - error_decay[nx_0:] * error_decay[nx_0:] * error_decay[nx_0:]) + * pred_with_diff[:2, 1] + ) + pred_error_ = np.concatenate((rot_error, d_rot_error)) + states_next, dF_dx, dF_du, _ = F_with_history_and_diff( + states, + inputs, + i=i, + j=j, + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + ) + + dF_dx[:2, 3] += d_rot_error * mpc_time_step + states_next[:nx_0] += rot_error * mpc_time_step + return states_next, dF_dx, dF_du, pred_with_diff[:, 2:] * mpc_time_step, pred_error_ + + +def F_with_model_for_candidates( + States: np.ndarray, + Inputs: np.ndarray, + Previous_error: np.ndarray, + k: int, + Pred: Callable, + i: int = acc_delay_step, + j: int = steer_delay_step, + acc_time_constant_ctrl: float = acc_time_constant, + steer_time_constant_ctrl: float = steer_time_constant, +) -> tuple[np.ndarray, np.ndarray]: + """For several candidates, integrate up to the MPC time width according to the trained model. + + This includes the history of the input to the state. + """ + if k == 0: + Error = Error_decay * Previous_error + (1 - Error_decay) * Pred(States.T).T + else: + Error = ( + Error_decay * Error_decay * Error_decay * Previous_error + + (1 - Error_decay * Error_decay * Error_decay) * Pred(States.T).T + ) + Previous_error_ = Error + + States_next, _ = F_with_history_for_candidates( + States, + Inputs, + i=i, + j=j, + acc_time_constant_ctrl=acc_time_constant_ctrl, + steer_time_constant_ctrl=steer_time_constant_ctrl, + ) + States_next[:, :nx_0] += Error * mpc_time_step + + return States_next, Previous_error_ + + +def sg_filter( + inputs: np.ndarray, + use_sg: bool, + sg_window_size: int, + sg_vector_left_edge: list[np.ndarray], + sg_vector_right_edge: list[np.ndarray], + sg_vector: np.ndarray, +) -> np.ndarray: + """SG Filter. Used for smoothing.""" + if use_sg: + input_len = inputs.shape[0] + filtered_inputs = np.zeros(inputs.shape) + for i in range(input_len): + if i < sg_window_size: + filtered_inputs[i] = ( + (inputs[: sg_window_size + i + 1].T * sg_vector_left_edge[i]) + .sum(axis=inputs.ndim - 1) + .T + ) + elif i > input_len - sg_window_size - 1: + filtered_inputs[i] = ( + (inputs[i - sg_window_size :].T * sg_vector_right_edge[input_len - i - 1]) + .sum(axis=inputs.ndim - 1) + .T + ) + else: + filtered_inputs[i] = ( + (inputs[i - sg_window_size : i + sg_window_size + 1].T * sg_vector) + .sum(axis=inputs.ndim - 1) + .T + ) + return filtered_inputs + else: + return inputs + + +def calc_sg_filter_weight(sg_deg, sg_window_size): + """Calculate weighted average weights from SG filter degree and window size.""" + sg_vector_left_edge = [] + sg_vector_right_edge = [] + e_0 = np.zeros(sg_deg + 1) + e_0[0] = 1.0 + for i in range(sg_window_size): + reg_times = (np.arange(sg_window_size + i + 1) - i) * mpc_time_step + T = np.ones((sg_window_size + i + 1, sg_deg + 1)) + W = np.eye(T.shape[0]) + for j in range(sg_deg): + T[:, j + 1] = T[:, j] * reg_times + sg_vector_left_edge.append(W @ T @ np.linalg.inv(T.T @ W @ T) @ e_0) + reg_times = (np.arange(sg_window_size + i + 1) - sg_window_size) * mpc_time_step + T = np.ones((sg_window_size + i + 1, sg_deg + 1)) + W = np.eye(T.shape[0]) + for j in range(sg_deg): + T[:, j + 1] = T[:, j] * reg_times + sg_vector_right_edge.append(W @ T @ np.linalg.inv(T.T @ W @ T) @ e_0) + reg_times = (np.arange(2 * sg_window_size + 1) - sg_window_size) * mpc_time_step + T = np.ones((2 * sg_window_size + 1, sg_deg + 1)) + for j in range(sg_deg): + T[:, j + 1] = T[:, j] * reg_times + sg_vector = T @ np.linalg.inv(T.T @ T) @ e_0 + return sg_vector, sg_vector_left_edge, sg_vector_right_edge + + +( + sg_vector_for_nominal_inputs, + sg_vector_left_edge_for_nominal_inputs, + sg_vector_right_edge_for_nominal_inputs, +) = calc_sg_filter_weight(sg_deg_for_nominal_inputs, sg_window_size_for_nominal_inputs) +( + sg_vector_for_trained_model_diff, + sg_vector_left_edge_for_trained_model_diff, + sg_vector_right_edge_for_trained_model_diff, +) = calc_sg_filter_weight(sg_deg_for_trained_model_diff, sg_window_size_for_trained_model_diff) +( + sg_vector_for_noise, + sg_vector_left_edge_for_noise, + sg_vector_right_edge_for_noise, +) = calc_sg_filter_weight(sg_deg_for_noise, sg_window_size_for_noise) + +sg_filter_for_nominal_inputs = partial( + sg_filter, + use_sg=use_sg_for_nominal_inputs, + sg_window_size=sg_window_size_for_nominal_inputs, + sg_vector_left_edge=sg_vector_left_edge_for_nominal_inputs, + sg_vector_right_edge=sg_vector_right_edge_for_nominal_inputs, + sg_vector=sg_vector_for_nominal_inputs, +) + +sg_filter_for_trained_model_diff = partial( + sg_filter, + use_sg=use_sg_for_trained_model_diff, + sg_window_size=sg_window_size_for_trained_model_diff, + sg_vector_left_edge=sg_vector_left_edge_for_trained_model_diff, + sg_vector_right_edge=sg_vector_right_edge_for_trained_model_diff, + sg_vector=sg_vector_for_trained_model_diff, +) + +sg_filter_for_noise = partial( + sg_filter, + use_sg=use_sg_for_noise, + sg_window_size=sg_window_size_for_noise, + sg_vector_left_edge=sg_vector_left_edge_for_noise, + sg_vector_right_edge=sg_vector_right_edge_for_noise, + sg_vector=sg_vector_for_noise, +) + + +def calc_gf_kernel(sigma): + """Calculate the kernel of the Gaussian filter from the variance.""" + kernel = np.zeros(int(round(4 * sigma)) * 2 + 1) + for i in range(kernel.shape[0]): + kernel[i] = np.exp(-((i - round(4 * sigma)) ** 2) / (2 * sigma**2)) + + kernel = kernel / kernel.sum() + return kernel + + +kernel_acc_for_learning = calc_gf_kernel(acc_sigma_for_learning) +kernel_steer_for_learning = calc_gf_kernel(steer_sigma_for_learning) +kernel_acc_des_for_learning = calc_gf_kernel(acc_des_sigma_for_learning) +kernel_steer_des_for_learning = calc_gf_kernel(steer_des_sigma_for_learning) + +max_input_queue_size_for_learning = max( + [ + kernel_acc_for_learning.shape[0], + kernel_steer_for_learning.shape[0], + kernel_acc_des_for_learning.shape[0], + kernel_steer_des_for_learning.shape[0], + ] +) + +kernel_x_out_for_learning = calc_gf_kernel(x_out_sigma_for_learning) +kernel_y_out_for_learning = calc_gf_kernel(y_out_sigma_for_learning) +kernel_v_out_for_learning = calc_gf_kernel(v_out_sigma_for_learning) +kernel_theta_out_for_learning = calc_gf_kernel(theta_out_sigma_for_learning) +kernel_acc_out_for_learning = calc_gf_kernel(acc_out_sigma_for_learning) +kernel_steer_out_for_learning = calc_gf_kernel(steer_out_sigma_for_learning) + +max_output_queue_size_for_learning = max( + [ + kernel_x_out_for_learning.shape[0], + kernel_y_out_for_learning.shape[0], + kernel_v_out_for_learning.shape[0], + kernel_theta_out_for_learning.shape[0], + kernel_acc_out_for_learning.shape[0], + kernel_steer_out_for_learning.shape[0], + ] +) + + +def u_cut_off( + u_input: np.ndarray, + u_old: np.ndarray, + steer_lim: float, + steer_rate_lim_lb: float, + steer_rate_lim_ub: float, + acc_lim: float, + acc_rate_lim: float, +) -> np.ndarray: + """Process input values to satisfy constraints.""" + u_input_ = u_input.copy() + lb_0 = max(-acc_lim, u_old[0] - acc_rate_lim * ctrl_time_step) + ub_0 = min(acc_lim, u_old[0] + acc_rate_lim * ctrl_time_step) + lb_1 = max(-steer_lim, u_old[1] + steer_rate_lim_lb * ctrl_time_step) + ub_1 = min(steer_lim, u_old[1] + steer_rate_lim_ub * ctrl_time_step) + if u_input[0] >= ub_0: + u_input_[0] = ub_0 + elif u_input[0] < lb_0: + u_input_[0] = lb_0 + if u_input[1] >= ub_1: + u_input_[1] = ub_1 + elif u_input[1] < lb_1: + u_input_[1] = lb_1 + return u_input_ diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_iLQR.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_iLQR.py new file mode 100644 index 0000000000000..261a72e680778 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_iLQR.py @@ -0,0 +1,644 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore numba njit fastmath Riccati Jacobians + +"""Optimize input based on iLQR.""" + + +from importlib import reload as ir +import time +from typing import Callable + +from numba import njit +import numpy as np +from smart_mpc_trajectory_follower.scripts import drive_functions + +index_cost = np.concatenate( + ( + np.arange(drive_functions.nx_0 + 1), + np.array([drive_functions.nx_0 + drive_functions.acc_ctrl_queue_size]), + ) +) +acc_index = drive_functions.nx_0 +steer_index = drive_functions.nx_0 + drive_functions.acc_ctrl_queue_size +actual_control_index = np.arange( + drive_functions.nx_0 + + drive_functions.acc_ctrl_queue_size + + drive_functions.steer_ctrl_queue_size_core +) +actual_state_dim = drive_functions.nx_0 +input_dim = drive_functions.nu_0 +mpc_freq = drive_functions.mpc_freq +acc_delay_step = drive_functions.acc_delay_step +steer_delay_step = drive_functions.steer_delay_step +acc_ctrl_queue_size = drive_functions.acc_ctrl_queue_size +steer_ctrl_queue_size = drive_functions.steer_ctrl_queue_size +ctrl_time_step = drive_functions.ctrl_time_step + + +@njit(cache=True, fastmath=True) +def sparse_right_action_for_state_diff( + Mat: np.ndarray, + A: np.ndarray, + actual_control_index=actual_control_index, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, + steer_ctrl_queue_size=steer_ctrl_queue_size, +) -> np.ndarray: + """Receives the sparse matrix `A₀` and computes `Mat @ A₀`. + + The argument A is part of A₀ . + The remaining A₀ components are known a priori. + """ + result = np.zeros( + (Mat.shape[0], actual_state_dim + acc_ctrl_queue_size + steer_ctrl_queue_size) + ) + result[:, actual_control_index] += Mat[:, :actual_state_dim] @ A + + result[:, actual_state_dim : actual_state_dim + acc_ctrl_queue_size - mpc_freq] += Mat[ + :, actual_state_dim + mpc_freq : actual_state_dim + acc_ctrl_queue_size + ] + result[ + :, + actual_state_dim + + acc_ctrl_queue_size : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size + - mpc_freq, + ] += Mat[ + :, + actual_state_dim + + acc_ctrl_queue_size + + mpc_freq : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size, + ] + for i in range(mpc_freq): + result[:, actual_state_dim] += Mat[:, actual_state_dim + i] + result[:, actual_state_dim + acc_ctrl_queue_size] += Mat[ + :, actual_state_dim + acc_ctrl_queue_size + i + ] + return result + + +@njit(cache=True, fastmath=True) +def sparse_left_action_for_state_diff( + A: np.ndarray, + Mat: np.ndarray, + actual_control_index=actual_control_index, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, + steer_ctrl_queue_size=steer_ctrl_queue_size, +) -> np.ndarray: + """Receives the sparse matrix A₀ and computes A₀.T @ Mat . + + The argument A is part of A₀ . + The remaining A₀ components are known a priori. + """ + result = np.zeros( + (actual_state_dim + acc_ctrl_queue_size + steer_ctrl_queue_size, Mat.shape[1]) + ) + result[actual_control_index] += A.T @ Mat[:actual_state_dim] + + result[actual_state_dim : actual_state_dim + acc_ctrl_queue_size - mpc_freq] += Mat[ + actual_state_dim + mpc_freq : actual_state_dim + acc_ctrl_queue_size + ] + result[ + actual_state_dim + + acc_ctrl_queue_size : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size + - mpc_freq + ] += Mat[ + actual_state_dim + + acc_ctrl_queue_size + + mpc_freq : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size + ] + for i in range(mpc_freq): + result[actual_state_dim] += Mat[actual_state_dim + i] + result[actual_state_dim + acc_ctrl_queue_size] += Mat[ + actual_state_dim + acc_ctrl_queue_size + i + ] + return result + + +@njit(cache=True, fastmath=True) +def vector_sparse_left_action_for_state_diff( + A: np.ndarray, + vec: np.ndarray, + actual_control_index=actual_control_index, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, + steer_ctrl_queue_size=steer_ctrl_queue_size, +) -> np.ndarray: + """Receives the sparse matrix A₀ and computes A₀.T @ vec. + + The argument A is part of A₀ . + The remaining A₀ components are known a priori. + """ + result = np.zeros(actual_state_dim + acc_ctrl_queue_size + steer_ctrl_queue_size) + result[actual_control_index] += A.T @ vec[:actual_state_dim] + + result[actual_state_dim : actual_state_dim + acc_ctrl_queue_size - mpc_freq] += vec[ + actual_state_dim + mpc_freq : actual_state_dim + acc_ctrl_queue_size + ] + result[ + actual_state_dim + + acc_ctrl_queue_size : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size + - mpc_freq + ] += vec[ + actual_state_dim + + acc_ctrl_queue_size + + mpc_freq : actual_state_dim + + acc_ctrl_queue_size + + steer_ctrl_queue_size + ] + for i in range(mpc_freq): + result[actual_state_dim] += vec[actual_state_dim + i] + result[actual_state_dim + acc_ctrl_queue_size] += vec[ + actual_state_dim + acc_ctrl_queue_size + i + ] + return result + + +@njit(cache=True, fastmath=True) +def sparse_right_action_for_input_diff( + Mat: np.ndarray, + input_dim=input_dim, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, +) -> np.ndarray: + """Compute Mat @ B for some sparse matrix B known a priori.""" + result = np.zeros((Mat.shape[0], input_dim)) + for i in range(mpc_freq): + result[:, 0] += (mpc_freq - i) * ctrl_time_step * Mat[:, actual_state_dim + i] + result[:, 1] += ( + (mpc_freq - i) * ctrl_time_step * Mat[:, actual_state_dim + acc_ctrl_queue_size + i] + ) + return result + + +@njit(cache=True, fastmath=True) +def sparse_left_action_for_input_diff( + Mat: np.ndarray, + input_dim=input_dim, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, +) -> np.ndarray: + """Compute B.T @ Mat for some sparse matrix B known a priori.""" + result = np.zeros((input_dim, Mat.shape[1])) + for i in range(mpc_freq): + result[0] += (mpc_freq - i) * ctrl_time_step * Mat[actual_state_dim + i] + result[1] += ( + (mpc_freq - i) * ctrl_time_step * Mat[actual_state_dim + acc_ctrl_queue_size + i] + ) + return result + + +@njit(cache=True, fastmath=True) +def vector_sparse_left_action_for_input_diff( + vec: np.ndarray, + input_dim=input_dim, + actual_state_dim=actual_state_dim, + acc_ctrl_queue_size=acc_ctrl_queue_size, +) -> np.ndarray: + """Compute B.T @ vec for some sparse matrix B known a priori.""" + result = np.zeros(input_dim) + for i in range(mpc_freq): + result[0] += (mpc_freq - i) * ctrl_time_step * vec[actual_state_dim + i] + result[1] += ( + (mpc_freq - i) * ctrl_time_step * vec[actual_state_dim + acc_ctrl_queue_size + i] + ) + return result + + +@njit(cache=False, fastmath=True) +def compute_iLQR_coef( + traj, + inputs, + A, + B, + Q_total, + R_total, + acc_lim_weights, + acc_lim_center, + steer_lim_weights, + steer_lim_center, + acc_rate_lim_weights, + acc_rate_lim_center, + steer_rate_lim_weights, + steer_rate_lim_center, + N, + nx, + nu, + X_des, + U_des, + Sigma_x=None, + dSigma_x=None, + Sigma_y=None, + dSigma_y=None, + Sigma_v=None, + dSigma_v=None, + Sigma_theta=None, + dSigma_theta=None, + Sigma_acc=None, + dSigma_acc=None, + Sigma_steer=None, + dSigma_steer=None, + index_cost=index_cost, + acc_index=acc_index, + steer_index=steer_index, + actual_control_index=actual_control_index, + actual_state_dim=actual_state_dim, +): + """Perform the main part of iLQR. + + Performs a Riccati recursion and returns the coefficients needed for the final output. + """ + P = np.zeros((N + 1, nx, nx)) + w = np.zeros((N + 1, nx)) + H_inv_G = np.zeros((N, nu, nx)) + H_inv_g = np.zeros((N, nu)) + P[N][:7, :7] = Q_total[-1][:7, :7] + P[N][steer_index, steer_index] = Q_total[-1][7, 7] + + P[N][acc_index, acc_index] += acc_lim_weights[N] + P[N][steer_index, steer_index] += steer_lim_weights[N] + + w[N][index_cost] = Q_total[-1] @ (traj[N] - X_des[N]) + w[N, acc_index] += acc_lim_weights[N] * (traj[N, acc_index] - acc_lim_center[N]) + w[N, steer_index] += steer_lim_weights[N] * (traj[N, acc_index + 1] - steer_lim_center[N]) + + for i in range(N): + j = N - i - 1 + Qj = Q_total[j] + Rj = R_total[j] + Aj = A[j] + Pj1Aj = sparse_right_action_for_state_diff( + P[j + 1], Aj[:actual_state_dim, actual_control_index] + ) + G = sparse_left_action_for_input_diff(Pj1Aj) + + H = sparse_left_action_for_input_diff(sparse_right_action_for_input_diff(P[j + 1])) + Rj + H[0, 0] += acc_rate_lim_weights[j] + H[1, 1] += steer_rate_lim_weights[j] + + g_ = vector_sparse_left_action_for_input_diff(w[j + 1]) + Rj @ (inputs[j] - U_des[j]) + g_[0] += acc_rate_lim_weights[j] * (inputs[j, 0] - acc_rate_lim_center[j]) + g_[1] += steer_rate_lim_weights[j] * (inputs[j, 1] - steer_rate_lim_center[j]) + + one_over_det = 1 / (H[0, 0] * H[1, 1] - H[1, 0] * H[1, 0]) + + H_inv = one_over_det * np.array([[H[1, 1], -H[1, 0]], [-H[1, 0], H[0, 0]]]) + + H_inv_G[j] = H_inv @ G + H_inv_g[j] = H_inv @ g_ + + P[j] = ( + sparse_left_action_for_state_diff(Aj[:actual_state_dim, actual_control_index], Pj1Aj) + - G.T @ H_inv_G[j] + ) + P[j][:7, :7] += Qj[:7, :7] + P[j][steer_index, steer_index] += Qj[7, 7] + + P[j][acc_index, acc_index] += acc_lim_weights[j] + P[j][steer_index, steer_index] += steer_lim_weights[j] + + w[j] = ( + vector_sparse_left_action_for_state_diff( + Aj[:actual_state_dim, actual_control_index], w[j + 1] + ) + - H_inv_G[j].T @ g_ + ) + + w[j, index_cost] += Qj @ (traj[j] - X_des[j]) + w[j, acc_index] += acc_lim_weights[j] * (traj[j, acc_index] - acc_lim_center[j]) + w[j, steer_index] += steer_lim_weights[j] * (traj[j, acc_index + 1] - steer_lim_center[j]) + P_noise = np.zeros((nx, nx)) + w_noise = np.zeros(nx) + if Sigma_x is not None: + sigma_x = Sigma_x[j] + d_sigma_x = dSigma_x[j] + vec_part = P[j][0, 0] * d_sigma_x + P_noise += d_sigma_x.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_x * vec_part + if Sigma_y is not None: + sigma_y = Sigma_y[j] + d_sigma_y = dSigma_y[j] + vec_part = P[j][1, 1] * d_sigma_y + P_noise += d_sigma_y.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_y * vec_part + if Sigma_v is not None: + sigma_v = Sigma_v[j] + d_sigma_v = dSigma_v[j] + vec_part = P[j][2, 2] * d_sigma_v + P_noise += d_sigma_v.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_v * vec_part + if Sigma_theta is not None: + sigma_theta = Sigma_theta[j] + d_sigma_theta = dSigma_theta[j] + vec_part = P[j][3, 3] * d_sigma_theta + P_noise += d_sigma_theta.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_theta * vec_part + if Sigma_acc is not None: + sigma_acc = Sigma_acc[j] + d_sigma_acc = dSigma_acc[j] + vec_part = P[j][4, 4] * d_sigma_acc + P_noise += d_sigma_acc.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_acc * vec_part + if Sigma_steer is not None: + sigma_steer = Sigma_steer[j] + d_sigma_steer = dSigma_steer[j] + vec_part = P[j][5, 5] * d_sigma_steer + P_noise += d_sigma_steer.reshape(-1, 1) @ vec_part.reshape(1, -1) + w_noise += sigma_steer * vec_part + + P[j] += P_noise + w[j] += w_noise + return P, w, H_inv_G, H_inv_g + + +@njit(cache=True, fastmath=True) +def calc_line_search_candidates(A, B, H_inv_g, H_inv_G, inputs, ls): + """Compute the candidate input columns for the line search in the final stage of iLQR.""" + ls_num = ls.shape[0] + nx = A.shape[2] + nu = B.shape[2] + N = A.shape[0] + + Inputs = np.zeros((ls_num, N, nu)) + delta_x_k = np.zeros((ls_num, nx)) + for k in range(N): + delta_u_k = -ls.reshape(-1, 1) @ H_inv_g[k].reshape(1, -1) - delta_x_k @ H_inv_G[k].T + Inputs[:, k, :] = inputs[k] + delta_u_k + delta_x_k = delta_x_k @ A[k].T + delta_u_k @ B[k].T + return Inputs + + +class drive_iLQR: + """Class that runs iLQR to compute optimal input values.""" + + ls_step: float + """ Line search step width """ + + max_iter_ls: int + """ Number of candidates for line search. """ + + max_iter_ilqr: int + """ Maximum number of iLQR iterations """ + + ilqr_tol: float + """ Tolerance to terminate iLQR iterations """ + + use_trained_model_diff: bool + """ Whether to use the derivative of the trained model """ + + def __init__( + self, + ls_step, + max_iter_ls, + max_iter_ilqr, + ilqr_tol, + use_trained_model_diff, + ): + ir(drive_functions) + self.ls_step = ls_step + self.max_iter_ls = max_iter_ls + self.max_iter_ilqr = max_iter_ilqr + self.ilqr_tol = ilqr_tol + self.use_trained_model_diff = use_trained_model_diff + + ls = np.ones(max_iter_ls + 1) + for i in range(max_iter_ls - 1): + ls[i + 1] = ls_step * ls[i] + ls[-1] = 0.0 + self.ls = ls + + def calc_forward_trajectories_with_cost( + self, + x_current: np.ndarray, + Inputs: np.ndarray, + X_des: np.ndarray, + U_des: np.ndarray, + previous_error: np.ndarray, + ) -> tuple[np.ndarray, np.ndarray]: + """Calculate the predicted trajectory and cost. + + Given the current state and the candidate input columns in the line search. + """ + N = Inputs.shape[1] + samples = Inputs.shape[0] + Traj = np.zeros((samples, N + 1, x_current.shape[0])) + Traj[:, 0, :] += x_current + Cost = np.zeros(samples) + + Previous_error = np.tile(previous_error[:6], (samples, 1)) + for k in range(N): + Cost += drive_functions.calc_cost( + X_des[k], + U_des[k], + Traj[:, k, index_cost], + Inputs[:, k, :], + k, + ) + Traj[:, k + 1], Previous_error = self.F_for_candidates( + Traj[:, k], Inputs[:, k], Previous_error, k + ) + Cost += drive_functions.calc_cost( + X_des[N], + U_des[N - 1], + Traj[:, N, index_cost], + Inputs[:, N - 1, :], + N, + ) + return Traj, Cost + + def calc_forward_trajectory_with_diff( + self, x_current: np.ndarray, inputs: np.ndarray, previous_error: np.ndarray + ) -> tuple[np.ndarray, np.ndarray, np.ndarray]: + """Calculate the derivatives (Jacobians) of the predicted trajectory t with diff. + + This also calculates "the function that returns the predicted trajectory from the current state and the input sequence", + given the current state and the input sequence. + """ + N = inputs.shape[0] + nx = x_current.shape[0] + nu = inputs.shape[1] + traj = np.zeros((N + 1, nx)) + traj[0] = x_current + A = np.zeros((N, nx, nx)) + B = np.zeros((N, nx, nu)) + C = np.zeros((N, 6, nx)) + previous_error_ = previous_error.copy() + for k in range(N): + if self.use_trained_model_diff: + traj[k + 1], A[k], B[k], C[k], previous_error_ = self.F_with_diff( + traj[k], inputs[k], previous_error_, k + ) + else: + traj[k + 1], A[k], B[k], previous_error_ = self.F_with_initial_diff( + traj[k], inputs[k], previous_error_, k + ) + if self.use_trained_model_diff: + A[:, :6] += drive_functions.sg_filter_for_trained_model_diff(C) + return traj, A, B + + def compute_optimal_control( + self, + x_current: np.ndarray, + inputs: np.ndarray, + X_des: np.ndarray, + U_des: np.ndarray, + previous_error: np.ndarray, + x_noise: Callable | None, + y_noise: Callable | None, + v_noise: Callable | None, + theta_noise: Callable | None, + acc_noise: Callable | None, + steer_noise: Callable | None, + ) -> tuple[np.ndarray, np.ndarray, np.ndarray, bool]: + """Calculate the optimal predictive trajectory and the input sequence at that time. + + It also determines whether the tolerance has been reached and returns whether the optimization should continue or not. + Performs one iteration of iLQR. + """ + nx = x_current.shape[0] + nu = inputs.shape[1] + N = inputs.shape[0] + self.time_1 = time.time() + traj, A, B = self.calc_forward_trajectory_with_diff(x_current, inputs, previous_error) + ( + Q_total, + R_total, + acc_lim_weights, + acc_lim_center, + steer_lim_weights, + steer_lim_center, + acc_rate_lim_weights, + acc_rate_lim_center, + steer_rate_lim_weights, + steer_rate_lim_center, + ) = drive_functions.transform_Q_R(X_des, U_des, traj, inputs) + self.time_2 = time.time() + if x_noise is None: + Sigma_x = None + dSigma_x = None + else: + Sigma_x, dSigma_x = x_noise(np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:]))) + Sigma_x = drive_functions.sg_filter_for_noise(Sigma_x) + dSigma_x = drive_functions.sg_filter_for_noise(dSigma_x) + if y_noise is None: + Sigma_y = None + dSigma_y = None + else: + Sigma_y, dSigma_y = y_noise(np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:]))) + Sigma_y = drive_functions.sg_filter_for_noise(Sigma_y) + dSigma_y = drive_functions.sg_filter_for_noise(dSigma_y) + if v_noise is None: + Sigma_v = None + dSigma_v = None + else: + Sigma_v, dSigma_v = v_noise(np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:]))) + Sigma_v = drive_functions.sg_filter_for_noise(Sigma_v) + dSigma_v = drive_functions.sg_filter_for_noise(dSigma_v) + if theta_noise is None: + Sigma_theta = None + dSigma_theta = None + else: + Sigma_theta, dSigma_theta = theta_noise( + np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:])) + ) + Sigma_theta = drive_functions.sg_filter_for_noise(Sigma_theta) + dSigma_theta = drive_functions.sg_filter_for_noise(dSigma_theta) + if acc_noise is None: + Sigma_acc = None + dSigma_acc = None + else: + Sigma_acc, dSigma_acc = acc_noise(np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:]))) + Sigma_acc = drive_functions.sg_filter_for_noise(Sigma_acc) + dSigma_acc = drive_functions.sg_filter_for_noise(dSigma_acc) + + if steer_noise is None: + Sigma_steer = None + dSigma_steer = None + else: + Sigma_steer, dSigma_steer = steer_noise( + np.hstack((traj[:-1, [2, 3, 5]], traj[:-1, 6:])) + ) + Sigma_steer = drive_functions.sg_filter_for_noise(Sigma_steer) + dSigma_steer = drive_functions.sg_filter_for_noise(dSigma_steer) + P, w, H_inv_G, H_inv_g = compute_iLQR_coef( + traj[:, index_cost], + inputs, + A, + B, + Q_total, + R_total, + acc_lim_weights, + acc_lim_center, + steer_lim_weights, + steer_lim_center, + acc_rate_lim_weights, + acc_rate_lim_center, + steer_rate_lim_weights, + steer_rate_lim_center, + N, + nx, + nu, + X_des, + U_des, + Sigma_x, + dSigma_x, + Sigma_y, + dSigma_y, + Sigma_v, + dSigma_v, + Sigma_theta, + dSigma_theta, + Sigma_acc, + dSigma_acc, + Sigma_steer, + dSigma_steer, + ) + self.time_3 = time.time() + # start line search + Inputs = calc_line_search_candidates(A, B, H_inv_g, H_inv_G, inputs, self.ls) + self.time_4 = time.time() + Traj, Cost = self.calc_forward_trajectories_with_cost( + x_current, Inputs, X_des, U_des, previous_error + ) + best_index = Cost.argmin() + self.time_5 = time.time() + + if Cost[best_index] < (1 - self.ilqr_tol) * Cost[-1]: + proceed = True + else: + proceed = False + + best_traj = Traj[best_index] + best_inputs = Inputs[best_index] + return best_inputs, best_inputs[0], best_traj, proceed + + def receive_model( + self, F_with_initial_diff: Callable, F_with_diff: Callable, F_for_candidates: Callable + ): + """Receive vehicle model for control.""" + self.F_with_initial_diff = F_with_initial_diff + self.F_with_diff = F_with_diff + self.F_for_candidates = F_for_candidates diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_mppi.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_mppi.py new file mode 100644 index 0000000000000..ca6e6f15f42ef --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/drive_mppi.py @@ -0,0 +1,170 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore numba njit fastmath + +from typing import Callable + +from numba import njit +import numpy as np +from smart_mpc_trajectory_follower.scripts import drive_functions + +index_cost = np.concatenate( + ( + np.arange(drive_functions.nx_0 + 1), + [drive_functions.nx_0 + drive_functions.acc_ctrl_queue_size], + ) +) + + +@njit(cache=False, fastmath=True) +def generate_input_perturbation(N, sample_num, step, Sigma_0, Sigma_1): + """Generate random perturbations of the input in MPPI.""" + change_input_index = np.concatenate((np.arange(N, step=step), np.array([N]))) + acc_perturbation = np.random.normal( + loc=0, scale=Sigma_0, size=(sample_num - 1, change_input_index.shape[0] - 1) + ) + steer_perturbation = np.random.normal( + loc=0, scale=Sigma_1, size=(sample_num - 1, change_input_index.shape[0] - 1) + ) + Input_perturbation = np.zeros((sample_num - 1, N, 2)) + + for i in range(change_input_index.shape[0] - 1): + Input_perturbation[ + :, change_input_index[i] : change_input_index[i + 1], 0 + ] += acc_perturbation[:, np.array([i])] + Input_perturbation[ + :, change_input_index[i] : change_input_index[i + 1], 1 + ] += steer_perturbation[:, np.array([i])] + + return Input_perturbation + + +class drive_mppi: + """Class that runs MPPI to compute optimal input values.""" + + def __init__( + self, + lam, + Sigma, + max_iter_mppi, + sample_num, + mppi_tol, + mppi_step, + ): + self.lam = lam + self.Sigma = Sigma + + self.max_iter_mppi = max_iter_mppi + self.sample_num = sample_num + self.mppi_tol = mppi_tol + self.mppi_step = mppi_step + + def generate_sample_inputs(self, inputs): + """Generate input samples in MPPI.""" + N = inputs.shape[0] + nu = inputs.shape[1] + Inputs = np.zeros((self.sample_num, N, nu)) + + Inputs += inputs + Inputs[1:] += generate_input_perturbation( + N, self.sample_num, self.mppi_step, self.Sigma[0], self.Sigma[1] + ) + return Inputs + + def calc_forward_trajectories_with_cost(self, x_current, Inputs, X_des, U_des, Previous_error): + """Calculate the predicted trajectory and cost. + + Given the current state and the candidate input columns in the line search. + """ + N = Inputs.shape[1] + samples = Inputs.shape[0] + Traj = np.zeros((samples, N + 1, x_current.shape[0])) + Traj[:, 0, :] += x_current + Cost = np.zeros(samples) + for k in range(N): + Cost += drive_functions.calc_cost_only_for_states( + X_des[k], Traj[:, k, index_cost], k + ) + self.lam * (Inputs[:, k, :] - Inputs[0, k, :]) @ ( + (1 / self.Sigma) * (Inputs[0, k, :] - U_des[k]) + ) + Traj[:, k + 1], Previous_error = self.F_for_candidates( + Traj[:, k], Inputs[:, k], Previous_error, k + ) + Cost += drive_functions.calc_cost_only_for_states(X_des[N], Traj[:, N, index_cost], N) + return Traj, Cost + + def proceed_mppi_step(self, x_current, inputs, X_des, U_des, previous_error): + """Proceed with MPPI iteration one time.""" + N = inputs.shape[0] + + previous_error_ = previous_error.reshape(1, -1).copy() + nominal_traj = np.zeros((N + 1, x_current.shape[0])) + nominal_traj[0] = x_current.copy() + for k in range(N): + if k == 0: + Traj_, previous_error_ = self.F_for_candidates( + nominal_traj[k].reshape(1, -1), inputs[k].reshape(1, -1), previous_error_, True + ) + nominal_traj[k + 1] = Traj_[0] + else: + Traj_, previous_error_ = self.F_for_candidates( + nominal_traj[k].reshape(1, -1), inputs[k].reshape(1, -1), previous_error_, False + ) + nominal_traj[k + 1] = Traj_[0] + + Inputs = self.generate_sample_inputs(inputs) + + Previous_error = np.tile(previous_error, (self.sample_num, 1)) + _, Cost = self.calc_forward_trajectories_with_cost( + x_current, Inputs, X_des, U_des, Previous_error + ) + original_cost = Cost[0] + best_cost = Cost.min() + Exps = np.exp(-(Cost - best_cost) / self.lam) + Exps = Exps / Exps.sum() + new_inputs = (Inputs.T @ Exps).T + previous_error_ = previous_error.reshape(1, -1).copy() + new_traj = np.zeros((N + 1, x_current.shape[0])) + new_traj[0] = x_current.copy() + for k in range(N): + if k == 0: + Traj_, previous_error_ = self.F_for_candidates( + new_traj[k].reshape(1, -1), new_inputs[k].reshape(1, -1), previous_error_, True + ) + new_traj[k + 1] = Traj_[0] + else: + Traj_, previous_error_ = self.F_for_candidates( + new_traj[k].reshape(1, -1), new_inputs[k].reshape(1, -1), previous_error_, False + ) + new_traj[k + 1] = Traj_[0] + if np.dot(Exps, Cost) < (1 - self.mppi_tol) * original_cost: + proceed = True + else: + proceed = False + return new_traj, new_inputs, proceed + + def compute_optimal_control(self, x_current, inputs, X_des, U_des, previous_error): + """Calculate the optimal input based on MPPI.""" + for i in range(self.max_iter_mppi): + new_traj, new_inputs, proceed = self.proceed_mppi_step( + x_current, inputs, X_des, U_des, previous_error + ) + if not proceed: + break + return new_inputs, new_inputs[0], new_traj + + def receive_model(self, F_for_candidates: Callable): + """Receive vehicle model for control.""" + self.F_for_candidates = F_for_candidates diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/proxima_calc.cpp b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/proxima_calc.cpp new file mode 100644 index 0000000000000..de65184ec9f8e --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/proxima_calc.cpp @@ -0,0 +1,487 @@ +// Copyright 2024 Proxima Technology Inc, TIER IV +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include + +#include +#include + +#include +namespace py = pybind11; + +double nominal_model_input(Eigen::VectorXd var, double lam, int step) +{ + double nominal_pred = var[0]; + nominal_pred += (var[step] - nominal_pred) * 0.03333 / lam; + nominal_pred += (var[step - 1] - nominal_pred) * 0.03333 / lam; + nominal_pred += (var[step - 2] - nominal_pred) * 0.03333 / lam; + return nominal_pred; +} +Eigen::RowVectorXd Nominal_model_input(Eigen::MatrixXd Var, double lam, int step) +{ + Eigen::RowVectorXd nominal_pred = Var.row(0); + nominal_pred += (Var.row(step) - nominal_pred) * 0.03333 / lam; + nominal_pred += (Var.row(step - 1) - nominal_pred) * 0.03333 / lam; + nominal_pred += (Var.row(step - 2) - nominal_pred) * 0.03333 / lam; + return nominal_pred; +} + +Eigen::VectorXd d_tanh(Eigen::VectorXd v) +{ + Eigen::VectorXd result = 1 / (v.array().cosh() * v.array().cosh()); + return result; +} +Eigen::VectorXd relu(Eigen::VectorXd x) +{ + Eigen::VectorXd x_ = x; + for (int i = 0; i < x.size(); i++) { + if (x[i] < 0) { + x_[i] = 0; + } + } + return x_; +} +Eigen::VectorXd d_relu(Eigen::VectorXd x) +{ + Eigen::VectorXd result = Eigen::VectorXd::Ones(x.size()); + for (int i = 0; i < x.size(); i++) { + if (x[i] < 0) { + result[i] = 0; + } + } + return result; +} + +Eigen::MatrixXd d_relu_product(Eigen::MatrixXd m, Eigen::VectorXd x) +{ + Eigen::MatrixXd result = Eigen::MatrixXd::Zero(m.rows(), m.cols()); + for (int i = 0; i < m.cols(); i++) { + if (x[i] >= 0) { + result.col(i) = m.col(i); + } + } + return result; +} +Eigen::MatrixXd d_tanh_product(Eigen::MatrixXd m, Eigen::VectorXd x) +{ + Eigen::MatrixXd result = Eigen::MatrixXd(m.rows(), m.cols()); + for (int i = 0; i < m.cols(); i++) { + result.col(i) = m.col(i) / (std::cosh(x[i]) * std::cosh(x[i])); + } + return result; +} +Eigen::MatrixXd test_product(Eigen::VectorXd v, Eigen::MatrixXd m) +{ + return v.asDiagonal() * m; +} +Eigen::VectorXd get_polynomial_features(Eigen::VectorXd x, int deg, int dim) +{ + int n_features = x.size(); + Eigen::VectorXd result = Eigen::VectorXd(dim); + result.head(n_features) = x; + if (deg >= 2) { + std::vector index = {}; + for (int feature_idx = 0; feature_idx < n_features + 1; feature_idx++) { + index.push_back(feature_idx); + } + int current_idx = n_features; + for (int i = 0; i < deg - 1; i++) { + std::vector new_index = {}; + int end = index[index.size() - 1]; + for (int feature_idx = 0; feature_idx < n_features; feature_idx++) { + int start = index[feature_idx]; + new_index.push_back(current_idx); + int next_idx = current_idx + end - start; + result.segment(current_idx, end - start) = + x[feature_idx] * result.segment(start, end - start); + current_idx = next_idx; + } + new_index.push_back(current_idx); + index = new_index; + } + } + return result; +} +Eigen::MatrixXd get_polynomial_features_with_diff(Eigen::VectorXd x, int deg, int dim) +{ + int n_features = x.size(); + Eigen::MatrixXd result = Eigen::MatrixXd::Zero(dim, n_features + 1); + result.block(0, 0, n_features, 1) = x; + result.block(0, 1, n_features, n_features) = Eigen::MatrixXd::Identity(n_features, n_features); + if (deg >= 2) { + std::vector index = {}; + for (int feature_idx = 0; feature_idx < n_features + 1; feature_idx++) { + index.push_back(feature_idx); + } + int current_idx = n_features; + for (int i = 0; i < deg - 1; i++) { + std::vector new_index = {}; + int end = index[index.size() - 1]; + for (int feature_idx = 0; feature_idx < n_features; feature_idx++) { + int start = index[feature_idx]; + new_index.push_back(current_idx); + int next_idx = current_idx + end - start; + result.block(current_idx, 0, end - start, n_features + 1) = + x[feature_idx] * result.block(start, 0, end - start, n_features + 1); + result.block(current_idx, feature_idx + 1, end - start, 1) += + result.block(start, 0, end - start, 1); + current_idx = next_idx; + } + new_index.push_back(current_idx); + index = new_index; + } + } + return result; +} +class transform_model_to_eigen +{ +private: + Eigen::MatrixXd weight_0; + Eigen::MatrixXd weight_1; + Eigen::MatrixXd weight_2; + Eigen::MatrixXd weight_3; + Eigen::MatrixXd weight_4; + Eigen::MatrixXd weight_5; + Eigen::MatrixXd weight_6; + Eigen::MatrixXd weight_7; + Eigen::VectorXd bias_0; + Eigen::VectorXd bias_1; + Eigen::VectorXd bias_2; + Eigen::VectorXd bias_3; + Eigen::VectorXd bias_4; + Eigen::VectorXd bias_5; + Eigen::VectorXd bias_6; + Eigen::VectorXd bias_7; + Eigen::MatrixXd A_linear_reg; + Eigen::VectorXd b_linear_reg; + int deg; + double acc_time_constant; + int acc_delay_step; + double steer_time_constant; + int steer_delay_step; + int acc_ctrl_queue_size; + int steer_ctrl_queue_size; + int steer_ctrl_queue_size_core; + double max_acc_error = 20.0; + double max_steer_error = 20.0; + +public: + transform_model_to_eigen() {} + void set_params( + Eigen::MatrixXd weight_0_, Eigen::MatrixXd weight_1_, Eigen::MatrixXd weight_2_, + Eigen::MatrixXd weight_3_, Eigen::MatrixXd weight_4_, Eigen::MatrixXd weight_5_, + Eigen::MatrixXd weight_6_, Eigen::MatrixXd weight_7_, Eigen::VectorXd bias_0_, + Eigen::VectorXd bias_1_, Eigen::VectorXd bias_2_, Eigen::VectorXd bias_3_, + Eigen::VectorXd bias_4_, Eigen::VectorXd bias_5_, Eigen::VectorXd bias_6_, + Eigen::VectorXd bias_7_, Eigen::MatrixXd A_linear_reg_, Eigen::VectorXd b_linear_reg_, int deg_, + double acc_time_constant_, int acc_delay_step_, double steer_time_constant_, + int steer_delay_step_, int acc_ctrl_queue_size_, int steer_ctrl_queue_size_, + int steer_ctrl_queue_size_core_) + { + weight_0 = weight_0_; + weight_1 = weight_1_; + weight_2 = weight_2_; + weight_3 = weight_3_; + weight_4 = weight_4_; + weight_5 = weight_5_; + weight_6 = weight_6_; + weight_7 = weight_7_; + bias_0 = bias_0_; + bias_1 = bias_1_; + bias_2 = bias_2_; + bias_3 = bias_3_; + bias_4 = bias_4_; + bias_5 = bias_5_; + bias_6 = bias_6_; + bias_7 = bias_7_; + A_linear_reg = A_linear_reg_; + b_linear_reg = b_linear_reg_; + deg = deg_; + acc_time_constant = acc_time_constant_; + acc_delay_step = acc_delay_step_; + steer_time_constant = steer_time_constant_; + steer_delay_step = steer_delay_step_; + acc_ctrl_queue_size = acc_ctrl_queue_size_; + steer_ctrl_queue_size = steer_ctrl_queue_size_; + steer_ctrl_queue_size_core = steer_ctrl_queue_size_core_; + } + Eigen::VectorXd error_prediction(Eigen::VectorXd x) + { + Eigen::VectorXd acc_sub(acc_ctrl_queue_size + 1); + acc_sub[0] = x[1]; + acc_sub.tail(acc_ctrl_queue_size) = x.segment(3, acc_ctrl_queue_size); + + Eigen::VectorXd steer_sub(steer_ctrl_queue_size_core + 1); + steer_sub[0] = x[2]; + steer_sub.tail(steer_ctrl_queue_size_core) = + x.segment(3 + acc_ctrl_queue_size, steer_ctrl_queue_size_core); + Eigen::VectorXd acc_layer_1 = relu(weight_0 * acc_sub + bias_0); + + Eigen::VectorXd steer_layer_1(bias_1.size() + bias_2.size()); + steer_layer_1.head(bias_1.size()) = relu(weight_1 * steer_sub + bias_1); + + Eigen::VectorXd steer_input_full = x.segment(3 + acc_ctrl_queue_size, steer_ctrl_queue_size); + steer_layer_1.tail(bias_2.size()) = relu(weight_2 * steer_input_full + bias_2); + + Eigen::VectorXd acc_layer_2 = (weight_3 * acc_layer_1 + bias_3).array().tanh(); + + Eigen::VectorXd steer_layer_2 = (weight_4 * steer_layer_1 + bias_4).array().tanh(); + + Eigen::VectorXd h1(1 + acc_layer_2.size() + steer_layer_2.size()); + h1[0] = x[0]; + h1.segment(1, acc_layer_2.size()) = acc_layer_2; + h1.tail(steer_layer_2.size()) = steer_layer_2; + Eigen::VectorXd h2 = relu(weight_5 * h1 + bias_5); + Eigen::VectorXd h3 = relu(weight_6 * h2 + bias_6); + Eigen::VectorXd h4(h3.size() + acc_layer_2.size() + steer_layer_2.size()); + h4.head(h3.size()) = h3; + h4.segment(h3.size(), acc_layer_2.size()) = acc_layer_2; + h4.tail(steer_layer_2.size()) = steer_layer_2; + Eigen::VectorXd x_for_polynomial_reg(5); + x_for_polynomial_reg.head(3) = x.head(3); + x_for_polynomial_reg[3] = x[3 + acc_delay_step]; + x_for_polynomial_reg[4] = x[3 + acc_ctrl_queue_size + steer_delay_step]; + Eigen::VectorXd y = + weight_7 * h4 + bias_7 + + A_linear_reg * get_polynomial_features(x_for_polynomial_reg, deg, A_linear_reg.cols()) + + b_linear_reg; + y[4] = std::min(std::max(y[4], -max_acc_error), max_acc_error); + y[5] = std::min(std::max(y[5], -max_steer_error), max_steer_error); + return y; + } + Eigen::VectorXd rot_and_d_rot_error_prediction(Eigen::VectorXd x) + { + int x_dim = x.size(); + double theta = x[3]; + double v = x[2]; + double coef = 2.0 * std::abs(v); + coef = coef * coef * coef * coef * coef * coef * coef; + if (coef > 1.0) { + coef = 1.0; + } + /* + In previous implementations, the training model was unreliable in the low speed range + because data in the low speed range was excluded from the training data + in order to exclude data not under control from them. + However, now the topic /system/operation_mode/state is used to identify + whether the data is under control or not. + Therefore, it may be safe to always set coef = 1, and this variable may be eliminated + once it is confirmed safe to do so. + */ + double cos = std::cos(theta); + double sin = std::sin(theta); + Eigen::Matrix2d Rot; + Rot << cos, -sin, sin, cos; + + Eigen::Matrix2d dRot; + dRot << -sin, -cos, cos, -sin; + Eigen::VectorXd vars(x_dim - 3); + vars[0] = x[2]; + vars[1] = x[4]; + vars[2] = x[5]; + vars.tail(x_dim - 6) = x.tail(x_dim - 6); + Eigen::VectorXd pred = error_prediction(vars); + Eigen::VectorXd rot_and_d_rot_pred(8); + rot_and_d_rot_pred.head(2) = Rot * pred.head(2); + rot_and_d_rot_pred.segment(2, 4) = pred.segment(2, 4); + rot_and_d_rot_pred.tail(2) = dRot * pred.head(2); + + return coef * rot_and_d_rot_pred; + } + Eigen::MatrixXd error_prediction_with_diff(Eigen::VectorXd x) + { + Eigen::VectorXd acc_sub(acc_ctrl_queue_size + 1); + acc_sub[0] = x[1]; + acc_sub.tail(acc_ctrl_queue_size) = x.segment(3, acc_ctrl_queue_size); + + Eigen::VectorXd steer_sub(steer_ctrl_queue_size_core + 1); + steer_sub[0] = x[2]; + steer_sub.tail(steer_ctrl_queue_size_core) = + x.segment(3 + acc_ctrl_queue_size, steer_ctrl_queue_size_core); + Eigen::VectorXd steer_input_full = x.segment(3 + acc_ctrl_queue_size, steer_ctrl_queue_size); + + Eigen::VectorXd u_acc_layer_1 = weight_0 * acc_sub + bias_0; + Eigen::VectorXd acc_layer_1 = relu(u_acc_layer_1); + + Eigen::VectorXd u_steer_layer_1(bias_1.size() + bias_2.size()); + u_steer_layer_1.head(bias_1.size()) = weight_1 * steer_sub + bias_1; + u_steer_layer_1.tail(bias_2.size()) = weight_2 * steer_input_full + bias_2; + Eigen::VectorXd steer_layer_1 = relu(u_steer_layer_1); + + Eigen::VectorXd u_acc_layer_2 = weight_3 * acc_layer_1 + bias_3; + Eigen::VectorXd acc_layer_2 = u_acc_layer_2.array().tanh(); + + Eigen::VectorXd u_steer_layer_2 = weight_4 * steer_layer_1 + bias_4; + Eigen::VectorXd steer_layer_2 = u_steer_layer_2.array().tanh(); + + Eigen::VectorXd h1(1 + acc_layer_2.size() + steer_layer_2.size()); + h1[0] = x[0]; + h1.segment(1, acc_layer_2.size()) = acc_layer_2; + h1.tail(steer_layer_2.size()) = steer_layer_2; + Eigen::VectorXd u2 = weight_5 * h1 + bias_5; + Eigen::VectorXd h2 = relu(u2); + Eigen::VectorXd u3 = weight_6 * h2 + bias_6; + Eigen::VectorXd h3 = relu(u3); + Eigen::VectorXd h4(h3.size() + acc_layer_2.size() + steer_layer_2.size()); + h4.head(h3.size()) = h3; + h4.segment(h3.size(), acc_layer_2.size()) = acc_layer_2; + h4.tail(steer_layer_2.size()) = steer_layer_2; + Eigen::VectorXd x_for_polynomial_reg(5); + x_for_polynomial_reg.head(3) = x.head(3); + x_for_polynomial_reg[3] = x[3 + acc_delay_step]; + x_for_polynomial_reg[4] = x[3 + acc_ctrl_queue_size + steer_delay_step]; + Eigen::MatrixXd polynomial_features_with_diff = + get_polynomial_features_with_diff(x_for_polynomial_reg, deg, A_linear_reg.cols()); + + Eigen::VectorXd y = + weight_7 * h4 + bias_7 + + A_linear_reg * polynomial_features_with_diff.block(0, 0, A_linear_reg.cols(), 1) + + b_linear_reg; + y[4] = std::min(std::max(y[4], -max_acc_error), max_acc_error); + y[5] = std::min(std::max(y[5], -max_steer_error), max_steer_error); + // Eigen::MatrixXd dy_dh4 = weight_7; + + Eigen::MatrixXd dy_dh3 = weight_7.block(0, 0, y.size(), h3.size()); + Eigen::MatrixXd dy_dh2 = d_relu_product(dy_dh3, u3) * weight_6; + Eigen::MatrixXd dy_dh1 = d_relu_product(dy_dh2, u2) * weight_5; + + Eigen::MatrixXd dy_da2 = dy_dh1.block(0, 1, y.size(), acc_layer_2.size()) + + weight_7.block(0, h3.size(), y.size(), acc_layer_2.size()); + Eigen::MatrixXd dy_ds2 = + dy_dh1.block(0, 1 + acc_layer_2.size(), y.size(), steer_layer_2.size()) + + weight_7.block(0, h3.size() + acc_layer_2.size(), y.size(), steer_layer_2.size()); + Eigen::MatrixXd dy_da1 = d_tanh_product(dy_da2, u_acc_layer_2) * weight_3; + Eigen::MatrixXd dy_ds1 = d_tanh_product(dy_ds2, u_steer_layer_2) * weight_4; + + Eigen::MatrixXd dy_d_acc = d_relu_product(dy_da1, u_acc_layer_1) * weight_0; + Eigen::MatrixXd dy_d_steer = Eigen::MatrixXd::Zero(y.size(), steer_input_full.size() + 1); + dy_d_steer.block(0, 1, y.size(), steer_input_full.size()) += + d_relu_product( + dy_ds1.block(0, bias_1.size(), y.size(), bias_2.size()), + u_steer_layer_1.tail(bias_2.size())) * + weight_2; + dy_d_steer.block(0, 0, y.size(), steer_sub.size()) += + d_relu_product( + dy_ds1.block(0, 0, y.size(), bias_1.size()), u_steer_layer_1.head(bias_1.size())) * + weight_1; + + Eigen::MatrixXd result = Eigen::MatrixXd::Zero(y.size(), x.size() + 1); + + result.col(0) = y; + + result.col(1) = dy_dh1.col(0); + result.col(2) = dy_d_acc.col(0); + result.col(3) = dy_d_steer.col(0); + result.block(0, 4, y.size(), acc_ctrl_queue_size) = + dy_d_acc.block(0, 1, y.size(), acc_ctrl_queue_size); + result.block(0, 4 + acc_ctrl_queue_size, y.size(), steer_ctrl_queue_size) = + dy_d_steer.block(0, 1, y.size(), steer_ctrl_queue_size); + + Eigen::MatrixXd polynomial_reg_diff = + A_linear_reg * + polynomial_features_with_diff.block(0, 1, A_linear_reg.cols(), x_for_polynomial_reg.size()); + result.block(0, 1, y.size(), 3) += polynomial_reg_diff.block(0, 0, y.size(), 3); + result.block(0, 4 + acc_delay_step, y.size(), 1) += + polynomial_reg_diff.block(0, 3, y.size(), 1); + result.block(0, 4 + acc_ctrl_queue_size + steer_delay_step, y.size(), 1) += + polynomial_reg_diff.block(0, 4, y.size(), 1); + return result; + } + Eigen::MatrixXd rot_and_d_rot_error_prediction_with_diff(Eigen::VectorXd x) + { + int x_dim = x.size(); + double theta = x[3]; + double v = x[2]; + double coef = 2.0 * std::abs(v); + coef = coef * coef * coef * coef * coef * coef * coef; + if (coef > 1.0) { + coef = 1.0; + } + double cos = std::cos(theta); + double sin = std::sin(theta); + Eigen::Matrix2d Rot; + Rot << cos, -sin, sin, cos; + + Eigen::Matrix2d dRot; + dRot << -sin, -cos, cos, -sin; + Eigen::VectorXd vars(x_dim - 3); + vars[0] = x[2]; + vars[1] = x[4]; + vars[2] = x[5]; + vars.tail(x_dim - 6) = x.tail(x_dim - 6); + + Eigen::MatrixXd pred_d_pred = error_prediction_with_diff(vars); + Eigen::VectorXd pred = pred_d_pred.col(0); + Eigen::MatrixXd d_pred = pred_d_pred.block(0, 1, 6, x_dim - 3); + Eigen::MatrixXd rot_and_d_rot_pred_with_diff = Eigen::MatrixXd::Zero(6, x_dim + 2); + Eigen::MatrixXd rot_pred_with_diff(6, x_dim - 3); + rot_pred_with_diff.block(0, 0, 2, x_dim - 3) = Rot * d_pred.block(0, 0, 2, x_dim - 3); + rot_pred_with_diff.block(2, 0, 4, x_dim - 3) = d_pred.block(2, 0, 4, x_dim - 3); + + rot_and_d_rot_pred_with_diff.block(0, 0, 2, 1) = Rot * pred.head(2); + rot_and_d_rot_pred_with_diff.block(2, 0, 4, 1) = pred.segment(2, 4); + rot_and_d_rot_pred_with_diff.block(0, 1, 2, 1) = dRot * pred.head(2); + rot_and_d_rot_pred_with_diff.col(2 + 2) = rot_pred_with_diff.col(0); + rot_and_d_rot_pred_with_diff.col(2 + 4) = rot_pred_with_diff.col(1); + rot_and_d_rot_pred_with_diff.col(2 + 5) = rot_pred_with_diff.col(2); + rot_and_d_rot_pred_with_diff.block(0, 2 + 6, 6, x_dim - 6) = + rot_pred_with_diff.block(0, 3, 6, x_dim - 6); + return coef * rot_and_d_rot_pred_with_diff; + } + Eigen::MatrixXd Rotated_error_prediction(Eigen::MatrixXd X) + { + int X_cols = X.cols(); + int x_dim = X.rows(); + Eigen::MatrixXd Pred(6, X_cols); + for (int i = 0; i < X_cols; i++) { + Eigen::VectorXd x = X.col(i); + double theta = x[3]; + double v = x[2]; + double coef = 2.0 * std::abs(v); + coef = coef * coef * coef * coef * coef * coef * coef; + if (coef > 1.0) { + coef = 1.0; + } + double cos = std::cos(theta); + double sin = std::sin(theta); + Eigen::Matrix2d Rot; + Rot << cos, -sin, sin, cos; + Eigen::VectorXd vars(x_dim - 3); + + vars[0] = x[2]; + + vars[1] = x[4]; + vars[2] = x[5]; + vars.tail(x_dim - 6) = x.tail(x_dim - 6); + Eigen::VectorXd pred = error_prediction(vars); + Pred.block(0, i, 2, 1) = coef * Rot * pred.head(2); + Pred.block(2, i, 4, 1) = coef * pred.tail(4); + } + return Pred; + } +}; + +PYBIND11_MODULE(proxima_calc, m) +{ + py::class_(m, "transform_model_to_eigen") + .def(py::init()) + .def("set_params", &transform_model_to_eigen::set_params) + .def( + "rot_and_d_rot_error_prediction", &transform_model_to_eigen::rot_and_d_rot_error_prediction) + .def("error_prediction_with_diff", &transform_model_to_eigen::error_prediction_with_diff) + .def( + "rot_and_d_rot_error_prediction_with_diff", + &transform_model_to_eigen::rot_and_d_rot_error_prediction_with_diff) + .def("Rotated_error_prediction", &transform_model_to_eigen::Rotated_error_prediction); +} diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/pympc_trajectory_follower.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/pympc_trajectory_follower.py new file mode 100755 index 0000000000000..409b6bf594c9e --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/scripts/pympc_trajectory_follower.py @@ -0,0 +1,859 @@ +#!/usr/bin/env python3 + +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore interp + +import time + +from autoware_adapi_v1_msgs.msg import OperationModeState +from autoware_auto_control_msgs.msg import AckermannControlCommand +from autoware_auto_planning_msgs.msg import Trajectory +from autoware_auto_planning_msgs.msg import TrajectoryPoint +from autoware_auto_vehicle_msgs.msg import SteeringReport +from builtin_interfaces.msg import Duration +from geometry_msgs.msg import AccelWithCovarianceStamped +from geometry_msgs.msg import PoseStamped +from nav_msgs.msg import Odometry +import numpy as np +import rclpy +from rclpy.node import Node +import scipy +import scipy.interpolate +from scipy.spatial.transform import Rotation as R +from scipy.spatial.transform import Slerp +from smart_mpc_trajectory_follower.scripts import drive_controller +from smart_mpc_trajectory_follower.scripts import drive_functions +from std_msgs.msg import String +from tier4_debug_msgs.msg import BoolStamped +from tier4_debug_msgs.msg import Float32MultiArrayStamped +from tier4_debug_msgs.msg import Float32Stamped + + +def getYaw(orientation_xyzw): + return R.from_quat(orientation_xyzw.reshape(-1, 4)).as_euler("xyz")[:, 2] + + +class PyMPCTrajectoryFollower(Node): + def __init__(self): + # MPC logic + self.controller = drive_controller.drive_controller( + model_file_name=(drive_functions.load_dir + "/model_for_test_drive.pth"), + ) + + # ROS 2 + super().__init__("pympc_trajectory_follower") + self.sub_trajectory_ = self.create_subscription( + Trajectory, + "/planning/scenario_planning/trajectory", + self.onTrajectory, + 1, + ) + self.sub_trajectory_ # prevent unused variable warning + + self.sub_odometry_ = self.create_subscription( + Odometry, + "/localization/kinematic_state", + self.onOdometry, + 1, + ) + self.sub_odometry_ + + self.sub_accel_ = self.create_subscription( + AccelWithCovarianceStamped, + "/localization/acceleration", + self.onAccel, + 1, + ) + self.sub_accel_ + + self.sub_steering_ = self.create_subscription( + SteeringReport, + "/vehicle/status/steering_status", + self.onSteering, + 1, + ) + self.sub_steering_ + + self.sub_operation_mode_ = self.create_subscription( + OperationModeState, + "/system/operation_mode/state", + self.onOperationMode, + 1, + ) + self.sub_operation_mode_ + + self.sub_stop_mode_reset_request_ = self.create_subscription( + String, + "/pympc_stop_mode_reset_request", + self.onStopModeResetRequest, + 1, + ) + self.sub_stop_mode_reset_request_ + + self.sub_goal_pose_ = self.create_subscription( + PoseStamped, + "/planning/mission_planning/echo_back_goal_pose", + self.onGoalPose, + 1, + ) + self.sub_goal_pose_ + + self.sub_step_response_trigger_ = self.create_subscription( + String, + "/pympc_step_response_trigger", + self.onStepResponseTrigger, + 1, + ) + self.sub_step_response_trigger_ + + self.sub_reload_mpc_param_trigger_ = self.create_subscription( + String, + "/pympc_reload_mpc_param_trigger", + self.onReloadMpcParamTrigger, + 1, + ) + self.sub_reload_mpc_param_trigger_ + + self.sub_control_command_control_cmd_ = self.create_subscription( + AckermannControlCommand, + "/control/command/control_cmd", + self.onControlCommandControlCmd, + 3, + ) + self.sub_control_command_control_cmd_ + + self.control_cmd_pub_ = self.create_publisher( + AckermannControlCommand, + "/control/trajectory_follower/control_cmd", + 1, + ) + + self.predicted_trajectory_pub_ = self.create_publisher( + Trajectory, + "/control/trajectory_follower/lateral/predicted_trajectory", + 1, + ) + + self.timer_period_callback = 0.03 # 30ms + + self.timer = self.create_timer(self.timer_period_callback, self.timer_callback) + + self.debug_mpc_x_current_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_x_current", + 1, + ) + self.debug_mpc_x_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_x_des", + 1, + ) + self.debug_mpc_y_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_y_des", + 1, + ) + self.debug_mpc_v_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_v_des", + 1, + ) + self.debug_mpc_yaw_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_yaw_des", + 1, + ) + self.debug_mpc_acc_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_acc_des", + 1, + ) + self.debug_mpc_steer_des_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_steer_des", + 1, + ) + + self.debug_mpc_X_des_converted_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_X_des_converted", + 1, + ) + + self.debug_mpc_nominal_traj_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_nominal_traj", + 1, + ) + + self.debug_mpc_nominal_inputs_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_nominal_inputs", + 1, + ) + + self.debug_mpc_X_input_list_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_X_input_list", + 1, + ) + + self.debug_mpc_Y_output_list_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_Y_output_list", + 1, + ) + + self.debug_mpc_error_prediction_pub_ = self.create_publisher( + Float32MultiArrayStamped, + "/debug_mpc_error_prediction", + 1, + ) + + self.debug_mpc_emergency_stop_mode_pub_ = self.create_publisher( + BoolStamped, + "/debug_mpc_emergency_stop_mode", + 1, + ) + + self.debug_mpc_goal_stop_mode_pub_ = self.create_publisher( + BoolStamped, + "/debug_mpc_goal_stop_mode", + 1, + ) + + self.debug_mpc_max_trajectory_err_pub_ = self.create_publisher( + Float32Stamped, + "/debug_mpc_max_trajectory_err", + 1, + ) + + self.debug_mpc_calc_u_opt_time_pub_ = self.create_publisher( + Float32Stamped, + "/debug_mpc_calc_u_opt_time", + 1, + ) + + self.debug_mpc_total_ctrl_time_pub_ = self.create_publisher( + Float32Stamped, + "/debug_mpc_total_ctrl_time", + 1, + ) + + self._present_trajectory = None + self._present_kinematic_state = None + self._present_acceleration = None + self._present_steering_status = None + self._present_operation_mode = None + self._goal_pose = None + self.control_cmd_time_stamp_list = [] + self.control_cmd_steer_list = [] + self.control_cmd_acc_list = [] + + self.emergency_stop_mode_flag = False + self.stop_mode_reset_request = False + self.step_response_flag = False + self.step_response_trigger = False + self.step_response_time_step = 0 + self.last_acc_cmd = 0.0 + self.last_steer_cmd = 0.0 + self.past_control_trajectory_mode = 1 + + def onTrajectory(self, msg): + self._present_trajectory = msg + + def onOdometry(self, msg): + self._present_kinematic_state = msg + + def onAccel(self, msg): + self._present_acceleration = msg + + def onSteering(self, msg): + self._present_steering_status = msg + + def onOperationMode(self, msg): + self._present_operation_mode = msg + + def onStopModeResetRequest(self, msg): + self.stop_mode_reset_request = True + self.step_response_flag = False + self.get_logger().info("receive stop mode reset request") + + def onGoalPose(self, msg): + self._goal_pose = msg + + def onStepResponseTrigger(self, msg): + self.step_response_trigger = True + self.get_logger().info("receive step response trigger") + + def onReloadMpcParamTrigger(self, msg): + self.get_logger().info("receive reload mpc param trigger") + + # Re-starting the controller + # Reloading parameters etc. internally. + self.controller = drive_controller.drive_controller( + model_file_name=(drive_functions.load_dir + "/model_for_test_drive.pth"), + ) + + def onControlCommandControlCmd(self, msg): + present_cmd_msg = msg + if self.past_control_trajectory_mode == 0: + self.control_cmd_time_stamp_list.append( + present_cmd_msg.stamp.sec + 1e-9 * present_cmd_msg.stamp.nanosec + ) + self.control_cmd_steer_list.append(present_cmd_msg.lateral.steering_tire_angle) + self.control_cmd_acc_list.append(present_cmd_msg.longitudinal.acceleration) + if self.control_cmd_time_stamp_list[-1] - self.control_cmd_time_stamp_list[0] > 3.0: + self.control_cmd_time_stamp_list.pop(0) + self.control_cmd_steer_list.pop(0) + self.control_cmd_acc_list.pop(0) + + def timer_callback(self): + if (self._present_trajectory is not None) and (self._present_kinematic_state is not None): + self.control() + + def control(self): + start_ctrl_time = time.time() + + # [1] Processing of information received from topics. + trajectory_position = [] + trajectory_orientation = [] + trajectory_longitudinal_velocity = [] + trajectory_lateral_velocity = [] + trajectory_acceleration = [] + trajectory_heading_rate = [] + points = self._present_trajectory.points + for i in range(len(points)): + trajectory_position.append( + [points[i].pose.position.x, points[i].pose.position.y, points[i].pose.position.z] + ) + trajectory_orientation.append( + [ + points[i].pose.orientation.x, + points[i].pose.orientation.y, + points[i].pose.orientation.z, + points[i].pose.orientation.w, + ] + ) + trajectory_longitudinal_velocity.append(points[i].longitudinal_velocity_mps) + trajectory_lateral_velocity.append(points[i].lateral_velocity_mps) + trajectory_acceleration.append(points[i].acceleration_mps2) + trajectory_heading_rate.append(points[i].heading_rate_rps) + trajectory_position = np.array(trajectory_position) + trajectory_orientation = np.array(trajectory_orientation) + trajectory_longitudinal_velocity = np.array(trajectory_longitudinal_velocity) + trajectory_lateral_velocity = np.array(trajectory_lateral_velocity) + trajectory_acceleration = np.array(trajectory_acceleration) + trajectory_heading_rate = np.array(trajectory_heading_rate) + + present_position = np.array( + [ + self._present_kinematic_state.pose.pose.position.x, + self._present_kinematic_state.pose.pose.position.y, + self._present_kinematic_state.pose.pose.position.z, + ] + ) + present_orientation = np.array( + [ + self._present_kinematic_state.pose.pose.orientation.x, + self._present_kinematic_state.pose.pose.orientation.y, + self._present_kinematic_state.pose.pose.orientation.z, + self._present_kinematic_state.pose.pose.orientation.w, + ] + ) + present_linear_velocity = np.array( + [ + self._present_kinematic_state.twist.twist.linear.x, + self._present_kinematic_state.twist.twist.linear.y, + self._present_kinematic_state.twist.twist.linear.z, + ] + ) + present_linear_acceleration = np.array( + [ + self._present_acceleration.accel.accel.linear.x, + self._present_acceleration.accel.accel.linear.y, + self._present_acceleration.accel.accel.linear.z, + ] + ) + + present_steering_tire_angle = np.array([self._present_steering_status.steering_tire_angle])[ + 0 + ] + + nearestIndex = ((trajectory_position - present_position) ** 2).sum(axis=1).argmin() + + is_applying_control = False + if self._present_operation_mode is not None: + if ( + self._present_operation_mode.mode == 2 + and self._present_operation_mode.is_autoware_control_enabled + ): + is_applying_control = True + + # [2] deviation check + position_deviation = np.sqrt( + ((trajectory_position[nearestIndex] - present_position) ** 2).sum() + ) + orientation_deviation = getYaw(present_orientation) - getYaw( + trajectory_orientation[nearestIndex] + ) + while True: + if orientation_deviation > np.pi: + orientation_deviation -= 2.0 * np.pi + if orientation_deviation < (-np.pi): + orientation_deviation += 2.0 * np.pi + if np.abs(orientation_deviation) < np.pi: + break + position_deviation_threshold = 2.0 + orientation_deviation_threshold = 60 * np.pi / 180.0 + + # The moment the threshold is exceeded, it enters emergency stop mode. + if is_applying_control: + if ( + position_deviation > position_deviation_threshold + or orientation_deviation > orientation_deviation_threshold + ): + self.emergency_stop_mode_flag = True + + # Normal return from emergency stop mode when within the threshold value and a request to cancel the stop mode has been received. + if ( + not ( + position_deviation > position_deviation_threshold + or orientation_deviation > orientation_deviation_threshold + ) + and self.stop_mode_reset_request + ): + self.emergency_stop_mode_flag = False + + # Processes to ensure that requests do not continue to remain after the stop mode is cancelled. + if not self.emergency_stop_mode_flag: + self.stop_mode_reset_request = False + + # [3] Control logic calculation + # [3-1] pure pursuit + # [3-1-1] compute pure pursuit acc cmd + longitudinal_vel_err = ( + present_linear_velocity - trajectory_longitudinal_velocity[nearestIndex] + ) + acc_kp = 0.5 + acc_lim = 2.0 + pure_pursuit_acc_cmd = np.clip(-acc_kp * longitudinal_vel_err, -acc_lim, acc_lim)[0] + + # [3-1-2] compute pure pursuit steer cmd + nearest_trajectory_point_yaw = getYaw(trajectory_orientation[nearestIndex]) + cos_yaw = np.cos(nearest_trajectory_point_yaw) + sin_yaw = np.sin(nearest_trajectory_point_yaw) + diff_position = present_position - trajectory_position[nearestIndex] + lat_err = -sin_yaw * diff_position[0] + cos_yaw * diff_position[1] + yaw_err = getYaw(present_orientation) - nearest_trajectory_point_yaw + while True: + if yaw_err > np.pi: + yaw_err -= 2.0 * np.pi + if yaw_err < (-np.pi): + yaw_err += 2.0 * np.pi + if np.abs(yaw_err) < np.pi: + break + wheel_base = drive_functions.L # 4.0 + lookahead_time = 3.0 + min_lookahead = 3.0 + lookahead = min_lookahead + lookahead_time * np.abs(present_linear_velocity[0]) + steer_kp = 2.0 * wheel_base / (lookahead * lookahead) + steer_kd = 2.0 * wheel_base / lookahead + steer_lim = 0.6 + pure_pursuit_steer_cmd = np.clip( + -steer_kp * lat_err - steer_kd * yaw_err, -steer_lim, steer_lim + )[0] + + # [3-2] MPC control logic calculation + # [3-2-1] State variables in the MPC + present_mpc_x = np.array( + [ + present_position[0], + present_position[1], + present_linear_velocity[0], + getYaw(present_orientation)[0], + present_linear_acceleration[0], + present_steering_tire_angle, + ] + ) + + # [3-2-2] resampling trajectory by time (except steer angle). + X_des = np.zeros((drive_functions.N + 1, 8)) + dist = np.sqrt(((trajectory_position[1:] - trajectory_position[:-1]) ** 2).sum(axis=1)) + timestamp_from_start = [0.0] + tmp_t = 0.0 + for i in range(len(dist)): + tmp_t += dist[i] / max(np.abs(trajectory_longitudinal_velocity[i]), 0.1) + timestamp_from_start.append(1 * tmp_t) + timestamp_from_start = np.array(timestamp_from_start) + + mpc_trajectory_time_step = 0.1 + timestamp_mpc = ( + np.arange(drive_functions.N + 1) * mpc_trajectory_time_step + + timestamp_from_start[nearestIndex] + ) + for i in range(drive_functions.N + 1): + if timestamp_mpc[drive_functions.N - i] > timestamp_from_start[-1]: + timestamp_mpc[drive_functions.N - i] = timestamp_from_start[-1] + else: + break + pos_x_interpolate = scipy.interpolate.interp1d( + timestamp_from_start, trajectory_position[:, 0] + ) + pos_y_interpolate = scipy.interpolate.interp1d( + timestamp_from_start, trajectory_position[:, 1] + ) + longitudinal_velocity_interpolate = scipy.interpolate.interp1d( + timestamp_from_start, trajectory_longitudinal_velocity + ) + key_rots = R.from_quat(trajectory_orientation.reshape(-1, 4)) + orientation_interpolate = Slerp(timestamp_from_start, key_rots) + acceleration_interpolate = scipy.interpolate.interp1d( + timestamp_from_start, trajectory_acceleration + ) + + X_des[:, 0] = pos_x_interpolate(timestamp_mpc) + X_des[:, 1] = pos_y_interpolate(timestamp_mpc) + X_des[:, 2] = longitudinal_velocity_interpolate(timestamp_mpc) + X_des[:, 3] = orientation_interpolate(timestamp_mpc).as_euler("xyz")[:, 2] + X_des[:, 4] = acceleration_interpolate(timestamp_mpc) + X_des[:, 6] = 1 * X_des[:, 4] + + # [3-2-3] resampling trajectory by time (steer angle) + previous_des_steer = 0.0 + steer_trajectory2 = np.zeros(len(timestamp_mpc)) + downsampling = 5 + for ii in range(2 + (int(len(timestamp_mpc) // downsampling))): + i = ii * downsampling + if i >= len(timestamp_mpc): + i = len(timestamp_mpc) - 1 + if (i % downsampling) == 0: + continue + + tmp_des_pos = 1 * X_des[i, :2] + distance_squared = ((trajectory_position[:, :2] - tmp_des_pos[:2]) ** 2).sum(axis=1) + tmp_nearest_index = distance_squared.argmin() + curvature_calculation_distance = 3.0 + nearestIndex_in_front = ( + np.abs( + distance_squared[tmp_nearest_index:] + - curvature_calculation_distance * curvature_calculation_distance + ) + ).argmin() + tmp_nearest_index + distance_in_front = np.sqrt(distance_squared[nearestIndex_in_front]) + if distance_in_front < curvature_calculation_distance: + curvature_calculation_distance = distance_in_front + if tmp_nearest_index > 0: + nearestIndex_behind = ( + np.abs( + distance_squared[:tmp_nearest_index] + - curvature_calculation_distance * curvature_calculation_distance + ) + ).argmin() + curvature_calculation_distance_threshold = 0.5 + if distance_in_front < curvature_calculation_distance_threshold: + # If there is no point in front, fill in with the value before it. + tmp_des_steer = 1 * previous_des_steer + else: + # Normal line passing through a point 3 m behind.：b1*x + b2*y + b3 = 0 + b1 = tmp_des_pos[0] - trajectory_position[nearestIndex_behind][0] + b2 = tmp_des_pos[1] - trajectory_position[nearestIndex_behind][1] + b3 = ( + -b1 * trajectory_position[nearestIndex_behind][0] + - b2 * trajectory_position[nearestIndex_behind][1] + ) + # Normal line through a point 3 m in front：f1*x + f2*y + f3 = 0 + f1 = tmp_des_pos[0] - trajectory_position[nearestIndex_in_front][0] + f2 = tmp_des_pos[1] - trajectory_position[nearestIndex_in_front][1] + f3 = ( + -f1 * trajectory_position[nearestIndex_in_front][0] + - f2 * trajectory_position[nearestIndex_in_front][1] + ) + det = b1 * f2 - b2 * f1 + if np.abs(det) < 1e-6: + # The two normals have the same slope, so steer is 0 + tmp_des_steer = 0.0 + else: + # solve Ax+b=0 + invA = np.array([[f2, -b2], [-f1, b1]]) / det + sol = -invA @ np.array([b3, f3]) # center of the circle + curvature = np.sqrt( + ((sol - trajectory_position[nearestIndex_behind][:2]) ** 2).sum() + ) + tmp_des_steer = np.arctan(drive_functions.L / curvature) + + tmp_vec_behind = sol - trajectory_position[nearestIndex_behind][:2] + # Line segment connecting backward point - centre of circle + cross_product = b1 * tmp_vec_behind[1] - b2 * tmp_vec_behind[0] + if cross_product < 0.0: + tmp_des_steer = -tmp_des_steer + + steer_trajectory2[i] = 1.0 * tmp_des_steer + previous_des_steer = 1.0 * tmp_des_steer + else: + steer_trajectory2[i] = 0.0 + previous_des_steer = 0.0 + + for i in range(len(timestamp_mpc) - 1): + reminder = i % downsampling + i0 = i - reminder + i1 = i0 + downsampling + if reminder == 0: + continue + if i1 >= len(timestamp_mpc): + i1 = len(timestamp_mpc) - 1 + w = (1.0 * reminder) / (i1 - i0) + steer_trajectory2[i] = (1 - w) * steer_trajectory2[i0] + w * steer_trajectory2[i1] + + X_des[:, 5] = steer_trajectory2 + X_des[:, 7] = 1 * X_des[:, 5] + + # [3-2-4] mpc computation + U_des = np.zeros((drive_functions.N, 2)) + start_calc_u_opt = time.time() + u_opt = self.controller.update_input_queue_and_get_optimal_control( + self.control_cmd_time_stamp_list, + self.control_cmd_acc_list, + self.control_cmd_steer_list, + present_mpc_x, + X_des, + U_des, + ) + end_calc_u_opt = time.time() + mpc_acc_cmd = u_opt[0] + mpc_steer_cmd = u_opt[1] + + # [3-3] Enter goal stop mode (override command value) to maintain stop at goal + self.goal_stop_mode_flag = False + if self._goal_pose is not None: + goal_position = np.array( + [ + self._goal_pose.pose.position.x, + self._goal_pose.pose.position.y, + self._goal_pose.pose.position.z, + ] + ) + + distance_from_goal = np.sqrt(((goal_position[:2] - present_position[:2]) ** 2).sum()) + goal_distance_threshold = 0.8 + if distance_from_goal < goal_distance_threshold: + self.goal_stop_mode_flag = True + + # [3-4] Override when doing step response + if self.step_response_trigger: + self.step_response_time_step = 0 + self.step_response_flag = True + self.step_response_trigger = False + + if self.step_response_flag: + step_response_elapsed_time = self.step_response_time_step * self.timer_period_callback + mpc_acc_cmd = 1.0 * self.last_acc_cmd + if step_response_elapsed_time < 3.0: + mpc_steer_cmd = 0.0 + else: + mpc_steer_cmd = -0.005 + self.get_logger().info( + "step_response_elapsed_time: " + + str(step_response_elapsed_time) + + ", mpc_steer_cmd: " + + str(mpc_steer_cmd) + ) + self.step_response_time_step += 1 + + # [3-5] Determine the control logic to be finally applied and publish it + acc_cmd = 0.0 + steer_cmd = 0.0 + if (not self.emergency_stop_mode_flag) and (not self.goal_stop_mode_flag): + # in normal mode + acc_cmd = mpc_acc_cmd + steer_cmd = mpc_steer_cmd + + overwrite_cmd_by_pure_pursuit_flag = False + if overwrite_cmd_by_pure_pursuit_flag: + steer_cmd = pure_pursuit_steer_cmd + acc_cmd = pure_pursuit_acc_cmd + else: + # in stop mode + acc_cmd_decrease_limit = 5.0 * self.timer_period_callback # lon_jerk_lim + steer_cmd_decrease_limit = 0.5 * self.timer_period_callback # steer_rate_lim + acc_cmd = max( + self.last_acc_cmd - acc_cmd_decrease_limit, -drive_functions.acc_lim_points[0] + ) # lon_acc_lim + if self.last_steer_cmd > (steer_cmd_decrease_limit + 1e-6): + steer_cmd = self.last_steer_cmd - steer_cmd_decrease_limit + elif self.last_steer_cmd < -(steer_cmd_decrease_limit + 1e-6): + steer_cmd = self.last_steer_cmd + steer_cmd_decrease_limit + else: + steer_cmd = 0.0 + + cmd_msg = AckermannControlCommand() + cmd_msg.stamp = cmd_msg.lateral.stamp = cmd_msg.longitudinal.stamp = ( + self.get_clock().now().to_msg() + ) + cmd_msg.longitudinal.speed = trajectory_longitudinal_velocity[nearestIndex] + cmd_msg.longitudinal.acceleration = acc_cmd + cmd_msg.lateral.steering_tire_angle = steer_cmd + + self.control_cmd_pub_.publish(cmd_msg) + self.last_acc_cmd = 1 * acc_cmd + self.last_steer_cmd = 1 * steer_cmd + + if self.past_control_trajectory_mode == 1: + self.control_cmd_time_stamp_list.append( + cmd_msg.stamp.sec + 1e-9 * cmd_msg.stamp.nanosec + ) + self.control_cmd_steer_list.append(steer_cmd) + self.control_cmd_acc_list.append(acc_cmd) + if self.control_cmd_time_stamp_list[-1] - self.control_cmd_time_stamp_list[0] > 3.0: + self.control_cmd_time_stamp_list.pop(0) + self.control_cmd_steer_list.pop(0) + self.control_cmd_acc_list.pop(0) + + # [4] Update MPC internal variables + if not is_applying_control: + self.controller.send_initialize_input_queue() + self.controller.stop_model_update() + self.control_cmd_time_stamp_list.clear() + self.control_cmd_steer_list.clear() + self.control_cmd_acc_list.clear() + + # [5] MPC prediction trajectory publish + traj_msg = Trajectory() + traj_msg.header.stamp = cmd_msg.stamp + traj_msg.header.frame_id = "map" + downsampling = 3 + for ii in range(int(self.controller.nominal_traj.shape[0] // downsampling)): + i = ii * downsampling + traj_msg.points += [TrajectoryPoint()] + int_sec = int(i * mpc_trajectory_time_step) + traj_msg.points[ii].time_from_start = Duration() + traj_msg.points[ii].time_from_start.sec = int_sec + traj_msg.points[ii].time_from_start.nanosec = int( + (i * mpc_trajectory_time_step - int_sec) * 1e9 + ) + traj_msg.points[ii].pose.position.x = self.controller.nominal_traj[i, 0] + traj_msg.points[ii].pose.position.y = self.controller.nominal_traj[i, 1] + traj_msg.points[ii].pose.position.z = present_position[2] + tmp_orientation_xyzw = R.from_euler("z", self.controller.nominal_traj[i, 3]).as_quat() + traj_msg.points[ii].pose.orientation.x = tmp_orientation_xyzw[0] + traj_msg.points[ii].pose.orientation.y = tmp_orientation_xyzw[1] + traj_msg.points[ii].pose.orientation.z = tmp_orientation_xyzw[2] + traj_msg.points[ii].pose.orientation.w = tmp_orientation_xyzw[3] + traj_msg.points[ii].longitudinal_velocity_mps = self.controller.nominal_traj[i, 2] + traj_msg.points[ii].acceleration_mps2 = self.controller.nominal_traj[i, 4] + + self.predicted_trajectory_pub_.publish(traj_msg) + + # [-1] Publish internal information for debugging + enable_debug_pub = True + if enable_debug_pub: + self.debug_mpc_emergency_stop_mode_pub_.publish( + BoolStamped(stamp=cmd_msg.stamp, data=self.emergency_stop_mode_flag) + ) + self.debug_mpc_goal_stop_mode_pub_.publish( + BoolStamped(stamp=cmd_msg.stamp, data=self.goal_stop_mode_flag) + ) + self.debug_mpc_x_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 0]) + ) + self.debug_mpc_y_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 1]) + ) + self.debug_mpc_v_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 2]) + ) + self.debug_mpc_yaw_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 3]) + ) + self.debug_mpc_acc_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 4]) + ) + self.debug_mpc_steer_des_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=X_des[:, 5]) + ) + self.debug_mpc_x_current_pub_.publish( + Float32MultiArrayStamped(stamp=cmd_msg.stamp, data=present_mpc_x.tolist()) + ) + self.debug_mpc_X_des_converted_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, data=self.controller.X_des.flatten().tolist() + ) + ) + self.debug_mpc_nominal_traj_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, data=self.controller.nominal_traj.flatten().tolist() + ) + ) + self.debug_mpc_nominal_inputs_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, data=self.controller.nominal_inputs.flatten().tolist() + ) + ) + self.debug_mpc_X_input_list_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, + data=np.array(self.controller.X_input_list[-1:]).flatten().tolist(), + ) + ) + self.debug_mpc_Y_output_list_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, + data=np.array(self.controller.Y_output_list[-1:]).flatten().tolist(), + ) + ) + self.debug_mpc_max_trajectory_err_pub_.publish( + Float32Stamped( + stamp=cmd_msg.stamp, + data=self.controller.err, + ) + ) + if self.controller.use_trained_model: + self.debug_mpc_error_prediction_pub_.publish( + Float32MultiArrayStamped( + stamp=cmd_msg.stamp, data=self.controller.previous_error[:6] + ) + ) + + end_ctrl_time = time.time() + + self.debug_mpc_calc_u_opt_time_pub_.publish( + Float32Stamped( + stamp=cmd_msg.stamp, + data=(end_calc_u_opt - start_calc_u_opt), + ) + ) + + self.debug_mpc_total_ctrl_time_pub_.publish( + Float32Stamped( + stamp=cmd_msg.stamp, + data=(end_ctrl_time - start_ctrl_time), + ) + ) + + +def main(args=None): + rclpy.init(args=args) + + pympc_trajectory_follower = PyMPCTrajectoryFollower() + + rclpy.spin(pympc_trajectory_follower) + + pympc_trajectory_follower.destroy_node() + rclpy.shutdown() + + +if __name__ == "__main__": + main() diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/.gitignore b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/.gitignore new file mode 100644 index 0000000000000..749ccdafd4f66 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/.gitignore @@ -0,0 +1,4 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/__init__.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/add_training_data_from_csv.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/add_training_data_from_csv.py new file mode 100644 index 0000000000000..3f6ef7a9f78d1 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/add_training_data_from_csv.py @@ -0,0 +1,293 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore ndimage usecols ndim interp savez + + +"""Class for preprocessing CSV data to obtain training data for training.""" + +import csv +import glob +import json +import os +from pathlib import Path + +import numpy as np +import scipy.interpolate +from scipy.ndimage import gaussian_filter +from scipy.spatial.transform import Rotation +from smart_mpc_trajectory_follower.scripts import drive_functions + + +def data_smoothing(data: np.ndarray, sigma: float) -> np.ndarray: + """Apply a Gaussian filter to the data.""" + data_ = gaussian_filter(data, sigma) + return data_ + + +def yaw_transform(raw_yaw: np.ndarray) -> np.ndarray: + """Adjust and transform within a period of 2π so that the yaw angle is continuous.""" + transformed_yaw = np.zeros(raw_yaw.shape) + transformed_yaw[0] = raw_yaw[0] + for i in range(raw_yaw.shape[0] - 1): + rotate_num = (raw_yaw[i + 1] - transformed_yaw[i]) // (2 * np.pi) + if raw_yaw[i + 1] - transformed_yaw[i] - 2 * rotate_num * np.pi < np.pi: + transformed_yaw[i + 1] = raw_yaw[i + 1] - 2 * rotate_num * np.pi + else: + transformed_yaw[i + 1] = raw_yaw[i + 1] - 2 * (rotate_num + 1) * np.pi + return transformed_yaw + + +class add_data_from_csv: + """Class for loading csv files containing driving data, converting them into teacher data for the NN training, and storing them in lists.""" + + X_input_list: list[np.ndarray] + """Input side of NN teacher data""" + + Y_output_list: list[np.ndarray] + """Output side of NN teacher data""" + + def __init__(self): + self.X_input_list = [] + self.Y_output_list = [] + + def clear_data(self): + """Clear the teacher data for the training.""" + self.X_input_list.clear() + self.Y_output_list.clear() + + def transform_rosbag_to_csv(self, dir_name: str, delete_csv_first: bool = True) -> None: + """Convert rosbag file to CSV format.""" + package_path_json = str(Path(__file__).parent.parent) + "/package_path.json" + with open(package_path_json, "r") as file: + package_path = json.load(file) + dir_exe = os.getcwd() + os.system( + "cp " + + package_path["path"] + + "/smart_mpc_trajectory_follower/training_and_data_check/rosbag2.bash " + + dir_name + ) + os.chdir(dir_name) + if len(glob.glob("*.csv")) > 0 and delete_csv_first: + os.system("rm *.csv") + os.system("bash rosbag2.bash") + os.chdir(dir_exe) + + def add_data_from_csv(self, dir_name: str) -> None: + """Adding teacher data for training from a CSV file.""" + acc_ctrl_queue_size = drive_functions.acc_ctrl_queue_size + steer_ctrl_queue_size = drive_functions.steer_ctrl_queue_size + ctrl_time_step = drive_functions.ctrl_time_step + mpc_time_step = drive_functions.mpc_time_step + mpc_freq = drive_functions.mpc_freq + acc_delay_step_ctrl = drive_functions.acc_delay_step + steer_delay_step_ctrl = drive_functions.steer_delay_step + acc_time_constant_ctrl = drive_functions.acc_time_constant + steer_time_constant_ctrl = drive_functions.steer_time_constant + + kinematic = np.loadtxt( + dir_name + "/kinematic_state.csv", delimiter=",", usecols=[0, 1, 4, 5, 7, 8, 9, 10, 47] + ) + pose_position_x = kinematic[:, 2] + pose_position_y = kinematic[:, 3] + vel = kinematic[:, 8] + raw_yaw = Rotation.from_quat(kinematic[:, 4:8]).as_euler("xyz")[:, 2] + yaw = yaw_transform(raw_yaw) + + loc_acc = np.loadtxt(dir_name + "/acceleration.csv", delimiter=",", usecols=[0, 1, 3]) + acc = loc_acc[:, 2] + + acc_sm = data_smoothing(acc, drive_functions.acc_sigma_for_learning) + + vehicle_steer = np.loadtxt( + dir_name + "/steering_status.csv", delimiter=",", usecols=[0, 1, 2] + ) + steer = vehicle_steer[:, 2] + steer_sm = steer.copy() + steer_sm = data_smoothing(steer, drive_functions.steer_sigma_for_learning) + + control_cmd = np.loadtxt( + dir_name + "/control_cmd_orig.csv", delimiter=",", usecols=[0, 1, 4, 9] + ) + acc_des = control_cmd[:, 3] + acc_des_sm = data_smoothing(acc_des, drive_functions.acc_des_sigma_for_learning) + + steer_des = control_cmd[:, 2] + steer_des_sm = steer_des.copy() + steer_des_sm = data_smoothing(steer_des, drive_functions.steer_des_sigma_for_learning) + + operation_mode = np.loadtxt( + dir_name + "/system_operation_mode_state.csv", delimiter=",", usecols=[0, 1, 2] + ) + if operation_mode.ndim == 1: + operation_mode = operation_mode.reshape(1, -1) + with open(dir_name + "/system_operation_mode_state.csv") as f: + reader = csv.reader(f, delimiter=",") + autoware_control_enabled_str = np.array([row[3] for row in reader]) + + proxima_control_enabled = np.zeros(operation_mode.shape[0]) + for i in range(operation_mode.shape[0]): + if operation_mode[i, 2] > 1.5 and autoware_control_enabled_str[i] == "True": + proxima_control_enabled[i] = 1.0 + for i in range(operation_mode.shape[0] - 1): + if proxima_control_enabled[i] < 0.5 and proxima_control_enabled[i + 1] > 0.5: + operation_start_time = operation_mode[i + 1, 0] + 1e-9 * operation_mode[i + 1, 1] + elif proxima_control_enabled[i] > 0.5 and proxima_control_enabled[i + 1] < 0.5: + operation_end_time = operation_mode[i + 1, 0] + 1e-9 * operation_mode[i + 1, 1] + break + operation_end_time = kinematic[-1, 0] + 1e-9 * kinematic[-1, 1] + if operation_mode.shape[0] == 1: + operation_end_time = kinematic[-1, 0] + 1e-9 * kinematic[-1, 1] + if proxima_control_enabled[0] > 0.5: + operation_start_time = operation_mode[0, 0] + 1e-9 * operation_mode[0, 1] + print("operation_start_time", operation_start_time) + print("operation_end_time", operation_end_time) + min_time_stamp = max( + [ + operation_start_time, + kinematic[0, 0] + 1e-9 * kinematic[0, 1], + loc_acc[0, 0] + 1e-9 * loc_acc[0, 1], + vehicle_steer[0, 0] + 1e-9 * vehicle_steer[0, 1], + control_cmd[0, 0] + 1e-9 * control_cmd[0, 1], + ] + ) + max_time_stamp = min( + [ + operation_end_time, + kinematic[-1, 0] + 1e-9 * kinematic[-1, 1], + loc_acc[-1, 0] + 1e-9 * loc_acc[-1, 1], + vehicle_steer[-1, 0] + 1e-9 * vehicle_steer[-1, 1], + control_cmd[-1, 0] + 1e-9 * control_cmd[-1, 1], + ] + ) + + trajectory_interpolator_list = [] + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(kinematic[:, 0] + 1e-9 * kinematic[:, 1], pose_position_x) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(kinematic[:, 0] + 1e-9 * kinematic[:, 1], pose_position_y) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(kinematic[:, 0] + 1e-9 * kinematic[:, 1], vel) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(kinematic[:, 0] + 1e-9 * kinematic[:, 1], yaw) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(loc_acc[:, 0] + 1e-9 * loc_acc[:, 1], acc_sm) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(vehicle_steer[:, 0] + 1e-9 * vehicle_steer[:, 1], steer_sm) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(control_cmd[:, 0] + 1e-9 * control_cmd[:, 1], acc_des_sm) + ) + trajectory_interpolator_list.append( + scipy.interpolate.interp1d(control_cmd[:, 0] + 1e-9 * control_cmd[:, 1], steer_des_sm) + ) + + def get_interpolated_state(s): + x_current = np.zeros(6) + for i in range(6): + x_current[i] = trajectory_interpolator_list[i](s) + return x_current + + def get_interpolated_input(s): + u_input = np.zeros(2) + for i in range(2): + u_input[i] = trajectory_interpolator_list[6 + i](s) + return u_input + + s = min_time_stamp + X = [] + U = [] + + Timestamp = [] + while True: + if s > max_time_stamp: + break + X.append(get_interpolated_state(s)) + + U.append(get_interpolated_input(s)) + + Timestamp.append(s) + s += ctrl_time_step + + X_array = np.array(X) + U_array = np.array(U) + X_input_list = [] + Y_output_list = [] + Timestamp_learn = [] + for i in range( + max(acc_ctrl_queue_size, steer_ctrl_queue_size) + 1, X_array.shape[0] - mpc_freq - 1 + ): + acc_input_queue = U_array[i - acc_ctrl_queue_size : i, 0].copy() + steer_input_queue = U_array[i - steer_ctrl_queue_size : i, 1].copy() + x_current = X_array[i + 3] + x_old = X_array[i] + + Timestamp_learn.append(Timestamp[i]) + X_input_list.append( + np.concatenate((x_old[[2, 4, 5]], acc_input_queue[::-1], steer_input_queue[::-1])) + ) + acc_start = acc_ctrl_queue_size - acc_delay_step_ctrl + acc_end = acc_ctrl_queue_size - acc_delay_step_ctrl + mpc_freq + steer_start = steer_ctrl_queue_size - steer_delay_step_ctrl + steer_end = steer_ctrl_queue_size - steer_delay_step_ctrl + mpc_freq + + u_for_predict_x_current = np.zeros((mpc_freq, 2)) + u_for_predict_x_current[:, 0] = acc_input_queue[acc_start:acc_end] + u_for_predict_x_current[:, 1] = steer_input_queue[steer_start:steer_end] + var_dot = x_current - drive_functions.F_multiple( + x_old, u_for_predict_x_current, acc_time_constant_ctrl, steer_time_constant_ctrl + ) + var_dot /= mpc_time_step + if var_dot[3] > 1: + print(i) + Y_output_list.append(drive_functions.rotate_data(x_old, var_dot)) + + Y_output_list_array = np.array(Y_output_list) + Y_smooth = Y_output_list_array.copy() + Y_smooth[:, 0] = data_smoothing( + Y_output_list_array[:, 0], drive_functions.x_out_sigma_for_learning + ) + Y_smooth[:, 1] = data_smoothing( + Y_output_list_array[:, 1], drive_functions.y_out_sigma_for_learning + ) + Y_smooth[:, 2] = data_smoothing( + Y_output_list_array[:, 2], drive_functions.v_out_sigma_for_learning + ) + Y_smooth[:, 3] = data_smoothing( + Y_output_list_array[:, 3], drive_functions.theta_out_sigma_for_learning + ) + Y_smooth[:, 4] = data_smoothing( + Y_output_list_array[:, 4], drive_functions.acc_out_sigma_for_learning + ) + Y_smooth[:, 5] = data_smoothing( + Y_output_list_array[:, 5], drive_functions.steer_out_sigma_for_learning + ) + + for i in range(len(X_input_list)): + self.X_input_list.append(X_input_list[i]) + self.Y_output_list.append(Y_smooth[i]) + + def save_train_data(self, save_dir=".") -> None: + """Save neural net teacher data.""" + np.savez( + save_dir + "/train_data", + X_input=np.array(self.X_input_list), + Y_output=np.array(self.Y_output_list), + ) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/data_checker.ipynb b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/data_checker.ipynb new file mode 100644 index 0000000000000..9ddd5fb6fad2a --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/data_checker.ipynb @@ -0,0 +1,252 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "85844bd8-91fa-4238-9bcf-cf45c9ef8c33", + "metadata": {}, + "outputs": [], + "source": [ + "# cspell: ignore ndimage usecols kernelspec ipykernel codemirror ipython nbconvert pygments nbformat \n", + "import numpy as np\n", + "from scipy.spatial.transform import Rotation\n", + "import scipy.interpolate\n", + "from scipy.ndimage import gaussian_filter\n", + "import os\n", + "import matplotlib.pyplot as plt\n", + "import csv\n", + "def yaw_transform(raw_yaw):\n", + " transformed_yaw = np.zeros(raw_yaw.shape)\n", + " transformed_yaw[0] = raw_yaw[0]\n", + " for i in range(raw_yaw.shape[0]-1):\n", + " rotate_num = (raw_yaw[i+1]-transformed_yaw[i])//(2*np.pi)\n", + " if raw_yaw[i+1]-transformed_yaw[i] - 2*rotate_num*np.pi < np.pi:\n", + " transformed_yaw[i+1] = raw_yaw[i+1] - 2*rotate_num*np.pi\n", + " else:\n", + " transformed_yaw[i+1] = raw_yaw[i+1] - 2*(rotate_num+1)*np.pi\n", + " return transformed_yaw\n", + "def steer_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.025,0.025] ):\n", + " kinematic=np.loadtxt(dir_name+\"/kinematic_state.csv\",delimiter=',',usecols=[0,1,4,5,7,8,9,10,47])\n", + " start_time= kinematic[0,0]+1e-9*kinematic[0,1]\n", + " total_time_default=kinematic[-1,0]+1e-9*kinematic[-1,1]-start_time\n", + " vehicle_steer = np.loadtxt(dir_name+\"/steering_status.csv\",delimiter=',',usecols=[0,1,2])\n", + " steer = vehicle_steer[:,2]\n", + " control_cmd = np.loadtxt(dir_name+\"/control_cmd_orig.csv\",delimiter=',',usecols=[0,1,4,9])\n", + " steer_des = control_cmd[:,2]\n", + " plt.plot(control_cmd[:,0] + 1e-9*control_cmd[:,1],steer_des,label=\"proxima_input\")\n", + " plt.plot(vehicle_steer[:,0] + 1e-9*vehicle_steer[:,1],steer,label=\"observed\")\n", + " \"\"\"\n", + " operation_mode = np.loadtxt(dir_name + \"/system_operation_mode_state.csv\", delimiter=\",\", usecols=[0, 1, 2])\n", + " operation_mode_time = np.zeros(2*operation_mode.shape[0])\n", + " operation_mode_time[::2] = operation_mode[:,0] + 1e-9*operation_mode[:,1]\n", + " operation_mode_time[1::2][:-1] = operation_mode_time[2::2]-1e-16\n", + " operation_mode_time[-1] = start_time+total_time_default\n", + " with open(dir_name+\"/system_operation_mode_state.csv\") as f:\n", + " reader=csv.reader(f,delimiter=',')\n", + " autoware_control_enabled_str=np.array([row[3] for row in reader])\n", + " with open(dir_name+\"/system_operation_mode_state.csv\") as f:\n", + " reader=csv.reader(f,delimiter=',')\n", + " autonomous_mode_available_str=np.array([row[6] for row in reader])\n", + " autoware_control_enabled = np.zeros(2*operation_mode.shape[0])\n", + " autonomous_mode_available = np.zeros(2*operation_mode.shape[0])\n", + " operation_mode_ = np.ones(2*operation_mode.shape[0])\n", + " for i in range(operation_mode.shape[0]):\n", + " if autoware_control_enabled_str[i] == \"True\":\n", + " autoware_control_enabled[2*i] = 1\n", + " autoware_control_enabled[2*i+1] = 1\n", + "\n", + " if operation_mode[i,2] > 1.5:\n", + " operation_mode_[2*i] = 2.0\n", + " operation_mode_[2*i+1] = 2.0\n", + " \"\"\"\n", + " # plt.plot(operation_mode_time,0.01*operation_mode_,label=\"operation_mode\")\n", + " # plt.plot(operation_mode_time,0.01*autoware_control_enabled,label=\"autoware_control_enabled\")\n", + "\n", + "\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.ylabel(\"steer [rad]\")\n", + " plt.xlabel(\"Time [s]\")\n", + "\n", + " plt.ylim(ylim)\n", + " plt.legend()\n", + " plt.show()\n", + "def acc_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.005,0.02] ):\n", + " kinematic=np.loadtxt(dir_name+\"/kinematic_state.csv\",delimiter=',',usecols=[0,1,4,5,7,8,9,10,47])\n", + " start_time= kinematic[0,0]+1e-9*kinematic[0,1]\n", + " total_time_default=kinematic[-1,0]+1e-9*kinematic[-1,1]-start_time\n", + " loc_acc = np.loadtxt(dir_name + \"/acceleration.csv\", delimiter=\",\", usecols=[0, 1, 3])\n", + " acc = loc_acc[:,2]\n", + " control_cmd = np.loadtxt(dir_name+\"/control_cmd_orig.csv\",delimiter=',',usecols=[0,1,4,9])\n", + " acc_des = control_cmd[:,3]\n", + " plt.plot(control_cmd[:,0] + 1e-9*control_cmd[:,1],acc_des,label=\"proxima_input\")\n", + " plt.plot(loc_acc[:,0] + 1e-9*loc_acc[:,1],acc,label=\"observed\")\n", + " \"\"\"\n", + " goal_stop_mode = np.loadtxt(dir_name + \"/debug_mpc_goal_stop_mode.csv\", delimiter=\",\",usecols=[0,1])\n", + "\n", + " with open(dir_name+\"/debug_mpc_goal_stop_mode.csv\") as f:\n", + " reader=csv.reader(f,delimiter=',')\n", + " stop_mode_str=np.array([row[2] for row in reader])\n", + "\n", + " stop_mode = np.zeros(goal_stop_mode.shape[0])\n", + " for i in range(goal_stop_mode.shape[0]):\n", + " if stop_mode_str[i] == \"True\":\n", + " stop_mode[i] = 1\n", + " plt.plot(goal_stop_mode[:,0] + 1e-9*goal_stop_mode[:,1],stop_mode,label=\"stop_mode\")\n", + " operation_mode = np.loadtxt(dir_name + \"/system_operation_mode_state.csv\", delimiter=\",\", usecols=[0, 1, 2])\n", + " operation_mode_time = np.zeros(2*operation_mode.shape[0])\n", + " operation_mode_time[::2] = operation_mode[:,0] + 1e-9*operation_mode[:,1]\n", + " operation_mode_time[1::2][:-1] = operation_mode_time[2::2]-1e-16\n", + " operation_mode_time[-1] = start_time+total_time_default\n", + " with open(dir_name+\"/system_operation_mode_state.csv\") as f:\n", + " reader=csv.reader(f,delimiter=',')\n", + " autoware_control_enabled_str=np.array([row[3] for row in reader])\n", + " with open(dir_name+\"/system_operation_mode_state.csv\") as f:\n", + " reader=csv.reader(f,delimiter=',')\n", + " autonomous_mode_available_str=np.array([row[6] for row in reader])\n", + " autoware_control_enabled = np.zeros(2*operation_mode.shape[0])\n", + " operation_mode_ = np.ones(2*operation_mode.shape[0])\n", + " for i in range(operation_mode.shape[0]):\n", + " if autoware_control_enabled_str[i] == \"True\":\n", + " autoware_control_enabled[2*i] = 1\n", + " autoware_control_enabled[2*i+1] = 1\n", + "\n", + " if operation_mode[i,2] > 1.5:\n", + " operation_mode_[2*i] = 2.0\n", + " operation_mode_[2*i+1] = 2.0\n", + " \"\"\"\n", + " # plt.plot(operation_mode_time,operation_mode_,label=\"operation_mode\")\n", + " # plt.plot(operation_mode_time,autoware_control_enabled,label=\"autoware_control_enabled\")\n", + "\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.ylabel(\"acc [m/s^2]\")\n", + " plt.xlabel(\"Time [s]\")\n", + " plt.ylim(ylim)\n", + " plt.legend()\n", + " plt.show()\n", + "def yaw_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.15,0.0]):\n", + " kinematic=np.loadtxt(dir_name+\"/kinematic_state.csv\",delimiter=',',usecols=[0,1,4,5,7,8,9,10,47])\n", + " raw_yaw = Rotation.from_quat(kinematic[:,4:8]).as_euler(\"xyz\")[:,2]\n", + " yaw = yaw_transform(raw_yaw)\n", + " start_time= kinematic[0,0]+1e-9*kinematic[0,1]\n", + " total_time_default=kinematic[-1,0]+1e-9*kinematic[-1,1]-start_time\n", + " plt.plot(kinematic[:,0] + 1e-9*kinematic[:,1],yaw,label=\"observed\")\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.ylabel(\"yaw [rad]\")\n", + " plt.xlabel(\"Time [s]\")\n", + "\n", + " plt.ylim(ylim)\n", + " plt.legend()\n", + " plt.show()\n", + "def vel_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.1,12.0]):\n", + " kinematic=np.loadtxt(dir_name+\"/kinematic_state.csv\",delimiter=',',usecols=[0,1,4,5,7,8,9,10,47])\n", + " vel = kinematic[:,8]\n", + " mpc_v_des=np.loadtxt(dir_name+\"/debug_mpc_v_des.csv\",delimiter=',',usecols=[0,1,3])\n", + " vel_des = mpc_v_des[:,2]\n", + " start_time= kinematic[0,0]+1e-9*kinematic[0,1]\n", + " total_time_default=kinematic[-1,0]+1e-9*kinematic[-1,1]-start_time\n", + " plt.plot(kinematic[:,0] + 1e-9*kinematic[:,1],vel,label=\"observed\")\n", + " plt.plot(mpc_v_des[:,0] + 1e-9*mpc_v_des[:,1],vel_des,label=\"des\")\n", + "\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.ylabel(\"vel [m/s]\")\n", + " plt.xlabel(\"Time [s]\")\n", + "\n", + " plt.ylim(ylim)\n", + " plt.legend()\n", + " plt.show()\n", + "def lateral_error_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.25,0.25],title=None):\n", + " lateral_error = np.loadtxt(dir_name+\"/lateral_error.csv\",delimiter=',')\n", + " start_time= lateral_error[0,0]+1e-9*lateral_error[0,1]\n", + " total_time_default=lateral_error[-1,0]+1e-9*lateral_error[-1,1]-start_time\n", + " plt.plot(lateral_error[:,0] + 1e-9*lateral_error[:,1],lateral_error[:,2],label=\"lateral_error\")\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.legend()\n", + " plt.ylim(ylim)\n", + " plt.ylabel(\"lateral_error [m]\")\n", + " plt.xlabel(\"Time [s]\")\n", + " if title is not None:\n", + " plt.title(title)\n", + " plt.savefig(\"lateral_error_\"+title+\".png\")\n", + " plt.show()\n", + "def computation_time_visualize(skip_time = 0,total_time = None,dir_name = \".\",ylim = [-0.05,0.5]):\n", + " control_cmd = np.loadtxt(dir_name+\"/control_cmd_orig.csv\",delimiter=',',usecols=[0,1])\n", + " cmd_time_stamp = control_cmd[:,0]+1e-9*control_cmd[:,1]\n", + " cmd_time_stamp_diff = cmd_time_stamp[1:] - cmd_time_stamp[:-1]\n", + " calc_u_opt_time = np.loadtxt(dir_name+\"/debug_mpc_calc_u_opt_time.csv\",delimiter=',')\n", + " total_ctrl_time = np.loadtxt(dir_name+\"/debug_mpc_total_ctrl_time.csv\",delimiter=',')\n", + " start_time= control_cmd[0,0]+1e-9*control_cmd[0,1]\n", + " total_time_default=control_cmd[-1,0]+1e-9*control_cmd[-1,1]-start_time\n", + "\n", + " plt.plot(cmd_time_stamp[1:],cmd_time_stamp_diff,label=\"/control/trajectory_follower/control_cmd publish_interval\")\n", + " plt.plot(total_ctrl_time[:,0] + 1e-9*total_ctrl_time[:,1],total_ctrl_time[:,2],label=\"total_ctrl_time\")\n", + " plt.plot(calc_u_opt_time[:,0] + 1e-9*calc_u_opt_time[:,1],calc_u_opt_time[:,2],label=\"calc_u_opt_time\")\n", + " plt.legend()\n", + " plt.ylim(ylim)\n", + " if total_time is None:\n", + " plt.xlim([start_time+skip_time,start_time+total_time_default])\n", + " else:\n", + " plt.xlim([start_time+skip_time,start_time+skip_time+total_time])\n", + " plt.xlabel(\"Time [s]\")\n", + " plt.ylabel(\"Processing Time [s]\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b07ed62c-a5b0-4c5f-b52d-633b0c61271b", + "metadata": {}, + "outputs": [], + "source": [ + "dirname = #specify rosbag dir\n", + "steer_visualize(20,20,dirname,ylim=[-0.05,0.05])\n", + "lateral_error_visualize(0,None,dirname,ylim=[-0.6,0.6])\n", + "vel_visualize(20,20,dirname,ylim=[-0.6,12.0])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f7012be5-0259-4618-a380-8ec7a29f59af", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/execute_train_drive_NN_model.ipynb b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/execute_train_drive_NN_model.ipynb new file mode 100644 index 0000000000000..c2955883d5699 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/execute_train_drive_NN_model.ipynb @@ -0,0 +1,77 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "c445f7e1-6d75-405d-be86-1b9c8f9eaae3", + "metadata": {}, + "outputs": [], + "source": [ + "# cspell: ignore kernelspec ipykernel codemirror ipython nbconvert pygments nbformat \n", + "import train_drive_NN_model" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "dc7aa5b8-15fa-4ad0-a776-664748a747ac", + "metadata": {}, + "outputs": [], + "source": [ + "model_trainer = train_drive_NN_model.train_drive_NN_model()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6559bc06-d55d-4230-a640-e1730e333df3", + "metadata": {}, + "outputs": [], + "source": [ + "load_dir = #specify rosbag dir\n", + "model_trainer.add_data_from_csv(load_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bdcd80a2-6484-4957-a34c-3ed193cc10e2", + "metadata": {}, + "outputs": [], + "source": [ + "model_trainer.get_trained_model(use_polynomial_reg=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dc4c2c45-60b1-4ff7-996b-4f1f60305f97", + "metadata": {}, + "outputs": [], + "source": [ + "model_trainer.save_models()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/rosbag2.bash b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/rosbag2.bash new file mode 100644 index 0000000000000..524dfe5a169df --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/rosbag2.bash @@ -0,0 +1,40 @@ +#!/bin/bash + +gnome-terminal -- bash -c 'ros2 topic echo /localization/kinematic_state nav_msgs/msg/Odometry --csv --qos-history keep_all --qos-reliability reliable > kinematic_state.csv' +gnome-terminal -- bash -c 'ros2 topic echo /localization/acceleration geometry_msgs/msg/AccelWithCovarianceStamped --csv --qos-history keep_all --qos-reliability reliable > acceleration.csv' +gnome-terminal -- bash -c 'ros2 topic echo /vehicle/status/steering_status autoware_auto_vehicle_msgs/msg/SteeringReport --csv --qos-history keep_all --qos-reliability reliable > steering_status.csv' + +gnome-terminal -- bash -c 'ros2 topic echo /control/command/control_cmd autoware_auto_control_msgs/msg/AckermannControlCommand --csv --qos-history keep_all --qos-reliability reliable > control_cmd.csv' +gnome-terminal -- bash -c 'ros2 topic echo /control/trajectory_follower/control_cmd autoware_auto_control_msgs/msg/AckermannControlCommand --csv --qos-history keep_all --qos-reliability reliable > control_cmd_orig.csv' + +gnome-terminal -- bash -c 'ros2 topic echo /control/trajectory_follower/lane_departure_checker_node/debug/deviation/lateral tier4_debug_msgs/msg/Float64Stamped --csv --qos-history keep_all --qos-reliability reliable > lateral_error.csv' +gnome-terminal -- bash -c 'ros2 topic echo /control/trajectory_follower/lane_departure_checker_node/debug/deviation/yaw tier4_debug_msgs/msg/Float64Stamped --csv --qos-history keep_all --qos-reliability reliable > yaw_error.csv' + +gnome-terminal -- bash -c 'ros2 topic echo /system/operation_mode/state autoware_adapi_v1_msgs/msg/OperationModeState --csv --qos-history keep_all --qos-reliability reliable > system_operation_mode_state.csv' +gnome-terminal -- bash -c 'ros2 topic echo /vehicle/status/control_mode autoware_auto_vehicle_msgs/msg/ControlModeReport --csv --qos-history keep_all --qos-reliability reliable > vehicle_status_control_mode.csv' +gnome-terminal -- bash -c 'ros2 topic echo /sensing/imu/imu_data sensor_msgs/msg/Imu --csv --qos-history keep_all --qos-reliability reliable > imu.csv' + +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_x_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_x_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_y_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_y_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_v_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_v_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_yaw_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_yaw_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_acc_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_acc_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_steer_des tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_steer_des.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_X_des_converted tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_X_des_converted.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_x_current tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_x_current.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_error_prediction tier4_debug_msgs/msg/Float32MultiArrayStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_error_prediction.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_max_trajectory_err tier4_debug_msgs/msg/Float32Stamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_max_trajectory_err.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_emergency_stop_mode tier4_debug_msgs/msg/BoolStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_emergency_stop_mode.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_goal_stop_mode tier4_debug_msgs/msg/BoolStamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_goal_stop_mode.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_total_ctrl_time tier4_debug_msgs/msg/Float32Stamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_total_ctrl_time.csv' +gnome-terminal -- bash -c 'ros2 topic echo /debug_mpc_calc_u_opt_time tier4_debug_msgs/msg/Float32Stamped --csv --qos-history keep_all --qos-reliability reliable > debug_mpc_calc_u_opt_time.csv' + +# wait a moment to open new terminals converting rosbag2 to csv +sleep 8 + +ros2 bag play rosbag2_*.db3 -r 10 + +sleep 3 + +# kill terminals converting rosbag2 to csv +pgrep -f "\ --csv\ --qos-history\ keep_all\ --qos-reliability\ reliable" | xargs kill -9 diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_GP_model.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_GP_model.py new file mode 100644 index 0000000000000..914ed7b53c6ec --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_GP_model.py @@ -0,0 +1,88 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore lengthscale savez + +import GPy +import numpy as np +from smart_mpc_trajectory_follower.training_and_data_check import add_training_data_from_csv + + +class train_drive_GP_model(add_training_data_from_csv.add_data_from_csv): + """Class for training the Gaussian process from driving data.""" + + def __init__(self): + super(train_drive_GP_model, self).__init__() + + def get_optimized_GP(self, i, save_name, inducting_num=100): + """Train Gaussian processes and save the information needed for vehicle control.""" + X_input = np.array(self.X_input_list) + Y_output = np.array(self.Y_output_list) + induction_index = np.random.choice(X_input.shape[0], inducting_num, replace=False) + kernel = GPy.kern.RBF(input_dim=X_input.shape[1], ARD=True) + m = GPy.models.SparseGPRegression( + X_input, Y_output[:, [i]], kernel, Z=X_input[induction_index] + ) + m.optimize() + theta_1 = kernel.variance[0] + theta_2 = 1 / np.array(np.array(kernel.lengthscale) ** 2) + Z_post = np.array(m.inducing_inputs) + + K_MM = kernel.K(Z_post, Z_post) + K_MN = kernel.K(Z_post, X_input) + K_MM_inv = np.linalg.inv(K_MM) + Lam_with_noise_inv = np.zeros(K_MN.shape[1]) + for n in range(K_MN.shape[1]): + Lam_with_noise_inv[n] = 1 / ( + kernel.variance + - np.dot(K_MM_inv @ K_MN[:, n], K_MN[:, n]) + + m.Gaussian_noise.variance + ) + Q_MM = K_MM + K_MN @ np.diag(Lam_with_noise_inv) @ K_MN.T + Q_MM_inv = np.linalg.inv(Q_MM) + U = K_MM @ Q_MM_inv @ K_MN @ (np.diag(Lam_with_noise_inv) @ Y_output[:, 4]) + K_MM_invUT = (K_MM_inv @ U).T + + np.savez( + save_name, + theta_1=theta_1, + theta_2=theta_2, + Z=Z_post, + mean_mtr=K_MM_invUT, + cov_mtr=K_MM_inv - Q_MM_inv, + ) + + def get_optimized_GP_x(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the longitudinal position.""" + self.get_optimized_GP(0, dir_name + "/GP_x_info", inducting_num) + + def get_optimized_GP_y(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the lateral position.""" + self.get_optimized_GP(1, dir_name + "/GP_y_info", inducting_num) + + def get_optimized_GP_v(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the velocity.""" + self.get_optimized_GP(2, dir_name + "/GP_v_info", inducting_num) + + def get_optimized_GP_theta(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the yaw angle.""" + self.get_optimized_GP(3, dir_name + "/GP_theta_info", inducting_num) + + def get_optimized_GP_acc(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the acceleration.""" + self.get_optimized_GP(4, dir_name + "/GP_acc_info", inducting_num) + + def get_optimized_GP_steer(self, dir_name=".", inducting_num=100): + """Save the information of the Gaussian process about the prediction error of the steering angle.""" + self.get_optimized_GP(5, dir_name + "/GP_steer_info", inducting_num) diff --git a/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model.py b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model.py new file mode 100644 index 0000000000000..269b577f83c25 --- /dev/null +++ b/control/smart_mpc_trajectory_follower/smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model.py @@ -0,0 +1,716 @@ +# Copyright 2024 Proxima Technology Inc, TIER IV +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# cspell: ignore optim savez suptitle + +"""Class for training neural nets from driving data.""" +import matplotlib.pyplot as plt +import numpy as np +from sklearn import linear_model +from sklearn.preprocessing import PolynomialFeatures +from smart_mpc_trajectory_follower.scripts import drive_NN +from smart_mpc_trajectory_follower.scripts import drive_functions +from smart_mpc_trajectory_follower.training_and_data_check import add_training_data_from_csv +import torch +from torch import nn +from torch.utils.data import DataLoader +from torch.utils.data import TensorDataset + +ctrl_index_for_polynomial_reg = np.concatenate( + ( + np.arange(3), + [3 + drive_functions.acc_delay_step], + [3 + drive_functions.acc_ctrl_queue_size + drive_functions.steer_delay_step], + ) +) + + +def nominal_model_acc(v: float, alpha_0: float, alpha: float) -> np.ndarray: + """Predicted acceleration value according to the nominal model.""" + nominal_pred = alpha_0 + nominal_v = v + nominal_pred * drive_functions.ctrl_time_step + nominal_pred = ( + nominal_pred + + (alpha - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.acc_time_constant + ) + nominal_v = v + nominal_pred * drive_functions.ctrl_time_step + nominal_pred = ( + nominal_pred + + (alpha - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.acc_time_constant + ) + nominal_v = v + nominal_pred * drive_functions.ctrl_time_step + nominal_pred = ( + nominal_pred + + (alpha - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.acc_time_constant + ) + return np.array([nominal_v, nominal_pred]) + + +def nominal_model_steer(delta_0: float, delta: float) -> float: + """Predicted steer angle according to the nominal model.""" + nominal_pred = delta_0 + nominal_pred = ( + nominal_pred + + (delta - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.steer_time_constant + ) + nominal_pred = ( + nominal_pred + + (delta - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.steer_time_constant + ) + nominal_pred = ( + nominal_pred + + (delta - nominal_pred) + * drive_functions.ctrl_time_step + / drive_functions.steer_time_constant + ) + return nominal_pred + + +class train_drive_NN_model(add_training_data_from_csv.add_data_from_csv): + """Class for training neural nets from driving data.""" + + tanh_gain: float + """Gain of tanh in the NN cost function""" + + lam: float + """Weights of the tanh term in the NN cost function.""" + + tol: float + """Tolerances for terminating training iterations.""" + + alpha_1: float + """L¹ regularization weights in the NN cost function""" + + alpha_2: float + """L² regularization weights in the NN cost function.""" + + alpha_1_for_polynomial_regression: float + """L¹ regularization weights for polynomial regression""" + + alpha_2_for_polynomial_regression: float + """L² regularization weights for polynomial regression""" + + x_loss: list[float] + """List of values for the loss function of the x component in the NN training.""" + + y_loss: list[float] + """List of values for the loss function of the y component in the NN training.""" + + v_loss: list[float] + """List of values for the loss function of the velocity component in the NN training.""" + + theta_loss: list[float] + """List of values for the loss function of the yaw angle component in the NN training.""" + + acc_loss: list[float] + """List of values for the loss function of the acceleration component in the NN training.""" + + steer_loss: list[float] + """List of values for the loss function of the steer angle component in the NN training.""" + + steer_loss_plus_tanh: list[float] + """List of values of the loss function for the steer angle component with tanh term in the NN training.""" + + total_loss: list[float] + """In NN training x_loss, ... , acc_loss, steer_loss_plus_tanh summed list of values""" + + model: drive_NN.DriveNeuralNetwork + """trained neural network model""" + + A: np.ndarray + """Coefficient matrix of polynomial regression model.""" + + b: np.ndarray + """Constant terms in polynomial regression models (bias)""" + + def __init__( + self, + tanh_gain=10, + lam=0.1, + tol=0.00001, + alpha_1=0.1**7, + alpha_2=0.1**7, + alpha_1_for_polynomial_regression=0.1**5, + alpha_2_for_polynomial_regression=0.1**5, + ): + super(train_drive_NN_model, self).__init__() + self.tanh_gain = tanh_gain + self.lam = lam + self.tol = tol + self.alpha_1 = alpha_1 + self.alpha_2 = alpha_2 + self.alpha_1_for_polynomial_regression = alpha_1_for_polynomial_regression + self.alpha_2_for_polynomial_regression = alpha_2_for_polynomial_regression + self.x_loss = [] + self.y_loss = [] + self.v_loss = [] + self.theta_loss = [] + self.acc_loss = [] + self.steer_loss = [] + self.steer_loss_plus_tanh = [] + self.total_loss = [] + + def train_model( + self, + model: drive_NN.DriveNeuralNetwork, + X_input: np.ndarray, + Y_output: np.ndarray, + learning_rates: list[float], + patience: int = 10, + batch_size: int | None = 50, + max_iter: int = 100000, + ) -> None: + """Train the model.""" + if batch_size is None: + batch_size = X_input.shape[0] // 50 + self.x_loss.clear() + self.y_loss.clear() + self.v_loss.clear() + self.theta_loss.clear() + self.acc_loss.clear() + self.steer_loss.clear() + self.steer_loss_plus_tanh.clear() + self.total_loss.clear() + sample_size = X_input.shape[0] + num_train = int(3 * sample_size / 4) + id_all = np.random.choice(sample_size, sample_size, replace=False) + id_train = id_all[:num_train] + id_val = id_all[num_train:] + X_tensor = torch.tensor(X_input.astype(np.float32)).clone() + Y_tensor = torch.tensor(Y_output.astype(np.float32)).clone() + X_train = X_tensor[id_train] + Y_train = Y_tensor[id_train] + X_val = X_tensor[id_val] + Y_val = Y_tensor[id_val] + + print("sample_size: ", X_input.shape[0]) + print("patience:", patience) + loss_fn = torch.nn.L1Loss() + learning_rate = learning_rates[0] + optimizer = torch.optim.Adam(params=model.parameters(), lr=learning_rate) + + drive_data = DataLoader( + TensorDataset(X_train, Y_train), batch_size=batch_size, shuffle=True + ) + initial_loss = drive_NN.loss_fn_plus_tanh( + loss_fn, + torch.tensor(np.zeros(Y_val.shape), dtype=torch.float32), + Y_val, + self.tanh_gain, + self.lam, + ) + print("initial_loss:", initial_loss.detach().item()) + early_stopping = drive_NN.EarlyStopping( + initial_loss=initial_loss, tol=self.tol, patience=patience + ) + k = 0 + print("learning_rate:", learning_rates[0]) + for i in range(max_iter): + model.train() + for X_batch, y_batch in drive_data: + y_pred = model(X_batch) + loss = drive_NN.loss_fn_plus_tanh( + loss_fn, y_pred, y_batch, self.tanh_gain, self.lam + ) + for w in model.parameters(): + loss = ( + loss + self.alpha_1 * torch.norm(w, p=1) + self.alpha_2 * torch.norm(w) ** 2 + ) + optimizer.zero_grad() + loss.backward() + optimizer.step() + + model.eval() + pred = model(X_val) + self.total_loss.append( + drive_NN.loss_fn_plus_tanh(loss_fn, pred, Y_val, self.tanh_gain, self.lam) + .detach() + .item() + ) + self.x_loss.append(loss_fn(pred[:, [0]], Y_val[:, [0]]).detach().item()) + self.y_loss.append(loss_fn(pred[:, [1]], Y_val[:, [1]]).detach().item()) + self.v_loss.append(loss_fn(pred[:, [2]], Y_val[:, [2]]).detach().item()) + self.theta_loss.append(loss_fn(pred[:, [3]], Y_val[:, [3]]).detach().item()) + self.acc_loss.append(loss_fn(pred[:, [4]], Y_val[:, [4]]).detach().item()) + self.steer_loss.append(loss_fn(pred[:, [5]], Y_val[:, [5]]).detach().item()) + self.steer_loss_plus_tanh.append( + loss_fn(pred[:, [5]], Y_val[:, [5]]).detach().item() + + self.lam + * loss_fn( + torch.tanh(self.tanh_gain * (pred[:, -1] - Y_val[:, -1])), + torch.zeros(Y_val.shape[0]), + ) + .detach() + .item() + ) + if i % 10 == 1: + current_loss = drive_NN.loss_fn_plus_tanh( + loss_fn, model(X_val), Y_val, self.tanh_gain, self.lam + ) + print(current_loss.detach().item(), i) + if early_stopping(current_loss): + k += 1 + if k == len(learning_rates): + break + else: + learning_rate = learning_rates[k] + print("update learning_rate to ", learning_rates[k]) + optimizer = torch.optim.Adam(params=model.parameters(), lr=learning_rate) + early_stopping = drive_NN.EarlyStopping( + initial_loss=initial_loss, tol=self.tol, patience=patience + ) + + def get_polynomial_regression_result( + self, + X_input_list: list[np.ndarray], + Y_output_list: list[np.ndarray], + use_polynomial_reg: bool, + use_selected_polynomial: bool, + deg: int, + fit_intercept: bool, + use_intercept: bool, + ) -> tuple[np.ndarray, np.ndarray]: + """Get the results of a polynomial regression.""" + X_input = np.array(X_input_list) + X_input_core = X_input[ + :, + : 3 + drive_functions.acc_ctrl_queue_size + drive_functions.steer_ctrl_queue_size_core, + ].copy() + Y_output = np.array(Y_output_list) + if use_selected_polynomial: + self.deg = 2 + else: + self.deg = deg + self.A, self.b, Y_output_minus = polynomial_regression( + X_input_core, + Y_output, + self.alpha_1_for_polynomial_regression, + self.alpha_2_for_polynomial_regression, + use_polynomial_reg, + use_selected_polynomial, + self.deg, + fit_intercept, + use_intercept, + ) + return X_input, Y_output_minus + + def plot_trained_result( + self, show_flag=False, save_dir=".", plot_range=np.arange(500, 1200) + ) -> None: + """Plot the results of the training.""" + polynomial_features = PolynomialFeatures(degree=self.deg, include_bias=False) + + X_input = np.array(self.X_input_list) + Y_output = np.array(self.Y_output_list) + X_tensor = torch.tensor(X_input.astype(np.float32)).clone() + acc_ctrl_queue_size = drive_functions.acc_ctrl_queue_size + steer_ctrl_queue_size = drive_functions.steer_ctrl_queue_size + ctrl_time_step = drive_functions.ctrl_time_step + Y_pred = ( + self.model(X_tensor).detach().numpy() + + polynomial_features.fit_transform(X_input[:, ctrl_index_for_polynomial_reg]) + @ (self.A).T + + self.b + ) + x = max(acc_ctrl_queue_size, steer_ctrl_queue_size) * ctrl_time_step + y_labels = [ + "x_error [m]", + "y_error [m]", + "vel_error [m/s]", + "yaw_error [rad]", + "acc_error [m/s^2]", + "steer_error [rad]", + ] + + plt.figure(figsize=(24, 15), tight_layout=True) + plt.subplot(231) + ax = [] + for i in range(6): + ax.append(plt.subplot(2, 3, i + 1)) + ax[-1].plot( + drive_functions.ctrl_time_step * plot_range + x, + Y_output[plot_range, i] * drive_functions.mpc_time_step, + label="nominal_error", + ) + ax[-1].plot( + drive_functions.ctrl_time_step * plot_range + x, + Y_pred[plot_range, i] * drive_functions.mpc_time_step, + label="pred_error", + ) + ax[-1].set_xlabel("sec") + ax[-1].set_ylabel(y_labels[i]) + ax[-1].legend() + if show_flag: + plt.show() + else: + plt.savefig(save_dir + "/train_drive_NN_model_fig.png") + plt.close() + + def plot_loss(self, show_flag=False, save_dir=".") -> None: + """Plot the progression of values of the loss function of the training.""" + plt.figure(figsize=(24, 15), tight_layout=True) + + y_loss_labels = [ + "total_loss", + "x_loss", + "y_loss", + "vel_loss", + "yaw_loss", + "acc_loss", + "steer_loss", + "steer_plus_tanh_loss", + ] + plt.subplot(241) + ax_2 = [] + loss_list = [ + np.array(self.total_loss), + np.array(self.x_loss), + np.array(self.y_loss), + np.array(self.v_loss), + np.array(self.theta_loss), + np.array(self.acc_loss), + np.array(self.steer_loss), + np.array(self.steer_loss_plus_tanh), + ] + for i in range(8): + ax_2.append(plt.subplot(2, 4, i + 1)) + ax_2[-1].plot( + np.arange(loss_list[i].shape[0]), + loss_list[i], + label="loss", + ) + ax_2[-1].set_xlabel("iteration") + ax_2[-1].set_ylabel(y_loss_labels[i]) + ax_2[-1].legend() + if show_flag: + plt.show() + else: + plt.savefig(save_dir + "/loss.png") + plt.close() + + def get_trained_model( + self, + learning_rates: list[float] = [1e-3, 1e-4, 1e-5, 1e-6], + randomize=0.01, + acc_drop_out=0.0, + steer_drop_out=0.0, + patience: int = 10, + batch_size: int | None = 50, + max_iter=100000, + use_polynomial_reg=False, + use_selected_polynomial=True, + force_NN_model_to_zero=False, + fit_intercept=True, + use_intercept=None, + deg: int = 2, + ): + """Train on a model for which initial values are randomly given in a suitable range.""" + if use_intercept is None: + if force_NN_model_to_zero: + use_intercept = True + else: + use_intercept = False + X_input, Y_output_minus = self.get_polynomial_regression_result( + self.X_input_list, + self.Y_output_list, + use_polynomial_reg, + use_selected_polynomial, + deg, + fit_intercept, + use_intercept, + ) + self.model = drive_NN.DriveNeuralNetwork( + randomize=randomize, + acc_drop_out=acc_drop_out, + steer_drop_out=steer_drop_out, + acc_queue_size=drive_functions.acc_ctrl_queue_size, + steer_queue_size=drive_functions.steer_ctrl_queue_size, + ) + if force_NN_model_to_zero: + for w in self.model.parameters(): + w.data = nn.Parameter(torch.zeros(w.shape)) + else: + self.train_model( + self.model, X_input, Y_output_minus, learning_rates, patience, batch_size, max_iter + ) + + def update_trained_model( + self, + learning_rates=[1e-4, 1e-5, 1e-6], + patience=5, + batch_size=50, + max_iter=100000, + use_polynomial_reg=False, + use_selected_polynomial=True, + force_NN_model_to_zero=False, + fit_intercept=True, + use_intercept=None, + deg: int = 2, + ): + """Update `self.model` with additional learning.""" + if use_intercept is None: + if force_NN_model_to_zero: + use_intercept = True + else: + use_intercept = False + X_input, Y_output_minus = self.get_polynomial_regression_result( + self.X_input_list, + self.Y_output_list, + use_polynomial_reg, + use_selected_polynomial, + deg, + fit_intercept, + use_intercept, + ) + if force_NN_model_to_zero: + for w in self.model.parameters(): + w.data = nn.Parameter(torch.zeros(w.shape)) + else: + self.train_model( + self.model, X_input, Y_output_minus, learning_rates, patience, batch_size, max_iter + ) + + def update_saved_trained_model( + self, + path="model_for_test_drive.pth", + learning_rates: list[float] = [1e-4, 1e-5, 1e-6], + patience=5, + batch_size: int | None = 50, + max_iter=100000, + use_polynomial_reg=False, + use_selected_polynomial=True, + force_NN_model_to_zero=False, + fit_intercept=True, + use_intercept=None, + deg: int = 2, + ) -> None: + """Load the saved model and update the model with additional training.""" + if use_intercept is None: + if force_NN_model_to_zero: + use_intercept = True + else: + use_intercept = False + X_input, Y_output_minus = self.get_polynomial_regression_result( + self.X_input_list, + self.Y_output_list, + use_polynomial_reg, + use_selected_polynomial, + deg, + fit_intercept, + use_intercept, + ) + self.model = torch.load(path) + if force_NN_model_to_zero: + for w in self.model.parameters(): + w.data = nn.Parameter(torch.zeros(w.shape)) + else: + self.train_model( + self.model, X_input, Y_output_minus, learning_rates, patience, batch_size, max_iter + ) + + def save_model(self, save_dir=".", path="model_for_test_drive.pth") -> None: + """Save trained NN models.""" + torch.save(self.model, save_dir + "/" + path) + + def save_polynomial_reg_info(self, save_dir=".", path="polynomial_reg_info") -> None: + """Save the coefficients and degree of the resulting polynomial regression.""" + np.savez(save_dir + "/" + path, A=self.A, b=self.b, deg=self.deg) + + def save_models( + self, + save_dir=".", + model_name="model_for_test_drive.pth", + polynomial_reg_info_name="polynomial_reg_info", + ) -> None: + """Run save_model and save_polynomial_reg_info.""" + self.save_model(save_dir, model_name) + self.save_polynomial_reg_info(save_dir, polynomial_reg_info_name) + + def predict_error( + self, v: float, alpha_0: float, delta_0: float, alpha: float, delta: float + ) -> np.ndarray: + """Predicts the prediction error when following a nominal model.""" + polynomial_features = PolynomialFeatures(degree=self.deg, include_bias=False) + x_input = np.zeros( + 3 + drive_functions.acc_ctrl_queue_size + drive_functions.steer_ctrl_queue_size + ) + x_input[0] = v + x_input[1] = alpha_0 + x_input[2] = delta_0 + x_input[3 : 3 + drive_functions.acc_ctrl_queue_size] += alpha + x_input[3 + drive_functions.acc_ctrl_queue_size :] += delta + x_input_tensor = torch.tensor(x_input.reshape(1, -1).astype(np.float32)) + return ( + self.model(x_input_tensor)[0].detach().numpy() + + self.A + @ polynomial_features.fit_transform( + x_input[ctrl_index_for_polynomial_reg].reshape(1, -1) + )[0] + + self.b + ) + + def sim( + self, v: float, alpha_0: float, alpha: float, delta_0: float, delta: float, iter_times: int + ) -> tuple[float, float, float]: + """Simulate velocity, acceleration and steer changes according to a trained model.""" + v_pred = v + alpha_pred = alpha_0 + delta_pred = delta_0 + for i in range(iter_times): + pred = ( + np.concatenate( + ( + nominal_model_acc(v_pred, alpha_pred, alpha), + np.array([nominal_model_steer(delta_pred, delta)]), + ) + ) + + self.predict_error(v_pred, alpha_pred, delta_pred, alpha, delta)[[2, 4, 5]] + * drive_functions.mpc_time_step + ) + v_pred = pred[0] + alpha_pred = pred[1] + steer_pred = pred[2] + return v_pred, alpha_pred, steer_pred + + def plot_acc_map(self, iter_times: int, starting_steer=0.0, target_steer=0.0) -> None: + """Run `sim` `iter_times` times. The simulation time is approximately 0.1*iter_times. + + Draw the resulting acceleration map. + """ + acc = np.arange(-1, 1, 0.05) + v_tests = np.arange(0, 12, 0.3) + acc_result = np.zeros((acc.shape[0], v_tests.shape[0])) + v_result = np.zeros((acc.shape[0], v_tests.shape[0])) + steer_result = np.zeros((acc.shape[0], v_tests.shape[0])) + for i in range(acc.shape[0]): + v_tests_tmp = v_tests - 0.1 * iter_times * acc[i] + for j in range(v_tests.shape[0]): + v_result[i, j], acc_result[i, j], steer_result[i, j] = self.sim( + v_tests_tmp[j], acc[i], acc[i], starting_steer, target_steer, iter_times + ) + fig = plt.figure() + ax = fig.add_subplot(111, projection="3d") + ax.plot_surface(np.tile(acc, (v_tests.shape[0], 1)).T, v_result, acc_result) + ax.set_xlabel("acc_input [m/s^2]") + ax.set_ylabel("vel [m/s]") + ax.set_zlabel("acc_sim [m/s^2]") + fig.suptitle(str(iter_times * drive_functions.mpc_time_step) + " sec simulation") + plt.show() + + def plot_steer_map(self, iter_times: int, starting_acc=0.0, target_acc=0.0) -> None: + """Run `sim` `iter_times` times. The simulation time is approximately 0.1*iter_times. + + Draw the resulting steer map. + """ + steer = np.arange(-1, 1, 0.05) + v_tests = np.arange(0, 12, 0.3) + acc_result = np.zeros((steer.shape[0], v_tests.shape[0])) + v_result = np.zeros((steer.shape[0], v_tests.shape[0])) + steer_result = np.zeros((steer.shape[0], v_tests.shape[0])) + for i in range(steer.shape[0]): + for j in range(v_tests.shape[0]): + v_result[i, j], acc_result[i, j], steer_result[i, j] = self.sim( + v_tests[j], starting_acc, target_acc, steer[i], steer[i], iter_times + ) + fig = plt.figure() + ax = fig.add_subplot(111, projection="3d") + ax.plot_surface(np.tile(steer, (v_tests.shape[0], 1)).T, v_result, steer_result) + ax.set_xlabel("steer_input [rad]") + ax.set_ylabel("vel [m/s]") + ax.set_zlabel("steer_sim [rad]") + fig.suptitle(str(iter_times * drive_functions.mpc_time_step) + " sec simulation") + plt.show() + + +def polynomial_regression( + X, + Y, + alpha_1, + alpha_2, + use_polynomial_reg, + use_selected_polynomial, + deg, + fit_intercept, + use_intercept, +): + polynomial_features = PolynomialFeatures(degree=deg, include_bias=False) + alpha = alpha_1 + alpha_2 + if use_polynomial_reg: + if use_selected_polynomial: + clf_1 = linear_model.ElasticNet( + fit_intercept=fit_intercept, alpha=alpha, l1_ratio=alpha_1 / alpha, max_iter=100000 + ) + clf_2 = linear_model.ElasticNet( + fit_intercept=fit_intercept, alpha=alpha, l1_ratio=alpha_1 / alpha, max_iter=100000 + ) + clf_3 = linear_model.ElasticNet( + fit_intercept=fit_intercept, alpha=alpha, l1_ratio=alpha_1 / alpha, max_iter=100000 + ) + X_poly = polynomial_features.fit_transform(X[:, ctrl_index_for_polynomial_reg]) + Y_error = Y.copy() + A = np.zeros((Y.shape[1], X_poly.shape[1])) + b = np.zeros(Y.shape[1]) + clf_1.fit(X_poly[:, [0, 7]], Y[:, [3]]) + clf_2.fit(X_poly[:, [1, 3]], Y[:, [4]]) + clf_3.fit(X_poly[:, [2, 4]], Y[:, [5]]) + A[3, [0, 7]] = clf_1.coef_ + A[4, [1, 3]] = clf_2.coef_ + A[5, [2, 4]] = clf_3.coef_ + if fit_intercept: + b[3] = clf_1.intercept_ + b[4] = clf_2.intercept_ + b[5] = clf_3.intercept_ + Y_error[:, 3] -= clf_1.predict(X_poly[:, [0, 7]]) + Y_error[:, 4] -= clf_2.predict(X_poly[:, [1, 3]]) + Y_error[:, 5] -= clf_3.predict(X_poly[:, [2, 4]]) + if not use_intercept: + Y_error += b + b = 0 * b + return A, b, Y_error + else: + clf = linear_model.ElasticNet( + fit_intercept=fit_intercept, alpha=alpha, l1_ratio=alpha_1 / alpha, max_iter=100000 + ) + X_poly = polynomial_features.fit_transform(X[:, ctrl_index_for_polynomial_reg]) + clf.fit(X_poly, Y) + if fit_intercept: + if use_intercept: + return ( + clf.coef_, + clf.intercept_, + Y - clf.predict(X_poly), + ) + else: + return ( + clf.coef_, + 0 * clf.intercept_, + Y - clf.predict(X_poly) + clf.intercept_, + ) + else: + return clf.coef_, np.zeros(Y.shape[1]), Y - clf.predict(X_poly) + else: + poly_dim = polynomial_features.fit_transform( + X[0, ctrl_index_for_polynomial_reg].reshape(1, -1) + ).shape[1] + return np.zeros((Y.shape[1], poly_dim)), np.zeros(Y.shape[1]), Y diff --git a/control/trajectory_follower_node/config/plot_juggler_trajectory_follower.xml b/control/trajectory_follower_node/config/plot_juggler_trajectory_follower.xml index 6956db84aff56..ab127c2d47b97 100644 --- a/control/trajectory_follower_node/config/plot_juggler_trajectory_follower.xml +++ b/control/trajectory_follower_node/config/plot_juggler_trajectory_follower.xml @@ -1,5 +1,5 @@ - + @@ -9,37 +9,37 @@ - + - + - + - + - + - + - + @@ -50,12 +50,12 @@ - + - + @@ -66,12 +66,12 @@ - + - + @@ -84,22 +84,22 @@ - + - + - + - + @@ -110,12 +110,12 @@ - + - + @@ -141,52 +141,52 @@ - + - + - + - + - + - + - + - + - + - + @@ -197,7 +197,7 @@ - + @@ -209,22 +209,22 @@ - + - + - + - + @@ -241,33 +241,42 @@ - + - + + - + + + + - + + - - - - - - + + + + - - + + + + + + + + - + diff --git a/control/vehicle_cmd_gate/src/vehicle_cmd_filter.cpp b/control/vehicle_cmd_gate/src/vehicle_cmd_filter.cpp index 4431534a76a5e..b289365b46b3b 100644 --- a/control/vehicle_cmd_gate/src/vehicle_cmd_filter.cpp +++ b/control/vehicle_cmd_gate/src/vehicle_cmd_filter.cpp @@ -90,6 +90,11 @@ void VehicleCmdFilter::setParam(const VehicleCmdFilterParam & p) } } +VehicleCmdFilterParam VehicleCmdFilter::getParam() const +{ + return param_; +} + void VehicleCmdFilter::limitLongitudinalWithVel(AckermannControlCommand & input) const { input.longitudinal.speed = std::max( diff --git a/control/vehicle_cmd_gate/src/vehicle_cmd_filter.hpp b/control/vehicle_cmd_gate/src/vehicle_cmd_filter.hpp index cf7a1f627a68a..e71fb405beda1 100644 --- a/control/vehicle_cmd_gate/src/vehicle_cmd_filter.hpp +++ b/control/vehicle_cmd_gate/src/vehicle_cmd_filter.hpp @@ -58,6 +58,7 @@ class VehicleCmdFilter void setActualSteerDiffLim(LimitArray v); void setCurrentSpeed(double v) { current_speed_ = v; } void setParam(const VehicleCmdFilterParam & p); + VehicleCmdFilterParam getParam() const; void setPrevCmd(const AckermannControlCommand & v) { prev_cmd_ = v; } void limitLongitudinalWithVel(AckermannControlCommand & input) const; diff --git a/control/vehicle_cmd_gate/src/vehicle_cmd_gate.cpp b/control/vehicle_cmd_gate/src/vehicle_cmd_gate.cpp index 27592b9405fc5..ffd452db0337c 100644 --- a/control/vehicle_cmd_gate/src/vehicle_cmd_gate.cpp +++ b/control/vehicle_cmd_gate/src/vehicle_cmd_gate.cpp @@ -15,6 +15,7 @@ #include "vehicle_cmd_gate.hpp" #include "marker_helper.hpp" +#include "tier4_autoware_utils/ros/update_param.hpp" #include #include @@ -244,6 +245,76 @@ VehicleCmdGate::VehicleCmdGate(const rclcpp::NodeOptions & node_options) logger_configure_ = std::make_unique(this); published_time_publisher_ = std::make_unique(this); + + // Parameter Callback + set_param_res_ = + this->add_on_set_parameters_callback(std::bind(&VehicleCmdGate::onParameter, this, _1)); +} + +rcl_interfaces::msg::SetParametersResult VehicleCmdGate::onParameter( + const std::vector & parameters) +{ + using tier4_autoware_utils::updateParam; + // Parameter + updateParam(parameters, "use_emergency_handling", use_emergency_handling_); + updateParam( + parameters, "check_external_emergency_heartbeat", check_external_emergency_heartbeat_); + updateParam( + parameters, "system_emergency_heartbeat_timeout", system_emergency_heartbeat_timeout_); + updateParam( + parameters, "external_emergency_stop_heartbeat_timeout", + external_emergency_stop_heartbeat_timeout_); + updateParam(parameters, "stop_hold_acceleration", stop_hold_acceleration_); + updateParam(parameters, "emergency_acceleration", emergency_acceleration_); + updateParam( + parameters, "moderate_stop_service_acceleration", moderate_stop_service_acceleration_); + updateParam(parameters, "stop_check_duration", stop_check_duration_); + updateParam(parameters, "enable_cmd_limit_filter", enable_cmd_limit_filter_); + updateParam( + parameters, "filter_activated_count_threshold", filter_activated_count_threshold_); + updateParam( + parameters, "filter_activated_velocity_threshold", filter_activated_velocity_threshold_); + + // Vehicle Parameter + const auto vehicle_info = vehicle_info_util::VehicleInfoUtil(*this).getVehicleInfo(); + { + VehicleCmdFilterParam p = filter_.getParam(); + p.wheel_base = vehicle_info.wheel_base_m; + updateParam(parameters, "nominal.vel_lim", p.vel_lim); + updateParam>( + parameters, "nominal.reference_speed_points", p.reference_speed_points); + updateParam>(parameters, "nominal.steer_lim", p.steer_lim); + updateParam>(parameters, "nominal.steer_rate_lim", p.steer_rate_lim); + updateParam>(parameters, "nominal.lon_acc_lim", p.lon_acc_lim); + updateParam>(parameters, "nominal.lon_jerk_lim", p.lon_jerk_lim); + updateParam>(parameters, "nominal.lat_acc_lim", p.lat_acc_lim); + updateParam>(parameters, "nominal.lat_jerk_lim", p.lat_jerk_lim); + updateParam>( + parameters, "nominal.actual_steer_diff_lim", p.actual_steer_diff_lim); + filter_.setParam(p); + } + + { + VehicleCmdFilterParam p = filter_on_transition_.getParam(); + p.wheel_base = vehicle_info.wheel_base_m; + updateParam(parameters, "on_transition.vel_lim", p.vel_lim); + updateParam>( + parameters, "on_transition.reference_speed_points", p.reference_speed_points); + updateParam>(parameters, "on_transition.steer_lim", p.steer_lim); + updateParam>(parameters, "on_transition.steer_rate_lim", p.steer_rate_lim); + updateParam>(parameters, "on_transition.lon_acc_lim", p.lon_acc_lim); + updateParam>(parameters, "on_transition.lon_jerk_lim", p.lon_jerk_lim); + updateParam>(parameters, "on_transition.lat_acc_lim", p.lat_acc_lim); + updateParam>(parameters, "on_transition.lat_jerk_lim", p.lat_jerk_lim); + updateParam>( + parameters, "on_transition.actual_steer_diff_lim", p.actual_steer_diff_lim); + filter_on_transition_.setParam(p); + } + + rcl_interfaces::msg::SetParametersResult result; + result.successful = true; + result.reason = "success"; + return result; } bool VehicleCmdGate::isHeartbeatTimeout( diff --git a/control/vehicle_cmd_gate/src/vehicle_cmd_gate.hpp b/control/vehicle_cmd_gate/src/vehicle_cmd_gate.hpp index 1907cf123632f..85bc183361b94 100644 --- a/control/vehicle_cmd_gate/src/vehicle_cmd_gate.hpp +++ b/control/vehicle_cmd_gate/src/vehicle_cmd_gate.hpp @@ -49,6 +49,7 @@ #include #include +#include namespace vehicle_cmd_gate { @@ -111,7 +112,10 @@ class VehicleCmdGate : public rclcpp::Node rclcpp::Publisher::SharedPtr filter_activated_marker_pub_; rclcpp::Publisher::SharedPtr filter_activated_marker_raw_pub_; rclcpp::Publisher::SharedPtr filter_activated_flag_pub_; - + // Parameter callback + OnSetParametersCallbackHandle::SharedPtr set_param_res_; + rcl_interfaces::msg::SetParametersResult onParameter( + const std::vector & parameters); // Subscription rclcpp::Subscription::SharedPtr external_emergency_stop_heartbeat_sub_; rclcpp::Subscription::SharedPtr gate_mode_sub_; diff --git a/evaluator/control_evaluator/CMakeLists.txt b/evaluator/control_evaluator/CMakeLists.txt new file mode 100644 index 0000000000000..b97a14e29cdcd --- /dev/null +++ b/evaluator/control_evaluator/CMakeLists.txt @@ -0,0 +1,23 @@ +cmake_minimum_required(VERSION 3.14) +project(control_evaluator) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +find_package(pluginlib REQUIRED) + +ament_auto_add_library(${PROJECT_NAME}_node SHARED + src/${PROJECT_NAME}_node.cpp +) + +rclcpp_components_register_node(${PROJECT_NAME}_node + PLUGIN "control_diagnostics::controlEvaluatorNode" + EXECUTABLE ${PROJECT_NAME} +) + + +ament_auto_package( + INSTALL_TO_SHARE + param + launch +) diff --git a/evaluator/control_evaluator/README.md b/evaluator/control_evaluator/README.md new file mode 100644 index 0000000000000..71bd5c0142570 --- /dev/null +++ b/evaluator/control_evaluator/README.md @@ -0,0 +1,5 @@ +# Planning Evaluator + +## Purpose + +This package provides nodes that generate metrics to evaluate the quality of control. diff --git a/evaluator/control_evaluator/include/control_evaluator/control_evaluator_node.hpp b/evaluator/control_evaluator/include/control_evaluator/control_evaluator_node.hpp new file mode 100644 index 0000000000000..3a3ba47d88e03 --- /dev/null +++ b/evaluator/control_evaluator/include/control_evaluator/control_evaluator_node.hpp @@ -0,0 +1,61 @@ +// Copyright 2024 Tier IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef CONTROL_EVALUATOR__CONTROL_EVALUATOR_NODE_HPP_ +#define CONTROL_EVALUATOR__CONTROL_EVALUATOR_NODE_HPP_ + +#include "rclcpp/rclcpp.hpp" + +#include "diagnostic_msgs/msg/diagnostic_array.hpp" + +#include +#include +#include +#include +#include + +namespace control_diagnostics +{ + +using diagnostic_msgs::msg::DiagnosticArray; +using diagnostic_msgs::msg::DiagnosticStatus; + +/** + * @brief Node for control evaluation + */ +class controlEvaluatorNode : public rclcpp::Node +{ +public: + explicit controlEvaluatorNode(const rclcpp::NodeOptions & node_options); + + /** + * @brief publish the given metric statistic + */ + DiagnosticStatus generateDiagnosticStatus(const bool is_emergency_brake) const; + void onDiagnostics(const DiagnosticArray::ConstSharedPtr diag_msg); + void onTimer(); + +private: + rclcpp::Subscription::SharedPtr control_diag_sub_; + rclcpp::Publisher::SharedPtr metrics_pub_; + + // Calculator + // Metrics + std::deque stamps_; + DiagnosticArray metrics_msg_; + rclcpp::TimerBase::SharedPtr timer_; +}; +} // namespace control_diagnostics + +#endif // CONTROL_EVALUATOR__CONTROL_EVALUATOR_NODE_HPP_ diff --git a/evaluator/control_evaluator/launch/control_evaluator.launch.xml b/evaluator/control_evaluator/launch/control_evaluator.launch.xml new file mode 100644 index 0000000000000..75012791888a6 --- /dev/null +++ b/evaluator/control_evaluator/launch/control_evaluator.launch.xml @@ -0,0 +1,12 @@ + + + + + + + + + + + + diff --git a/evaluator/control_evaluator/package.xml b/evaluator/control_evaluator/package.xml new file mode 100644 index 0000000000000..10686e9b73761 --- /dev/null +++ b/evaluator/control_evaluator/package.xml @@ -0,0 +1,29 @@ + + + + control_evaluator + 0.1.0 + ROS 2 node for evaluating control + Daniel SANCHEZ + takayuki MUROOKA + Apache License 2.0 + + Daniel SANCHEZ + takayuki MUROOKA + + ament_cmake_auto + autoware_cmake + + diagnostic_msgs + pluginlib + rclcpp + rclcpp_components + + ament_cmake_ros + ament_lint_auto + autoware_lint_common + + + ament_cmake + + diff --git a/evaluator/control_evaluator/param/control_evaluator.defaults.yaml b/evaluator/control_evaluator/param/control_evaluator.defaults.yaml new file mode 100644 index 0000000000000..a20dbd7ffd3d9 --- /dev/null +++ b/evaluator/control_evaluator/param/control_evaluator.defaults.yaml @@ -0,0 +1,2 @@ +/**: + ros__parameters: diff --git a/evaluator/control_evaluator/src/control_evaluator_node.cpp b/evaluator/control_evaluator/src/control_evaluator_node.cpp new file mode 100644 index 0000000000000..d575a35a2389f --- /dev/null +++ b/evaluator/control_evaluator/src/control_evaluator_node.cpp @@ -0,0 +1,86 @@ +// Copyright 2024 Tier IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "control_evaluator/control_evaluator_node.hpp" + +#include +#include +#include +#include +#include +#include +#include + +namespace control_diagnostics +{ +controlEvaluatorNode::controlEvaluatorNode(const rclcpp::NodeOptions & node_options) +: Node("control_evaluator", node_options) +{ + using std::placeholders::_1; + + control_diag_sub_ = create_subscription( + "~/input/diagnostics", 1, std::bind(&controlEvaluatorNode::onDiagnostics, this, _1)); + + // Publisher + metrics_pub_ = create_publisher("~/metrics", 1); + + // Timer callback to publish evaluator diagnostics + using namespace std::literals::chrono_literals; + timer_ = + rclcpp::create_timer(this, get_clock(), 100ms, std::bind(&controlEvaluatorNode::onTimer, this)); +} + +DiagnosticStatus controlEvaluatorNode::generateDiagnosticStatus(const bool is_emergency_brake) const +{ + DiagnosticStatus status; + status.level = status.OK; + status.name = "autonomous_emergency_braking"; + diagnostic_msgs::msg::KeyValue key_value; + key_value.key = "decision"; + key_value.value = (is_emergency_brake) ? "stop" : "none"; + status.values.push_back(key_value); + return status; +} + +void controlEvaluatorNode::onTimer() +{ + if (!metrics_msg_.status.empty()) { + metrics_pub_->publish(metrics_msg_); + metrics_msg_.status.clear(); + } +} + +void controlEvaluatorNode::onDiagnostics(const DiagnosticArray::ConstSharedPtr diag_msg) +{ + const auto start = now(); + const auto aeb_status = + std::find_if(diag_msg->status.begin(), diag_msg->status.end(), [](const auto & status) { + const bool aeb_found = status.name.find("autonomous_emergency_braking") != std::string::npos; + return aeb_found; + }); + + if (aeb_status == diag_msg->status.end()) return; + + const bool is_emergency_brake = (aeb_status->level == DiagnosticStatus::ERROR); + metrics_msg_.header.stamp = now(); + metrics_msg_.status.emplace_back(generateDiagnosticStatus(is_emergency_brake)); + + const auto runtime = (now() - start).seconds(); + RCLCPP_DEBUG(get_logger(), "control evaluation calculation time: %2.2f ms", runtime * 1e3); +} + +} // namespace control_diagnostics + +#include "rclcpp_components/register_node_macro.hpp" +RCLCPP_COMPONENTS_REGISTER_NODE(control_diagnostics::controlEvaluatorNode) diff --git a/evaluator/perception_online_evaluator/CMakeLists.txt b/evaluator/perception_online_evaluator/CMakeLists.txt index e1cd0546ea94a..b323d07a882e8 100644 --- a/evaluator/perception_online_evaluator/CMakeLists.txt +++ b/evaluator/perception_online_evaluator/CMakeLists.txt @@ -6,12 +6,11 @@ autoware_package() find_package(pluginlib REQUIRED) -find_package(glog REQUIRED) - ament_auto_add_library(${PROJECT_NAME}_node SHARED src/metrics_calculator.cpp src/${PROJECT_NAME}_node.cpp src/metrics/deviation_metrics.cpp + src/metrics/detection_count.cpp src/utils/marker_utils.cpp src/utils/objects_filtering.cpp ) @@ -31,7 +30,7 @@ target_link_libraries(${PROJECT_NAME}_node glog::glog) if(BUILD_TESTING) ament_add_ros_isolated_gtest(test_${PROJECT_NAME} test/test_perception_online_evaluator_node.cpp - TIMEOUT 180 + TIMEOUT 300 ) target_link_libraries(test_${PROJECT_NAME} ${PROJECT_NAME}_node diff --git a/evaluator/perception_online_evaluator/README.md b/evaluator/perception_online_evaluator/README.md index 4fcd4fdf9cc84..7ee93d2ffddf2 100644 --- a/evaluator/perception_online_evaluator/README.md +++ b/evaluator/perception_online_evaluator/README.md @@ -8,14 +8,23 @@ This module allows for the evaluation of how accurately perception results are g ## Inner-workings / Algorithms -- Calculates lateral deviation between the predicted path and the actual traveled trajectory. -- Calculates lateral deviation between the smoothed traveled trajectory and the perceived position to evaluate the stability of lateral position recognition. -- Calculates yaw deviation between the smoothed traveled trajectory and the perceived position to evaluate the stability of yaw recognition. -- Calculates yaw rate based on the yaw of the object received in the previous cycle to evaluate the stability of the yaw rate recognition. +The evaluated metrics are as follows: + +- predicted_path_deviation +- predicted_path_deviation_variance +- lateral_deviation +- yaw_deviation +- yaw_rate +- total_objects_count +- average_objects_count +- interval_objects_count ### Predicted Path Deviation / Predicted Path Deviation Variance -Compare the predicted path of past objects with their actual traveled path to determine the deviation. For each object, calculate the mean distance between the predicted path points and the corresponding points on the actual path, up to the specified time step. In other words, this calculates the Average Displacement Error (ADE). The target object to be evaluated is the object from $T_N$ seconds ago, where $T_N$ is the maximum value of the prediction time horizon $[T_1, T_2, ..., T_N]$. +Compare the predicted path of past objects with their actual traveled path to determine the deviation for **MOVING OBJECTS**. For each object, calculate the mean distance between the predicted path points and the corresponding points on the actual path, up to the specified time step. In other words, this calculates the Average Displacement Error (ADE). The target object to be evaluated is the object from $T_N$ seconds ago, where $T_N$ is the maximum value of the prediction time horizon $[T_1, T_2, ..., T_N]$. + +> [!NOTE] +> The object from $T_N$ seconds ago is the target object for all metrics. This is to unify the time of the target object across metrics. ![path_deviation_each_object](./images/path_deviation_each_object.drawio.svg) @@ -64,6 +73,86 @@ $$ The actual metric name is determined by the object class and time horizon. For example, `predicted_path_deviation_variance_CAR_5.00` +### Lateral Deviation + +Calculates lateral deviation between the smoothed traveled trajectory and the perceived position to evaluate the stability of lateral position recognition for **MOVING OBJECTS**. The smoothed traveled trajectory is calculated by applying a centered moving average filter whose window size is specified by the parameter `smoothing_window_size`. The lateral deviation is calculated by comparing the smoothed traveled trajectory with the perceived position of the past object whose timestamp is $T=T_n$ seconds ago. For stopped objects, the smoothed traveled trajectory is unstable, so this metric is not calculated. + +![lateral_deviation](./images/lateral_deviation.drawio.svg) + +### Yaw Deviation + +Calculates the deviation between the recognized yaw angle of an past object and the yaw azimuth angle of the smoothed traveled trajectory for **MOVING OBJECTS**. The smoothed traveled trajectory is calculated by applying a centered moving average filter whose window size is specified by the parameter `smoothing_window_size`. The yaw deviation is calculated by comparing the yaw azimuth angle of smoothed traveled trajectory with the perceived orientation of the past object whose timestamp is $T=T_n$ seconds ago. +For stopped objects, the smoothed traveled trajectory is unstable, so this metric is not calculated. + +![yaw_deviation](./images/yaw_deviation.drawio.svg) + +### Yaw Rate + +Calculates the yaw rate of an object based on the change in yaw angle from the previous time step. It is evaluated for **STATIONARY OBJECTS** and assesses the stability of yaw rate recognition. The yaw rate is calculated by comparing the yaw angle of the past object with the yaw angle of the object received in the previous cycle. Here, t2 is the timestamp that is $T_n$ seconds ago. + +![yaw_rate](./images/yaw_rate.drawio.svg) + +### Object Counts + +Counts the number of detections for each object class within the specified detection range. These metrics are measured for the most recent object not past objects. + +![detection_counts](./images/detection_counts.drawio.svg) + +In the provided illustration, the range $R$ is determined by a combination of lists of radii (e.g., $r_1, r_2, \ldots$) and heights (e.g., $h_1, h_2, \ldots$). +For example, + +- the number of CAR in range $R = (r_1, h_1)$ equals 1 +- the number of CAR in range $R = (r_1, h_2)$ equals 2 +- the number of CAR in range $R = (r_2, h_1)$ equals 3 +- the number of CAR in range $R = (r_2, h_2)$ equals 4 + +#### Total Object Count + +Counts the number of unique objects for each class within the specified detection range. The total object count is calculated as follows: + +$$ +\begin{align} +\text{Total Object Count (Class, Range)} = \left| \bigcup_{t=0}^{T_{\text{now}}} \{ \text{uuid} \mid \text{class}(t, \text{uuid}) = C \wedge \text{position}(t, \text{uuid}) \in R \} \right| +\end{align} +$$ + +where: + +- $\bigcup$ represents the union across all frames from $t = 0$ to $T_{\text{now}}$, which ensures that each uuid is counted only once. +- $\text{class}(t, \text{uuid}) = C$ specifies that the object with uuid at time $t$ belongs to class $C$. +- $\text{position}(t, \text{uuid}) \in R$ indicates that the object with uuid at time $t$ is within the specified range $R$. +- $\left| \{ \ldots \} \right|$ denotes the cardinality of the set, which counts the number of unique uuids that meet the class and range criteria across all considered times. + +#### Average Object Count + +Counts the average number of objects for each class within the specified detection range. This metric measures how many objects were detected in one frame, without considering uuids. The average object count is calculated as follows: + +$$ +\begin{align} +\text{Average Object Count (Class, Range)} = \frac{1}{N} \sum_{t=0}^{T_{\text{now}}} \left| \{ \text{object} \mid \text{class}(t, \text{object}) = C \wedge \text{position}(t, \text{object}) \in R \} \right| +\end{align} +$$ + +where: + +- $N$ represents the total number of frames within the time period time to $T\_{\text{now}}$ (it is precisely `detection_count_purge_seconds`) +- $text{object}$ denotes the number of objects that meet the class and range criteria at time $t$. + +#### Interval Object Count + +Counts the average number of objects for each class within the specified detection range over the last `objects_count_window_seconds`. This metric measures how many objects were detected in one frame, without considering uuids. The interval object count is calculated as follows: + +$$ +\begin{align} +\text{Interval Object Count (Class, Range)} = \frac{1}{W} \sum_{t=T_{\text{now}} - T_W}^{T_{\text{now}}} \left| \{ \text{object} \mid \text{class}(t, \text{object}) = C \wedge \text{position}(t, \text{object}) \in R \} \right| +\end{align} +$$ + +where: + +- $W$ represents the total number of frames within the last `objects_count_window_seconds`. +- $T_W$ represents the time window `objects_count_window_seconds` + ## Inputs / Outputs | Name | Type | Description | @@ -74,14 +163,24 @@ The actual metric name is determined by the object class and time horizon. For e ## Parameters -| Name | Type | Description | -| --------------------------------- | ------------ | ------------------------------------------------------------------------------------------------ | -| `selected_metrics` | List | Metrics to be evaluated, such as lateral deviation, yaw deviation, and predicted path deviation. | -| `smoothing_window_size` | Integer | Determines the window size for smoothing path, should be an odd number. | -| `prediction_time_horizons` | list[double] | Time horizons for prediction evaluation in seconds. | -| `stopped_velocity_threshold` | double | threshold velocity to check if vehicle is stopped | -| `target_object.*.check_deviation` | bool | Whether to check deviation for specific object types (car, truck, etc.). | -| `debug_marker.*` | bool | Debugging parameters for marker visualization (history path, predicted path, etc.). | +| Name | Type | Description | +| ------------------------------------------------------ | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- | +| `selected_metrics` | List | Metrics to be evaluated, such as lateral deviation, yaw deviation, and predicted path deviation. | +| `smoothing_window_size` | Integer | Determines the window size for smoothing path, should be an odd number. | +| `prediction_time_horizons` | list[double] | Time horizons for prediction evaluation in seconds. | +| `stopped_velocity_threshold` | double | threshold velocity to check if vehicle is stopped | +| `detection_radius_list` | list[double] | Detection radius for objects to be evaluated.(used for objects count only) | +| `detection_height_list` | list[double] | Detection height for objects to be evaluated. (used for objects count only) | +| `detection_count_purge_seconds` | double | Time window for purging object detection counts. | +| `objects_count_window_seconds` | double | Time window for keeping object detection counts. The number of object detections within this time window is stored in `detection_count_vector_` | +| `target_object.*.check_lateral_deviation` | bool | Whether to check lateral deviation for specific object types (car, truck, etc.). | +| `target_object.*.check_yaw_deviation` | bool | Whether to check yaw deviation for specific object types (car, truck, etc.). | +| `target_object.*.check_predicted_path_deviation` | bool | Whether to check predicted path deviation for specific object types (car, truck, etc.). | +| `target_object.*.check_yaw_rate` | bool | Whether to check yaw rate for specific object types (car, truck, etc.). | +| `target_object.*.check_total_objects_count` | bool | Whether to check total object count for specific object types (car, truck, etc.). | +| `target_object.*.check_average_objects_count` | bool | Whether to check average object count for specific object types (car, truck, etc.). | +| `target_object.*.check_interval_average_objects_count` | bool | Whether to check interval average object count for specific object types (car, truck, etc.). | +| `debug_marker.*` | bool | Debugging parameters for marker visualization (history path, predicted path, etc.). | ## Assumptions / Known limits diff --git a/evaluator/perception_online_evaluator/images/detection_counts.drawio.svg b/evaluator/perception_online_evaluator/images/detection_counts.drawio.svg new file mode 100644 index 0000000000000..f6dc7431e7ae6 --- /dev/null +++ b/evaluator/perception_online_evaluator/images/detection_counts.drawio.svg @@ -0,0 +1,445 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
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+ + + + + + + + + + + + + + + + + + + + + + +
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+ + `r_2` + + + + + + + + + + +
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+ + `r_1` + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + +
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+ + `h_1` + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + +
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+ + `h_2` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/evaluator/perception_online_evaluator/images/lateral_deviation.drawio.svg b/evaluator/perception_online_evaluator/images/lateral_deviation.drawio.svg new file mode 100644 index 0000000000000..5d7b34323db9a --- /dev/null +++ b/evaluator/perception_online_evaluator/images/lateral_deviation.drawio.svg @@ -0,0 +1,296 @@ + + + + + + + + + + + + + + + + + + +
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+ recognized object +
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+ + recognized object + + + + + + + + + + +
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+ smoothed traveled trajectory +
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+ + smoothed traveled trajectory + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - T +
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+ + `T_{now}`... + + + + + + + + + + +
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+ + `T_{now}` + + + + + diff --git a/evaluator/perception_online_evaluator/images/yaw_deviation.drawio.svg b/evaluator/perception_online_evaluator/images/yaw_deviation.drawio.svg new file mode 100644 index 0000000000000..f0319e9a38b7c --- /dev/null +++ b/evaluator/perception_online_evaluator/images/yaw_deviation.drawio.svg @@ -0,0 +1,302 @@ + + + + + + + + + + + + + + + + + + +
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+ recognized object +
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+ + recognized object + + + + + + + + + + +
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+ smoothed traveled trajectory +
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+ + smoothed traveled trajectory + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - T +
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+ + `T_{now}` + + + + + diff --git a/evaluator/perception_online_evaluator/images/yaw_rate.drawio.svg b/evaluator/perception_online_evaluator/images/yaw_rate.drawio.svg new file mode 100644 index 0000000000000..eeabd7dca8d43 --- /dev/null +++ b/evaluator/perception_online_evaluator/images/yaw_rate.drawio.svg @@ -0,0 +1,381 @@ + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + +
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+ + `t_2` + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + +
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+ + `t_1` + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + `\Deltayaw` + + + + + + + + + + +
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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + `\omega_{yaw} = (\Delta yaw) /... + + + + + + + + diff --git a/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/detection_count.hpp b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/detection_count.hpp new file mode 100644 index 0000000000000..5715f22669fdc --- /dev/null +++ b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/detection_count.hpp @@ -0,0 +1,149 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef PERCEPTION_ONLINE_EVALUATOR__METRICS__DETECTION_COUNT_HPP_ +#define PERCEPTION_ONLINE_EVALUATOR__METRICS__DETECTION_COUNT_HPP_ + +#include "perception_online_evaluator/parameters.hpp" +#include "perception_online_evaluator/stat.hpp" +#include "tf2_ros/buffer.h" + +#include + +#include "autoware_auto_perception_msgs/msg/object_classification.hpp" +#include "autoware_auto_perception_msgs/msg/predicted_objects.hpp" +#include + +#include +#include +#include +#include +#include +#include +#include + +namespace perception_diagnostics +{ +namespace metrics +{ +using autoware_auto_perception_msgs::msg::ObjectClassification; +using autoware_auto_perception_msgs::msg::PredictedObjects; + +struct DetectionRange +{ + double radius; + double height; + + DetectionRange(double radius, double height) : radius(radius), height(height) {} + + std::string toString() const + { + std::ostringstream oss; + oss << std::fixed << std::setprecision(2); + oss << "r" << radius << "_h" << height; + return oss.str(); + } +}; +using DetectionRanges = std::vector; + +/* + * @brief Class to count objects detected within a certain range for each class + * The overall frame is not eternal, and data older than the purge seconds is deleted to prevent + memory bloat. + 1. Count the total number of unique objects detected across the overall frame. Data older than the + purge seconds is deleted to prevent memory bloat. + 2. Calculate the average number of objects detected in each frame across the overall frame. + 3. Calculate the average number of objects detected in each frame within a certain time frame. + */ +class DetectionCounter +{ +public: + /* + * @brief Constructor + * @param parameters Parameters for the perception online evaluator + */ + explicit DetectionCounter(const std::shared_ptr & parameters) + : parameters_(parameters) + { + } + /* + * @brief Add objects to the detection counter + * @param objects Predicted objects + * @param tf_buffer tf2 buffer for transforming object poses + */ + void addObjects(const PredictedObjects & objects, const tf2_ros::Buffer & tf_buffer); + + /* + * @brief Get the average count of objects detected in the last `seconds` seconds + * @param seconds Time window in seconds + * @return Map of classification to range to average count + */ + std::unordered_map> getAverageCount( + double seconds) const; + + /* + * @brief Get the overall average count of objects detected + * @return Map of classification to range to average count + */ + std::unordered_map> getOverallAverageCount() + const; + + /* + * @brief Get the total count of objects detected + * @return Map of classification to range to total count + */ + std::unordered_map> getTotalCount() const; + +private: + /* + * @brief Initialize the detection map + */ + void initializeDetectionMap(); + + /* + * @brief Update the detection map with a new detection + * @param uuid UUID of the detected object + * @param classification Classification of the detected object + * @param range Range of the detected object + * @param timestamp Timestamp of the detection + */ + void updateDetectionMap( + const std::string uuid, const std::uint8_t classification, const std::string & range, + const rclcpp::Time & timestamp); + + /* + * @brief Purge old records from the detection map + * @param current_time Current time + */ + void purgeOldRecords(rclcpp::Time current_time); + + /* + * @brief Get the DetectionRanges from parameters + * @return Detection ranges + */ + DetectionRanges getRanges() const; + + std::shared_ptr parameters_; + std::set unique_timestamps_; + + // Structures for storing detection counts and UUIDs for uniqueness checks + std::unordered_map>> + time_series_counts_; + std::unordered_map>> + seen_uuids_; +}; +} // namespace metrics +} // namespace perception_diagnostics + +#endif // PERCEPTION_ONLINE_EVALUATOR__METRICS__DETECTION_COUNT_HPP_ diff --git a/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/metric.hpp b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/metric.hpp index e11ae89e48106..926fbb7435f3a 100644 --- a/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/metric.hpp +++ b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics/metric.hpp @@ -32,6 +32,7 @@ enum class Metric { yaw_deviation, predicted_path_deviation, yaw_rate, + objects_count, SIZE, }; @@ -47,20 +48,23 @@ static const std::unordered_map str_to_metric = { {"lateral_deviation", Metric::lateral_deviation}, {"yaw_deviation", Metric::yaw_deviation}, {"predicted_path_deviation", Metric::predicted_path_deviation}, - {"yaw_rate", Metric::yaw_rate}}; + {"yaw_rate", Metric::yaw_rate}, + {"objects_count", Metric::objects_count}}; static const std::unordered_map metric_to_str = { {Metric::lateral_deviation, "lateral_deviation"}, {Metric::yaw_deviation, "yaw_deviation"}, {Metric::predicted_path_deviation, "predicted_path_deviation"}, - {Metric::yaw_rate, "yaw_rate"}}; + {Metric::yaw_rate, "yaw_rate"}, + {Metric::objects_count, "objects_count"}}; // Metrics descriptions static const std::unordered_map metric_descriptions = { {Metric::lateral_deviation, "Lateral_deviation[m]"}, {Metric::yaw_deviation, "Yaw_deviation[rad]"}, {Metric::predicted_path_deviation, "Predicted_path_deviation[m]"}, - {Metric::yaw_rate, "Yaw_rate[rad/s]"}}; + {Metric::yaw_rate, "Yaw_rate[rad/s]"}, + {Metric::objects_count, "objects_count"}}; namespace details { diff --git a/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics_calculator.hpp b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics_calculator.hpp index ee0a1eac73762..96b1c01ee2d16 100644 --- a/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics_calculator.hpp +++ b/evaluator/perception_online_evaluator/include/perception_online_evaluator/metrics_calculator.hpp @@ -15,21 +15,27 @@ #ifndef PERCEPTION_ONLINE_EVALUATOR__METRICS_CALCULATOR_HPP_ #define PERCEPTION_ONLINE_EVALUATOR__METRICS_CALCULATOR_HPP_ +#include "perception_online_evaluator/metrics/detection_count.hpp" #include "perception_online_evaluator/metrics/deviation_metrics.hpp" #include "perception_online_evaluator/metrics/metric.hpp" #include "perception_online_evaluator/parameters.hpp" #include "perception_online_evaluator/stat.hpp" #include "perception_online_evaluator/utils/objects_filtering.hpp" +#include "tf2_ros/buffer.h" #include +#include "autoware_auto_perception_msgs/msg/object_classification.hpp" #include "autoware_auto_perception_msgs/msg/predicted_objects.hpp" #include "geometry_msgs/msg/pose.hpp" #include #include #include +#include #include +#include +#include #include #include @@ -39,6 +45,7 @@ using autoware_auto_perception_msgs::msg::PredictedObject; using autoware_auto_perception_msgs::msg::PredictedObjects; using geometry_msgs::msg::Point; using geometry_msgs::msg::Pose; +using metrics::DetectionCounter; using unique_identifier_msgs::msg::UUID; struct ObjectData @@ -80,7 +87,9 @@ class MetricsCalculator { public: explicit MetricsCalculator(const std::shared_ptr & parameters) - : parameters_(parameters){}; + : parameters_(parameters), detection_counter_(parameters) + { + } /** * @brief calculate @@ -92,8 +101,11 @@ class MetricsCalculator /** * @brief set the dynamic objects used to calculate obstacle metrics * @param [in] objects predicted objects + * @param [in] tf_buffer tf buffer */ - void setPredictedObjects(const PredictedObjects & objects); + void setPredictedObjects(const PredictedObjects & objects, const tf2_ros::Buffer & tf_buffer); + + void updateObjectsCountMap(const PredictedObjects & objects, const tf2_ros::Buffer & tf_buffer); HistoryPathMap getHistoryPathMap() const { return history_path_map_; } ObjectDataMap getDebugObjectData() const { return debug_target_object_; } @@ -107,6 +119,8 @@ class MetricsCalculator rclcpp::Time current_stamp_; + DetectionCounter detection_counter_; + // debug mutable ObjectDataMap debug_target_object_; @@ -129,6 +143,7 @@ class MetricsCalculator PredictedPathDeviationMetrics calcPredictedPathDeviationMetrics( const PredictedObjects & objects, const double time_horizon) const; MetricStatMap calcYawRateMetrics(const ClassObjectsMap & class_objects_map) const; + MetricStatMap calcObjectsCountMetrics() const; bool hasPassedTime(const rclcpp::Time stamp) const; bool hasPassedTime(const std::string uuid, const rclcpp::Time stamp) const; diff --git a/evaluator/perception_online_evaluator/include/perception_online_evaluator/parameters.hpp b/evaluator/perception_online_evaluator/include/perception_online_evaluator/parameters.hpp index e15ae2f350954..b4cf23b85effb 100644 --- a/evaluator/perception_online_evaluator/include/perception_online_evaluator/parameters.hpp +++ b/evaluator/perception_online_evaluator/include/perception_online_evaluator/parameters.hpp @@ -28,7 +28,13 @@ namespace perception_diagnostics struct ObjectParameter { - bool check_deviation{false}; + bool check_lateral_deviation{false}; + bool check_yaw_deviation{false}; + bool check_predicted_path_deviation{false}; + bool check_yaw_rate{false}; + bool check_total_objects_count{false}; + bool check_average_objects_count{false}; + bool check_interval_average_objects_count{false}; }; struct DebugMarkerParameter @@ -49,6 +55,10 @@ struct Parameters size_t smoothing_window_size{0}; std::vector prediction_time_horizons; double stopped_velocity_threshold{0.0}; + std::vector detection_radius_list; + std::vector detection_height_list; + double detection_count_purge_seconds; + double objects_count_window_seconds; DebugMarkerParameter debug_marker_parameters; // parameters depend on object class std::unordered_map object_parameters; diff --git a/evaluator/perception_online_evaluator/include/perception_online_evaluator/perception_online_evaluator_node.hpp b/evaluator/perception_online_evaluator/include/perception_online_evaluator/perception_online_evaluator_node.hpp index b7535935ccd5f..e5c41ff28c4da 100644 --- a/evaluator/perception_online_evaluator/include/perception_online_evaluator/perception_online_evaluator_node.hpp +++ b/evaluator/perception_online_evaluator/include/perception_online_evaluator/perception_online_evaluator_node.hpp @@ -40,6 +40,7 @@ using autoware_auto_perception_msgs::msg::PredictedObjects; using diagnostic_msgs::msg::DiagnosticArray; using diagnostic_msgs::msg::DiagnosticStatus; using nav_msgs::msg::Odometry; +using TFMessage = tf2_msgs::msg::TFMessage; using MarkerArray = visualization_msgs::msg::MarkerArray; diff --git a/evaluator/perception_online_evaluator/package.xml b/evaluator/perception_online_evaluator/package.xml index 18dde41c99566..3f855e2f1f887 100644 --- a/evaluator/perception_online_evaluator/package.xml +++ b/evaluator/perception_online_evaluator/package.xml @@ -21,8 +21,8 @@ diagnostic_msgs eigen geometry_msgs + glog lanelet2_extension - libgoogle-glog-dev motion_utils nav_msgs object_recognition_utils diff --git a/evaluator/perception_online_evaluator/param/perception_online_evaluator.defaults.yaml b/evaluator/perception_online_evaluator/param/perception_online_evaluator.defaults.yaml index 46ea68c991090..807f247807d98 100644 --- a/evaluator/perception_online_evaluator/param/perception_online_evaluator.defaults.yaml +++ b/evaluator/perception_online_evaluator/param/perception_online_evaluator.defaults.yaml @@ -5,6 +5,7 @@ - yaw_deviation - predicted_path_deviation - yaw_rate + - objects_count # this should be an odd number, because it includes the target point smoothing_window_size: 11 @@ -12,24 +13,75 @@ prediction_time_horizons: [1.0, 2.0, 3.0, 5.0] stopped_velocity_threshold: 1.0 - + detection_radius_list: [50.0, 100.0, 150.0, 200.0] + detection_height_list: [10.0] + detection_count_purge_seconds: 36000.0 + objects_count_window_seconds: 1.0 target_object: car: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false truck: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false bus: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false trailer: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false bicycle: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false motorcycle: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false pedestrian: - check_deviation: true + check_lateral_deviation: true + check_yaw_deviation: true + check_predicted_path_deviation: true + check_yaw_rate: true + check_total_objects_count: true + check_average_objects_count: false + check_interval_average_objects_count: false unknown: - check_deviation: false + check_lateral_deviation: false + check_yaw_deviation: false + check_predicted_path_deviation: false + check_yaw_rate: false + check_total_objects_count: true + check_average_objects_count: true + check_interval_average_objects_count: true debug_marker: history_path: false diff --git a/evaluator/perception_online_evaluator/src/metrics/detection_count.cpp b/evaluator/perception_online_evaluator/src/metrics/detection_count.cpp new file mode 100644 index 0000000000000..047d278334eb1 --- /dev/null +++ b/evaluator/perception_online_evaluator/src/metrics/detection_count.cpp @@ -0,0 +1,234 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "perception_online_evaluator/metrics/detection_count.hpp" + +#include "object_recognition_utils/object_recognition_utils.hpp" +#include "perception_online_evaluator/utils/objects_filtering.hpp" +#include "tier4_autoware_utils/geometry/geometry.hpp" + +#include + +namespace perception_diagnostics +{ +namespace metrics +{ +using tier4_autoware_utils::toHexString; + +bool isCountObject( + const std::uint8_t classification, const std::unordered_map & params) +{ + const auto & p = params; + + if (p.find(classification) == p.end()) { + return false; + } + + return p.at(classification).check_total_objects_count || + p.at(classification).check_average_objects_count || + p.at(classification).check_interval_average_objects_count; +} + +DetectionRanges DetectionCounter::getRanges() const +{ + DetectionRanges ranges; + for (const auto & radius : parameters_->detection_radius_list) { + for (const auto & height : parameters_->detection_height_list) { + ranges.push_back(DetectionRange(radius, height)); + } + } + + return ranges; +} + +void DetectionCounter::addObjects( + const PredictedObjects & objects, const tf2_ros::Buffer & tf_buffer) +{ + // initialize the data structures if new class or new range is detected + initializeDetectionMap(); + + const auto objects_frame_id = objects.header.frame_id; + geometry_msgs::msg::TransformStamped transform_stamped; + try { + transform_stamped = tf_buffer.lookupTransform( + "base_link", objects_frame_id, tf2::TimePointZero, tf2::durationFromSec(1.0)); + } catch (const tf2::TransformException & ex) { + return; + } + + const auto timestamp = objects.header.stamp; + unique_timestamps_.insert(timestamp); + + for (const auto & object : objects.objects) { + const auto uuid = toHexString(object.object_id); + const auto label = object_recognition_utils::getHighestProbLabel(object.classification); + if (!isCountObject(label, parameters_->object_parameters)) { + continue; + } + for (const auto & range : getRanges()) { + geometry_msgs::msg::PoseStamped pose_in, pose_out; + pose_in.header.frame_id = objects_frame_id; + pose_in.pose = object.kinematics.initial_pose_with_covariance.pose; + + // Transform the object's pose into the 'base_link' coordinate frame + tf2::doTransform(pose_in, pose_out, transform_stamped); + + const double distance_to_base_link = + std::hypot(pose_out.pose.position.x, pose_out.pose.position.y); + + // If the pose is within the detection_radius and below a detection_height, increment the + // count + const bool is_within_detection_radius = distance_to_base_link < range.radius; + const bool is_below_detection_height = pose_out.pose.position.z < range.height; + if (is_within_detection_radius && is_below_detection_height) { + updateDetectionMap(uuid, label, range.toString(), timestamp); + } + } + } +} + +void DetectionCounter::initializeDetectionMap() +{ + for (std::uint8_t i = ObjectClassification::UNKNOWN; i < ObjectClassification::PEDESTRIAN + 1; + ++i) { + for (const auto & range : getRanges()) { + std::string range_str = range.toString(); + if (time_series_counts_.find(i) == time_series_counts_.end()) { + time_series_counts_[i][range_str] = std::vector(); + seen_uuids_[i][range_str] = std::set(); + } else if (time_series_counts_[i].find(range_str) == time_series_counts_[i].end()) { + time_series_counts_[i][range_str] = std::vector(); + seen_uuids_[i][range_str] = std::set(); + } + } + } +} + +void DetectionCounter::updateDetectionMap( + const std::string uuid, const std::uint8_t classification, const std::string & range, + const rclcpp::Time & timestamp) +{ + seen_uuids_[classification][range].insert(uuid); + + // Record the detection time for averaging + time_series_counts_[classification][range].push_back(timestamp); + + // Purge old records if necessary + purgeOldRecords(timestamp); +} + +std::unordered_map> +DetectionCounter::getAverageCount(double seconds) const +{ + std::unordered_map> averages; + if (unique_timestamps_.size() == 0) { + return averages; + } + const rclcpp::Time cutoff_time = + *unique_timestamps_.rbegin() - rclcpp::Duration::from_seconds(seconds); + + for (auto & [classification, range_map] : time_series_counts_) { + if ( + parameters_->object_parameters.find(classification) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(classification).check_interval_average_objects_count) { + continue; + } + for (auto & [range, timestamps] : range_map) { + // Calculate the number of detections within the given time window + const size_t count = std::count_if( + timestamps.begin(), timestamps.end(), + [&](const rclcpp::Time & time) { return time >= cutoff_time; }); + + // Calculate the number of unique frames within the given time window + const size_t frame_count = std::count_if( + unique_timestamps_.begin(), unique_timestamps_.end(), + [&](const rclcpp::Time & time) { return time >= cutoff_time; }); + + if (frame_count > 0) { + averages[classification][range] = static_cast(count) / frame_count; + } else { + averages[classification][range] = 0; + } + } + } + + return averages; +} + +std::unordered_map> +DetectionCounter::getOverallAverageCount() const +{ + std::unordered_map> averages; + + for (auto & [classification, range_map] : time_series_counts_) { + if ( + parameters_->object_parameters.find(classification) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(classification).check_average_objects_count) { + continue; + } + for (auto & [range, timestamps] : range_map) { + const size_t count = timestamps.size(); + const size_t frame_count = unique_timestamps_.size(); + if (frame_count > 0) { + averages[classification][range] = static_cast(count) / frame_count; + } else { + averages[classification][range] = 0; + } + } + } + + return averages; +} + +std::unordered_map> +DetectionCounter::getTotalCount() const +{ + std::unordered_map> total_counts; + for (auto & [classification, range_map] : seen_uuids_) { + if ( + parameters_->object_parameters.find(classification) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(classification).check_total_objects_count) { + continue; + } + for (auto & [range, uuids] : range_map) { + total_counts[classification][range] = uuids.size(); + } + } + + return total_counts; +} + +void DetectionCounter::purgeOldRecords(rclcpp::Time current_time) +{ + const rclcpp::Time cutoff_time = + current_time - rclcpp::Duration::from_seconds(parameters_->detection_count_purge_seconds); + + // Remove timestamps older than purge_seconds_ from time_series_counts_ + for (auto & [classification, range_map] : time_series_counts_) { + for (auto & [range, timestamps] : range_map) { + timestamps.erase( + std::remove_if( + timestamps.begin(), timestamps.end(), + [&](const rclcpp::Time & time) { return time < cutoff_time; }), + timestamps.end()); + } + } + + // Remove timestamps older than purge_seconds_ from unique_timestamps_ + while (!unique_timestamps_.empty() && *unique_timestamps_.begin() < cutoff_time) { + unique_timestamps_.erase(unique_timestamps_.begin()); + } +} +} // namespace metrics +} // namespace perception_diagnostics diff --git a/evaluator/perception_online_evaluator/src/metrics_calculator.cpp b/evaluator/perception_online_evaluator/src/metrics_calculator.cpp index c31a7f22d16c4..9c1e0667e4fef 100644 --- a/evaluator/perception_online_evaluator/src/metrics_calculator.cpp +++ b/evaluator/perception_online_evaluator/src/metrics_calculator.cpp @@ -15,6 +15,7 @@ #include "perception_online_evaluator/metrics_calculator.hpp" #include "motion_utils/trajectory/trajectory.hpp" +#include "object_recognition_utils/object_classification.hpp" #include "object_recognition_utils/object_recognition_utils.hpp" #include "tier4_autoware_utils/geometry/geometry.hpp" @@ -23,41 +24,59 @@ namespace perception_diagnostics { using object_recognition_utils::convertLabelToString; +using tier4_autoware_utils::inverseTransformPoint; std::optional MetricsCalculator::calculate(const Metric & metric) const { - if (object_map_.empty()) { - return {}; - } - - // time delay is max element of parameters_->prediction_time_horizons - const double time_delay = getTimeDelay(); - const auto target_stamp = current_stamp_ - rclcpp::Duration::from_seconds(time_delay); - if (!hasPassedTime(target_stamp)) { - return {}; + // clang-format off + const bool use_past_objects = metric == Metric::lateral_deviation || + metric == Metric::yaw_deviation || + metric == Metric::predicted_path_deviation || + metric == Metric::yaw_rate; + // clang-format on + + // todo(kosuke55): todo separate function and add timestamp of checked objects to diagnostics + if (use_past_objects) { + if (object_map_.empty()) { + return {}; + } + // time delay is max element of parameters_->prediction_time_horizons + const double time_delay = getTimeDelay(); + const auto target_stamp = current_stamp_ - rclcpp::Duration::from_seconds(time_delay); + if (!hasPassedTime(target_stamp)) { + return {}; + } + const auto target_stamp_objects = getObjectsByStamp(target_stamp); + + // extract moving objects + const auto moving_objects = filterObjectsByVelocity( + target_stamp_objects, parameters_->stopped_velocity_threshold, + /*remove_above_threshold=*/false); + const auto class_moving_objects_map = separateObjectsByClass(moving_objects); + + // extract stopped objects + const auto stopped_objects = + filterObjectsByVelocity(target_stamp_objects, parameters_->stopped_velocity_threshold); + const auto class_stopped_objects_map = separateObjectsByClass(stopped_objects); + + switch (metric) { + case Metric::lateral_deviation: + return calcLateralDeviationMetrics(class_moving_objects_map); + case Metric::yaw_deviation: + return calcYawDeviationMetrics(class_moving_objects_map); + case Metric::predicted_path_deviation: + return calcPredictedPathDeviationMetrics(class_moving_objects_map); + case Metric::yaw_rate: + return calcYawRateMetrics(class_stopped_objects_map); + default: + return {}; + } } - const auto target_stamp_objects = getObjectsByStamp(target_stamp); - - // extract moving objects - const auto moving_objects = filterObjectsByVelocity( - target_stamp_objects, parameters_->stopped_velocity_threshold, - /*remove_above_threshold=*/false); - const auto class_moving_objects_map = separateObjectsByClass(moving_objects); - - // extract stopped objects - const auto stopped_objects = - filterObjectsByVelocity(target_stamp_objects, parameters_->stopped_velocity_threshold); - const auto class_stopped_objects_map = separateObjectsByClass(stopped_objects); + // use latest objects switch (metric) { - case Metric::lateral_deviation: - return calcLateralDeviationMetrics(class_moving_objects_map); - case Metric::yaw_deviation: - return calcYawDeviationMetrics(class_moving_objects_map); - case Metric::predicted_path_deviation: - return calcPredictedPathDeviationMetrics(class_moving_objects_map); - case Metric::yaw_rate: - return calcYawRateMetrics(class_stopped_objects_map); + case Metric::objects_count: + return calcObjectsCountMetrics(); default: return {}; } @@ -211,6 +230,11 @@ MetricStatMap MetricsCalculator::calcLateralDeviationMetrics( { MetricStatMap metric_stat_map{}; for (const auto & [label, objects] : class_objects_map) { + if ( + parameters_->object_parameters.find(label) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(label).check_lateral_deviation) { + continue; + } Stat stat{}; const auto stamp = rclcpp::Time(objects.header.stamp); for (const auto & object : objects.objects) { @@ -235,6 +259,11 @@ MetricStatMap MetricsCalculator::calcYawDeviationMetrics( { MetricStatMap metric_stat_map{}; for (const auto & [label, objects] : class_objects_map) { + if ( + parameters_->object_parameters.find(label) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(label).check_yaw_deviation) { + continue; + } Stat stat{}; const auto stamp = rclcpp::Time(objects.header.stamp); for (const auto & object : objects.objects) { @@ -261,6 +290,11 @@ MetricStatMap MetricsCalculator::calcPredictedPathDeviationMetrics( MetricStatMap metric_stat_map{}; for (const auto & [label, objects] : class_objects_map) { + if ( + parameters_->object_parameters.find(label) == parameters_->object_parameters.end() || + !parameters_->object_parameters.at(label).check_predicted_path_deviation) { + continue; + } for (const double time_horizon : time_horizons) { const auto metrics = calcPredictedPathDeviationMetrics(objects, time_horizon); std::ostringstream stream; @@ -385,7 +419,6 @@ MetricStatMap MetricsCalculator::calcYawRateMetrics(const ClassObjectsMap & clas // calculate yaw rate for each object MetricStatMap metric_stat_map{}; - for (const auto & [label, objects] : class_objects_map) { Stat stat{}; const auto stamp = rclcpp::Time(objects.header.stamp); @@ -409,13 +442,12 @@ MetricStatMap MetricsCalculator::calcYawRateMetrics(const ClassObjectsMap & clas tf2::getYaw(object.kinematics.initial_pose_with_covariance.pose.orientation); const double previous_yaw = tf2::getYaw(previous_object.kinematics.initial_pose_with_covariance.pose.orientation); + // Calculate the absolute difference between current_yaw and previous_yaw const double yaw_diff = std::abs(tier4_autoware_utils::normalizeRadian(current_yaw - previous_yaw)); - // if yaw_diff is close to PI, reversal of orientation is likely occurring, so ignore it - if (std::abs(M_PI - yaw_diff) < 0.1) { - continue; - } - const auto yaw_rate = yaw_diff / time_diff; + // The yaw difference is flipped if the angle is larger than 90 degrees + const double yaw_diff_flip_fixed = std::min(yaw_diff, M_PI - yaw_diff); + const double yaw_rate = yaw_diff_flip_fixed / time_diff; stat.add(yaw_rate); } metric_stat_map["yaw_rate_" + convertLabelToString(label)] = stat; @@ -423,22 +455,58 @@ MetricStatMap MetricsCalculator::calcYawRateMetrics(const ClassObjectsMap & clas return metric_stat_map; } -void MetricsCalculator::setPredictedObjects(const PredictedObjects & objects) +MetricStatMap MetricsCalculator::calcObjectsCountMetrics() const +{ + MetricStatMap metric_stat_map; + // calculate the average number of objects in the detection area in all past frames + const auto overall_average_count = detection_counter_.getOverallAverageCount(); + for (const auto & [label, range_and_count] : overall_average_count) { + for (const auto & [range, count] : range_and_count) { + metric_stat_map["average_objects_count_" + convertLabelToString(label) + "_" + range].add( + count); + } + } + // calculate the average number of objects in the detection area in the past + // `objects_count_window_seconds` + const auto average_count = + detection_counter_.getAverageCount(parameters_->objects_count_window_seconds); + for (const auto & [label, range_and_count] : average_count) { + for (const auto & [range, count] : range_and_count) { + metric_stat_map["interval_average_objects_count_" + convertLabelToString(label) + "_" + range] + .add(count); + } + } + + // calculate the total number of objects in the detection area + const auto total_count = detection_counter_.getTotalCount(); + for (const auto & [label, range_and_count] : total_count) { + for (const auto & [range, count] : range_and_count) { + metric_stat_map["total_objects_count_" + convertLabelToString(label) + "_" + range].add( + count); + } + } + + return metric_stat_map; +} + +void MetricsCalculator::setPredictedObjects( + const PredictedObjects & objects, const tf2_ros::Buffer & tf_buffer) { current_stamp_ = objects.header.stamp; // store objects to check deviation { - auto deviation_check_objects = objects; - filterDeviationCheckObjects(deviation_check_objects, parameters_->object_parameters); using tier4_autoware_utils::toHexString; - for (const auto & object : deviation_check_objects.objects) { + for (const auto & object : objects.objects) { std::string uuid = toHexString(object.object_id); updateObjects(uuid, current_stamp_, object); } deleteOldObjects(current_stamp_); updateHistoryPath(); } + + // store objects to calculate object count + detection_counter_.addObjects(objects, tf_buffer); } void MetricsCalculator::deleteOldObjects(const rclcpp::Time stamp) diff --git a/evaluator/perception_online_evaluator/src/perception_online_evaluator_node.cpp b/evaluator/perception_online_evaluator/src/perception_online_evaluator_node.cpp index ceb304894ad8c..0fcdd77f4d515 100644 --- a/evaluator/perception_online_evaluator/src/perception_online_evaluator_node.cpp +++ b/evaluator/perception_online_evaluator/src/perception_online_evaluator_node.cpp @@ -43,8 +43,10 @@ PerceptionOnlineEvaluatorNode::PerceptionOnlineEvaluatorNode( { using std::placeholders::_1; - google::InitGoogleLogging("perception_online_evaluator_node"); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging("perception_online_evaluator_node"); + google::InstallFailureSignalHandler(); + } objects_sub_ = create_subscription( "~/input/objects", 1, std::bind(&PerceptionOnlineEvaluatorNode::onObjects, this, _1)); @@ -111,7 +113,7 @@ DiagnosticStatus PerceptionOnlineEvaluatorNode::generateDiagnosticStatus( void PerceptionOnlineEvaluatorNode::onObjects(const PredictedObjects::ConstSharedPtr objects_msg) { - metrics_calculator_.setPredictedObjects(*objects_msg); + metrics_calculator_.setPredictedObjects(*objects_msg, *tf_buffer_); publishMetrics(); } @@ -215,55 +217,36 @@ rcl_interfaces::msg::SetParametersResult PerceptionOnlineEvaluatorNode::onParame updateParam(parameters, "smoothing_window_size", p->smoothing_window_size); updateParam(parameters, "stopped_velocity_threshold", p->stopped_velocity_threshold); - - // update metrics - { - std::vector metrics_str; - updateParam>(parameters, "selected_metrics", metrics_str); - std::vector metrics; - for (const std::string & selected_metric : metrics_str) { - const Metric metric = str_to_metric.at(selected_metric); - metrics.push_back(metric); - } - p->metrics = metrics; - } + updateParam( + parameters, "detection_count_purge_seconds", p->detection_count_purge_seconds); + updateParam(parameters, "objects_count_window_seconds", p->objects_count_window_seconds); // update parameters for each object class - { - const auto get_object_param = [&](std::string && ns) -> std::optional { - ObjectParameter param{}; - if (updateParam(parameters, ns + "check_deviation", param.check_deviation)) { - return param; - } - return std::nullopt; - }; - - const std::string ns = "target_object."; - if (const auto new_param = get_object_param(ns + "car.")) { - p->object_parameters.at(ObjectClassification::CAR) = *new_param; - } - if (const auto new_param = get_object_param(ns + "truck.")) { - p->object_parameters.at(ObjectClassification::TRUCK) = *new_param; - } - if (const auto new_param = get_object_param(ns + "bus.")) { - p->object_parameters.at(ObjectClassification::BUS) = *new_param; - } - if (const auto new_param = get_object_param(ns + "trailer.")) { - p->object_parameters.at(ObjectClassification::TRAILER) = *new_param; - } - if (const auto new_param = get_object_param(ns + "bicycle.")) { - p->object_parameters.at(ObjectClassification::BICYCLE) = *new_param; - } - if (const auto new_param = get_object_param(ns + "motorcycle.")) { - p->object_parameters.at(ObjectClassification::MOTORCYCLE) = *new_param; - } - if (const auto new_param = get_object_param(ns + "pedestrian.")) { - p->object_parameters.at(ObjectClassification::PEDESTRIAN) = *new_param; - } - if (const auto new_param = get_object_param(ns + "unknown.")) { - p->object_parameters.at(ObjectClassification::UNKNOWN) = *new_param; - } - } + const auto update_object_param = [&p, ¶meters]( + const auto & semantic, const std::string & ns) { + auto & config = p->object_parameters.at(semantic); + updateParam(parameters, ns + "check_lateral_deviation", config.check_lateral_deviation); + updateParam(parameters, ns + "check_yaw_deviation", config.check_yaw_deviation); + updateParam( + parameters, ns + "check_predicted_path_deviation", config.check_predicted_path_deviation); + updateParam(parameters, ns + "check_yaw_rate", config.check_yaw_rate); + updateParam( + parameters, ns + "check_total_objects_count", config.check_total_objects_count); + updateParam( + parameters, ns + "check_average_objects_count", config.check_average_objects_count); + updateParam( + parameters, ns + "check_interval_average_objects_count", + config.check_interval_average_objects_count); + }; + const std::string ns = "target_object."; + update_object_param(ObjectClassification::MOTORCYCLE, ns + "motorcycle."); + update_object_param(ObjectClassification::CAR, ns + "car."); + update_object_param(ObjectClassification::TRUCK, ns + "truck."); + update_object_param(ObjectClassification::TRAILER, ns + "trailer."); + update_object_param(ObjectClassification::BUS, ns + "bus."); + update_object_param(ObjectClassification::PEDESTRIAN, ns + "pedestrian."); + update_object_param(ObjectClassification::BICYCLE, ns + "bicycle."); + update_object_param(ObjectClassification::UNKNOWN, ns + "unknown."); // update debug marker parameters { @@ -307,6 +290,14 @@ void PerceptionOnlineEvaluatorNode::initParameter() getOrDeclareParameter>(*this, "prediction_time_horizons"); p->stopped_velocity_threshold = getOrDeclareParameter(*this, "stopped_velocity_threshold"); + p->detection_radius_list = + getOrDeclareParameter>(*this, "detection_radius_list"); + p->detection_height_list = + getOrDeclareParameter>(*this, "detection_height_list"); + p->detection_count_purge_seconds = + getOrDeclareParameter(*this, "detection_count_purge_seconds"); + p->objects_count_window_seconds = + getOrDeclareParameter(*this, "objects_count_window_seconds"); // set metrics const auto selected_metrics = @@ -320,7 +311,18 @@ void PerceptionOnlineEvaluatorNode::initParameter() { const auto get_object_param = [&](std::string && ns) -> ObjectParameter { ObjectParameter param{}; - param.check_deviation = getOrDeclareParameter(*this, ns + "check_deviation"); + param.check_lateral_deviation = + getOrDeclareParameter(*this, ns + "check_lateral_deviation"); + param.check_yaw_deviation = getOrDeclareParameter(*this, ns + "check_yaw_deviation"); + param.check_predicted_path_deviation = + getOrDeclareParameter(*this, ns + "check_predicted_path_deviation"); + param.check_yaw_rate = getOrDeclareParameter(*this, ns + "check_yaw_rate"); + param.check_total_objects_count = + getOrDeclareParameter(*this, ns + "check_total_objects_count"); + param.check_average_objects_count = + getOrDeclareParameter(*this, ns + "check_average_objects_count"); + param.check_interval_average_objects_count = + getOrDeclareParameter(*this, ns + "check_interval_average_objects_count"); return param; }; diff --git a/evaluator/perception_online_evaluator/src/utils/objects_filtering.cpp b/evaluator/perception_online_evaluator/src/utils/objects_filtering.cpp index 0c292fcb9a9c4..6ffb80eb40b59 100644 --- a/evaluator/perception_online_evaluator/src/utils/objects_filtering.cpp +++ b/evaluator/perception_online_evaluator/src/utils/objects_filtering.cpp @@ -27,43 +27,6 @@ bool velocity_filter(const PredictedObject & object, double velocity_threshold, } } // namespace filter -ObjectTypesToCheck getDeviationCheckObjectTypes( - const std::unordered_map & params) -{ - ObjectTypesToCheck object_types_to_check; - for (const auto & [object_class, object_param] : params) { - switch (object_class) { - case ObjectClassification::CAR: - object_types_to_check.check_car = object_param.check_deviation; - break; - case ObjectClassification::TRUCK: - object_types_to_check.check_truck = object_param.check_deviation; - break; - case ObjectClassification::BUS: - object_types_to_check.check_bus = object_param.check_deviation; - break; - case ObjectClassification::TRAILER: - object_types_to_check.check_trailer = object_param.check_deviation; - break; - case ObjectClassification::BICYCLE: - object_types_to_check.check_bicycle = object_param.check_deviation; - break; - case ObjectClassification::MOTORCYCLE: - object_types_to_check.check_motorcycle = object_param.check_deviation; - break; - case ObjectClassification::PEDESTRIAN: - object_types_to_check.check_pedestrian = object_param.check_deviation; - break; - case ObjectClassification::UNKNOWN: - object_types_to_check.check_unknown = object_param.check_deviation; - break; - default: - break; - } - } - return object_types_to_check; -} - std::uint8_t getHighestProbLabel(const std::vector & classification) { std::uint8_t label = ObjectClassification::UNKNOWN; @@ -115,13 +78,6 @@ void filterObjectsByClass( filterObjects(objects, filter); } -void filterDeviationCheckObjects( - PredictedObjects & objects, const std::unordered_map & params) -{ - const auto object_types = getDeviationCheckObjectTypes(params); - filterObjectsByClass(objects, object_types); -} - PredictedObjects filterObjectsByVelocity( const PredictedObjects & objects, const double velocity_threshold, const bool remove_above_threshold) diff --git a/evaluator/perception_online_evaluator/test/test_perception_online_evaluator_node.cpp b/evaluator/perception_online_evaluator/test/test_perception_online_evaluator_node.cpp index e64411a66f521..95d6f07cca5d9 100644 --- a/evaluator/perception_online_evaluator/test/test_perception_online_evaluator_node.cpp +++ b/evaluator/perception_online_evaluator/test/test_perception_online_evaluator_node.cpp @@ -40,6 +40,8 @@ using PredictedObject = autoware_auto_perception_msgs::msg::PredictedObject; using DiagnosticArray = diagnostic_msgs::msg::DiagnosticArray; using MarkerArray = visualization_msgs::msg::MarkerArray; using ObjectClassification = autoware_auto_perception_msgs::msg::ObjectClassification; +using nav_msgs::msg::Odometry; +using TFMessage = tf2_msgs::msg::TFMessage; using tier4_autoware_utils::generateUUID; @@ -59,7 +61,19 @@ class EvalTest : public ::testing::Test {"--ros-args", "--params-file", share_dir + "/param/perception_online_evaluator.defaults.yaml"}); options.append_parameter_override("prediction_time_horizons", std::vector{5.0}); + options.append_parameter_override("detection_radius_list", std::vector{100.0}); + options.append_parameter_override("detection_height_list", std::vector{10.0}); options.append_parameter_override("smoothing_window_size", 11); + options.append_parameter_override( + "objects_count_window_seconds", objects_count_window_seconds_); + options.append_parameter_override("target_object.car.check_total_objects_count", true); + options.append_parameter_override("target_object.car.check_average_objects_count", true); + options.append_parameter_override( + "target_object.car.check_interval_average_objects_count", true); + options.append_parameter_override("target_object.unknown.check_total_objects_count", true); + options.append_parameter_override("target_object.unknown.check_average_objects_count", true); + options.append_parameter_override( + "target_object.unknown.check_interval_average_objects_count", true); dummy_node = std::make_shared("perception_online_evaluator_test", options); eval_node = std::make_shared(options); @@ -76,6 +90,7 @@ class EvalTest : public ::testing::Test } objects_pub_ = rclcpp::create_publisher( dummy_node, "/perception_online_evaluator/input/objects", 1); + tf_pub_ = rclcpp::create_publisher(dummy_node, "/tf", 1); uuid_ = generateUUID(); } @@ -86,6 +101,30 @@ class EvalTest : public ::testing::Test google::ShutdownGoogleLogging(); } + void publishEgoTF(const double time = 0.0) + { + geometry_msgs::msg::TransformStamped tf; + tf.header.frame_id = "map"; + tf.header.stamp = rclcpp::Time(0) + rclcpp::Duration::from_seconds(time); + tf.child_frame_id = "base_link"; + + geometry_msgs::msg::Quaternion quaternion; + quaternion.x = 0.; + quaternion.y = 0.; + quaternion.z = 0.; + quaternion.w = 1.; + tf.transform.rotation = quaternion; + + tf.transform.translation.x = 0.; + tf.transform.translation.y = 0.; + tf.transform.translation.z = 0.; + + TFMessage tf_msg; + tf_msg.transforms.push_back(tf); + + tf_pub_->publish(tf_msg); + } + void setTargetMetric(perception_diagnostics::Metric metric) { const auto metric_str = perception_diagnostics::metric_to_str.at(metric); @@ -110,10 +149,11 @@ class EvalTest : public ::testing::Test PredictedObject makePredictedObject( const std::vector> & predicted_path, - const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0) + const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0, + const unique_identifier_msgs::msg::UUID uuid = unique_identifier_msgs::msg::UUID()) { PredictedObject object; - object.object_id = uuid_; + object.object_id = uuid; ObjectClassification classification; classification.label = label; classification.probability = 1.0; @@ -154,35 +194,39 @@ class EvalTest : public ::testing::Test PredictedObjects makePredictedObjects( const std::vector> & predicted_path, - const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0) + const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0, + const unique_identifier_msgs::msg::UUID uuid = unique_identifier_msgs::msg::UUID()) { PredictedObjects objects; - objects.objects.push_back(makePredictedObject(predicted_path, label, velocity)); + objects.objects.push_back(makePredictedObject(predicted_path, label, velocity, uuid)); objects.header.stamp = rclcpp::Time(0); + objects.header.frame_id = "map"; return objects; } PredictedObjects makeStraightPredictedObjects( - const double time, const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0) + const double time, const uint8_t label = ObjectClassification::CAR, const double velocity = 2.0, + const unique_identifier_msgs::msg::UUID uuid = unique_identifier_msgs::msg::UUID()) { std::vector> predicted_path; for (size_t i = 0; i <= time_horizon_ / time_step_; i++) { predicted_path.push_back({velocity * (time + i * time_step_), 0.0}); } - auto objects = makePredictedObjects(predicted_path, label, velocity); + auto objects = makePredictedObjects(predicted_path, label, velocity, uuid); objects.header.stamp = rclcpp::Time(0) + rclcpp::Duration::from_seconds(time); return objects; } PredictedObjects makeDeviatedStraightPredictedObjects( const double time, const double deviation, const uint8_t label = ObjectClassification::CAR, - const double velocity = 2.0) + const double velocity = 2.0, + const unique_identifier_msgs::msg::UUID uuid = unique_identifier_msgs::msg::UUID()) { std::vector> predicted_path; for (size_t i = 0; i <= time_horizon_ / time_step_; i++) { predicted_path.push_back({velocity * (time + i * time_step_), deviation}); } - auto objects = makePredictedObjects(predicted_path, label, velocity); + auto objects = makePredictedObjects(predicted_path, label, velocity, uuid); objects.header.stamp = rclcpp::Time(0) + rclcpp::Duration::from_seconds(time); return objects; } @@ -197,6 +241,26 @@ class EvalTest : public ::testing::Test return rotated_objects; } + PredictedObjects moveObjects( + const PredictedObjects objects, const double x, const double y, const double z) + { + PredictedObjects moved_objects = objects; + for (auto & object : moved_objects.objects) { + object.kinematics.initial_pose_with_covariance.pose.position.x += x; + object.kinematics.initial_pose_with_covariance.pose.position.y += y; + object.kinematics.initial_pose_with_covariance.pose.position.z += z; + + for (auto & path : object.kinematics.predicted_paths) { + for (auto & pose : path.path) { + pose.position.x += x; + pose.position.y += y; + pose.position.z += z; + } + } + } + return moved_objects; + } + double publishObjectsAndGetMetric(const PredictedObjects & objects) { metric_updated_ = false; @@ -241,12 +305,21 @@ class EvalTest : public ::testing::Test // Pub/Sub rclcpp::Publisher::SharedPtr objects_pub_; rclcpp::Subscription::SharedPtr metric_sub_; - - double time_delay_ = 5.0; - double time_step_ = 0.5; - double time_horizon_ = 10.0; - + rclcpp::Subscription::SharedPtr marker_sub_; + rclcpp::Publisher::SharedPtr tf_pub_; + bool has_received_marker_{false}; unique_identifier_msgs::msg::UUID uuid_; + + // Constants + static constexpr double time_delay_ = 5.0; + static constexpr double time_step_ = 0.5; + static constexpr double time_horizon_ = 10.0; + static constexpr double objects_count_window_seconds_ = 3.0; + const std::vector class_list_ = { + ObjectClassification::UNKNOWN, ObjectClassification::CAR, + ObjectClassification::TRUCK, ObjectClassification::BUS, + ObjectClassification::TRAILER, ObjectClassification::MOTORCYCLE, + ObjectClassification::BICYCLE, ObjectClassification::PEDESTRIAN}; }; // ========================================================================================== @@ -259,6 +332,7 @@ TEST_F(EvalTest, testLateralDeviation_deviation0) const double deviation = 0.0; for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } @@ -274,6 +348,7 @@ TEST_F(EvalTest, testLateralDeviation_deviation1) const double deviation = 1.0; for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } @@ -296,6 +371,7 @@ TEST_F(EvalTest, testLateralDeviation_oscillation) objects = makeDeviatedStraightPredictedObjects(time, deviation * sign); sign *= -1.0; } + publishEgoTF(time); publishObjects(objects); } @@ -318,6 +394,7 @@ TEST_F(EvalTest, testLateralDeviation_distortion) } else { objects = makeDeviatedStraightPredictedObjects(time, 0); } + publishEgoTF(time); publishObjects(objects); } @@ -334,6 +411,7 @@ TEST_F(EvalTest, testLateralDeviation_deviation0_PEDESTRIAN) for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation, ObjectClassification::PEDESTRIAN); + publishEgoTF(time); publishObjects(objects); } @@ -353,6 +431,7 @@ TEST_F(EvalTest, testYawDeviation_deviation0) const double deviation = 0.0; for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } @@ -368,6 +447,7 @@ TEST_F(EvalTest, testYawDeviation_deviation1) const double deviation = 1.0; for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } @@ -390,6 +470,7 @@ TEST_F(EvalTest, testYawDeviation_oscillation) objects = makeDeviatedStraightPredictedObjects(time, deviation * sign); sign *= -1.0; } + publishEgoTF(time); publishObjects(objects); } @@ -412,6 +493,7 @@ TEST_F(EvalTest, testYawDeviation_distortion) } else { objects = makeDeviatedStraightPredictedObjects(time, 0); } + publishEgoTF(time); publishObjects(objects); } @@ -436,6 +518,7 @@ TEST_F(EvalTest, testYawDeviation_oscillation_rotate) makeDeviatedStraightPredictedObjects(time, deviation * sign), 2 * M_PI * std::rand()); sign *= -1.0; } + publishEgoTF(time); publishObjects(objects); } @@ -462,6 +545,7 @@ TEST_F(EvalTest, testYawDeviation_distortion_rotate) objects = rotateObjects(makeDeviatedStraightPredictedObjects(time, 0), 2 * M_PI * std::rand()); } + publishEgoTF(time); publishObjects(objects); } @@ -479,6 +563,7 @@ TEST_F(EvalTest, testYawDeviation_deviation0_PEDESTRIAN) for (double time = 0; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation, ObjectClassification::PEDESTRIAN); + publishEgoTF(time); publishObjects(objects); } @@ -496,17 +581,20 @@ TEST_F(EvalTest, testPredictedPathDeviation_deviation0) setTargetMetric("predicted_path_deviation_CAR_5.00"); const auto init_objects = makeStraightPredictedObjects(0); + publishEgoTF(); publishObjects(init_objects); const double deviation = 0.0; for (double time = time_step_; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } const auto last_objects = makeDeviatedStraightPredictedObjects(time_delay_, deviation); const double num_points = time_delay_ / time_step_ + 1; const double mean_deviation = deviation * (num_points - 1) / num_points; + publishEgoTF(time_delay_); EXPECT_NEAR(publishObjectsAndGetMetric(last_objects), mean_deviation, epsilon); } @@ -522,12 +610,14 @@ TEST_F(EvalTest, testPredictedPathDeviation_deviation1) const double deviation = 1.0; for (double time = time_step_; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } const auto last_objects = makeDeviatedStraightPredictedObjects(time_delay_, deviation); const double num_points = time_delay_ / time_step_ + 1; const double mean_deviation = deviation * (num_points - 1) / num_points; + publishEgoTF(time_delay_); EXPECT_NEAR(publishObjectsAndGetMetric(last_objects), mean_deviation, epsilon); } @@ -538,17 +628,20 @@ TEST_F(EvalTest, testPredictedPathDeviation_deviation2) setTargetMetric("predicted_path_deviation_CAR_5.00"); const auto init_objects = makeStraightPredictedObjects(0); + publishEgoTF(); publishObjects(init_objects); const double deviation = 2.0; for (double time = time_step_; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation); + publishEgoTF(time); publishObjects(objects); } const auto last_objects = makeDeviatedStraightPredictedObjects(time_delay_, deviation); const double num_points = time_delay_ / time_step_ + 1; const double mean_deviation = deviation * (num_points - 1) / num_points; + publishEgoTF(time_delay_); EXPECT_NEAR(publishObjectsAndGetMetric(last_objects), mean_deviation, epsilon); } @@ -559,12 +652,14 @@ TEST_F(EvalTest, testPredictedPathDeviation_deviation0_PEDESTRIAN) setTargetMetric("predicted_path_deviation_PEDESTRIAN_5.00"); const auto init_objects = makeStraightPredictedObjects(0, ObjectClassification::PEDESTRIAN); + publishEgoTF(); publishObjects(init_objects); const double deviation = 0.0; for (double time = time_step_; time < time_delay_; time += time_step_) { const auto objects = makeDeviatedStraightPredictedObjects(time, deviation, ObjectClassification::PEDESTRIAN); + publishEgoTF(time); publishObjects(objects); } const auto last_objects = @@ -572,6 +667,7 @@ TEST_F(EvalTest, testPredictedPathDeviation_deviation0_PEDESTRIAN) const double num_points = time_delay_ / time_step_ + 1; const double mean_deviation = deviation * (num_points - 1) / num_points; + publishEgoTF(time_delay_); EXPECT_NEAR(publishObjectsAndGetMetric(last_objects), mean_deviation, epsilon); } // ========================================================================================== @@ -722,13 +818,15 @@ TEST_F(EvalTest, testYawRate_0) waitForDummyNode(); setTargetMetric("yaw_rate_CAR"); - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0); + publishEgoTF(time); publishObjects(objects); } const auto last_objects = makeStraightPredictedObjects(time_delay_ + time_step_, ObjectClassification::CAR, 0.0); + publishEgoTF(time_delay_ + time_step_); EXPECT_NEAR(publishObjectsAndGetMetric(last_objects), 0.0, epsilon); } @@ -739,15 +837,17 @@ TEST_F(EvalTest, testYawRate_01) const double yaw_rate = 0.1; - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); + publishEgoTF(time); EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); } } @@ -759,15 +859,17 @@ TEST_F(EvalTest, testYawRate_minus_01) const double yaw_rate = 0.1; - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); + publishEgoTF(time); EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); } } @@ -779,15 +881,17 @@ TEST_F(EvalTest, testYawRate_1) const double yaw_rate = 1.0; - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); + publishEgoTF(time); EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); } } @@ -799,15 +903,17 @@ TEST_F(EvalTest, testYawRate_minus_1) const double yaw_rate = 1.0; - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); + publishEgoTF(time); EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); } } @@ -818,17 +924,21 @@ TEST_F(EvalTest, testYawRate_5) setTargetMetric("yaw_rate_CAR"); const double yaw_rate = 5.0; + const double yaw_rate_flip_fixed = + std::min(yaw_rate, (M_PI - yaw_rate * time_step_) / time_step_); - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), yaw_rate * time); - EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); + publishEgoTF(time); + EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate_flip_fixed, epsilon); } } @@ -838,18 +948,274 @@ TEST_F(EvalTest, testYawRate_minus_5) setTargetMetric("yaw_rate_CAR"); const double yaw_rate = 5.0; + const double yaw_rate_flip_fixed = + std::min(yaw_rate, (M_PI - yaw_rate * time_step_) / time_step_); - for (double time = 0; time <= time_delay_; time += time_step_) { + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); + publishEgoTF(time); publishObjects(objects); } for (double time = time_delay_ + time_step_; time < time_delay_ * 2; time += time_step_) { const auto objects = rotateObjects( makeStraightPredictedObjects(time, ObjectClassification::CAR, 0.0), -yaw_rate * time); - EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate, epsilon); + publishEgoTF(time); + EXPECT_NEAR(publishObjectsAndGetMetric(objects), yaw_rate_flip_fixed, epsilon); + } +} +// ========================================================================================== + +// ========================================================================================== +// average objects count +TEST_F(EvalTest, testAverageObjectsCount_CAR) +{ + waitForDummyNode(); + setTargetMetric("average_objects_count_CAR_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time)); + } + + const double mean_num_objects = 1.0; + + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects(time_delay_)), mean_num_objects, + epsilon); +} + +TEST_F(EvalTest, testAverageObjectsCount_UNKNOWN) +{ + waitForDummyNode(); + setTargetMetric("average_objects_count_UNKNOWN_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time, ObjectClassification::UNKNOWN)); + } + + const double mean_num_objects = 1.0; + + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric( + makeStraightPredictedObjects(time_delay_, ObjectClassification::UNKNOWN)), + mean_num_objects, epsilon); +} + +TEST_F(EvalTest, testAverageObjectsCount_MultiClass) +{ + waitForDummyNode(); + setTargetMetric("average_objects_count_UNKNOWN_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + const size_t index = size_t(time / time_step_) % class_list_.size(); + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time, class_list_[index])); + } + + // All: 11 frames (including last objects) (time_delay_ / time_step_ + 1) + // UNKNOWN: 2 frames + // CAR: 2 frames + // TRUCK: 2 frame + // BUS: 1 frame + // TRAILER: 1 frame + // MOTORCYCLE: 1 frame + // BICYCLE: 1 frame + // PEDESTRIAN: 1 frames + const size_t unknown_index = + std::find(class_list_.begin(), class_list_.end(), ObjectClassification::UNKNOWN) - + class_list_.begin(); // =0 + const size_t num_frames = time_delay_ / time_step_ + 1; // =11 + const double num_unknown = + std::round(static_cast(num_frames) / static_cast(class_list_.size())) + + ((num_frames % class_list_.size()) > unknown_index ? 1. : 0.); // =2 + const double mean_num_unknown = num_unknown / num_frames; // =2/11 + const size_t index = num_frames % class_list_.size(); + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects(time_delay_, class_list_[index])), + mean_num_unknown, epsilon); +} +// ========================================================================================== + +// ========================================================================================== +// interval objects count +TEST_F(EvalTest, testIntervalAverageObjectsCount_CAR) +{ + waitForDummyNode(); + setTargetMetric("interval_average_objects_count_CAR_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time)); } + + const double mean_num_objects = 1.0; + + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects(time_delay_)), mean_num_objects, + epsilon); } -// TEST_F(EvalTest, testYawRate_rate01) + +TEST_F(EvalTest, testIntervalAverageObjectsCount_UNKNOWN) +{ + waitForDummyNode(); + setTargetMetric("interval_average_objects_count_UNKNOWN_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time, ObjectClassification::UNKNOWN)); + } + + const double mean_num_objects = 1.0; + + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric( + makeStraightPredictedObjects(time_delay_, ObjectClassification::UNKNOWN)), + mean_num_objects, epsilon); +} + +TEST_F(EvalTest, testIntervalAverageObjectsCount_MultiClass) +{ + waitForDummyNode(); + setTargetMetric("interval_average_objects_count_UNKNOWN_r100.00_h10.00"); + + // objects within the last `objects_count_window_seconds` + // UNKNOWN: 1 frames + // CAR: 1 frames + // TRUCK: 0 frame + // BUS: 1 frame + // TRAILER: 1 frame + // MOTORCYCLE: 1 frame + // BICYCLE: 1 frame + // PEDESTRIAN: 1 frames + size_t num_unknown = 0; + const size_t unknown_index = + std::find(class_list_.begin(), class_list_.end(), ObjectClassification::UNKNOWN) - + class_list_.begin(); // =0 + for (double time = 0; time <= time_delay_ + 0.01; time += time_step_) { + const size_t index = size_t(time / time_step_) % class_list_.size(); + if (index == unknown_index && time >= time_delay_ - objects_count_window_seconds_) { + num_unknown++; + } + if (time < time_delay_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time, class_list_[index])); + } else { // time == time_delay_ + const double num_frames = objects_count_window_seconds_ / time_step_ + 1; // =7 + const double mean_num_unknown = num_unknown / num_frames; // =1/7 + publishEgoTF(time); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects(time_delay_, class_list_[index])), + mean_num_unknown, epsilon); + } + } +} +// ========================================================================================== + +// ========================================================================================== +// total objects count +TEST_F(EvalTest, testTotalObjectsCount_CAR) +{ + waitForDummyNode(); + setTargetMetric("total_objects_count_CAR_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time)); + } + + const double num_objects = 1; + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects(time_delay_)), num_objects, epsilon); +} + +TEST_F(EvalTest, testTotalObjectsCount_UNKNOWN) +{ + waitForDummyNode(); + setTargetMetric("total_objects_count_UNKNOWN_r100.00_h10.00"); + + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(makeStraightPredictedObjects(time, ObjectClassification::UNKNOWN)); + } + + const double num_objects = 1; + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric( + makeStraightPredictedObjects(time_delay_, ObjectClassification::UNKNOWN)), + num_objects, epsilon); +} + +TEST_F(EvalTest, testTotalObjectsCount_DifferentCAR) +{ + waitForDummyNode(); + setTargetMetric("total_objects_count_CAR_r100.00_h10.00"); + constexpr double velocity = 0.0; + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects( + makeStraightPredictedObjects(time, ObjectClassification::CAR, velocity, generateUUID())); + } + + const double num_objects = 11.0; + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(makeStraightPredictedObjects( + time_delay_, ObjectClassification::CAR, velocity, generateUUID())), + num_objects, epsilon); +} + +TEST_F(EvalTest, testTotalObjectsCount_OutsideCAR) +{ + waitForDummyNode(); + setTargetMetric("total_objects_count_CAR_r100.00_h10.00"); + + constexpr double velocity = 0.0; + const double offset = 100 / std::sqrt(2) + 1.; + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(moveObjects( + makeStraightPredictedObjects(time, ObjectClassification::CAR, velocity), offset, offset, + 0.0)); + } + + const double num_objects = 0.0; + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(moveObjects( + makeStraightPredictedObjects(time_delay_, ObjectClassification::CAR, velocity), offset, + offset, 0.0)), + num_objects, epsilon); +} + +TEST_F(EvalTest, testTotalObjectsCount_OutsideHeightCAR) +{ + waitForDummyNode(); + setTargetMetric("total_objects_count_CAR_r100.00_h10.00"); + + constexpr double velocity = 0.0; + for (double time = 0; time < time_delay_; time += time_step_) { + publishEgoTF(time); + publishObjects(moveObjects( + makeStraightPredictedObjects(time, ObjectClassification::CAR, velocity), 0., 0., 11.0)); + } + + const double num_objects = 0.0; + publishEgoTF(time_delay_); + EXPECT_NEAR( + publishObjectsAndGetMetric(moveObjects( + makeStraightPredictedObjects(time_delay_, ObjectClassification::CAR, velocity), 0., 0., + 11.0)), + num_objects, epsilon); +} + // ========================================================================================== diff --git a/evaluator/tier4_metrics_rviz_plugin/CMakeLists.txt b/evaluator/tier4_metrics_rviz_plugin/CMakeLists.txt deleted file mode 100644 index 8475b596e6d6b..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/CMakeLists.txt +++ /dev/null @@ -1,31 +0,0 @@ -cmake_minimum_required(VERSION 3.14) -project(tier4_metrics_rviz_plugin) - -find_package(autoware_cmake REQUIRED) -autoware_package() - -find_package(Qt5 REQUIRED Core Widgets Charts) -set(QT_WIDGETS_LIB Qt5::Widgets) -set(QT_CHARTS_LIB Qt5::Charts) -set(CMAKE_AUTOMOC ON) -add_definitions(-DQT_NO_KEYWORDS) - -ament_auto_add_library(${PROJECT_NAME} SHARED - src/metrics_visualize_panel.cpp - include/metrics_visualize_panel.hpp -) - -target_link_libraries(${PROJECT_NAME} - ${QT_WIDGETS_LIB} - ${QT_CHARTS_LIB} -) - -target_compile_options(${PROJECT_NAME} PUBLIC -Wno-error=deprecated-copy -Wno-error=pedantic) -# Export the plugin to be imported by rviz2 -pluginlib_export_plugin_description_file(rviz_common plugins/plugin_description.xml) - -ament_auto_package( - INSTALL_TO_SHARE - icons - plugins -) diff --git a/evaluator/tier4_metrics_rviz_plugin/README.md b/evaluator/tier4_metrics_rviz_plugin/README.md deleted file mode 100644 index be94141254030..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/README.md +++ /dev/null @@ -1,16 +0,0 @@ -# tier4_metrics_rviz_plugin - -## Purpose - -This plugin panel to visualize `planning_evaluator` output. - -## Inputs / Outputs - -| Name | Type | Description | -| ---------------------------------------- | --------------------------------------- | ------------------------------------- | -| `/diagnostic/planning_evaluator/metrics` | `diagnostic_msgs::msg::DiagnosticArray` | Subscribe `planning_evaluator` output | - -## HowToUse - -1. Start rviz and select panels/Add new panel. -2. Select MetricsVisualizePanel and press OK. diff --git a/evaluator/tier4_metrics_rviz_plugin/icons/classes/MetricsVisualizePanel.png b/evaluator/tier4_metrics_rviz_plugin/icons/classes/MetricsVisualizePanel.png deleted file mode 100644 index 6a67573717ae1..0000000000000 Binary files a/evaluator/tier4_metrics_rviz_plugin/icons/classes/MetricsVisualizePanel.png and /dev/null differ diff --git a/evaluator/tier4_metrics_rviz_plugin/include/metrics_visualize_panel.hpp b/evaluator/tier4_metrics_rviz_plugin/include/metrics_visualize_panel.hpp deleted file mode 100644 index 3d66099988d8b..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/include/metrics_visualize_panel.hpp +++ /dev/null @@ -1,254 +0,0 @@ -// Copyright 2024 TIER IV, Inc. All rights reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. -// - -#ifndef METRICS_VISUALIZE_PANEL_HPP_ -#define METRICS_VISUALIZE_PANEL_HPP_ - -#ifndef Q_MOC_RUN -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include -#endif - -#include -#include - -#include - -#include -#include -#include -#include -#include -#include - -namespace rviz_plugins -{ - -using diagnostic_msgs::msg::DiagnosticArray; -using diagnostic_msgs::msg::DiagnosticStatus; -using diagnostic_msgs::msg::KeyValue; -using QtCharts::QChart; -using QtCharts::QChartView; -using QtCharts::QLineSeries; - -struct Metric -{ -public: - explicit Metric(const DiagnosticStatus & status) : chart(new QChartView), table(new QTableWidget) - { - init(status); - } - - void init(const DiagnosticStatus & status) - { - QStringList header{}; - - { - auto label = new QLabel; - label->setAlignment(Qt::AlignCenter); - label->setText(QString::fromStdString(status.name)); - labels.emplace("metric_name", label); - - header.push_back("metric_name"); - } - - for (const auto & [key, value] : status.values) { - auto label = new QLabel; - label->setAlignment(Qt::AlignCenter); - labels.emplace(key, label); - - auto plot = new QLineSeries; - plot->setName(QString::fromStdString(key)); - plots.emplace(key, plot); - chart->chart()->addSeries(plot); - chart->chart()->createDefaultAxes(); - - header.push_back(QString::fromStdString(key)); - } - - { - chart->chart()->setTitle(QString::fromStdString(status.name)); - chart->chart()->legend()->setVisible(true); - chart->chart()->legend()->detachFromChart(); - chart->setRenderHint(QPainter::Antialiasing); - } - - { - table->setColumnCount(status.values.size() + 1); - table->setHorizontalHeaderLabels(header); - table->verticalHeader()->hide(); - table->horizontalHeader()->setSectionResizeMode(QHeaderView::Stretch); - table->setRowCount(1); - table->setSizeAdjustPolicy(QAbstractScrollArea::AdjustToContents); - } - } - - void updateData(const double time, const DiagnosticStatus & status) - { - for (const auto & [key, value] : status.values) { - const double data = std::stod(value); - labels.at(key)->setText(QString::fromStdString(toString(data))); - plots.at(key)->append(time, data); - updateMinMax(data); - } - - { - const auto area = chart->chart()->plotArea(); - const auto rect = chart->chart()->legend()->rect(); - chart->chart()->legend()->setGeometry( - QRectF(area.x(), area.y(), area.width(), rect.height())); - chart->chart()->axes(Qt::Horizontal).front()->setRange(time - 100.0, time); - } - - { - table->setCellWidget(0, 0, labels.at("metric_name")); - } - - for (size_t i = 0; i < status.values.size(); ++i) { - table->setCellWidget(0, i + 1, labels.at(status.values.at(i).key)); - } - } - - void updateMinMax(double data) - { - if (data < y_range_min) { - y_range_min = data > 0.0 ? 0.9 * data : 1.1 * data; - chart->chart()->axes(Qt::Vertical).front()->setMin(y_range_min); - } - - if (data > y_range_max) { - y_range_max = data > 0.0 ? 1.1 * data : 0.9 * data; - chart->chart()->axes(Qt::Vertical).front()->setMax(y_range_max); - } - } - - void updateTable() { table->update(); } - - void updateGraph() { chart->update(); } - - QChartView * getChartView() const { return chart; } - - QTableWidget * getTable() const { return table; } - - std::unordered_map getLabels() const { return labels; } - -private: - static std::optional getValue(const DiagnosticStatus & status, std::string && key) - { - const auto itr = std::find_if( - status.values.begin(), status.values.end(), - [&](const auto & value) { return value.key == key; }); - - if (itr == status.values.end()) { - return std::nullopt; - } - - return itr->value; - } - - static std::string toString(const double & value) - { - std::stringstream ss; - ss << std::scientific << std::setprecision(2) << value; - return ss.str(); - } - - QChartView * chart; - QTableWidget * table; - - std::unordered_map labels; - std::unordered_map plots; - - double y_range_min{std::numeric_limits::max()}; - double y_range_max{std::numeric_limits::lowest()}; -}; - -class MetricsVisualizePanel : public rviz_common::Panel -{ - Q_OBJECT - -public: - explicit MetricsVisualizePanel(QWidget * parent = nullptr); - void onInitialize() override; - -private Q_SLOTS: - // Slot functions triggered by UI events - void onTopicChanged(); - void onSpecificMetricChanged(); - void onClearButtonClicked(); - void onTabChanged(); - -private: - // ROS 2 node and subscriptions for handling metrics data - rclcpp::Node::SharedPtr raw_node_; - rclcpp::TimerBase::SharedPtr timer_; - std::unordered_map::SharedPtr> subscriptions_; - - // Topics from which metrics are collected - std::vector topics_ = { - "/diagnostic/planning_evaluator/metrics", "/diagnostic/perception_online_evaluator/metrics"}; - - // Timer and metrics message callback - void onTimer(); - void onMetrics(const DiagnosticArray::ConstSharedPtr & msg, const std::string & topic_name); - - // Functions to update UI based on selected metrics - void updateViews(); - void updateSelectedMetric(const std::string & metric_name); - - // UI components - QGridLayout * grid_; - QComboBox * topic_selector_; - QTabWidget * tab_widget_; - - // "Specific Metrics" tab components - QComboBox * specific_metric_selector_; - QChartView * specific_metric_chart_view_; - QTableWidget * specific_metric_table_; - - // Selected metrics data - std::optional> selected_metrics_; - - // Cache for received messages by topics - std::unordered_map current_msg_map_; - - // Mapping from topics to metrics widgets (tables and charts) - std::unordered_map< - std::string, std::unordered_map>> - topic_widgets_map_; - - // Synchronization - std::mutex mutex_; - - // Stored metrics data - std::unordered_map metrics_; - - // Utility functions for managing widget visibility based on topics - void updateWidgetVisibility(const std::string & target_topic, const bool show); - void showCurrentTopicWidgets(); - void hideInactiveTopicWidgets(); -}; -} // namespace rviz_plugins - -#endif // METRICS_VISUALIZE_PANEL_HPP_ diff --git a/evaluator/tier4_metrics_rviz_plugin/package.xml b/evaluator/tier4_metrics_rviz_plugin/package.xml deleted file mode 100644 index d06382bc8c539..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/package.xml +++ /dev/null @@ -1,33 +0,0 @@ - - - - tier4_metrics_rviz_plugin - 0.0.0 - The tier4_metrics_rviz_plugin package - Satoshi OTA - Kyoichi Sugahara - Maxime CLEMENT - Kosuke Takeuchi - Fumiya Watanabe - Apache License 2.0 - - ament_cmake_auto - autoware_cmake - - diagnostic_msgs - libqt5-charts-dev - libqt5-core - libqt5-gui - libqt5-widgets - qtbase5-dev - rclcpp - rviz_common - - ament_lint_auto - autoware_lint_common - - - ament_cmake - - - diff --git a/evaluator/tier4_metrics_rviz_plugin/plugins/plugin_description.xml b/evaluator/tier4_metrics_rviz_plugin/plugins/plugin_description.xml deleted file mode 100644 index 5aca5bd7faa54..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/plugins/plugin_description.xml +++ /dev/null @@ -1,5 +0,0 @@ - - - MetricsVisualizePanel - - diff --git a/evaluator/tier4_metrics_rviz_plugin/src/metrics_visualize_panel.cpp b/evaluator/tier4_metrics_rviz_plugin/src/metrics_visualize_panel.cpp deleted file mode 100644 index b92a9a7ace53d..0000000000000 --- a/evaluator/tier4_metrics_rviz_plugin/src/metrics_visualize_panel.cpp +++ /dev/null @@ -1,262 +0,0 @@ -// Copyright 2024 TIER IV, Inc. All rights reserved. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. -// - -#include "metrics_visualize_panel.hpp" - -#include - -#include - -#include -#include -#include -#include - -namespace rviz_plugins -{ -MetricsVisualizePanel::MetricsVisualizePanel(QWidget * parent) -: rviz_common::Panel(parent), grid_(new QGridLayout()) -{ - // Initialize the main tab widget - tab_widget_ = new QTabWidget(); - - // Create and configure the "All Metrics" tab - QWidget * all_metrics_widget = new QWidget(); - grid_ = new QGridLayout(all_metrics_widget); // Apply grid layout to the widget directly - all_metrics_widget->setLayout(grid_); - - // Add topic selector combobox - topic_selector_ = new QComboBox(); - for (const auto & topic : topics_) { - topic_selector_->addItem(QString::fromStdString(topic)); - } - grid_->addWidget(topic_selector_, 0, 0, 1, -1); // Add topic selector to the grid layout - connect(topic_selector_, SIGNAL(currentIndexChanged(int)), this, SLOT(onTopicChanged())); - - tab_widget_->addTab( - all_metrics_widget, "All Metrics"); // Add "All Metrics" tab to the tab widget - - // Create and configure the "Specific Metrics" tab - QWidget * specific_metrics_widget = new QWidget(); - QVBoxLayout * specific_metrics_layout = new QVBoxLayout(); - specific_metrics_widget->setLayout(specific_metrics_layout); - - // Add specific metric selector combobox - specific_metric_selector_ = new QComboBox(); - specific_metrics_layout->addWidget(specific_metric_selector_); - connect( - specific_metric_selector_, SIGNAL(currentIndexChanged(int)), this, - SLOT(onSpecificMetricChanged())); - - // Add clear button - QPushButton * clear_button = new QPushButton("Clear"); - specific_metrics_layout->addWidget(clear_button); - connect(clear_button, &QPushButton::clicked, this, &MetricsVisualizePanel::onClearButtonClicked); - - // Add chart view for specific metrics - specific_metric_chart_view_ = new QChartView(); - specific_metrics_layout->addWidget(specific_metric_chart_view_); - - tab_widget_->addTab( - specific_metrics_widget, "Specific Metrics"); // Add "Specific Metrics" tab to the tab widget - - // Set the main layout of the panel - QVBoxLayout * main_layout = new QVBoxLayout(); - main_layout->addWidget(tab_widget_); - setLayout(main_layout); -} - -void MetricsVisualizePanel::onInitialize() -{ - using std::placeholders::_1; - - raw_node_ = this->getDisplayContext()->getRosNodeAbstraction().lock()->get_raw_node(); - - for (const auto & topic_name : topics_) { - const auto callback = [this, topic_name](const DiagnosticArray::ConstSharedPtr msg) { - this->onMetrics(msg, topic_name); - }; - const auto subscription = - raw_node_->create_subscription(topic_name, rclcpp::QoS{1}, callback); - subscriptions_[topic_name] = subscription; - } - - const auto period = std::chrono::milliseconds(static_cast(1e3 / 10)); - timer_ = raw_node_->create_wall_timer(period, [&]() { onTimer(); }); -} - -void MetricsVisualizePanel::updateWidgetVisibility( - const std::string & target_topic, const bool show) -{ - for (const auto & [topic_name, metric_widgets_pair] : topic_widgets_map_) { - const bool is_target_topic = (topic_name == target_topic); - if ((!is_target_topic && show) || (is_target_topic && !show)) { - continue; - } - for (const auto & [metric, widgets] : metric_widgets_pair) { - widgets.first->setVisible(show); - widgets.second->setVisible(show); - } - } -} - -void MetricsVisualizePanel::showCurrentTopicWidgets() -{ - const std::string current_topic = topic_selector_->currentText().toStdString(); - updateWidgetVisibility(current_topic, true); -} - -void MetricsVisualizePanel::hideInactiveTopicWidgets() -{ - const std::string current_topic = topic_selector_->currentText().toStdString(); - updateWidgetVisibility(current_topic, false); -} - -void MetricsVisualizePanel::onTopicChanged() -{ - std::lock_guard message_lock(mutex_); - hideInactiveTopicWidgets(); - showCurrentTopicWidgets(); -} - -void MetricsVisualizePanel::updateSelectedMetric(const std::string & metric_name) -{ - std::lock_guard message_lock(mutex_); - - for (const auto & [topic, msg] : current_msg_map_) { - const auto time = msg->header.stamp.sec + msg->header.stamp.nanosec * 1e-9; - for (const auto & status : msg->status) { - if (metric_name == status.name) { - selected_metrics_ = {metric_name, Metric(status)}; - selected_metrics_->second.updateData(time, status); - return; - } - } - } -} - -void MetricsVisualizePanel::updateViews() -{ - if (!selected_metrics_) { - return; - } - - Metric & metric = selected_metrics_->second; - specific_metric_chart_view_->setChart(metric.getChartView()->chart()); - auto * specific_metrics_widget = dynamic_cast(tab_widget_->widget(1)); - auto * specific_metrics_layout = dynamic_cast(specific_metrics_widget->layout()); - specific_metrics_layout->removeWidget(specific_metric_table_); - specific_metric_table_ = metric.getTable(); - QSizePolicy sizePolicy(QSizePolicy::Preferred, QSizePolicy::Fixed); - sizePolicy.setHeightForWidth(specific_metric_table_->sizePolicy().hasHeightForWidth()); - specific_metric_table_->setSizePolicy(sizePolicy); - specific_metrics_layout->insertWidget(1, specific_metric_table_); -} - -void MetricsVisualizePanel::onSpecificMetricChanged() -{ - const auto selected_metrics_str = specific_metric_selector_->currentText().toStdString(); - updateSelectedMetric(selected_metrics_str); - updateViews(); -} - -void MetricsVisualizePanel::onClearButtonClicked() -{ - if (!selected_metrics_) { - return; - } - updateSelectedMetric(selected_metrics_->first); - updateViews(); -} - -void MetricsVisualizePanel::onTimer() -{ - std::lock_guard message_lock(mutex_); - - for (auto & [name, metric] : metrics_) { - metric.updateGraph(); - metric.updateTable(); - } - - if (selected_metrics_) { - selected_metrics_->second.updateGraph(); - selected_metrics_->second.updateTable(); - } -} - -void MetricsVisualizePanel::onMetrics( - const DiagnosticArray::ConstSharedPtr & msg, const std::string & topic_name) -{ - std::lock_guard message_lock(mutex_); - - const auto time = msg->header.stamp.sec + msg->header.stamp.nanosec * 1e-9; - constexpr size_t GRAPH_COL_SIZE = 5; - - for (const auto & status : msg->status) { - const size_t num_current_metrics = topic_widgets_map_[topic_name].size(); - if (metrics_.count(status.name) == 0) { - const auto metric = Metric(status); - metrics_.emplace(status.name, metric); - - // Calculate grid position - const size_t row = num_current_metrics / GRAPH_COL_SIZE * 2 + - 2; // start from 2 to leave space for the topic selector and tab widget - const size_t col = num_current_metrics % GRAPH_COL_SIZE; - - // Get the widgets from the metric - const auto tableWidget = metric.getTable(); - const auto chartViewWidget = metric.getChartView(); - - // Get the layout for the "All Metrics" tab - auto all_metrics_widget = dynamic_cast(tab_widget_->widget(0)); - QGridLayout * all_metrics_layout = dynamic_cast(all_metrics_widget->layout()); - - // Add the widgets to the "All Metrics" tab layout - all_metrics_layout->addWidget(tableWidget, row, col); - all_metrics_layout->setRowStretch(row, false); - all_metrics_layout->addWidget(chartViewWidget, row + 1, col); - all_metrics_layout->setRowStretch(row + 1, true); - all_metrics_layout->setColumnStretch(col, true); - - // Also add the widgets to the topic_widgets_map_ for easy management - topic_widgets_map_[topic_name][status.name] = std::make_pair(tableWidget, chartViewWidget); - } - metrics_.at(status.name).updateData(time, status); - - // update selected metrics - const auto selected_metrics_str = specific_metric_selector_->currentText().toStdString(); - if (selected_metrics_str == status.name) { - if (selected_metrics_) { - selected_metrics_->second.updateData(time, status); - } - } - } - - // Update the specific metric selector - QSignalBlocker blocker(specific_metric_selector_); - for (const auto & status : msg->status) { - if (specific_metric_selector_->findText(QString::fromStdString(status.name)) == -1) { - specific_metric_selector_->addItem(QString::fromStdString(status.name)); - } - } - - // save the message for metrics selector - current_msg_map_[topic_name] = msg; -} - -} // namespace rviz_plugins - -#include -PLUGINLIB_EXPORT_CLASS(rviz_plugins::MetricsVisualizePanel, rviz_common::Panel) diff --git a/launch/tier4_control_launch/launch/control.launch.py b/launch/tier4_control_launch/launch/control.launch.py index a63e7f547fef1..77140b0e0f630 100644 --- a/launch/tier4_control_launch/launch/control.launch.py +++ b/launch/tier4_control_launch/launch/control.launch.py @@ -24,6 +24,7 @@ from launch.substitutions import LaunchConfiguration from launch_ros.actions import ComposableNodeContainer from launch_ros.actions import LoadComposableNodes +from launch_ros.actions import Node from launch_ros.actions import PushRosNamespace from launch_ros.descriptions import ComposableNode from launch_ros.substitutions import FindPackageShare @@ -65,6 +66,7 @@ def launch_setup(context, *args, **kwargs): aeb_param = yaml.safe_load(f)["/**"]["ros__parameters"] with open(LaunchConfiguration("predicted_path_checker_param_path").perform(context), "r") as f: predicted_path_checker_param = yaml.safe_load(f)["/**"]["ros__parameters"] + trajectory_follower_mode = LaunchConfiguration("trajectory_follower_mode").perform(context) controller_component = ComposableNode( package="trajectory_follower_node", @@ -328,21 +330,57 @@ def launch_setup(context, *args, **kwargs): ) # set container to run all required components in the same process - container = ComposableNodeContainer( - name="control_container", - namespace="", - package="rclcpp_components", - executable=LaunchConfiguration("container_executable"), - composable_node_descriptions=[ - controller_component, - lane_departure_component, - shift_decider_component, - vehicle_cmd_gate_component, - operation_mode_transition_manager_component, - glog_component, + if trajectory_follower_mode == "trajectory_follower_node": + container = ComposableNodeContainer( + name="control_container", + namespace="", + package="rclcpp_components", + executable=LaunchConfiguration("container_executable"), + composable_node_descriptions=[ + controller_component, + lane_departure_component, + shift_decider_component, + vehicle_cmd_gate_component, + operation_mode_transition_manager_component, + glog_component, + ], + ) + + elif trajectory_follower_mode == "smart_mpc_trajectory_follower": + container = ComposableNodeContainer( + name="control_container", + namespace="", + package="rclcpp_components", + executable=LaunchConfiguration("container_executable"), + composable_node_descriptions=[ + lane_departure_component, + shift_decider_component, + vehicle_cmd_gate_component, + operation_mode_transition_manager_component, + glog_component, + ], + ) + else: + raise Exception( + f"The argument trajectory_follower_mode must be either trajectory_follower_node or smart_mpc_trajectory_follower, but {trajectory_follower_mode} was given." + ) + + # control evaluator + control_evaluator_component = ComposableNode( + package="control_evaluator", + plugin="control_diagnostics::controlEvaluatorNode", + name="control_evaluator", + remappings=[ + ("~/input/diagnostics", "/diagnostics"), + ("~/output/metrics", "~/metrics"), ], ) + control_evaluator_loader = LoadComposableNodes( + composable_node_descriptions=[control_evaluator_component], + target_container="/control/control_container", + ) + # control validator checker control_validator_component = ComposableNode( package="control_validator", @@ -369,6 +407,7 @@ def launch_setup(context, *args, **kwargs): obstacle_collision_checker_loader, autonomous_emergency_braking_loader, predicted_path_checker_loader, + control_evaluator_loader, ] ) @@ -391,7 +430,16 @@ def launch_setup(context, *args, **kwargs): ), ] ) - return [group, control_validator_group] + + smart_mpc_trajectory_follower = Node( + package="smart_mpc_trajectory_follower", + executable="pympc_trajectory_follower.py", + name="pympc_trajectory_follower", + ) + if trajectory_follower_mode == "trajectory_follower_node": + return [group, control_validator_group] + elif trajectory_follower_mode == "smart_mpc_trajectory_follower": + return [group, control_validator_group, smart_mpc_trajectory_follower] def generate_launch_description(): @@ -430,11 +478,17 @@ def add_launch_arg(name: str, default_value=None, description=None): # component add_launch_arg("use_intra_process", "false", "use ROS 2 component container communication") add_launch_arg("use_multithread", "true", "use multithread") + add_launch_arg( + "trajectory_follower_mode", + "trajectory_follower_node", + "Options for which trajectory_follower to use. Options: `trajectory_follower_node`, `smart_mpc_trajectory_follower`", + ) set_container_executable = SetLaunchConfiguration( "container_executable", "component_container", condition=UnlessCondition(LaunchConfiguration("use_multithread")), ) + set_container_mt_executable = SetLaunchConfiguration( "container_executable", "component_container_mt", diff --git a/launch/tier4_control_launch/package.xml b/launch/tier4_control_launch/package.xml index 4bfefa4d93747..801fa274dd086 100644 --- a/launch/tier4_control_launch/package.xml +++ b/launch/tier4_control_launch/package.xml @@ -11,6 +11,7 @@ ament_cmake_auto autoware_cmake + control_evaluator external_cmd_converter external_cmd_selector lane_departure_checker diff --git a/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml b/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml index 686e6d6cf12bc..ef3522b215227 100644 --- a/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml +++ b/launch/tier4_localization_launch/launch/pose_twist_estimator/ndt_scan_matcher.launch.xml @@ -1,5 +1,6 @@ + @@ -8,7 +9,7 @@ - + diff --git a/launch/tier4_localization_launch/launch/pose_twist_estimator/pose_twist_estimator.launch.xml b/launch/tier4_localization_launch/launch/pose_twist_estimator/pose_twist_estimator.launch.xml index c09443be8cab6..fa6bce0e38e55 100644 --- a/launch/tier4_localization_launch/launch/pose_twist_estimator/pose_twist_estimator.launch.xml +++ b/launch/tier4_localization_launch/launch/pose_twist_estimator/pose_twist_estimator.launch.xml @@ -1,5 +1,6 @@ + @@ -29,7 +30,20 @@ - + + + + + + + + + + diff --git a/launch/tier4_perception_launch/launch/object_recognition/detection/detector/camera_lidar_detector.launch.xml b/launch/tier4_perception_launch/launch/object_recognition/detection/detector/camera_lidar_detector.launch.xml index ddcbbbaeae107..6294df64279a5 100644 --- a/launch/tier4_perception_launch/launch/object_recognition/detection/detector/camera_lidar_detector.launch.xml +++ b/launch/tier4_perception_launch/launch/object_recognition/detection/detector/camera_lidar_detector.launch.xml @@ -8,6 +8,7 @@ + @@ -82,8 +83,9 @@ - - + + + @@ -207,9 +209,19 @@ + - + + + + + + + + + + diff --git a/launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_dnn_detector.launch.xml b/launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_dnn_detector.launch.xml index ab89da7112b66..f941bc8d771b1 100644 --- a/launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_dnn_detector.launch.xml +++ b/launch/tier4_perception_launch/launch/object_recognition/detection/detector/lidar_dnn_detector.launch.xml @@ -19,7 +19,8 @@ - + + diff --git a/launch/tier4_perception_launch/launch/object_recognition/detection/pointcloud_map_filter.launch.py b/launch/tier4_perception_launch/launch/object_recognition/detection/pointcloud_map_filter.launch.py index a5af24595c593..5fa71cd1aa0e9 100644 --- a/launch/tier4_perception_launch/launch/object_recognition/detection/pointcloud_map_filter.launch.py +++ b/launch/tier4_perception_launch/launch/object_recognition/detection/pointcloud_map_filter.launch.py @@ -85,7 +85,7 @@ def create_compare_map_pipeline(self): components.append( ComposableNode( package="pointcloud_preprocessor", - plugin="pointcloud_preprocessor::ApproximateDownsampleFilterComponent", + plugin="pointcloud_preprocessor::VoxelGridDownsampleFilterComponent", name="voxel_grid_downsample_filter", remappings=[ ("input", LaunchConfiguration("input_topic")), diff --git a/launch/tier4_perception_launch/launch/perception.launch.xml b/launch/tier4_perception_launch/launch/perception.launch.xml index d9e18e76bc4c4..d60f54c2e641a 100644 --- a/launch/tier4_perception_launch/launch/perception.launch.xml +++ b/launch/tier4_perception_launch/launch/perception.launch.xml @@ -77,6 +77,7 @@ + + @@ -119,9 +121,32 @@ description="if use_radar_tracking_fusion:=true, radar information is merged in tracking launch. Otherwise, radar information is merged in detection launch." /> + + + + + + + + + + + + + + + + + + + + + + + @@ -131,7 +156,7 @@ - + @@ -140,7 +165,7 @@ - + @@ -160,7 +185,7 @@ - + @@ -249,7 +274,7 @@ - + diff --git a/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml b/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml index aa47d094d824e..3be8678113728 100644 --- a/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml +++ b/launch/tier4_perception_launch/launch/traffic_light_recognition/traffic_light.launch.xml @@ -12,8 +12,8 @@ + - @@ -144,36 +144,37 @@ - + + + + + + + + + + - - + + - - + + - - - - - - - - diff --git a/launch/tier4_planning_launch/launch/planning.launch.xml b/launch/tier4_planning_launch/launch/planning.launch.xml index 710fb20631a45..0e693943a4d03 100644 --- a/launch/tier4_planning_launch/launch/planning.launch.xml +++ b/launch/tier4_planning_launch/launch/planning.launch.xml @@ -43,5 +43,10 @@ + + + + + diff --git a/launch/tier4_planning_launch/package.xml b/launch/tier4_planning_launch/package.xml index 950ef67865a85..d04a405a61c7b 100644 --- a/launch/tier4_planning_launch/package.xml +++ b/launch/tier4_planning_launch/package.xml @@ -57,6 +57,7 @@ ament_cmake_auto autoware_cmake + autoware_remaining_distance_time_calculator behavior_path_planner behavior_velocity_planner costmap_generator diff --git a/launch/tier4_simulator_launch/launch/simulator.launch.xml b/launch/tier4_simulator_launch/launch/simulator.launch.xml index 76fb66e4ebfdf..2ffd2a701fb65 100644 --- a/launch/tier4_simulator_launch/launch/simulator.launch.xml +++ b/launch/tier4_simulator_launch/launch/simulator.launch.xml @@ -21,6 +21,7 @@ + @@ -89,7 +90,7 @@ - + diff --git a/localization/autoware_pose_covariance_modifier/CMakeLists.txt b/localization/autoware_pose_covariance_modifier/CMakeLists.txt new file mode 100644 index 0000000000000..192434cc588d5 --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/CMakeLists.txt @@ -0,0 +1,19 @@ +cmake_minimum_required(VERSION 3.14) +project(autoware_pose_covariance_modifier) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +ament_auto_add_library(${PROJECT_NAME} SHARED + src/pose_covariance_modifier.cpp +) + +rclcpp_components_register_node(${PROJECT_NAME} + PLUGIN "autoware::pose_covariance_modifier::PoseCovarianceModifierNode" + EXECUTABLE ${PROJECT_NAME}_node +) + +ament_auto_package(INSTALL_TO_SHARE + config + launch +) diff --git a/localization/autoware_pose_covariance_modifier/README.md b/localization/autoware_pose_covariance_modifier/README.md new file mode 100644 index 0000000000000..392df9caca6eb --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/README.md @@ -0,0 +1,213 @@ +# Autoware Pose Covariance Modifier Node + +## Purpose + +This package makes it possible to use GNSS and NDT poses together in real time localization. + +## Function + +This package takes in GNSS (Global Navigation Satellite System) +and NDT (Normal Distribution Transform) poses with covariances. + +It outputs a single pose with covariance: + +- Directly the GNSS pose and its covariance. +- Directly the NDT pose and its covariance. +- Both GNSS and NDT poses with modified covariances. + +> - This package doesn't modify the pose information it receives. +> - It only modifies NDT covariance values under certain conditions. + +## Assumptions + +- The NDT matcher provides a pose with a fixed covariance. +- The NDT matcher is unable to provide a dynamic, reliable covariance value. + +## Requirements + +- The GNSS/INS module must provide standard deviation values (its error / RMSE) for the position and orientation. +- It probably needs RTK support to provide accurate position and orientation information. +- You need to have a geo-referenced map. +- GNSS/INS module and the base_link frame must be calibrated well enough. +- In an environment where GNSS/INS and NDT systems work well, the `base_link` poses from both systems should be close to + each other. + +## Description + +GNSS and NDT nodes provide the pose with covariance data utilized in an Extended Kalman Filter (EKF). + +Accurate covariance values are crucial for the effectiveness of the EKF in estimating the state. + +The GNSS system generates reliable standard deviation values, which can be transformed into covariance measures. + +But we currently don't have a reliable way to determine the covariance values for the NDT poses. +And the NDT matching system in Autoware outputs poses with preset covariance values. + +For this reason, this package is designed to manage the selection of the pose source, +based on the standard deviation values provided by the GNSS system. + +It also tunes the covariance values of the NDT poses, based on the GNSS standard deviation values. + +## Flowcharts + +### Without this package + +Only NDT pose is used in localization. GNSS pose is only used for initialization. + +```mermaid +graph TD + ndt_scan_matcher["ndt_scan_matcher"] --> |"/localization/pose_estimator/pose_with_covariance"| ekf_localizer["ekf_localizer"] + +classDef cl_node fill:#FFF2CC,stroke-width:3px,stroke:#D6B656; + +class ndt_scan_matcher cl_node; +class ekf_localizer cl_node; +``` + +### With this package + +Both NDT and GNSS poses are used in localization, depending on the standard deviation values coming from the GNSS +system. + +Here is a flowchart depicting the process and the predefined thresholds: + +```mermaid +graph TD + gnss_poser["gnss_poser"] --> |"/sensing/gnss/\npose_with_covariance"| pose_covariance_modifier_node + ndt_scan_matcher["ndt_scan_matcher"] --> |"/localization/pose_estimator/ndt_scan_matcher/\npose_with_covariance"| pose_covariance_modifier_node + + subgraph pose_covariance_modifier_node ["Pose Covariance Modifier Node"] + pc1{{"gnss_pose_yaw\nstddev"}} + pc1 -->|"<= 0.3 rad"| pc2{{"gnss_pose_z\nstddev"}} + pc2 -->|"<= 0.1 m"| pc3{{"gnss_pose_xy\nstddev"}} + pc2 -->|"> 0.1 m"| ndt_pose("NDT Pose") + pc3 -->|"<= 0.1 m"| gnss_pose("GNSS Pose") + pc3 -->|"0.1 m < x <= 0.2 m"| gnss_ndt_pose("`Both GNSS and NDT Pose + (_with modified covariance_)`") + pc3 -->|"> 0.2 m"| ndt_pose + pc1 -->|"> 0.3 rad"| ndt_pose + end + + pose_covariance_modifier_node -->|"/localization/pose_estimator/pose_with_covariance"| ekf_localizer["ekf_localizer"] + +classDef cl_node fill:#FFF2CC,stroke-width:3px,stroke:#D6B656; +classDef cl_conditional fill:#FFE6CC,stroke-width:3px,stroke:#D79B00; +classDef cl_output fill:#D5E8D4,stroke-width:3px,stroke:#82B366; + +class gnss_poser cl_node; +class ndt_scan_matcher cl_node; +class ekf_localizer cl_node; +class pose_covariance_modifier_node cl_node; + +class pc1 cl_conditional; +class pc2 cl_conditional; +class pc3 cl_conditional; + +class ndt_pose cl_output; +class gnss_pose cl_output; +class gnss_ndt_pose cl_output; +``` + +## How to use this package + +> **This package is disabled by default in Autoware, you need to manually enable it.** + +To enable this package, you need to change the `use_autoware_pose_covariance_modifier` parameter to `true` within +the [pose_twist_estimator.launch.xml](../../launch/tier4_localization_launch/launch/pose_twist_estimator/pose_twist_estimator.launch.xml#L3). + +### Without this condition (default) + +- The output of the [ndt_scan_matcher](../../localization/ndt_scan_matcher) is directly sent + to [ekf_localizer](../../localization/ekf_localizer). + - It has a preset covariance value. + - **topic name:** `/localization/pose_estimator/pose_with_covariance` +- The GNSS pose does not enter the ekf_localizer. +- This node does not launch. + +### With this condition + +- The output of the [ndt_scan_matcher](../../localization/ndt_scan_matcher) is renamed + - **from:** `/localization/pose_estimator/pose_with_covariance`. + - **to:** `/localization/pose_estimator/ndt_scan_matcher/pose_with_covariance`. +- The `ndt_scan_matcher` output enters the `autoware_pose_covariance_modifier`. +- The output of this package goes to [ekf_localizer](../../localization/ekf_localizer) with: + - **topic name:** `/localization/pose_estimator/pose_with_covariance`. + +## Node + +### Subscribed topics + +| Name | Type | Description | +| -------------------------------- | ----------------------------------------------- | ---------------------- | +| `input_gnss_pose_with_cov_topic` | `geometry_msgs::msg::PoseWithCovarianceStamped` | Input GNSS pose topic. | +| `input_ndt_pose_with_cov_topic` | `geometry_msgs::msg::PoseWithCovarianceStamped` | Input NDT pose topic. | + +### Published topics + +| Name | Type | Description | +| ----------------------------------- | ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- | +| `output_pose_with_covariance_topic` | `geometry_msgs::msg::PoseWithCovarianceStamped` | Output pose topic. This topic is used by the ekf_localizer package. | +| `selected_pose_type` | `std_msgs::msg::String` | Declares which pose sources are used in the output of this package | +| `output/ndt_position_stddev` | `std_msgs::msg::Float64` | Output pose ndt average standard deviation in position xy. It is published only when the enable_debug_topics is true. | +| `output/gnss_position_stddev` | `std_msgs::msg::Float64` | Output pose gnss average standard deviation in position xy. It is published only when the enable_debug_topics is true. | + +### Parameters + +The parameters are set +in [config/pose_covariance_modifier.param.yaml](config/pose_covariance_modifier.param.yaml) . + +{{ json_to_markdown(" +localization/autoware_pose_covariance_modifier/schema/pose_covariance_modifier.schema.json") }} + +## FAQ + +### How are varying frequency rates handled? + +The GNSS and NDT pose topics may have different frequencies. +The GNSS pose topic may have a higher frequency than the NDT. + +Let's assume that the inputs have the following frequencies: + +| Source | Frequency | +| ------ | --------- | +| GNSS | 200 Hz | +| NDT | 10 Hz | + +This package publishes the output poses as they come in, depending on the mode. + +End result: + +| Mode | Output Freq | +| ---------- | ----------- | +| GNSS Only | 200 Hz | +| GNSS + NDT | 210 Hz | +| NDT Only | 10 Hz | + +### How and when are the NDT covariance values overwritten? + +| Mode | Outputs, Covariance | +| ---------- | ------------------------------------------- | +| GNSS Only | GNSS, Unmodified | +| GNSS + NDT | **GNSS:** Unmodified, **NDT:** Interpolated | +| NDT Only | NDT, Unmodified | + +NDT covariance values overwritten only for the `GNSS + NDT` mode. + +This enables a smooth transition between `GNSS Only` and `NDT Only` modes. + +In this mode, both NDT and GNSS poses are published from this node. + +#### NDT covariance calculation + +As the `gnss_std_dev` increases within its bounds, `ndt_std_dev` should proportionally decrease within its own bounds. + +To achieve this, we first linearly interpolate: + +- Base value: `gnss_std_dev` +- Base range: [`threshold_gnss_stddev_xy_bound_lower`, `threshold_gnss_stddev_xy_bound_upper`] +- Target range: [`ndt_std_dev_bound_lower`, `ndt_std_dev_bound_upper`] +- Target value: `ndt_std_dev_target` + +- Final value = `ndt_std_dev_bound_lower` + `ndt_std_dev_bound_upper` - `ndt_std_dev_target` (to get the inverse) + +range to range lerp animation diff --git a/localization/autoware_pose_covariance_modifier/config/pose_covariance_modifier.param.yaml b/localization/autoware_pose_covariance_modifier/config/pose_covariance_modifier.param.yaml new file mode 100644 index 0000000000000..7d63b3b6de4cb --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/config/pose_covariance_modifier.param.yaml @@ -0,0 +1,24 @@ +/**: + ros__parameters: + # If GNSS yaw standard deviation values are larger than this, trust only NDT + threshold_gnss_stddev_yaw_deg_max: 0.3 + + # If GNSS position Z standard deviation values are larger than this, trust only NDT + threshold_gnss_stddev_z_max: 0.1 + + # If GNSS position XY standard deviation values are lower than this, trust only GNSS + threshold_gnss_stddev_xy_bound_lower: 0.1 + + # If GNSS position XY standard deviation values are higher than this, trust only NDT + threshold_gnss_stddev_xy_bound_upper: 0.25 + + # Lower bound value for standard deviation of NDT positions (x, y, z) when used with GNSS + ndt_std_dev_bound_lower: 0.14 + + # Upper bound value for standard deviation of NDT positions (x, y, z) when used with GNSS + ndt_std_dev_bound_upper: 0.30 + + # If GNSS data is not received for this duration, trust only NDT + gnss_pose_timeout_sec: 1.0 + + enable_debug_topics: true diff --git a/localization/autoware_pose_covariance_modifier/doc/range_lerp.svg b/localization/autoware_pose_covariance_modifier/doc/range_lerp.svg new file mode 100644 index 0000000000000..747777b14de58 --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/doc/range_lerp.svg @@ -0,0 +1,36 @@ + + + + + + + + + + + + +Base + + + + +Target + + + + diff --git a/localization/autoware_pose_covariance_modifier/launch/pose_covariance_modifier.launch.xml b/localization/autoware_pose_covariance_modifier/launch/pose_covariance_modifier.launch.xml new file mode 100755 index 0000000000000..0395496ae0b78 --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/launch/pose_covariance_modifier.launch.xml @@ -0,0 +1,14 @@ + + + + + + + + + + + + + + diff --git a/localization/autoware_pose_covariance_modifier/package.xml b/localization/autoware_pose_covariance_modifier/package.xml new file mode 100644 index 0000000000000..c6c5a49f991dd --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/package.xml @@ -0,0 +1,24 @@ + + + + autoware_pose_covariance_modifier + 1.0.0 + Add a description. + + Melike Tanrikulu + + Apache License 2.0 + + ament_cmake_auto + autoware_cmake + + geometry_msgs + interpolation + rclcpp + rclcpp_components + std_msgs + + + ament_cmake + + diff --git a/localization/autoware_pose_covariance_modifier/schema/pose_covariance_modifier.schema.json b/localization/autoware_pose_covariance_modifier/schema/pose_covariance_modifier.schema.json new file mode 100644 index 0000000000000..02cf301d731b1 --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/schema/pose_covariance_modifier.schema.json @@ -0,0 +1,73 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Pose Covariance Modifier Node Parameters", + "type": "object", + "actual_parameters": { + "type": "object", + "properties": { + "threshold_gnss_stddev_yaw_deg_max": { + "type": "number", + "default": 0.3, + "description": "If GNSS yaw standard deviation values are larger than this, trust only NDT" + }, + "threshold_gnss_stddev_z_max": { + "type": "number", + "default": 0.1, + "description": "If GNSS position Z standard deviation values are larger than this, trust only NDT" + }, + "threshold_gnss_stddev_xy_bound_lower": { + "type": "number", + "default": 0.1, + "description": "If GNSS position XY standard deviation values are lower than this, trust only GNSS" + }, + "threshold_gnss_stddev_xy_bound_upper": { + "type": "number", + "default": 0.25, + "description": "If GNSS position XY standard deviation values are higher than this, trust only NDT" + }, + "ndt_std_dev_bound_lower": { + "type": "number", + "default": 0.15, + "description": "Lower bound value for standard deviation of NDT positions (x, y, z) when used with GNSS" + }, + "ndt_std_dev_bound_upper": { + "type": "number", + "default": 0.3, + "description": "Upper bound value for standard deviation of NDT positions (x, y, z) when used with GNSS" + }, + "gnss_pose_timeout_sec": { + "type": "number", + "default": 1.0, + "description": "If GNSS data is not received for this duration, trust only NDT" + }, + "enable_debug_topics": { + "type": "boolean", + "default": true, + "description": "Publish additional debug topics" + } + }, + "required": [ + "threshold_gnss_stddev_yaw_deg_max", + "threshold_gnss_stddev_z_max", + "threshold_gnss_stddev_xy_bound_lower", + "threshold_gnss_stddev_xy_bound_upper", + "gnss_pose_timeout_sec", + "enable_debug_topics" + ], + "additionalProperties": false + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/actual_parameters" + } + }, + "required": ["ros__parameters"], + "additionalProperties": false + } + }, + "required": ["/**"], + "additionalProperties": false +} diff --git a/localization/autoware_pose_covariance_modifier/src/include/pose_covariance_modifier.hpp b/localization/autoware_pose_covariance_modifier/src/include/pose_covariance_modifier.hpp new file mode 100644 index 0000000000000..ffafe41269468 --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/src/include/pose_covariance_modifier.hpp @@ -0,0 +1,86 @@ +// Copyright 2024 The Autoware Foundation +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. +#ifndef POSE_COVARIANCE_MODIFIER_HPP_ +#define POSE_COVARIANCE_MODIFIER_HPP_ + +#include + +#include +#include +#include + +namespace autoware::pose_covariance_modifier +{ +class PoseCovarianceModifierNode : public rclcpp::Node +{ +public: + explicit PoseCovarianceModifierNode(const rclcpp::NodeOptions & node_options); + + enum class PoseSource { + GNSS = 0, + GNSS_NDT = 1, + NDT = 2, + }; + +private: + // covariance matrix indexes + const int X_POS_IDX_ = 0; + const int Y_POS_IDX_ = 7; + const int Z_POS_IDX_ = 14; + const int YAW_POS_IDX_ = 35; + + // parameters + double threshold_gnss_stddev_yaw_deg_max_; + double threshold_gnss_stddev_z_max_; + double threshold_gnss_stddev_xy_bound_lower_; + double threshold_gnss_stddev_xy_bound_upper_; + double ndt_std_dev_bound_lower_; + double ndt_std_dev_bound_upper_; + double gnss_pose_timeout_sec_; + bool debug_mode_; + + rclcpp::Time gnss_pose_received_time_last_; + geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr gnss_pose_with_cov_last_; + PoseSource pose_source_; + + rclcpp::Subscription::SharedPtr + sub_gnss_pose_with_cov_; + rclcpp::Subscription::SharedPtr + sub_ndt_pose_with_cov_; + rclcpp::Publisher::SharedPtr + pub_pose_with_covariance_stamped_; + rclcpp::Publisher::SharedPtr pub_str_pose_source_; + rclcpp::Publisher::SharedPtr pub_double_ndt_position_stddev_; + rclcpp::Publisher::SharedPtr pub_double_gnss_position_stddev_; + + void callback_gnss_pose_with_cov( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr & msg); + + void callback_ndt_pose_with_cov( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr & msg_pose_with_cov_in); + + bool gnss_pose_has_timed_out(const rclcpp::Time & gnss_pose_received_time_last); + + PoseSource pose_source_from_gnss_stddev( + double gnss_pose_yaw_stddev_deg, double gnss_pose_stddev_z, double gnss_pose_stddev_xy) const; + + std::array update_ndt_covariances_from_gnss( + const std::array & ndt_covariance_in); + + void publish_pose_type(const PoseSource & pose_source); +}; + +} // namespace autoware::pose_covariance_modifier + +#endif // POSE_COVARIANCE_MODIFIER_HPP_ diff --git a/localization/autoware_pose_covariance_modifier/src/pose_covariance_modifier.cpp b/localization/autoware_pose_covariance_modifier/src/pose_covariance_modifier.cpp new file mode 100644 index 0000000000000..bb811c55d585d --- /dev/null +++ b/localization/autoware_pose_covariance_modifier/src/pose_covariance_modifier.cpp @@ -0,0 +1,246 @@ +// Copyright 2024 The Autoware Foundation +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "include/pose_covariance_modifier.hpp" + +#include +#include + +#include +#include +#include + +namespace autoware::pose_covariance_modifier +{ +using PoseSource = PoseCovarianceModifierNode::PoseSource; + +PoseCovarianceModifierNode::PoseCovarianceModifierNode(const rclcpp::NodeOptions & node_options) +: Node("PoseCovarianceModifierNode", node_options), + gnss_pose_received_time_last_(this->now()), + pose_source_(PoseSource::NDT) +{ + // parameters + threshold_gnss_stddev_yaw_deg_max_ = + this->declare_parameter("threshold_gnss_stddev_yaw_deg_max"); + threshold_gnss_stddev_z_max_ = this->declare_parameter("threshold_gnss_stddev_z_max"); + threshold_gnss_stddev_xy_bound_lower_ = + this->declare_parameter("threshold_gnss_stddev_xy_bound_lower"); + threshold_gnss_stddev_xy_bound_upper_ = + this->declare_parameter("threshold_gnss_stddev_xy_bound_upper"); + ndt_std_dev_bound_lower_ = this->declare_parameter("ndt_std_dev_bound_lower"); + ndt_std_dev_bound_upper_ = this->declare_parameter("ndt_std_dev_bound_upper"); + gnss_pose_timeout_sec_ = this->declare_parameter("gnss_pose_timeout_sec"); + debug_mode_ = this->declare_parameter("enable_debug_topics"); + + // subscribers + sub_gnss_pose_with_cov_ = + this->create_subscription( + "input_gnss_pose_with_cov_topic", 10, + std::bind( + &PoseCovarianceModifierNode::callback_gnss_pose_with_cov, this, std::placeholders::_1)); + + sub_ndt_pose_with_cov_ = this->create_subscription( + "input_ndt_pose_with_cov_topic", 10, + std::bind( + &PoseCovarianceModifierNode::callback_ndt_pose_with_cov, this, std::placeholders::_1)); + + // publishers + pub_pose_with_covariance_stamped_ = + this->create_publisher( + "output_pose_with_covariance_topic", 10); + + pub_str_pose_source_ = this->create_publisher("~/selected_pose_type", 10); + + if (debug_mode_) { + pub_double_ndt_position_stddev_ = + this->create_publisher("~/debug/ndt_position_stddev", 10); + pub_double_gnss_position_stddev_ = + this->create_publisher("~/debug/gnss_position_stddev", 10); + } +} + +void PoseCovarianceModifierNode::callback_gnss_pose_with_cov( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr & msg_pose_with_cov_in) +{ + // will be used to check if GNSS pose has timed out in the NDT pose callback + gnss_pose_received_time_last_ = this->now(); + + // if the pose source is not GNSS, it will be used to calculate the NDT covariance in the NDT pose + // callback + gnss_pose_with_cov_last_ = msg_pose_with_cov_in; + + const double gnss_pose_yaw_stddev_deg = + std::sqrt(msg_pose_with_cov_in->pose.covariance[YAW_POS_IDX_]) * 180 / M_PI; + + const double gnss_pose_stddev_z = std::sqrt(msg_pose_with_cov_in->pose.covariance[Z_POS_IDX_]); + + const double gnss_pose_stddev_xy = + (std::sqrt(msg_pose_with_cov_in->pose.covariance[X_POS_IDX_]) + + std::sqrt(msg_pose_with_cov_in->pose.covariance[Y_POS_IDX_])) / + 2; + + pose_source_ = + pose_source_from_gnss_stddev(gnss_pose_yaw_stddev_deg, gnss_pose_stddev_z, gnss_pose_stddev_xy); + publish_pose_type(pose_source_); + + if (pose_source_ == PoseSource::NDT) { + // if the pose source is only NDT, don't publish GNSS poses + return; + } + + pub_pose_with_covariance_stamped_->publish(*msg_pose_with_cov_in); + + if (debug_mode_) { + std_msgs::msg::Float64 msg_double; + msg_double.data = gnss_pose_stddev_xy; + pub_double_gnss_position_stddev_->publish(msg_double); + } +} + +void PoseCovarianceModifierNode::callback_ndt_pose_with_cov( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr & msg_pose_with_cov_in) +{ + if (pose_source_ == PoseSource::GNSS) { + // if the pose source is only gnss, GNSS pose will be used in the GNSS pose callback + return; + } + geometry_msgs::msg::PoseWithCovarianceStamped msg_pose_with_cov_out; + + // pose_source_ was determined in the GNSS callback + if (gnss_pose_has_timed_out(gnss_pose_received_time_last_) || pose_source_ == PoseSource::NDT) { + msg_pose_with_cov_out = *msg_pose_with_cov_in; + } else if (pose_source_ == PoseSource::GNSS_NDT) { + auto ndt_pose_with_cov_updated = *msg_pose_with_cov_in; + ndt_pose_with_cov_updated.pose.covariance = + update_ndt_covariances_from_gnss(msg_pose_with_cov_in->pose.covariance); + msg_pose_with_cov_out = ndt_pose_with_cov_updated; + } + + pub_pose_with_covariance_stamped_->publish(msg_pose_with_cov_out); + + if (debug_mode_) { + std_msgs::msg::Float64 msg_double; + msg_double.data = (std::sqrt(msg_pose_with_cov_out.pose.covariance[X_POS_IDX_]) + + std::sqrt(msg_pose_with_cov_out.pose.covariance[Y_POS_IDX_])) / + 2.0; + pub_double_ndt_position_stddev_->publish(msg_double); + } +} + +bool PoseCovarianceModifierNode::gnss_pose_has_timed_out( + const rclcpp::Time & gnss_pose_received_time_last) +{ + auto duration = this->now() - gnss_pose_received_time_last; + if (duration.seconds() > gnss_pose_timeout_sec_) { + RCLCPP_WARN(this->get_logger(), "GNSS pose has timed out"); + return true; + } + return false; +} + +PoseSource PoseCovarianceModifierNode::pose_source_from_gnss_stddev( + const double gnss_pose_yaw_stddev_deg, const double gnss_pose_stddev_z, + const double gnss_pose_stddev_xy) const +{ + // If the GNSS pose z or yaw has a high standard deviation, use NDT pose + if ( + gnss_pose_yaw_stddev_deg > threshold_gnss_stddev_yaw_deg_max_ || + gnss_pose_stddev_z > threshold_gnss_stddev_z_max_) { + return PoseSource::NDT; + } + if (gnss_pose_stddev_xy <= threshold_gnss_stddev_xy_bound_lower_) { + return PoseSource::GNSS; + } + if (gnss_pose_stddev_xy <= threshold_gnss_stddev_xy_bound_upper_) { + return PoseSource::GNSS_NDT; + } + // If the gnss xy standard deviation is above the upper bound, use NDT pose + return PoseSource::NDT; +} + +std::array PoseCovarianceModifierNode::update_ndt_covariances_from_gnss( + const std::array & ndt_covariance_in) +{ + // See the ../README.md#NDT-covariance-calculation for detailed explanation + + auto lerp_range_to_range = [](double x, double x_min, double x_max, double y_min, double y_max) { + // Normalize input value to range [0, 1] + const double input_normalized = (x - x_min) / (x_max - x_min); + + // Interpolate to the output range + return interpolation::lerp(y_min, y_max, input_normalized); + }; + + auto ndt_variance_from_gnss_variance = [&](double ndt_variance, double gnss_variance) { + // Check NDT stddev bound values. + double ndt_stddev = std::sqrt(ndt_variance); + if (ndt_stddev > ndt_std_dev_bound_upper_ || ndt_stddev < ndt_std_dev_bound_lower_) { + RCLCPP_ERROR( + get_logger(), + "Input variance of NDT exceeds bound values. Variance values of NDT were not modified. " + "Check your bound values for NDT stddev."); + return ndt_variance; + } + // calculate NDT covariance value based on gnss covariance + const double gnss_std_dev = std::sqrt(gnss_variance); + + // interpolate the gnss_std_dev from gnss ranges to ndt ranges + const double interpolated_std_dev = lerp_range_to_range( + gnss_std_dev, threshold_gnss_stddev_xy_bound_lower_, threshold_gnss_stddev_xy_bound_upper_, + ndt_std_dev_bound_lower_, ndt_std_dev_bound_upper_); + + // As the gnss error increases, the ndt error should decrease + const double reversed_std_dev = + ndt_std_dev_bound_lower_ + ndt_std_dev_bound_upper_ - interpolated_std_dev; + + const double interpolated_variance = std::pow(reversed_std_dev, 2); + + // Make sure the ndt covariance is not below the lower bounds of ndt covariance value and return + return (std::max(interpolated_variance, std::pow(ndt_std_dev_bound_lower_, 2))); + }; + + std::array ndt_covariance = ndt_covariance_in; + std::array indices = {X_POS_IDX_, Y_POS_IDX_, Z_POS_IDX_}; + for (int idx : indices) { + ndt_covariance[idx] = ndt_variance_from_gnss_variance( + ndt_covariance_in[idx], gnss_pose_with_cov_last_->pose.covariance[idx]); + } + + return ndt_covariance; +} + +void PoseCovarianceModifierNode::publish_pose_type(const PoseSource & pose_source) +{ + std_msgs::msg::String selected_pose_type; + switch (pose_source) { + case PoseSource::GNSS: + selected_pose_type.data = "GNSS"; + break; + case PoseSource::GNSS_NDT: + selected_pose_type.data = "GNSS_NDT"; + break; + case PoseSource::NDT: + selected_pose_type.data = "NDT"; + break; + default: + selected_pose_type.data = "NOT_DEFINED"; + break; + } + pub_str_pose_source_->publish(selected_pose_type); +} + +} // namespace autoware::pose_covariance_modifier + +#include +RCLCPP_COMPONENTS_REGISTER_NODE(autoware::pose_covariance_modifier::PoseCovarianceModifierNode) diff --git a/localization/ekf_localizer/README.md b/localization/ekf_localizer/README.md index 1b09420f5047d..b91282015732e 100644 --- a/localization/ekf_localizer/README.md +++ b/localization/ekf_localizer/README.md @@ -130,6 +130,26 @@ Increasing the number will improve the smoothness of the estimation, but may hav - `proc_stddev_yaw_c` : This parameter describes the correlation between the yaw and yaw rate. A large value means the change in yaw does not correlate to the estimated yaw rate. If this is set to 0, it means the change in estimated yaw is equal to yaw rate. Usually, this should be set to 0. - `proc_stddev_yaw_bias_c` : This parameter is the standard deviation for the rate of change in yaw bias. In most cases, yaw bias is constant, so it can be very small, but must be non-zero. +### 3. Tune gate parameters + +EKF performs gating using Mahalanobis distance before updating by observation. The gate size is determined by the `pose_gate_dist` parameter and the `twist_gate_dist`. If the Mahalanobis distance is larger than this value, the observation is ignored. + +This gating process is based on a statistical test using the chi-square distribution. As modeled, we assume that the Mahalanobis distance follows a chi-square distribution with 3 degrees of freedom for pose and 2 degrees of freedom for twist. + +Currently, the accuracy of covariance estimation itself is not very good, so it is recommended to set the significance level to a very small value to reduce rejection due to false positives. + +| Significance level | Threshold for 2 dof | Threshold for 3 dof | +| ------------------ | ------------------- | ------------------- | +| $10 ^ {-2}$ | 9.21 | 11.3 | +| $10 ^ {-3}$ | 13.8 | 16.3 | +| $10 ^ {-4}$ | 18.4 | 21.1 | +| $10 ^ {-5}$ | 23.0 | 25.9 | +| $10 ^ {-6}$ | 27.6 | 30.7 | +| $10 ^ {-7}$ | 32.2 | 35.4 | +| $10 ^ {-8}$ | 36.8 | 40.1 | +| $10 ^ {-9}$ | 41.4 | 44.8 | +| $10 ^ {-10}$ | 46.1 | 49.5 | + ## Kalman Filter Model ### kinematics model in update function diff --git a/localization/ekf_localizer/config/ekf_localizer.param.yaml b/localization/ekf_localizer/config/ekf_localizer.param.yaml index 4cc71e0904ca8..19bfd2d498b68 100644 --- a/localization/ekf_localizer/config/ekf_localizer.param.yaml +++ b/localization/ekf_localizer/config/ekf_localizer.param.yaml @@ -13,13 +13,13 @@ pose_additional_delay: 0.0 pose_measure_uncertainty_time: 0.01 pose_smoothing_steps: 5 - pose_gate_dist: 10000.0 + pose_gate_dist: 49.5 # corresponds to significance level = 10^-10 twist_measurement: # for twist measurement twist_additional_delay: 0.0 twist_smoothing_steps: 2 - twist_gate_dist: 10000.0 + twist_gate_dist: 46.1 # corresponds to significance level = 10^-10 process_noise: # for process model diff --git a/localization/ekf_localizer/media/ekf_diagnostics.png b/localization/ekf_localizer/media/ekf_diagnostics.png index 2580d6d973290..16de42ac2d85a 100644 Binary files a/localization/ekf_localizer/media/ekf_diagnostics.png and b/localization/ekf_localizer/media/ekf_diagnostics.png differ diff --git a/localization/ekf_localizer/schema/sub/pose_measurement.sub_schema.json b/localization/ekf_localizer/schema/sub/pose_measurement.sub_schema.json index 8b931d5f68d12..d2bc313d4dc75 100644 --- a/localization/ekf_localizer/schema/sub/pose_measurement.sub_schema.json +++ b/localization/ekf_localizer/schema/sub/pose_measurement.sub_schema.json @@ -23,7 +23,7 @@ "pose_gate_dist": { "type": "number", "description": "Limit of Mahalanobis distance used for outliers detection", - "default": 10000.0 + "default": 49.5 } }, "required": [ diff --git a/localization/ekf_localizer/schema/sub/twist_measurement.sub_schema.json b/localization/ekf_localizer/schema/sub/twist_measurement.sub_schema.json index 727830a90a288..7b80133cb38aa 100644 --- a/localization/ekf_localizer/schema/sub/twist_measurement.sub_schema.json +++ b/localization/ekf_localizer/schema/sub/twist_measurement.sub_schema.json @@ -18,7 +18,7 @@ "twist_gate_dist": { "type": "number", "description": "Limit of Mahalanobis distance used for outliers detection", - "default": 10000.0 + "default": 46.1 } }, "required": ["twist_additional_delay", "twist_smoothing_steps", "twist_gate_dist"], diff --git a/localization/ndt_scan_matcher/CMakeLists.txt b/localization/ndt_scan_matcher/CMakeLists.txt index 4806838cf0103..7ac78514c49fe 100644 --- a/localization/ndt_scan_matcher/CMakeLists.txt +++ b/localization/ndt_scan_matcher/CMakeLists.txt @@ -27,10 +27,11 @@ find_package(PCL REQUIRED COMPONENTS common io registration) include_directories(${PCL_INCLUDE_DIRS}) ament_auto_add_executable(ndt_scan_matcher - src/particle.cpp - src/ndt_scan_matcher_node.cpp - src/ndt_scan_matcher_core.cpp + src/diagnostics_module.cpp src/map_update_module.cpp + src/ndt_scan_matcher_core.cpp + src/ndt_scan_matcher_node.cpp + src/particle.cpp ) link_directories(${PCL_LIBRARY_DIRS}) @@ -45,15 +46,19 @@ if(BUILD_TESTING) find_package(ament_cmake_gtest REQUIRED) ament_auto_add_gtest(standard_sequence_for_initial_pose_estimation test/test_cases/standard_sequence_for_initial_pose_estimation.cpp - src/particle.cpp - src/ndt_scan_matcher_core.cpp + src/diagnostics_module.cpp src/map_update_module.cpp + src/ndt_scan_matcher_core.cpp +# src/ndt_scan_matcher_node.cpp + src/particle.cpp ) ament_auto_add_gtest(once_initialize_at_out_of_map_then_initialize_correctly test/test_cases/once_initialize_at_out_of_map_then_initialize_correctly.cpp - src/particle.cpp - src/ndt_scan_matcher_core.cpp + src/diagnostics_module.cpp src/map_update_module.cpp + src/ndt_scan_matcher_core.cpp +# src/ndt_scan_matcher_node.cpp + src/particle.cpp ) endif() diff --git a/localization/ndt_scan_matcher/README.md b/localization/ndt_scan_matcher/README.md index 424a7051de883..fbc2fa3c9a3f3 100644 --- a/localization/ndt_scan_matcher/README.md +++ b/localization/ndt_scan_matcher/README.md @@ -255,3 +255,103 @@ initial_pose_offset_model is rotated around (x,y) = (0,0) in the direction of th initial_pose_offset_model_x & initial_pose_offset_model_y must have the same number of elements. {{ json_to_markdown("localization/ndt_scan_matcher/schema/sub/covariance_covariance_estimation.json") }} + +## Diagnostics + +### scan_matching_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | Whether to reject the estimation result (affects `skipping_publish_num`) | +| ----------------------------------------- | -------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------- | ------------------------------------------------------------------------ | +| `topic_time_stamp` | the time stamp of input topic | none | none | no | +| `sensor_points_size` | the size of sensor points | the size is 0 | none | yes | +| `sensor_points_delay_time_sec` | the delay time of sensor points | the time is **longer** than `validation.lidar_topic_timeout_sec` | none | yes | +| `is_succeed_transform_sensor_points` | whether transform sensor points is succeed or not | none | failed | yes | +| `sensor_points_max_distance` | the max distance of sensor points | the max distance is **shorter** than `sensor_points.required_distance` | none | yes | +| `is_activated` | whether the node is in the "activate" state or not | not "activate" state | none | yes | +| `is_succeed_interpolate_initial_pose` | whether the interpolate of initial pose is succeed or not | failed.
(1) the size of `initial_pose_buffer_` is **smaller** than 2.
(2) the timestamp difference between initial_pose and sensor pointcloud is **longer** than `validation.initial_pose_timeout_sec`.
(3) distance difference between two initial poses used for linear interpolation is **longer** than `validation.initial_pose_distance_tolerance_m` | none | yes | +| `is_set_map_points` | whether the map points is set or not | not set | none | yes | +| `iteration_num` | the number of times calculate alignment | the number of times is **larger** than `ndt.max_iterations` | none | yes | +| `local_optimal_solution_oscillation_num` | the number of times the solution is judged to be oscillating | the number of times is **larger** than 10 | none | yes | +| `transform_probability` | the score of how well the map aligns with the sensor points | the score is **smaller** than`score_estimation.converged_param_transform_probability` (only in the case of `score_estimation.converged_param_type` is 0=TRANSFORM_PROBABILITY) | none | yes | +| `nearest_voxel_transformation_likelihood` | the score of how well the map aligns with the sensor points | the score is **smaller** than `score_estimation.converged_param_nearest_voxel_transformation_likelihood` (only in the case of `score_estimation.converged_param_type` is 1=NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD) | none | yes | +| `distance_initial_to_result` | the distance between the position before convergence processing and the position after | the distance is **longer** than 3 | none | no | +| `execution_time` | the time for convergence processing | the time is **longer** than `validation.critical_upper_bound_exe_time_ms` | none | no | +| `skipping_publish_num` | the number of times rejected estimation results consecutively | none | the number of times is 5 or more | - | + +※The `sensor_points_callback` shares the same callback group as the `trigger_node_service` and `ndt_align_service`. Consequently, if the initial pose estimation takes too long, this diagnostic may become stale. + +### initial_pose_subscriber_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | +| ---------------------- | ------------------------------------------------------------------ | ------------------------------- | ----------------------------- | +| `topic_time_stamp` | the time stamp of input topic | none | none | +| `is_activated` | whether the node is in the "activate" state or not | not "activate" state | none | +| `is_expected_frame_id` | whether the input frame_id is the same as `frame.map_frame` or not | none | not the same | + +### regularization_pose_subscriber_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | +| ------------------ | ----------------------------- | ------------------------------- | ----------------------------- | +| `topic_time_stamp` | the time stamp of input topic | none | none | + +### trigger_node_service_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | +| ------------------------- | -------------------------------------------------- | ------------------------------- | ----------------------------- | +| `service_call_time_stamp` | the time stamp of service calling | none | none | +| `is_activated` | whether the node is in the "activate" state or not | none | none | +| `is_succeed_service` | whether the process of service is succeed or not | none | none | + +※ +This diagnostic is only published when the service is called, so it becomes stale after the initial pose estimation is completed. + +### ndt_align_service_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | +| ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------- | ----------------------------------------------------------- | +| `service_call_time_stamp` | the time stamp of service calling | none | none | +| `is_succeed_transform_initial_pose` | whether transform initial pose is succeed or not | none | failed | +| `is_need_rebuild` | whether it need to rebuild the map. If the map has not been loaded yet or if `distance_last_update_position_to_current_position encounters` is an Error state, it is considered necessary to reconstruct the map, and `is_need_rebuild` becomes `True`. | none | none | +| `maps_size_before` | the number of maps before update map | none | none | +| `is_succeed_call_pcd_loader` | whether call pcd_loader service is succeed or not | failed | none | +| `maps_to_add_size` | the number of maps to be added | none | none | +| `maps_to_remove_size` | the number of maps to be removed | none | none | +| `map_update_execution_time` | the time for map updating | none | none | +| `maps_size_after` | the number of maps after update map | none | none | +| `is_updated_map` | whether map is updated. If the map update couldn't be performed or there was no need to update the map, it becomes `False` | none | `is_updated_map` is `False` but `is_need_rebuild` is `True` | +| `is_set_map_points` | whether the map points is set or not | not set | none | +| `is_set_sensor_points` | whether the sensor points is set or not | not set | none | +| `best_particle_score` | the best score of particle | none | none | +| `is_succeed_service` | whether the process of service is succeed or not | failed | none | + +※ +This diagnostic is only published when the service is called, so it becomes stale after the initial pose estimation is completed. + +### map_update_status + +drawing + +| Name | Description | Transition condition to Warning | Transition condition to Error | +| --------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------- | ------------------------------------------------------------------------------------------------------- | +| `timer_callback_time_stamp` | the time stamp of timer_callback calling | none | none | +| `is_activated` | whether the node is in the "activate" state or not | not "activate" state | none | +| `is_set_last_update_position` | whether the `last_update_position` is set or not | not set | none | +| `distance_last_update_position_to_current_position` | the distance of `last_update_position` to current position | none | (the distance + `dynamic_map_loading.lidar_radius`) is **larger** than `dynamic_map_loading.map_radius` | +| `is_need_rebuild` | whether it need to rebuild the map. If the map has not been loaded yet or if `distance_last_update_position_to_current_position encounters` is an Error state, it is considered necessary to reconstruct the map, and `is_need_rebuild` becomes `True`. | none | none | +| `maps_size_before` | the number of maps before update map | none | none | +| `is_succeed_call_pcd_loader` | whether call pcd_loader service is succeed or not | failed | none | +| `maps_to_add_size` | the number of maps to be added | none | none | +| `maps_to_remove_size` | the number of maps to be removed | none | none | +| `map_update_execution_time` | the time for map updating | none | none | +| `maps_size_after` | the number of maps after update map | none | none | +| `is_updated_map` | whether map is updated. If the map update couldn't be performed or there was no need to update the map, it becomes `False` | none | `is_updated_map` is `False` but `is_need_rebuild` is `True` | diff --git a/localization/ndt_scan_matcher/config/ndt_scan_matcher.param.yaml b/localization/ndt_scan_matcher/config/ndt_scan_matcher.param.yaml index 241892e67b66c..ec80a0ef79c69 100644 --- a/localization/ndt_scan_matcher/config/ndt_scan_matcher.param.yaml +++ b/localization/ndt_scan_matcher/config/ndt_scan_matcher.param.yaml @@ -48,7 +48,7 @@ # The number of initial random trials in the TPE (Tree-Structured Parzen Estimator). # This value should be equal to or less than 'initial_estimate_particles_num' and more than 0. # If it is equal to 'initial_estimate_particles_num', the search will be the same as a full random search. - n_startup_trials: 20 + n_startup_trials: 100 validation: diff --git a/localization/ndt_scan_matcher/include/ndt_scan_matcher/diagnostics_module.hpp b/localization/ndt_scan_matcher/include/ndt_scan_matcher/diagnostics_module.hpp new file mode 100644 index 0000000000000..828eb6bed346b --- /dev/null +++ b/localization/ndt_scan_matcher/include/ndt_scan_matcher/diagnostics_module.hpp @@ -0,0 +1,59 @@ +// Copyright 2023 Autoware Foundation +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef NDT_SCAN_MATCHER__DIAGNOSTICS_MODULE_HPP_ +#define NDT_SCAN_MATCHER__DIAGNOSTICS_MODULE_HPP_ + +#include + +#include + +#include +#include + +class DiagnosticsModule +{ +public: + DiagnosticsModule(rclcpp::Node * node, const std::string & diagnostic_name); + void clear(); + void addKeyValue(const diagnostic_msgs::msg::KeyValue & key_value_msg); + template + void addKeyValue(const std::string & key, const T & value); + void updateLevelAndMessage(const int8_t level, const std::string & message); + void publish(); + +private: + diagnostic_msgs::msg::DiagnosticArray createDiagnosticsArray() const; + + rclcpp::Clock::SharedPtr clock_; + rclcpp::Publisher::SharedPtr diagnostics_pub_; + + diagnostic_msgs::msg::DiagnosticStatus diagnostics_status_msg_; +}; + +template +void DiagnosticsModule::addKeyValue(const std::string & key, const T & value) +{ + diagnostic_msgs::msg::KeyValue key_value; + key_value.key = key; + key_value.value = std::to_string(value); + addKeyValue(key_value); +} + +template <> +void DiagnosticsModule::addKeyValue(const std::string & key, const std::string & value); +template <> +void DiagnosticsModule::addKeyValue(const std::string & key, const bool & value); + +#endif // NDT_SCAN_MATCHER__DIAGNOSTICS_MODULE_HPP_ diff --git a/localization/ndt_scan_matcher/include/ndt_scan_matcher/hyper_parameters.hpp b/localization/ndt_scan_matcher/include/ndt_scan_matcher/hyper_parameters.hpp index ee1e2369c79bd..bc7bf1fe40d36 100644 --- a/localization/ndt_scan_matcher/include/ndt_scan_matcher/hyper_parameters.hpp +++ b/localization/ndt_scan_matcher/include/ndt_scan_matcher/hyper_parameters.hpp @@ -20,6 +20,7 @@ #include #include +#include #include #include @@ -162,10 +163,11 @@ struct HyperParameters initial_pose_offset_model_y[i]; } } else { - RCLCPP_WARN( - node->get_logger(), - "Invalid initial pose offset model parameters. Disable covariance estimation."); - covariance.covariance_estimation.enable = false; + std::stringstream message; + message << "Invalid initial pose offset model parameters." + << "Please make sure that the number of elements in " + << "initial_pose_offset_model_x and initial_pose_offset_model_y are the same."; + throw std::runtime_error(message.str()); } } diff --git a/localization/ndt_scan_matcher/include/ndt_scan_matcher/map_update_module.hpp b/localization/ndt_scan_matcher/include/ndt_scan_matcher/map_update_module.hpp index 04c762ae950a4..2bcb6f4cf6fb8 100644 --- a/localization/ndt_scan_matcher/include/ndt_scan_matcher/map_update_module.hpp +++ b/localization/ndt_scan_matcher/include/ndt_scan_matcher/map_update_module.hpp @@ -16,6 +16,7 @@ #define NDT_SCAN_MATCHER__MAP_UPDATE_MODULE_HPP_ #include "localization_util/util_func.hpp" +#include "ndt_scan_matcher/diagnostics_module.hpp" #include "ndt_scan_matcher/hyper_parameters.hpp" #include "ndt_scan_matcher/particle.hpp" @@ -54,10 +55,20 @@ class MapUpdateModule private: friend class NDTScanMatcher; + void callback_timer( + const bool is_activated, const std::optional & position, + std::unique_ptr & diagnostics_ptr); + + [[nodiscard]] bool should_update_map( + const geometry_msgs::msg::Point & position, + std::unique_ptr & diagnostics_ptr); + void update_map( + const geometry_msgs::msg::Point & position, + std::unique_ptr & diagnostics_ptr); // Update the specified NDT - bool update_ndt(const geometry_msgs::msg::Point & position, NdtType & ndt); - void update_map(const geometry_msgs::msg::Point & position); - [[nodiscard]] bool should_update_map(const geometry_msgs::msg::Point & position); + bool update_ndt( + const geometry_msgs::msg::Point & position, NdtType & ndt, + std::unique_ptr & diagnostics_ptr); void publish_partial_pcd_map(); rclcpp::Publisher::SharedPtr loaded_pcd_pub_; diff --git a/localization/ndt_scan_matcher/include/ndt_scan_matcher/ndt_scan_matcher_core.hpp b/localization/ndt_scan_matcher/include/ndt_scan_matcher/ndt_scan_matcher_core.hpp index 26c96ce7e3248..4f8042d106c75 100644 --- a/localization/ndt_scan_matcher/include/ndt_scan_matcher/ndt_scan_matcher_core.hpp +++ b/localization/ndt_scan_matcher/include/ndt_scan_matcher/ndt_scan_matcher_core.hpp @@ -18,6 +18,7 @@ #define FMT_HEADER_ONLY #include "localization_util/smart_pose_buffer.hpp" +#include "ndt_scan_matcher/diagnostics_module.hpp" #include "ndt_scan_matcher/hyper_parameters.hpp" #include "ndt_scan_matcher/map_update_module.hpp" @@ -62,6 +63,7 @@ #include #include #include +#include #include #include #include @@ -77,21 +79,32 @@ class NDTScanMatcher : public rclcpp::Node explicit NDTScanMatcher(const rclcpp::NodeOptions & options = rclcpp::NodeOptions()); private: - void service_ndt_align( - const tier4_localization_msgs::srv::PoseWithCovarianceStamped::Request::SharedPtr req, - tier4_localization_msgs::srv::PoseWithCovarianceStamped::Response::SharedPtr res); - void service_trigger_node( - const std_srvs::srv::SetBool::Request::SharedPtr req, - std_srvs::srv::SetBool::Response::SharedPtr res); - void callback_timer(); - void callback_sensor_points( - sensor_msgs::msg::PointCloud2::ConstSharedPtr sensor_points_msg_in_sensor_frame); + void callback_initial_pose( geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr initial_pose_msg_ptr); + void callback_initial_pose_main( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr initial_pose_msg_ptr); + void callback_regularization_pose( geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr pose_conv_msg_ptr); + void callback_sensor_points( + sensor_msgs::msg::PointCloud2::ConstSharedPtr sensor_points_msg_in_sensor_frame); + bool callback_sensor_points_main( + sensor_msgs::msg::PointCloud2::ConstSharedPtr sensor_points_msg_in_sensor_frame); + + void service_trigger_node( + const std_srvs::srv::SetBool::Request::SharedPtr req, + std_srvs::srv::SetBool::Response::SharedPtr res); + + void service_ndt_align( + const tier4_localization_msgs::srv::PoseWithCovarianceStamped::Request::SharedPtr req, + tier4_localization_msgs::srv::PoseWithCovarianceStamped::Response::SharedPtr res); + void service_ndt_align_main( + const tier4_localization_msgs::srv::PoseWithCovarianceStamped::Request::SharedPtr req, + tier4_localization_msgs::srv::PoseWithCovarianceStamped::Response::SharedPtr res); + geometry_msgs::msg::PoseWithCovarianceStamped align_pose( const geometry_msgs::msg::PoseWithCovarianceStamped & initial_pose_with_cov); @@ -116,11 +129,6 @@ class NDTScanMatcher : public rclcpp::Node const geometry_msgs::msg::PoseWithCovarianceStamped & initial_pose_old_msg, const geometry_msgs::msg::PoseWithCovarianceStamped & initial_pose_new_msg); - bool validate_num_iteration(const int iter_num, const int max_iter_num); - bool validate_score( - const double score, const double score_threshold, const std::string & score_name); - bool validate_converged_param( - const double & transform_probability, const double & nearest_voxel_transformation_likelihood); static int count_oscillation(const std::vector & result_pose_msg_array); std::array rotate_covariance( @@ -131,8 +139,6 @@ class NDTScanMatcher : public rclcpp::Node void add_regularization_pose(const rclcpp::Time & sensor_ros_time); - void publish_diagnostic(); - rclcpp::TimerBase::SharedPtr map_update_timer_; rclcpp::Subscription::SharedPtr initial_pose_sub_; rclcpp::Subscription::SharedPtr sensor_points_sub_; @@ -168,7 +174,6 @@ class NDTScanMatcher : public rclcpp::Node rclcpp::Publisher::SharedPtr ndt_marker_pub_; rclcpp::Publisher::SharedPtr ndt_monte_carlo_initial_pose_marker_pub_; - rclcpp::Publisher::SharedPtr diagnostics_pub_; rclcpp::Service::SharedPtr service_; rclcpp::Service::SharedPtr service_trigger_node_; @@ -180,7 +185,6 @@ class NDTScanMatcher : public rclcpp::Node rclcpp::CallbackGroup::SharedPtr timer_callback_group_; std::shared_ptr ndt_ptr_; - std::shared_ptr> state_ptr_; Eigen::Matrix4f base_to_sensor_matrix_; @@ -194,6 +198,12 @@ class NDTScanMatcher : public rclcpp::Node std::unique_ptr regularization_pose_buffer_; std::atomic is_activated_; + std::unique_ptr diagnostics_scan_points_; + std::unique_ptr diagnostics_initial_pose_; + std::unique_ptr diagnostics_regularization_pose_; + std::unique_ptr diagnostics_map_update_; + std::unique_ptr diagnostics_ndt_align_; + std::unique_ptr diagnostics_trigger_node_; std::unique_ptr map_update_module_; std::unique_ptr logger_configure_; diff --git a/localization/ndt_scan_matcher/media/diagnostic_initial_pose_subscriber_status.png b/localization/ndt_scan_matcher/media/diagnostic_initial_pose_subscriber_status.png new file mode 100644 index 0000000000000..766888359ed8e Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_initial_pose_subscriber_status.png differ diff --git a/localization/ndt_scan_matcher/media/diagnostic_map_update_status.png b/localization/ndt_scan_matcher/media/diagnostic_map_update_status.png new file mode 100644 index 0000000000000..0fe7016fe7e3c Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_map_update_status.png differ diff --git a/localization/ndt_scan_matcher/media/diagnostic_ndt_align_service_status.png b/localization/ndt_scan_matcher/media/diagnostic_ndt_align_service_status.png new file mode 100644 index 0000000000000..e1da17966080f Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_ndt_align_service_status.png differ diff --git a/localization/ndt_scan_matcher/media/diagnostic_regularization_pose_subscriber_status.png b/localization/ndt_scan_matcher/media/diagnostic_regularization_pose_subscriber_status.png new file mode 100644 index 0000000000000..6d777ff360481 Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_regularization_pose_subscriber_status.png differ diff --git a/localization/ndt_scan_matcher/media/diagnostic_scan_matching_status.png b/localization/ndt_scan_matcher/media/diagnostic_scan_matching_status.png new file mode 100644 index 0000000000000..2687db23d4714 Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_scan_matching_status.png differ diff --git a/localization/ndt_scan_matcher/media/diagnostic_trigger_node_service_status.png b/localization/ndt_scan_matcher/media/diagnostic_trigger_node_service_status.png new file mode 100644 index 0000000000000..178e2a8bf361f Binary files /dev/null and b/localization/ndt_scan_matcher/media/diagnostic_trigger_node_service_status.png differ diff --git a/localization/ndt_scan_matcher/package.xml b/localization/ndt_scan_matcher/package.xml index 0913ee04174f5..b9a1f7dbad1bd 100644 --- a/localization/ndt_scan_matcher/package.xml +++ b/localization/ndt_scan_matcher/package.xml @@ -22,7 +22,7 @@ diagnostic_msgs fmt geometry_msgs - libgoogle-glog-dev + glog libpcl-all-dev localization_util nav_msgs diff --git a/localization/ndt_scan_matcher/schema/sub/initial_pose_estimation.json b/localization/ndt_scan_matcher/schema/sub/initial_pose_estimation.json index 9817f3145bbd3..20250d05782f9 100644 --- a/localization/ndt_scan_matcher/schema/sub/initial_pose_estimation.json +++ b/localization/ndt_scan_matcher/schema/sub/initial_pose_estimation.json @@ -14,7 +14,7 @@ "n_startup_trials": { "type": "number", "description": "The number of initial random trials in the TPE (Tree-Structured Parzen Estimator). This value should be equal to or less than 'initial_estimate_particles_num' and more than 0. If it is equal to 'initial_estimate_particles_num', the search will be the same as a full random search.", - "default": 20, + "default": 100, "minimum": 1 } }, diff --git a/localization/ndt_scan_matcher/src/diagnostics_module.cpp b/localization/ndt_scan_matcher/src/diagnostics_module.cpp new file mode 100644 index 0000000000000..9d7eed46414ea --- /dev/null +++ b/localization/ndt_scan_matcher/src/diagnostics_module.cpp @@ -0,0 +1,104 @@ +// Copyright 2023 Autoware Foundation +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "ndt_scan_matcher/diagnostics_module.hpp" + +#include + +#include + +#include +#include + +DiagnosticsModule::DiagnosticsModule(rclcpp::Node * node, const std::string & diagnostic_name) +: clock_(node->get_clock()) +{ + diagnostics_pub_ = + node->create_publisher("/diagnostics", 10); + + diagnostics_status_msg_.name = + std::string(node->get_name()) + std::string(": ") + diagnostic_name; + diagnostics_status_msg_.hardware_id = node->get_name(); +} + +void DiagnosticsModule::clear() +{ + diagnostics_status_msg_.values.clear(); + diagnostics_status_msg_.values.shrink_to_fit(); + + diagnostics_status_msg_.level = diagnostic_msgs::msg::DiagnosticStatus::OK; + diagnostics_status_msg_.message = ""; +} + +void DiagnosticsModule::addKeyValue(const diagnostic_msgs::msg::KeyValue & key_value_msg) +{ + auto it = std::find_if( + std::begin(diagnostics_status_msg_.values), std::end(diagnostics_status_msg_.values), + [key_value_msg](const auto & arg) { return arg.key == key_value_msg.key; }); + + if (it != std::cend(diagnostics_status_msg_.values)) { + it->value = key_value_msg.value; + } else { + diagnostics_status_msg_.values.push_back(key_value_msg); + } +} + +template <> +void DiagnosticsModule::addKeyValue(const std::string & key, const std::string & value) +{ + diagnostic_msgs::msg::KeyValue key_value; + key_value.key = key; + key_value.value = value; + addKeyValue(key_value); +} + +template <> +void DiagnosticsModule::addKeyValue(const std::string & key, const bool & value) +{ + diagnostic_msgs::msg::KeyValue key_value; + key_value.key = key; + key_value.value = value ? "True" : "False"; + addKeyValue(key_value); +} + +void DiagnosticsModule::updateLevelAndMessage(const int8_t level, const std::string & message) +{ + if ((level > diagnostic_msgs::msg::DiagnosticStatus::OK)) { + if (!diagnostics_status_msg_.message.empty()) { + diagnostics_status_msg_.message += "; "; + } + diagnostics_status_msg_.message += message; + } + if (level > diagnostics_status_msg_.level) { + diagnostics_status_msg_.level = level; + } +} + +void DiagnosticsModule::publish() +{ + diagnostics_pub_->publish(createDiagnosticsArray()); +} + +diagnostic_msgs::msg::DiagnosticArray DiagnosticsModule::createDiagnosticsArray() const +{ + diagnostic_msgs::msg::DiagnosticArray diagnostics_msg; + diagnostics_msg.header.stamp = clock_->now(); + diagnostics_msg.status.push_back(diagnostics_status_msg_); + + if (diagnostics_msg.status.at(0).level == diagnostic_msgs::msg::DiagnosticStatus::OK) { + diagnostics_msg.status.at(0).message = "OK"; + } + + return diagnostics_msg; +} diff --git a/localization/ndt_scan_matcher/src/map_update_module.cpp b/localization/ndt_scan_matcher/src/map_update_module.cpp index ca56a93cec859..43174a39b797e 100644 --- a/localization/ndt_scan_matcher/src/map_update_module.cpp +++ b/localization/ndt_scan_matcher/src/map_update_module.cpp @@ -34,7 +34,10 @@ MapUpdateModule::MapUpdateModule( if (ndt_ptr_) { *secondary_ndt_ptr_ = *ndt_ptr_; } else { - RCLCPP_ERROR_STREAM_THROTTLE(logger_, *clock_, 1000, "Attempt to update a null NDT pointer."); + std::stringstream message; + message << "Error at MapUpdateModule::MapUpdateModule." + << "`ndt_ptr_` is a null NDT pointer."; + throw std::runtime_error(message.str()); } // Initially, a direct map update on ndt_ptr_ is needed. @@ -45,7 +48,41 @@ MapUpdateModule::MapUpdateModule( need_rebuild_ = true; } -bool MapUpdateModule::should_update_map(const geometry_msgs::msg::Point & position) +void MapUpdateModule::callback_timer( + const bool is_activated, const std::optional & position, + std::unique_ptr & diagnostics_ptr) +{ + diagnostics_ptr->addKeyValue("timer_callback_time_stamp", clock_->now().seconds()); + + // check is_activated + diagnostics_ptr->addKeyValue("is_activated", is_activated); + if (!is_activated) { + std::stringstream message; + message << "Node is not activated."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return; + } + + // check is_set_last_update_position + const bool is_set_last_update_position = (position != std::nullopt); + diagnostics_ptr->addKeyValue("is_set_last_update_position", is_set_last_update_position); + if (!is_set_last_update_position) { + std::stringstream message; + message << "Cannot find the reference position for map update." + << "Please check if the EKF odometry is provided to NDT."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return; + } + + if (should_update_map(position.value(), diagnostics_ptr)) { + update_map(position.value(), diagnostics_ptr); + } +} + +bool MapUpdateModule::should_update_map( + const geometry_msgs::msg::Point & position, std::unique_ptr & diagnostics_ptr) { if (last_update_position_ == std::nullopt) { need_rebuild_ = true; @@ -55,8 +92,15 @@ bool MapUpdateModule::should_update_map(const geometry_msgs::msg::Point & positi const double dx = position.x - last_update_position_.value().x; const double dy = position.y - last_update_position_.value().y; const double distance = std::hypot(dx, dy); + + // check distance_last_update_position_to_current_position + diagnostics_ptr->addKeyValue("distance_last_update_position_to_current_position", distance); if (distance + param_.lidar_radius > param_.map_radius) { - RCLCPP_ERROR_STREAM_THROTTLE(logger_, *clock_, 1000, "Dynamic map loading is not keeping up."); + std::stringstream message; + message << "Dynamic map loading is not keeping up."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + // If the map does not keep up with the current position, // lock ndt_ptr_ entirely until it is fully rebuilt. need_rebuild_ = true; @@ -65,8 +109,11 @@ bool MapUpdateModule::should_update_map(const geometry_msgs::msg::Point & positi return distance > param_.update_distance; } -void MapUpdateModule::update_map(const geometry_msgs::msg::Point & position) +void MapUpdateModule::update_map( + const geometry_msgs::msg::Point & position, std::unique_ptr & diagnostics_ptr) { + diagnostics_ptr->addKeyValue("is_need_rebuild", need_rebuild_); + // If the current position is super far from the previous loading position, // lock and rebuild ndt_ptr_ if (need_rebuild_) { @@ -82,25 +129,37 @@ void MapUpdateModule::update_map(const geometry_msgs::msg::Point & position) ndt_ptr_->setInputSource(input_source); } - const bool updated = update_ndt(position, *ndt_ptr_); + const bool updated = update_ndt(position, *ndt_ptr_, diagnostics_ptr); + + // check is_updated_map + diagnostics_ptr->addKeyValue("is_updated_map", updated); if (!updated) { - RCLCPP_ERROR_STREAM_THROTTLE( - logger_, *clock_, 1000, - "update_ndt failed. If this happens with initial position estimation, make sure that" - "(1) the initial position matches the pcd map and (2) the map_loader is working properly."); + std::stringstream message; + message + << "update_ndt failed. If this happens with initial position estimation, make sure that" + << "(1) the initial position matches the pcd map and (2) the map_loader is working " + "properly."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + RCLCPP_ERROR_STREAM_THROTTLE(logger_, *clock_, 1000, message.str()); last_update_position_ = position; ndt_ptr_mutex_->unlock(); return; } + ndt_ptr_mutex_->unlock(); need_rebuild_ = false; + } else { // Load map to the secondary_ndt_ptr, which does not require a mutex lock // Since the update of the secondary ndt ptr and the NDT align (done on // the main ndt_ptr_) overlap, the latency of updating/alignment reduces partly. // If the updating is done the main ndt_ptr_, either the update or the NDT // align will be blocked by the other. - const bool updated = update_ndt(position, *secondary_ndt_ptr_); + const bool updated = update_ndt(position, *secondary_ndt_ptr_, diagnostics_ptr); + + // check is_updated_map + diagnostics_ptr->addKeyValue("is_updated_map", updated); if (!updated) { last_update_position_ = position; return; @@ -128,8 +187,12 @@ void MapUpdateModule::update_map(const geometry_msgs::msg::Point & position) publish_partial_pcd_map(); } -bool MapUpdateModule::update_ndt(const geometry_msgs::msg::Point & position, NdtType & ndt) +bool MapUpdateModule::update_ndt( + const geometry_msgs::msg::Point & position, NdtType & ndt, + std::unique_ptr & diagnostics_ptr) { + diagnostics_ptr->addKeyValue("maps_size_before", ndt.getCurrentMapIDs().size()); + auto request = std::make_shared(); request->area.center_x = static_cast(position.x); @@ -138,7 +201,13 @@ bool MapUpdateModule::update_ndt(const geometry_msgs::msg::Point & position, Ndt request->cached_ids = ndt.getCurrentMapIDs(); while (!pcd_loader_client_->wait_for_service(std::chrono::seconds(1)) && rclcpp::ok()) { - RCLCPP_INFO(logger_, "Waiting for pcd loader service. Check the pointcloud_map_loader."); + diagnostics_ptr->addKeyValue("is_succeed_call_pcd_loader", false); + + std::stringstream message; + message << "Waiting for pcd loader service. Check the pointcloud_map_loader."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; } // send a request to map_loader @@ -148,20 +217,27 @@ bool MapUpdateModule::update_ndt(const geometry_msgs::msg::Point & position, Ndt std::future_status status = result.wait_for(std::chrono::seconds(0)); while (status != std::future_status::ready) { - RCLCPP_INFO(logger_, "waiting response"); + // check is_succeed_call_pcd_loader if (!rclcpp::ok()) { + diagnostics_ptr->addKeyValue("is_succeed_call_pcd_loader", false); + + std::stringstream message; + message << "pcd_loader service is not working."; + diagnostics_ptr->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); return false; // No update } status = result.wait_for(std::chrono::seconds(1)); } + diagnostics_ptr->addKeyValue("is_succeed_call_pcd_loader", true); auto & maps_to_add = result.get()->new_pointcloud_with_ids; auto & map_ids_to_remove = result.get()->ids_to_remove; - RCLCPP_INFO( - logger_, "Update map (Add: %lu, Remove: %lu)", maps_to_add.size(), map_ids_to_remove.size()); + diagnostics_ptr->addKeyValue("maps_to_add_size", maps_to_add.size()); + diagnostics_ptr->addKeyValue("maps_to_remove_size", map_ids_to_remove.size()); + if (maps_to_add.empty() && map_ids_to_remove.empty()) { - RCLCPP_INFO(logger_, "Skip map update"); return false; // No update } @@ -187,7 +263,9 @@ bool MapUpdateModule::update_ndt(const geometry_msgs::msg::Point & position, Ndt const auto duration_micro_sec = std::chrono::duration_cast(exe_end_time - exe_start_time).count(); const auto exe_time = static_cast(duration_micro_sec) / 1000.0; - RCLCPP_DEBUG(logger_, "Time duration for creating new ndt_ptr: %lf [ms]", exe_time); + diagnostics_ptr->addKeyValue("map_update_execution_time", exe_time); + diagnostics_ptr->addKeyValue("maps_size_after", ndt.getCurrentMapIDs().size()); + diagnostics_ptr->addKeyValue("is_succeed_call_pcd_loader", true); return true; // Updated } diff --git a/localization/ndt_scan_matcher/src/ndt_scan_matcher_core.cpp b/localization/ndt_scan_matcher/src/ndt_scan_matcher_core.cpp index ba4190d9f66fb..8e7685180c1f9 100644 --- a/localization/ndt_scan_matcher/src/ndt_scan_matcher_core.cpp +++ b/localization/ndt_scan_matcher/src/ndt_scan_matcher_core.cpp @@ -22,8 +22,6 @@ #include #include -#include - #include #ifdef ROS_DISTRO_GALACTIC @@ -70,12 +68,9 @@ NDTScanMatcher::NDTScanMatcher(const rclcpp::NodeOptions & options) tf2_buffer_(this->get_clock()), tf2_listener_(tf2_buffer_), ndt_ptr_(new NormalDistributionsTransform), - state_ptr_(new std::map), is_activated_(false), param_(this) { - (*state_ptr_)["state"] = "Initializing"; - timer_callback_group_ = this->create_callback_group(rclcpp::CallbackGroupType::MutuallyExclusive); rclcpp::CallbackGroup::SharedPtr initial_pose_callback_group = this->create_callback_group(rclcpp::CallbackGroupType::MutuallyExclusive); @@ -117,6 +112,9 @@ NDTScanMatcher::NDTScanMatcher(const rclcpp::NodeOptions & options) const double value_as_unlimited = 1000.0; regularization_pose_buffer_ = std::make_unique(this->get_logger(), value_as_unlimited, value_as_unlimited); + + diagnostics_regularization_pose_ = + std::make_unique(this, "regularization_pose_subscriber_status"); } sensor_aligned_pose_pub_ = @@ -158,8 +156,6 @@ NDTScanMatcher::NDTScanMatcher(const rclcpp::NodeOptions & options) this->create_publisher( "initial_to_result_distance_new", 10); ndt_marker_pub_ = this->create_publisher("ndt_marker", 10); - diagnostics_pub_ = - this->create_publisher("/diagnostics", 10); ndt_monte_carlo_initial_pose_marker_pub_ = this->create_publisher( "monte_carlo_initial_pose_marker", 10); @@ -184,112 +180,68 @@ NDTScanMatcher::NDTScanMatcher(const rclcpp::NodeOptions & options) map_update_module_ = std::make_unique(this, &ndt_ptr_mtx_, ndt_ptr_, param_.dynamic_map_loading); + diagnostics_scan_points_ = std::make_unique(this, "scan_matching_status"); + diagnostics_initial_pose_ = + std::make_unique(this, "initial_pose_subscriber_status"); + diagnostics_map_update_ = std::make_unique(this, "map_update_status"); + diagnostics_ndt_align_ = std::make_unique(this, "ndt_align_service_status"); + diagnostics_trigger_node_ = + std::make_unique(this, "trigger_node_service_status"); + logger_configure_ = std::make_unique(this); } -void NDTScanMatcher::publish_diagnostic() +void NDTScanMatcher::callback_timer() { - diagnostic_msgs::msg::DiagnosticStatus diag_status_msg; - diag_status_msg.name = "ndt_scan_matcher"; - diag_status_msg.hardware_id = ""; - - for (const auto & key_value : (*state_ptr_)) { - diagnostic_msgs::msg::KeyValue key_value_msg; - key_value_msg.key = key_value.first; - key_value_msg.value = key_value.second; - diag_status_msg.values.push_back(key_value_msg); - } - - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::OK; - diag_status_msg.message = ""; - if (state_ptr_->count("state") && (*state_ptr_)["state"] == "Initializing") { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::WARN; - diag_status_msg.message += "Initializing State. "; - } - if ( - state_ptr_->count("lidar_topic_delay_time_sec") && - std::stod((*state_ptr_)["lidar_topic_delay_time_sec"]) > - param_.validation.lidar_topic_timeout_sec) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::WARN; - diag_status_msg.message += "lidar_topic_delay_time_sec exceed limit. "; - } - if ( - state_ptr_->count("skipping_publish_num") && - std::stoi((*state_ptr_)["skipping_publish_num"]) > 1 && - std::stoi((*state_ptr_)["skipping_publish_num"]) < 5) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::WARN; - diag_status_msg.message += "skipping_publish_num > 1. "; - } - if ( - state_ptr_->count("skipping_publish_num") && - std::stoi((*state_ptr_)["skipping_publish_num"]) >= 5) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::ERROR; - diag_status_msg.message += "skipping_publish_num exceed limit. "; - } - if ( - state_ptr_->count("nearest_voxel_transformation_likelihood") && - std::stod((*state_ptr_)["nearest_voxel_transformation_likelihood"]) < - param_.score_estimation.converged_param_nearest_voxel_transformation_likelihood) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::WARN; - diag_status_msg.message += "NDT score is unreliably low. "; - } - if ( - state_ptr_->count("execution_time") && std::stod((*state_ptr_)["execution_time"]) >= - param_.validation.critical_upper_bound_exe_time_ms) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::WARN; - diag_status_msg.message += - "NDT exe time is too long. (took " + (*state_ptr_)["execution_time"] + " [ms])"; - } - // Ignore local optimal solution - if ( - state_ptr_->count("is_local_optimal_solution_oscillation") && - std::stoi((*state_ptr_)["is_local_optimal_solution_oscillation"])) { - diag_status_msg.level = diagnostic_msgs::msg::DiagnosticStatus::OK; - diag_status_msg.message = "local optimal solution oscillation occurred"; - } - - diagnostic_msgs::msg::DiagnosticArray diag_msg; - diag_msg.header.stamp = this->now(); - diag_msg.status.push_back(diag_status_msg); - - diagnostics_pub_->publish(diag_msg); + diagnostics_map_update_->clear(); + + map_update_module_->callback_timer(is_activated_, latest_ekf_position_, diagnostics_map_update_); + + diagnostics_map_update_->publish(); } -void NDTScanMatcher::callback_timer() +void NDTScanMatcher::callback_initial_pose( + const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr initial_pose_msg_ptr) { - if (!is_activated_) { - return; - } - std::lock_guard lock(latest_ekf_position_mtx_); - if (latest_ekf_position_ == std::nullopt) { - RCLCPP_ERROR_STREAM_THROTTLE( - this->get_logger(), *this->get_clock(), 1000, - "Cannot find the reference position for map update. Please check if the EKF odometry is " - "provided to NDT."); - return; - } - // continue only if we should update the map - if (map_update_module_->should_update_map(latest_ekf_position_.value())) { - RCLCPP_INFO(this->get_logger(), "Start updating NDT map (timer_callback)"); - map_update_module_->update_map(latest_ekf_position_.value()); - } + diagnostics_initial_pose_->clear(); + + callback_initial_pose_main(initial_pose_msg_ptr); + + diagnostics_initial_pose_->publish(); } -void NDTScanMatcher::callback_initial_pose( +void NDTScanMatcher::callback_initial_pose_main( const geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr initial_pose_msg_ptr) { - if (!is_activated_) return; + diagnostics_initial_pose_->addKeyValue( + "topic_time_stamp", static_cast(initial_pose_msg_ptr->header.stamp).seconds()); - if (initial_pose_msg_ptr->header.frame_id == param_.frame.map_frame) { - initial_pose_buffer_->push_back(initial_pose_msg_ptr); - } else { - RCLCPP_ERROR_STREAM_THROTTLE( - get_logger(), *this->get_clock(), 1000, - "Received initial pose message with frame_id " - << initial_pose_msg_ptr->header.frame_id << ", but expected " << param_.frame.map_frame - << ". Please check the frame_id in the input topic and ensure it is correct."); + // check is_activated + diagnostics_initial_pose_->addKeyValue("is_activated", static_cast(is_activated_)); + if (!is_activated_) { + std::stringstream message; + message << "Node is not activated."; + diagnostics_initial_pose_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return; } + // check is_expected_frame_id + const bool is_expected_frame_id = + (initial_pose_msg_ptr->header.frame_id == param_.frame.map_frame); + diagnostics_initial_pose_->addKeyValue("is_expected_frame_id", is_expected_frame_id); + if (!is_expected_frame_id) { + std::stringstream message; + message << "Received initial pose message with frame_id " + << initial_pose_msg_ptr->header.frame_id << ", but expected " << param_.frame.map_frame + << ". Please check the frame_id in the input topic and ensure it is correct."; + diagnostics_initial_pose_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + return; + } + + initial_pose_buffer_->push_back(initial_pose_msg_ptr); + { // latest_ekf_position_ is also used by callback_timer, so it is necessary to acquire the lock std::lock_guard lock(latest_ekf_position_mtx_); @@ -300,41 +252,82 @@ void NDTScanMatcher::callback_initial_pose( void NDTScanMatcher::callback_regularization_pose( geometry_msgs::msg::PoseWithCovarianceStamped::ConstSharedPtr pose_conv_msg_ptr) { + diagnostics_regularization_pose_->clear(); + + diagnostics_regularization_pose_->addKeyValue( + "topic_time_stamp", static_cast(pose_conv_msg_ptr->header.stamp).seconds()); + regularization_pose_buffer_->push_back(pose_conv_msg_ptr); + + diagnostics_regularization_pose_->publish(); } void NDTScanMatcher::callback_sensor_points( sensor_msgs::msg::PointCloud2::ConstSharedPtr sensor_points_msg_in_sensor_frame) { - if (sensor_points_msg_in_sensor_frame->data.empty()) { - RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1, "Empty sensor points!"); - return; + // clear diagnostics + diagnostics_scan_points_->clear(); + + // scan matching + const bool is_succeed_scan_matching = + callback_sensor_points_main(sensor_points_msg_in_sensor_frame); + + // check skipping_publish_num + static size_t skipping_publish_num = 0; + const size_t error_skipping_publish_num = 5; + skipping_publish_num = is_succeed_scan_matching ? 0 : (skipping_publish_num + 1); + diagnostics_scan_points_->addKeyValue("skipping_publish_num", skipping_publish_num); + if (skipping_publish_num >= error_skipping_publish_num) { + std::stringstream message; + message << "skipping_publish_num exceed limit (" << skipping_publish_num << " times)."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); } + diagnostics_scan_points_->publish(); +} + +bool NDTScanMatcher::callback_sensor_points_main( + sensor_msgs::msg::PointCloud2::ConstSharedPtr sensor_points_msg_in_sensor_frame) +{ + const auto exe_start_time = std::chrono::system_clock::now(); + + // check topic_time_stamp const rclcpp::Time sensor_ros_time = sensor_points_msg_in_sensor_frame->header.stamp; - const double lidar_topic_delay_time_sec = (this->now() - sensor_ros_time).seconds(); - (*state_ptr_)["lidar_topic_delay_time_sec"] = std::to_string(lidar_topic_delay_time_sec); + diagnostics_scan_points_->addKeyValue("topic_time_stamp", sensor_ros_time.seconds()); + + // check sensor_points_size + const size_t sensor_points_size = sensor_points_msg_in_sensor_frame->width; + diagnostics_scan_points_->addKeyValue("sensor_points_size", sensor_points_size); + if (sensor_points_size == 0) { + std::stringstream message; + message << "Sensor points is empty."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; + } - if (lidar_topic_delay_time_sec > param_.validation.lidar_topic_timeout_sec) { - RCLCPP_WARN( - this->get_logger(), - "The LiDAR topic is experiencing latency. The delay time is %lf[sec] (the tolerance is " - "%lf[sec])", - lidar_topic_delay_time_sec, param_.validation.lidar_topic_timeout_sec); + // check sensor_points_delay_time_sec + const double sensor_points_delay_time_sec = + (this->now() - sensor_points_msg_in_sensor_frame->header.stamp).seconds(); + diagnostics_scan_points_->addKeyValue( + "sensor_points_delay_time_sec", sensor_points_delay_time_sec); + if (sensor_points_delay_time_sec > param_.validation.lidar_topic_timeout_sec) { + std::stringstream message; + message << "sensor points is experiencing latency." + << "The delay time is " << sensor_points_delay_time_sec << "[sec] " + << "(the tolerance is " << param_.validation.lidar_topic_timeout_sec << "[sec])."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); // If the delay time of the LiDAR topic exceeds the delay compensation time of ekf_localizer, // even if further processing continues, the estimated result will be rejected by ekf_localizer. // Therefore, it would be acceptable to exit the function here. // However, for now, we will continue the processing as it is. - // return; + // return false; } - // mutex ndt_ptr_ - std::lock_guard lock(ndt_ptr_mtx_); - - const auto exe_start_time = std::chrono::system_clock::now(); - // preprocess input pointcloud pcl::shared_ptr> sensor_points_in_sensor_frame( new pcl::PointCloud); @@ -343,34 +336,73 @@ void NDTScanMatcher::callback_sensor_points( const std::string & sensor_frame = sensor_points_msg_in_sensor_frame->header.frame_id; pcl::fromROSMsg(*sensor_points_msg_in_sensor_frame, *sensor_points_in_sensor_frame); - transform_sensor_measurement( - sensor_frame, param_.frame.base_frame, sensor_points_in_sensor_frame, - sensor_points_in_baselink_frame); - // check max distance of sensor points + // transform sensor points from sensor-frame to base_link + try { + transform_sensor_measurement( + sensor_frame, param_.frame.base_frame, sensor_points_in_sensor_frame, + sensor_points_in_baselink_frame); + } catch (const std::exception & ex) { + std::stringstream message; + message << ex.what() << ". Please publish TF " << sensor_frame << " to " + << param_.frame.base_frame; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + RCLCPP_ERROR_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1000, message.str()); + diagnostics_scan_points_->addKeyValue("is_succeed_transform_sensor_points", false); + return false; + } + diagnostics_scan_points_->addKeyValue("is_succeed_transform_sensor_points", true); + + // check sensor_points_max_distance double max_distance = 0.0; for (const auto & point : sensor_points_in_baselink_frame->points) { const double distance = std::hypot(point.x, point.y, point.z); max_distance = std::max(max_distance, distance); } + + diagnostics_scan_points_->addKeyValue("sensor_points_max_distance", max_distance); if (max_distance < param_.sensor_points.required_distance) { - RCLCPP_WARN_STREAM( - this->get_logger(), "Max distance of sensor points = " - << std::fixed << std::setprecision(3) << max_distance << " [m] < " - << param_.sensor_points.required_distance << " [m]"); - return; + std::stringstream message; + message << "Max distance of sensor points = " << std::fixed << std::setprecision(3) + << max_distance << " [m] < " << param_.sensor_points.required_distance << " [m]"; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; } + // lock mutex + std::lock_guard lock(ndt_ptr_mtx_); + + // set sensor points to ndt class ndt_ptr_->setInputSource(sensor_points_in_baselink_frame); - if (!is_activated_) return; + + // check is_activated + diagnostics_scan_points_->addKeyValue("is_activated", static_cast(is_activated_)); + if (!is_activated_) { + std::stringstream message; + message << "Node is not activated."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; + } // calculate initial pose std::optional interpolation_result_opt = initial_pose_buffer_->interpolate(sensor_ros_time); - if (!interpolation_result_opt) { - RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1, "No interpolated pose!"); - return; + + // check is_succeed_interpolate_initial_pose + const bool is_succeed_interpolate_initial_pose = (interpolation_result_opt != std::nullopt); + diagnostics_scan_points_->addKeyValue( + "is_succeed_interpolate_initial_pose", is_succeed_interpolate_initial_pose); + if (!is_succeed_interpolate_initial_pose) { + std::stringstream message; + message << "Couldn't interpolate pose. Please check the initial pose topic"; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; } + initial_pose_buffer_->pop_old(sensor_ros_time); const SmartPoseBuffer::InterpolateResult & interpolation_result = interpolation_result_opt.value(); @@ -380,9 +412,15 @@ void NDTScanMatcher::callback_sensor_points( add_regularization_pose(sensor_ros_time); } - if (ndt_ptr_->getInputTarget() == nullptr) { - RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1, "No MAP!"); - return; + // check is_set_map_points + const bool is_set_map_points = (ndt_ptr_->getInputTarget() != nullptr); + diagnostics_scan_points_->addKeyValue("is_set_map_points", is_set_map_points); + if (!is_set_map_points) { + std::stringstream message; + message << "Map points is not set."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + return false; } // perform ndt scan matching @@ -399,26 +437,68 @@ void NDTScanMatcher::callback_sensor_points( transformation_msg_array.push_back(pose_ros); } - // perform several validations - bool is_ok_iteration_num = - validate_num_iteration(ndt_result.iteration_num, ndt_ptr_->getMaximumIterations()); - const int oscillation_num = count_oscillation(transformation_msg_array); - bool is_local_optimal_solution_oscillation = false; + // check iteration_num + diagnostics_scan_points_->addKeyValue("iteration_num", ndt_result.iteration_num); + const bool is_ok_iteration_num = (ndt_result.iteration_num < ndt_ptr_->getMaximumIterations()); if (!is_ok_iteration_num) { - constexpr int oscillation_threshold = 10; - is_local_optimal_solution_oscillation = (oscillation_num > oscillation_threshold); + std::stringstream message; + message << "The number of iterations has reached its upper limit. The number of iterations: " + << ndt_result.iteration_num << ", Limit: " << ndt_ptr_->getMaximumIterations() << "."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); } - bool is_ok_converged_param = validate_converged_param( - ndt_result.transform_probability, ndt_result.nearest_voxel_transformation_likelihood); - bool is_converged = is_ok_iteration_num && is_ok_converged_param; - static size_t skipping_publish_num = 0; - if (is_converged) { - skipping_publish_num = 0; + + // check local_optimal_solution_oscillation_num + constexpr int oscillation_num_threshold = 10; + const int oscillation_num = count_oscillation(transformation_msg_array); + diagnostics_scan_points_->addKeyValue("local_optimal_solution_oscillation_num", oscillation_num); + const bool is_local_optimal_solution_oscillation = (oscillation_num > oscillation_num_threshold); + if (is_local_optimal_solution_oscillation) { + std::stringstream message; + message << "There is a possibility of oscillation in a local minimum"; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + } + + // check score + diagnostics_scan_points_->addKeyValue("transform_probability", ndt_result.transform_probability); + diagnostics_scan_points_->addKeyValue( + "nearest_voxel_transformation_likelihood", ndt_result.nearest_voxel_transformation_likelihood); + std::string score_name = ""; + double score = 0.0; + double score_threshold = 0.0; + if (param_.score_estimation.converged_param_type == ConvergedParamType::TRANSFORM_PROBABILITY) { + score_name = "Transform Probability"; + score = ndt_result.transform_probability; + score_threshold = param_.score_estimation.converged_param_transform_probability; + } else if ( + param_.score_estimation.converged_param_type == + ConvergedParamType::NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD) { + score_name = "Nearest Voxel Transformation Likelihood"; + score = ndt_result.nearest_voxel_transformation_likelihood; + score_threshold = + param_.score_estimation.converged_param_nearest_voxel_transformation_likelihood; } else { - ++skipping_publish_num; - RCLCPP_WARN(get_logger(), "Not Converged"); + std::stringstream message; + message << "Unknown converged param type. Please check `score_estimation.converged_param_type`"; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + return false; } + bool is_ok_score = (score > score_threshold); + if (!is_ok_score) { + std::stringstream message; + message << "Score is below the threshold. Score: " << score + << ", Threshold: " << score_threshold; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + RCLCPP_WARN_STREAM(this->get_logger(), message.str()); + } + + // check is_converged + bool is_converged = (is_ok_iteration_num || is_local_optimal_solution_oscillation) && is_ok_score; + // covariance estimation const Eigen::Quaterniond map_to_base_link_quat = Eigen::Quaterniond( result_pose_msg.orientation.w, result_pose_msg.orientation.x, result_pose_msg.orientation.y, @@ -435,10 +515,31 @@ void NDTScanMatcher::callback_sensor_points( ndt_covariance = estimated_covariance; } + // check distance_initial_to_result + const auto distance_initial_to_result = static_cast( + norm(interpolation_result.interpolated_pose.pose.pose.position, result_pose_msg.position)); + diagnostics_scan_points_->addKeyValue("distance_initial_to_result", distance_initial_to_result); + const double warn_distance_initial_to_result = 3.0; + if (distance_initial_to_result > warn_distance_initial_to_result) { + std::stringstream message; + message << "distance_initial_to_result is too large (" << distance_initial_to_result + << " [m])."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + } + + // check execution_time const auto exe_end_time = std::chrono::system_clock::now(); const auto duration_micro_sec = std::chrono::duration_cast(exe_end_time - exe_start_time).count(); const auto exe_time = static_cast(duration_micro_sec) / 1000.0f; + diagnostics_scan_points_->addKeyValue("execution_time", exe_time); + if (exe_time > param_.validation.critical_upper_bound_exe_time_ms) { + std::stringstream message; + message << "NDT exe time is too long (took " << exe_time << " [ms])."; + diagnostics_scan_points_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + } // publish initial_pose_with_covariance_pub_->publish(interpolation_result.interpolated_pose); @@ -492,18 +593,7 @@ void NDTScanMatcher::callback_sensor_points( make_float32_stamped(sensor_ros_time, no_ground_nearest_voxel_transformation_likelihood)); } - (*state_ptr_)["state"] = "Aligned"; - (*state_ptr_)["transform_probability"] = std::to_string(ndt_result.transform_probability); - (*state_ptr_)["nearest_voxel_transformation_likelihood"] = - std::to_string(ndt_result.nearest_voxel_transformation_likelihood); - (*state_ptr_)["iteration_num"] = std::to_string(ndt_result.iteration_num); - (*state_ptr_)["skipping_publish_num"] = std::to_string(skipping_publish_num); - (*state_ptr_)["oscillation_count"] = std::to_string(oscillation_num); - (*state_ptr_)["is_local_optimal_solution_oscillation"] = - std::to_string(is_local_optimal_solution_oscillation); - (*state_ptr_)["execution_time"] = std::to_string(exe_time); - - publish_diagnostic(); + return is_converged; } void NDTScanMatcher::transform_sensor_measurement( @@ -520,12 +610,7 @@ void NDTScanMatcher::transform_sensor_measurement( try { transform = tf2_buffer_.lookupTransform(target_frame, source_frame, tf2::TimePointZero); } catch (tf2::TransformException & ex) { - RCLCPP_WARN(this->get_logger(), "%s", ex.what()); - RCLCPP_WARN( - this->get_logger(), "Please publish TF %s to %s", target_frame.c_str(), source_frame.c_str()); - // Since there is no clear error handling policy, temporarily return as is. - sensor_points_output_ptr = sensor_points_input_ptr; - return; + throw; } const geometry_msgs::msg::PoseStamped target_to_source_pose_stamped = @@ -638,54 +723,6 @@ void NDTScanMatcher::publish_initial_to_result( make_float32_stamped(sensor_ros_time, initial_to_result_distance_new)); } -bool NDTScanMatcher::validate_num_iteration(const int iter_num, const int max_iter_num) -{ - bool is_ok_iter_num = iter_num < max_iter_num; - if (!is_ok_iter_num) { - RCLCPP_WARN( - get_logger(), - "The number of iterations has reached its upper limit. The number of iterations: %d, Limit: " - "%d", - iter_num, max_iter_num); - } - return is_ok_iter_num; -} - -bool NDTScanMatcher::validate_score( - const double score, const double score_threshold, const std::string & score_name) -{ - bool is_ok_score = score > score_threshold; - if (!is_ok_score) { - RCLCPP_WARN( - get_logger(), "%s is below the threshold. Score: %lf, Threshold: %lf", score_name.c_str(), - score, score_threshold); - } - return is_ok_score; -} - -bool NDTScanMatcher::validate_converged_param( - const double & transform_probability, const double & nearest_voxel_transformation_likelihood) -{ - bool is_ok_converged_param = false; - if (param_.score_estimation.converged_param_type == ConvergedParamType::TRANSFORM_PROBABILITY) { - is_ok_converged_param = validate_score( - transform_probability, param_.score_estimation.converged_param_transform_probability, - "Transform Probability"); - } else if ( - param_.score_estimation.converged_param_type == - ConvergedParamType::NEAREST_VOXEL_TRANSFORMATION_LIKELIHOOD) { - is_ok_converged_param = validate_score( - nearest_voxel_transformation_likelihood, - param_.score_estimation.converged_param_nearest_voxel_transformation_likelihood, - "Nearest Voxel Transformation Likelihood"); - } else { - is_ok_converged_param = false; - RCLCPP_ERROR_STREAM_THROTTLE( - this->get_logger(), *this->get_clock(), 1, "Unknown converged param type."); - } - return is_ok_converged_param; -} - int NDTScanMatcher::count_oscillation( const std::vector & result_pose_msg_array) { @@ -744,7 +781,10 @@ std::array NDTScanMatcher::estimate_covariance( rot = find_rotation_matrix_aligning_covariance_to_principal_axes( ndt_result.hessian.inverse().block(0, 0, 2, 2)); } catch (const std::exception & e) { - RCLCPP_WARN(get_logger(), "Error in Eigen solver: %s", e.what()); + std::stringstream message; + message << "Error in Eigen solver: " << e.what(); + RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1000, message.str()); + return param_.covariance.output_pose_covariance; } @@ -822,24 +862,53 @@ void NDTScanMatcher::add_regularization_pose(const rclcpp::Time & sensor_ros_tim interpolation_result_opt.value(); const Eigen::Matrix4f pose = pose_to_matrix4f(interpolation_result.interpolated_pose.pose.pose); ndt_ptr_->setRegularizationPose(pose); - RCLCPP_DEBUG_STREAM(get_logger(), "Regularization pose is set to NDT"); } void NDTScanMatcher::service_trigger_node( const std_srvs::srv::SetBool::Request::SharedPtr req, std_srvs::srv::SetBool::Response::SharedPtr res) { + diagnostics_trigger_node_->clear(); + diagnostics_trigger_node_->addKeyValue("service_call_time_stamp", this->now().seconds()); + is_activated_ = req->data; if (is_activated_) { initial_pose_buffer_->clear(); } res->success = true; + + diagnostics_trigger_node_->addKeyValue("is_activated", static_cast(is_activated_)); + diagnostics_trigger_node_->addKeyValue("is_succeed_service", res->success); + diagnostics_trigger_node_->publish(); } void NDTScanMatcher::service_ndt_align( const tier4_localization_msgs::srv::PoseWithCovarianceStamped::Request::SharedPtr req, tier4_localization_msgs::srv::PoseWithCovarianceStamped::Response::SharedPtr res) { + diagnostics_ndt_align_->clear(); + + service_ndt_align_main(req, res); + + // check is_succeed_service + bool is_succeed_service = res->success; + diagnostics_ndt_align_->addKeyValue("is_succeed_service", is_succeed_service); + if (!is_succeed_service) { + std::stringstream message; + message << "ndt_align_service is failed."; + diagnostics_ndt_align_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + } + + diagnostics_ndt_align_->publish(); +} + +void NDTScanMatcher::service_ndt_align_main( + const tier4_localization_msgs::srv::PoseWithCovarianceStamped::Request::SharedPtr req, + tier4_localization_msgs::srv::PoseWithCovarianceStamped::Response::SharedPtr res) +{ + diagnostics_ndt_align_->addKeyValue("service_call_time_stamp", this->now().seconds()); + // get TF from pose_frame to map_frame const std::string & target_frame = param_.frame.map_frame; const std::string & source_frame = req->pose_with_covariance.header.frame_id; @@ -851,32 +920,50 @@ void NDTScanMatcher::service_ndt_align( // Note: Up to AWSIMv1.1.0, there is a known bug where the GNSS frame_id is incorrectly set to // "gnss_link" instead of "map". The ndt_align is designed to return identity when this issue // occurs. However, in the future, converting to a non-existent frame_id should be prohibited. - RCLCPP_WARN(this->get_logger(), "%s", ex.what()); - RCLCPP_WARN( - this->get_logger(), "Please publish TF %s to %s", target_frame.c_str(), source_frame.c_str()); - transform_s2t.header.stamp = get_clock()->now(); - transform_s2t.header.frame_id = target_frame; - transform_s2t.child_frame_id = source_frame; - transform_s2t.transform = tf2::toMsg(tf2::Transform::getIdentity()); + + diagnostics_ndt_align_->addKeyValue("is_succeed_transform_initial_pose", false); + + std::stringstream message; + message << "Please publish TF " << target_frame.c_str() << " to " << source_frame.c_str(); + diagnostics_ndt_align_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::ERROR, message.str()); + RCLCPP_ERROR_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1000, message.str()); + res->success = false; + return; } + diagnostics_ndt_align_->addKeyValue("is_succeed_transform_initial_pose", true); // transform pose_frame to map_frame const auto initial_pose_msg_in_map_frame = transform(req->pose_with_covariance, transform_s2t); - map_update_module_->update_map(initial_pose_msg_in_map_frame.pose.pose.position); + map_update_module_->update_map( + initial_pose_msg_in_map_frame.pose.pose.position, diagnostics_ndt_align_); // mutex Map std::lock_guard lock(ndt_ptr_mtx_); - if (ndt_ptr_->getInputTarget() == nullptr) { + // check is_set_map_points + bool is_set_map_points = (ndt_ptr_->getInputTarget() != nullptr); + diagnostics_ndt_align_->addKeyValue("is_set_map_points", is_set_map_points); + if (!is_set_map_points) { + std::stringstream message; + message << "No InputTarget. Please check the map file and the map_loader service"; + diagnostics_ndt_align_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1000, message.str()); res->success = false; - RCLCPP_WARN( - get_logger(), "No InputTarget. Please check the map file and the map_loader service"); return; } - if (ndt_ptr_->getInputSource() == nullptr) { + // check is_set_sensor_points + bool is_set_sensor_points = (ndt_ptr_->getInputSource() != nullptr); + diagnostics_ndt_align_->addKeyValue("is_set_sensor_points", is_set_sensor_points); + if (!is_set_sensor_points) { + std::stringstream message; + message << "No InputSource. Please check the input lidar topic"; + diagnostics_ndt_align_->updateLevelAndMessage( + diagnostic_msgs::msg::DiagnosticStatus::WARN, message.str()); + RCLCPP_WARN_STREAM_THROTTLE(this->get_logger(), *this->get_clock(), 1000, message.str()); res->success = false; - RCLCPP_WARN(get_logger(), "No InputSource. Please check the input lidar topic"); return; } @@ -899,34 +986,20 @@ geometry_msgs::msg::PoseWithCovarianceStamped NDTScanMatcher::align_pose( const double stddev_roll = std::sqrt(covariance(3, 3)); const double stddev_pitch = std::sqrt(covariance(4, 4)); - // Let phi be the cumulative distribution function of the standard normal distribution. - // It has the following relationship with the error function (erf). - // phi(x) = 1/2 (1 + erf(x / sqrt(2))) - // so, 2 * phi(x) - 1 = erf(x / sqrt(2)). - // The range taken by 2 * phi(x) - 1 is [-1, 1], so it can be used as a uniform distribution in - // TPE. Let u = 2 * phi(x) - 1, then x = sqrt(2) * erf_inv(u). Computationally, it is not a good - // to give erf_inv -1 and 1, so it is rounded off at (-1 + eps, 1 - eps). - const double sqrt2 = std::sqrt(2); - auto uniform_to_normal = [&sqrt2](const double uniform) { - assert(-1.0 <= uniform && uniform <= 1.0); - constexpr double epsilon = 1.0e-6; - const double clamped = std::clamp(uniform, -1.0 + epsilon, 1.0 - epsilon); - return boost::math::erf_inv(clamped) * sqrt2; - }; - - auto normal_to_uniform = [&sqrt2](const double normal) { - return boost::math::erf(normal / sqrt2); + // Since only yaw is uniformly sampled, we define the mean and standard deviation for the others. + const std::vector sample_mean{ + initial_pose_with_cov.pose.pose.position.x, // trans_x + initial_pose_with_cov.pose.pose.position.y, // trans_y + initial_pose_with_cov.pose.pose.position.z, // trans_z + base_rpy.x, // angle_x + base_rpy.y // angle_y }; + const std::vector sample_stddev{stddev_x, stddev_y, stddev_z, stddev_roll, stddev_pitch}; // Optimizing (x, y, z, roll, pitch, yaw) 6 dimensions. - // The last dimension (yaw) is a loop variable. - // Although roll and pitch are also angles, they are considered non-looping variables that follow - // a normal distribution with a small standard deviation. This assumes that the initial pose of - // the ego vehicle is aligned with the ground to some extent about roll and pitch. - const std::vector is_loop_variable = {false, false, false, false, false, true}; TreeStructuredParzenEstimator tpe( TreeStructuredParzenEstimator::Direction::MAXIMIZE, - param_.initial_pose_estimation.n_startup_trials, is_loop_variable); + param_.initial_pose_estimation.n_startup_trials, sample_mean, sample_stddev); std::vector particle_array; auto output_cloud = std::make_shared>(); @@ -940,16 +1013,13 @@ geometry_msgs::msg::PoseWithCovarianceStamped NDTScanMatcher::align_pose( const TreeStructuredParzenEstimator::Input input = tpe.get_next_input(); geometry_msgs::msg::Pose initial_pose; - initial_pose.position.x = - initial_pose_with_cov.pose.pose.position.x + uniform_to_normal(input[0]) * stddev_x; - initial_pose.position.y = - initial_pose_with_cov.pose.pose.position.y + uniform_to_normal(input[1]) * stddev_y; - initial_pose.position.z = - initial_pose_with_cov.pose.pose.position.z + uniform_to_normal(input[2]) * stddev_z; + initial_pose.position.x = input[0]; + initial_pose.position.y = input[1]; + initial_pose.position.z = input[2]; geometry_msgs::msg::Vector3 init_rpy; - init_rpy.x = base_rpy.x + uniform_to_normal(input[3]) * stddev_roll; - init_rpy.y = base_rpy.y + uniform_to_normal(input[4]) * stddev_pitch; - init_rpy.z = base_rpy.z + input[5] * M_PI; + init_rpy.x = input[3]; + init_rpy.y = input[4]; + init_rpy.z = input[5]; tf2::Quaternion tf_quaternion; tf_quaternion.setRPY(init_rpy.x, init_rpy.y, init_rpy.z); initial_pose.orientation = tf2::toMsg(tf_quaternion); @@ -972,22 +1042,13 @@ geometry_msgs::msg::PoseWithCovarianceStamped NDTScanMatcher::align_pose( const geometry_msgs::msg::Pose pose = matrix4f_to_pose(ndt_result.pose); const geometry_msgs::msg::Vector3 rpy = get_rpy(pose); - const double diff_x = pose.position.x - initial_pose_with_cov.pose.pose.position.x; - const double diff_y = pose.position.y - initial_pose_with_cov.pose.pose.position.y; - const double diff_z = pose.position.z - initial_pose_with_cov.pose.pose.position.z; - const double diff_roll = rpy.x - base_rpy.x; - const double diff_pitch = rpy.y - base_rpy.y; - const double diff_yaw = rpy.z - base_rpy.z; - - // Only yaw is a loop_variable, so only simple normalization is performed. - // All other variables are converted from normal distribution to uniform distribution. - TreeStructuredParzenEstimator::Input result(is_loop_variable.size()); - result[0] = normal_to_uniform(diff_x / stddev_x); - result[1] = normal_to_uniform(diff_y / stddev_y); - result[2] = normal_to_uniform(diff_z / stddev_z); - result[3] = normal_to_uniform(diff_roll / stddev_roll); - result[4] = normal_to_uniform(diff_pitch / stddev_pitch); - result[5] = diff_yaw / M_PI; + TreeStructuredParzenEstimator::Input result(6); + result[0] = pose.position.x; + result[1] = pose.position.y; + result[2] = pose.position.z; + result[3] = rpy.x; + result[4] = rpy.y; + result[5] = rpy.z; tpe.add_trial(TreeStructuredParzenEstimator::Trial{result, ndt_result.transform_probability}); auto sensor_points_in_map_ptr = std::make_shared>(); @@ -1007,7 +1068,7 @@ geometry_msgs::msg::PoseWithCovarianceStamped NDTScanMatcher::align_pose( result_pose_with_cov_msg.pose.pose = best_particle_ptr->result_pose; output_pose_with_cov_to_log(get_logger(), "align_pose_output", result_pose_with_cov_msg); - RCLCPP_DEBUG_STREAM(get_logger(), "best_score," << best_particle_ptr->score); + diagnostics_ndt_align_->addKeyValue("best_particle_score", best_particle_ptr->score); return result_pose_with_cov_msg; } diff --git a/localization/ndt_scan_matcher/src/ndt_scan_matcher_node.cpp b/localization/ndt_scan_matcher/src/ndt_scan_matcher_node.cpp index 6e2ed022f531e..785055eef3700 100644 --- a/localization/ndt_scan_matcher/src/ndt_scan_matcher_node.cpp +++ b/localization/ndt_scan_matcher/src/ndt_scan_matcher_node.cpp @@ -20,8 +20,10 @@ int main(int argc, char ** argv) { - google::InitGoogleLogging(argv[0]); // NOLINT - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging(argv[0]); // NOLINT + google::InstallFailureSignalHandler(); + } rclcpp::init(argc, argv); auto ndt_scan_matcher = std::make_shared(); diff --git a/localization/pose_estimator_arbiter/package.xml b/localization/pose_estimator_arbiter/package.xml index b416d42c8617f..480b323f3031d 100644 --- a/localization/pose_estimator_arbiter/package.xml +++ b/localization/pose_estimator_arbiter/package.xml @@ -15,8 +15,8 @@ autoware_auto_mapping_msgs diagnostic_msgs geometry_msgs + glog lanelet2_extension - libgoogle-glog-dev magic_enum pcl_conversions pcl_ros diff --git a/localization/pose_estimator_arbiter/src/pose_estimator_arbiter/pose_estimator_arbiter_node.cpp b/localization/pose_estimator_arbiter/src/pose_estimator_arbiter/pose_estimator_arbiter_node.cpp index e48507948520b..20aaaf10abaab 100644 --- a/localization/pose_estimator_arbiter/src/pose_estimator_arbiter/pose_estimator_arbiter_node.cpp +++ b/localization/pose_estimator_arbiter/src/pose_estimator_arbiter/pose_estimator_arbiter_node.cpp @@ -18,8 +18,10 @@ int main(int argc, char * argv[]) { - google::InitGoogleLogging(argv[0]); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging(argv[0]); + google::InstallFailureSignalHandler(); + } rclcpp::init(argc, argv); auto node = std::make_shared(); diff --git a/localization/tree_structured_parzen_estimator/include/tree_structured_parzen_estimator/tree_structured_parzen_estimator.hpp b/localization/tree_structured_parzen_estimator/include/tree_structured_parzen_estimator/tree_structured_parzen_estimator.hpp index b7b522b4e6b76..30d36e7150113 100644 --- a/localization/tree_structured_parzen_estimator/include/tree_structured_parzen_estimator/tree_structured_parzen_estimator.hpp +++ b/localization/tree_structured_parzen_estimator/include/tree_structured_parzen_estimator/tree_structured_parzen_estimator.hpp @@ -44,37 +44,40 @@ class TreeStructuredParzenEstimator MAXIMIZE = 1, }; + enum Index { + TRANS_X = 0, + TRANS_Y = 1, + TRANS_Z = 2, + ANGLE_X = 3, + ANGLE_Y = 4, + ANGLE_Z = 5, + INDEX_NUM = 6, + }; + TreeStructuredParzenEstimator() = delete; TreeStructuredParzenEstimator( - const Direction direction, const int64_t n_startup_trials, std::vector is_loop_variable); + const Direction direction, const int64_t n_startup_trials, + const std::vector & sample_mean, const std::vector & sample_stddev); void add_trial(const Trial & trial); Input get_next_input() const; private: - static constexpr double BASE_STDDEV_COEFF = 0.2; static constexpr double MAX_GOOD_RATE = 0.10; - static constexpr double MAX_VALUE = 1.0; - static constexpr double MIN_VALUE = -1.0; - static constexpr double VALUE_WIDTH = MAX_VALUE - MIN_VALUE; static constexpr int64_t N_EI_CANDIDATES = 100; - static constexpr double PRIOR_WEIGHT = 0.0; static std::mt19937_64 engine; - static std::uniform_real_distribution dist_uniform; - static std::normal_distribution dist_normal; double compute_log_likelihood_ratio(const Input & input) const; double log_gaussian_pdf(const Input & input, const Input & mu, const Input & sigma) const; - static std::vector get_weights(const int64_t n); - static double normalize_loop_variable(const double value); std::vector trials_; int64_t above_num_; const Direction direction_; const int64_t n_startup_trials_; const int64_t input_dimension_; - const std::vector is_loop_variable_; - const Input base_stddev_; + const std::vector sample_mean_; + const std::vector sample_stddev_; + Input base_stddev_; }; #endif // TREE_STRUCTURED_PARZEN_ESTIMATOR__TREE_STRUCTURED_PARZEN_ESTIMATOR_HPP_ diff --git a/localization/tree_structured_parzen_estimator/src/tree_structured_parzen_estimator.cpp b/localization/tree_structured_parzen_estimator/src/tree_structured_parzen_estimator.cpp index 99c70a844f331..c81962c14f61c 100644 --- a/localization/tree_structured_parzen_estimator/src/tree_structured_parzen_estimator.cpp +++ b/localization/tree_structured_parzen_estimator/src/tree_structured_parzen_estimator.cpp @@ -21,19 +21,33 @@ // random number generator std::mt19937_64 TreeStructuredParzenEstimator::engine(std::random_device{}()); -std::uniform_real_distribution TreeStructuredParzenEstimator::dist_uniform( - TreeStructuredParzenEstimator::MIN_VALUE, TreeStructuredParzenEstimator::MAX_VALUE); -std::normal_distribution TreeStructuredParzenEstimator::dist_normal(0.0, 1.0); TreeStructuredParzenEstimator::TreeStructuredParzenEstimator( - const Direction direction, const int64_t n_startup_trials, std::vector is_loop_variable) + const Direction direction, const int64_t n_startup_trials, + const std::vector & sample_mean, const std::vector & sample_stddev) : above_num_(0), direction_(direction), n_startup_trials_(n_startup_trials), - input_dimension_(is_loop_variable.size()), - is_loop_variable_(is_loop_variable), - base_stddev_(input_dimension_, VALUE_WIDTH) + input_dimension_(INDEX_NUM), + sample_mean_(sample_mean), + sample_stddev_(sample_stddev) { + if (sample_mean_.size() != ANGLE_Z) { + std::cerr << "sample_mean size is invalid" << std::endl; + throw std::runtime_error("sample_mean size is invalid"); + } + if (sample_stddev_.size() != ANGLE_Z) { + std::cerr << "sample_stddev size is invalid" << std::endl; + throw std::runtime_error("sample_stddev size is invalid"); + } + // base_stddev_ is defined as the stable convergence range of ndt_scan_matcher. + base_stddev_.resize(input_dimension_); + base_stddev_[TRANS_X] = 0.25; // [m] + base_stddev_[TRANS_Y] = 0.25; // [m] + base_stddev_[TRANS_Z] = 0.25; // [m] + base_stddev_[ANGLE_X] = 1.0 / 180.0 * M_PI; // [rad] + base_stddev_[ANGLE_Y] = 1.0 / 180.0 * M_PI; // [rad] + base_stddev_[ANGLE_Z] = 2.5 / 180.0 * M_PI; // [rad] } void TreeStructuredParzenEstimator::add_trial(const Trial & trial) @@ -43,47 +57,45 @@ void TreeStructuredParzenEstimator::add_trial(const Trial & trial) return (direction_ == Direction::MAXIMIZE ? lhs.score > rhs.score : lhs.score < rhs.score); }); above_num_ = - std::min(static_cast(25), static_cast(trials_.size() * MAX_GOOD_RATE)); + std::min({static_cast(10), static_cast(trials_.size() * MAX_GOOD_RATE)}); } TreeStructuredParzenEstimator::Input TreeStructuredParzenEstimator::get_next_input() const { + std::normal_distribution dist_normal_trans_x( + sample_mean_[TRANS_X], sample_stddev_[TRANS_X]); + std::normal_distribution dist_normal_trans_y( + sample_mean_[TRANS_Y], sample_stddev_[TRANS_Y]); + std::normal_distribution dist_normal_trans_z( + sample_mean_[TRANS_Z], sample_stddev_[TRANS_Z]); + std::normal_distribution dist_normal_angle_x( + sample_mean_[ANGLE_X], sample_stddev_[ANGLE_X]); + std::normal_distribution dist_normal_angle_y( + sample_mean_[ANGLE_Y], sample_stddev_[ANGLE_Y]); + std::uniform_real_distribution dist_uniform_angle_z(-M_PI, M_PI); + if (static_cast(trials_.size()) < n_startup_trials_ || above_num_ == 0) { // Random sampling based on prior until the number of trials reaches `n_startup_trials_`. Input input(input_dimension_); - for (int64_t j = 0; j < input_dimension_; j++) { - input[j] = dist_uniform(engine); - } + input[TRANS_X] = dist_normal_trans_x(engine); + input[TRANS_Y] = dist_normal_trans_y(engine); + input[TRANS_Z] = dist_normal_trans_z(engine); + input[ANGLE_X] = dist_normal_angle_x(engine); + input[ANGLE_Y] = dist_normal_angle_y(engine); + input[ANGLE_Z] = dist_uniform_angle_z(engine); return input; } Input best_input; double best_log_likelihood_ratio = std::numeric_limits::lowest(); - const double coeff = BASE_STDDEV_COEFF * std::pow(above_num_, -1.0 / (4 + input_dimension_)); - std::vector weights = get_weights(above_num_); - weights.push_back(PRIOR_WEIGHT); - std::discrete_distribution dist(weights.begin(), weights.end()); for (int64_t i = 0; i < N_EI_CANDIDATES; i++) { - Input mu, sigma; - const int64_t index = dist(engine); - if (index == above_num_) { - mu = Input(input_dimension_, 0.0); - sigma = base_stddev_; - } else { - mu = trials_[index].input; - sigma = base_stddev_; - for (int64_t j = 0; j < input_dimension_; j++) { - sigma[j] *= coeff; - } - } - // sample from the normal distribution Input input(input_dimension_); - for (int64_t j = 0; j < input_dimension_; j++) { - input[j] = mu[j] + dist_normal(engine) * sigma[j]; - input[j] = - (is_loop_variable_[j] ? normalize_loop_variable(input[j]) - : std::clamp(input[j], MIN_VALUE, MAX_VALUE)); - } + input[TRANS_X] = dist_normal_trans_x(engine); + input[TRANS_Y] = dist_normal_trans_y(engine); + input[TRANS_Z] = dist_normal_trans_z(engine); + input[ANGLE_X] = dist_normal_angle_x(engine); + input[ANGLE_Y] = dist_normal_angle_y(engine); + input[ANGLE_Z] = dist_uniform_angle_z(engine); const double log_likelihood_ratio = compute_log_likelihood_ratio(input); if (log_likelihood_ratio > best_log_likelihood_ratio) { best_log_likelihood_ratio = log_likelihood_ratio; @@ -102,50 +114,19 @@ double TreeStructuredParzenEstimator::compute_log_likelihood_ratio(const Input & std::vector above_logs; std::vector below_logs; - // Scott's rule - const double coeff_above = - BASE_STDDEV_COEFF * std::pow(above_num_, -1.0 / (4 + input_dimension_)); - const double coeff_below = - BASE_STDDEV_COEFF * std::pow(n - above_num_, -1.0 / (4 + input_dimension_)); - Input sigma_above = base_stddev_; - Input sigma_below = base_stddev_; - for (int64_t j = 0; j < input_dimension_; j++) { - sigma_above[j] *= coeff_above; - sigma_below[j] *= coeff_below; - } - - std::vector above_weights = get_weights(above_num_); - std::vector below_weights = get_weights(n - above_num_); - std::reverse(below_weights.begin(), below_weights.end()); // below_weights is ascending order - - // calculate the sum of weights to normalize - double above_sum = std::accumulate(above_weights.begin(), above_weights.end(), 0.0); - double below_sum = std::accumulate(below_weights.begin(), below_weights.end(), 0.0); - - // above includes prior - above_sum += PRIOR_WEIGHT; - for (int64_t i = 0; i < n; i++) { + const double log_p = log_gaussian_pdf(input, trials_[i].input, base_stddev_); if (i < above_num_) { - const double log_p = log_gaussian_pdf(input, trials_[i].input, sigma_above); - const double w = above_weights[i] / above_sum; + const double w = 1.0 / above_num_; const double log_w = std::log(w); above_logs.push_back(log_p + log_w); } else { - const double log_p = log_gaussian_pdf(input, trials_[i].input, sigma_below); - const double w = below_weights[i - above_num_] / below_sum; + const double w = 1.0 / (n - above_num_); const double log_w = std::log(w); below_logs.push_back(log_p + log_w); } } - // prior - if (PRIOR_WEIGHT > 0.0) { - const double log_p = log_gaussian_pdf(input, Input(input_dimension_, 0.0), base_stddev_); - const double log_w = std::log(PRIOR_WEIGHT / above_sum); - above_logs.push_back(log_p + log_w); - } - auto log_sum_exp = [](const std::vector & log_vec) { const double max = *std::max_element(log_vec.begin(), log_vec.end()); double sum = 0.0; @@ -157,7 +138,11 @@ double TreeStructuredParzenEstimator::compute_log_likelihood_ratio(const Input & const double above = log_sum_exp(above_logs); const double below = log_sum_exp(below_logs); - const double r = above - below; + + // Multiply by a constant so that the score near the "below sample" becomes lower. + // cspell:disable-line TODO(Shintaro Sakoda): It's theoretically incorrect, consider it again + // later. + const double r = above - below * 5.0; return r; } @@ -174,44 +159,21 @@ double TreeStructuredParzenEstimator::log_gaussian_pdf( double result = 0.0; for (int64_t i = 0; i < n; i++) { double diff = input[i] - mu[i]; - if (is_loop_variable_[i]) { - diff = normalize_loop_variable(diff); + if (i == ANGLE_Z) { + // Normalize the loop variable to [-pi, pi) + while (diff >= M_PI) { + diff -= 2 * M_PI; + } + while (diff < -M_PI) { + diff += 2 * M_PI; + } } - result += log_gaussian_pdf_1d(diff, sigma[i]); - } - return result; -} - -std::vector TreeStructuredParzenEstimator::get_weights(const int64_t n) -{ - // See optuna - // https://github.com/optuna/optuna/blob/4bfab78e98bf786f6a2ce6e593a26e3f8403e08d/optuna/samplers/_tpe/sampler.py#L50-L58 - std::vector weights; - constexpr int64_t WEIGHT_ALPHA = 25; - if (n == 0) { - return weights; - } else if (n < WEIGHT_ALPHA) { - weights.resize(n, 1.0); - } else { - weights.resize(n); - const double unit = (1.0 - 1.0 / n) / (n - WEIGHT_ALPHA); - for (int64_t i = 0; i < n; i++) { - weights[i] = (i < WEIGHT_ALPHA ? 1.0 : 1.0 - unit * (i - WEIGHT_ALPHA)); + // Experimentally, it is better to consider only trans_xy and yaw, so ignore trans_z, angle_x, + // angle_y. + if (i == TRANS_Z || i == ANGLE_X || i == ANGLE_Y) { + continue; } - } - - return weights; -} - -double TreeStructuredParzenEstimator::normalize_loop_variable(const double value) -{ - // Normalize the loop variable to [-1, 1) - double result = value; - while (result >= MAX_VALUE) { - result -= VALUE_WIDTH; - } - while (result < MIN_VALUE) { - result += VALUE_WIDTH; + result += log_gaussian_pdf_1d(diff, sigma[i]); } return result; } diff --git a/localization/tree_structured_parzen_estimator/test/test_tpe.cpp b/localization/tree_structured_parzen_estimator/test/test_tpe.cpp index 32eb66e70fb16..f8a697878d6a3 100644 --- a/localization/tree_structured_parzen_estimator/test/test_tpe.cpp +++ b/localization/tree_structured_parzen_estimator/test/test_tpe.cpp @@ -28,19 +28,25 @@ TEST(TreeStructuredParzenEstimatorTest, TPE_is_better_than_random_search_on_sphe return value; }; - constexpr int64_t kOuterTrialsNum = 10; - constexpr int64_t kInnerTrialsNum = 100; + constexpr int64_t kOuterTrialsNum = 20; + constexpr int64_t kInnerTrialsNum = 200; std::cout << std::fixed; std::vector mean_scores; - for (const int64_t n_startup_trials : {kInnerTrialsNum, kInnerTrialsNum / 10}) { + const int64_t n_startup_trials = kInnerTrialsNum / 10; + const std::string method = ((n_startup_trials == kInnerTrialsNum) ? "Random" : "TPE"); + + const std::vector sample_mean(5, 0.0); + const std::vector sample_stddev{1.0, 1.0, 0.1, 0.1, 0.1}; + + for (const int64_t n_startup_trials : {kInnerTrialsNum, kInnerTrialsNum / 2}) { const std::string method = ((n_startup_trials == kInnerTrialsNum) ? "Random" : "TPE"); std::vector scores; for (int64_t i = 0; i < kOuterTrialsNum; i++) { double best_score = std::numeric_limits::lowest(); - const std::vector is_loop_variable(6, false); TreeStructuredParzenEstimator estimator( - TreeStructuredParzenEstimator::Direction::MAXIMIZE, n_startup_trials, is_loop_variable); + TreeStructuredParzenEstimator::Direction::MAXIMIZE, n_startup_trials, sample_mean, + sample_stddev); for (int64_t trial = 0; trial < kInnerTrialsNum; trial++) { const TreeStructuredParzenEstimator::Input input = estimator.get_next_input(); const double score = -sphere_function(input); diff --git a/localization/yabloc/yabloc_common/package.xml b/localization/yabloc/yabloc_common/package.xml index 710ec0aeb75f8..213057f428c38 100644 --- a/localization/yabloc/yabloc_common/package.xml +++ b/localization/yabloc/yabloc_common/package.xml @@ -19,9 +19,9 @@ autoware_auto_mapping_msgs cv_bridge geometry_msgs + glog lanelet2_core lanelet2_extension - libgoogle-glog-dev pcl_conversions rclcpp sensor_msgs diff --git a/localization/yabloc/yabloc_common/src/ground_server/ground_server_node.cpp b/localization/yabloc/yabloc_common/src/ground_server/ground_server_node.cpp index ff50eeee0421d..4e032ff72c998 100644 --- a/localization/yabloc/yabloc_common/src/ground_server/ground_server_node.cpp +++ b/localization/yabloc/yabloc_common/src/ground_server/ground_server_node.cpp @@ -18,8 +18,10 @@ int main(int argc, char ** argv) { - google::InitGoogleLogging(argv[0]); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging(argv[0]); + google::InstallFailureSignalHandler(); + } rclcpp::init(argc, argv); rclcpp::spin(std::make_shared()); diff --git a/localization/yabloc/yabloc_particle_filter/src/camera_corrector/camera_particle_corrector_node.cpp b/localization/yabloc/yabloc_particle_filter/src/camera_corrector/camera_particle_corrector_node.cpp index 4def604030c95..01378f05a0ac8 100644 --- a/localization/yabloc/yabloc_particle_filter/src/camera_corrector/camera_particle_corrector_node.cpp +++ b/localization/yabloc/yabloc_particle_filter/src/camera_corrector/camera_particle_corrector_node.cpp @@ -18,8 +18,10 @@ int main(int argc, char * argv[]) { - google::InitGoogleLogging(argv[0]); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging(argv[0]); + google::InstallFailureSignalHandler(); + } namespace mpf = yabloc::modularized_particle_filter; rclcpp::init(argc, argv); diff --git a/localization/yabloc/yabloc_pose_initializer/src/camera/projector_module.cpp b/localization/yabloc/yabloc_pose_initializer/src/camera/projector_module.cpp index 86a403f68a957..baa199d5548a1 100644 --- a/localization/yabloc/yabloc_pose_initializer/src/camera/projector_module.cpp +++ b/localization/yabloc/yabloc_pose_initializer/src/camera/projector_module.cpp @@ -50,9 +50,9 @@ cv::Mat ProjectorModule::project_image(const cv::Mat & mask_image) cv::findContours(masks[i], contours, cv::RETR_LIST, cv::CHAIN_APPROX_NONE); std::vector > projected_contours; - for (auto contour : contours) { + for (const auto & contour : contours) { std::vector projected; - for (auto c : contour) { + for (const auto & c : contour) { auto opt = project_func_(c); if (!opt.has_value()) continue; diff --git a/perception/ground_segmentation/include/ground_segmentation/ray_ground_filter_nodelet.hpp b/perception/ground_segmentation/include/ground_segmentation/ray_ground_filter_nodelet.hpp index 069c6ea27b1fa..6e2638e8566d8 100644 --- a/perception/ground_segmentation/include/ground_segmentation/ray_ground_filter_nodelet.hpp +++ b/perception/ground_segmentation/include/ground_segmentation/ray_ground_filter_nodelet.hpp @@ -186,15 +186,16 @@ class RayGroundFilterComponent : public pointcloud_preprocessor::Filter * @param out_removed_indices_cloud_ptr Resulting PointCloud with the indices removed */ void ExtractPointsIndices( - const pcl::PointCloud::Ptr in_cloud_ptr, const pcl::PointIndices & in_indices, - pcl::PointCloud::Ptr out_only_indices_cloud_ptr, - pcl::PointCloud::Ptr out_removed_indices_cloud_ptr); + const PointCloud2::ConstSharedPtr in_cloud_ptr, pcl::PointIndices & in_indices, + PointCloud2::SharedPtr out_only_indices_cloud_ptr, + PointCloud2::SharedPtr out_removed_indices_cloud_ptr); boost::optional calcPointVehicleIntersection(const Point & point); void setVehicleFootprint( const double min_x, const double max_x, const double min_y, const double max_y); - + void initializePointCloud2( + const PointCloud2::ConstSharedPtr & in_cloud_ptr, PointCloud2::SharedPtr & out_cloud_msg_ptr); /** \brief Parameter service callback result : needed to be hold */ OnSetParametersCallbackHandle::SharedPtr set_param_res_; diff --git a/perception/ground_segmentation/package.xml b/perception/ground_segmentation/package.xml index 1734487dcc6b3..05d5d18baf29e 100644 --- a/perception/ground_segmentation/package.xml +++ b/perception/ground_segmentation/package.xml @@ -8,6 +8,7 @@ Yukihiro Saito Shunsuke Miura Dai Nguyen + Yoshi Ri Apache License 2.0 diff --git a/perception/ground_segmentation/src/ransac_ground_filter_nodelet.cpp b/perception/ground_segmentation/src/ransac_ground_filter_nodelet.cpp index ed5fb6abe7fe7..587db9c9e0dac 100644 --- a/perception/ground_segmentation/src/ransac_ground_filter_nodelet.cpp +++ b/perception/ground_segmentation/src/ransac_ground_filter_nodelet.cpp @@ -284,19 +284,36 @@ void RANSACGroundFilterComponent::filter( const Eigen::Affine3d plane_affine = getPlaneAffine(*segment_ground_cloud_ptr, plane_normal); pcl::PointCloud::Ptr no_ground_cloud_ptr(new pcl::PointCloud); + int x_offset = input->fields[pcl::getFieldIndex(*input, "x")].offset; + int y_offset = input->fields[pcl::getFieldIndex(*input, "y")].offset; + int z_offset = input->fields[pcl::getFieldIndex(*input, "z")].offset; + int point_step = input->point_step; + + sensor_msgs::msg::PointCloud2::SharedPtr no_ground_cloud_msg_ptr( + new sensor_msgs::msg::PointCloud2); + no_ground_cloud_msg_ptr->header = input->header; + no_ground_cloud_msg_ptr->fields = input->fields; + no_ground_cloud_msg_ptr->point_step = point_step; + size_t output_size = 0; // use not downsampled pointcloud for extract pointcloud that higher than height threshold - for (const auto & p : current_sensor_cloud_ptr->points) { - const Eigen::Vector3d transformed_point = - plane_affine.inverse() * Eigen::Vector3d(p.x, p.y, p.z); + for (size_t global_size = 0; global_size < input->data.size(); global_size += point_step) { + float x = *reinterpret_cast(input->data[global_size + x_offset]); + float y = *reinterpret_cast(input->data[global_size + y_offset]); + float z = *reinterpret_cast(input->data[global_size + z_offset]); + const Eigen::Vector3d transformed_point = plane_affine.inverse() * Eigen::Vector3d(x, y, z); if (std::abs(transformed_point.z()) > height_threshold_) { - no_ground_cloud_ptr->points.push_back(p); + std::memcpy( + &no_ground_cloud_msg_ptr->data[output_size], &input->data[global_size], point_step); + output_size += point_step; } } + no_ground_cloud_msg_ptr->data.resize(output_size); + no_ground_cloud_msg_ptr->height = input->height; + no_ground_cloud_msg_ptr->width = output_size / point_step / input->height; + no_ground_cloud_msg_ptr->row_step = output_size / input->height; + no_ground_cloud_msg_ptr->is_dense = input->is_dense; + no_ground_cloud_msg_ptr->is_bigendian = input->is_bigendian; - sensor_msgs::msg::PointCloud2::SharedPtr no_ground_cloud_msg_ptr( - new sensor_msgs::msg::PointCloud2); - pcl::toROSMsg(*no_ground_cloud_ptr, *no_ground_cloud_msg_ptr); - no_ground_cloud_msg_ptr->header = input->header; sensor_msgs::msg::PointCloud2::SharedPtr no_ground_cloud_transformed_msg_ptr( new sensor_msgs::msg::PointCloud2); if (!transformPointCloud( diff --git a/perception/ground_segmentation/src/ray_ground_filter_nodelet.cpp b/perception/ground_segmentation/src/ray_ground_filter_nodelet.cpp index 7bcae47fd9f1f..c58f1c0e507e5 100644 --- a/perception/ground_segmentation/src/ray_ground_filter_nodelet.cpp +++ b/perception/ground_segmentation/src/ray_ground_filter_nodelet.cpp @@ -257,20 +257,53 @@ void RayGroundFilterComponent::ClassifyPointCloud( // return (true); // } -void RayGroundFilterComponent::ExtractPointsIndices( - const pcl::PointCloud::Ptr in_cloud_ptr, const pcl::PointIndices & in_indices, - pcl::PointCloud::Ptr out_only_indices_cloud_ptr, - pcl::PointCloud::Ptr out_removed_indices_cloud_ptr) +void RayGroundFilterComponent::initializePointCloud2( + const PointCloud2::ConstSharedPtr & in_cloud_ptr, PointCloud2::SharedPtr & out_cloud_msg_ptr) { - pcl::ExtractIndices extract_ground; - extract_ground.setInputCloud(in_cloud_ptr); - extract_ground.setIndices(pcl::make_shared(in_indices)); - - extract_ground.setNegative(false); // true removes the indices, false leaves only the indices - extract_ground.filter(*out_only_indices_cloud_ptr); + out_cloud_msg_ptr->header = in_cloud_ptr->header; + out_cloud_msg_ptr->height = in_cloud_ptr->height; + out_cloud_msg_ptr->fields = in_cloud_ptr->fields; + out_cloud_msg_ptr->is_bigendian = in_cloud_ptr->is_bigendian; + out_cloud_msg_ptr->point_step = in_cloud_ptr->point_step; + out_cloud_msg_ptr->is_dense = in_cloud_ptr->is_dense; + out_cloud_msg_ptr->data.resize(in_cloud_ptr->data.size()); +} - extract_ground.setNegative(true); // true removes the indices, false leaves only the indices - extract_ground.filter(*out_removed_indices_cloud_ptr); +void RayGroundFilterComponent::ExtractPointsIndices( + const PointCloud2::ConstSharedPtr in_cloud_ptr, pcl::PointIndices & in_indices, + PointCloud2::SharedPtr ground_cloud_msg_ptr, PointCloud2::SharedPtr no_ground_cloud_msg_ptr) +{ + initializePointCloud2(in_cloud_ptr, ground_cloud_msg_ptr); + initializePointCloud2(in_cloud_ptr, no_ground_cloud_msg_ptr); + int point_step = in_cloud_ptr->point_step; + size_t ground_count = 0; + size_t no_ground_count = 0; + std::vector is_ground_idx(in_cloud_ptr->width, false); + for (const auto & idx : in_indices.indices) { + if (std::size_t(idx) >= is_ground_idx.size()) { + continue; + } + is_ground_idx[idx] = true; + } + for (size_t i = 0; i < is_ground_idx.size(); ++i) { + if (is_ground_idx[i]) { + std::memcpy( + &ground_cloud_msg_ptr->data[ground_count * point_step], &in_cloud_ptr->data[i * point_step], + point_step); + ground_count++; + } else { + std::memcpy( + &no_ground_cloud_msg_ptr->data[no_ground_count * point_step], + &in_cloud_ptr->data[i * point_step], point_step); + no_ground_count++; + } + } + ground_cloud_msg_ptr->data.resize(ground_count * point_step); + no_ground_cloud_msg_ptr->data.resize(no_ground_count * point_step); + ground_cloud_msg_ptr->width = ground_count; + no_ground_cloud_msg_ptr->width = no_ground_count; + ground_cloud_msg_ptr->row_step = ground_count * point_step; + no_ground_cloud_msg_ptr->row_step = no_ground_count * point_step; } void RayGroundFilterComponent::filter( @@ -299,14 +332,11 @@ void RayGroundFilterComponent::filter( pcl::PointCloud::Ptr no_ground_cloud_ptr(new pcl::PointCloud); pcl::PointCloud::Ptr radials_cloud_ptr(new pcl::PointCloud); - ExtractPointsIndices( - current_sensor_cloud_ptr, ground_indices, ground_cloud_ptr, no_ground_cloud_ptr); - sensor_msgs::msg::PointCloud2::SharedPtr no_ground_cloud_msg_ptr( new sensor_msgs::msg::PointCloud2); - pcl::toROSMsg(*no_ground_cloud_ptr, *no_ground_cloud_msg_ptr); - no_ground_cloud_msg_ptr->header = input->header; + sensor_msgs::msg::PointCloud2::SharedPtr ground_cloud_msg_ptr(new sensor_msgs::msg::PointCloud2); + ExtractPointsIndices(input, ground_indices, ground_cloud_msg_ptr, no_ground_cloud_msg_ptr); output = *no_ground_cloud_msg_ptr; } diff --git a/perception/ground_segmentation/src/scan_ground_filter_nodelet.cpp b/perception/ground_segmentation/src/scan_ground_filter_nodelet.cpp index 34573b564fa36..6399726740041 100644 --- a/perception/ground_segmentation/src/scan_ground_filter_nodelet.cpp +++ b/perception/ground_segmentation/src/scan_ground_filter_nodelet.cpp @@ -388,19 +388,13 @@ void ScanGroundFilterComponent::classifyPointCloudGridScan( } // initialize lists of previous gnd grids - if (prev_list_init == false && initialized_first_gnd_grid == true) { + if (!prev_list_init) { float h = ground_cluster.getAverageHeight(); float r = ground_cluster.getAverageRadius(); initializeFirstGndGrids(h, r, p->grid_id, gnd_grids); prev_list_init = true; } - if (prev_list_init == false && initialized_first_gnd_grid == false) { - // assume first gnd grid is zero - initializeFirstGndGrids(0.0f, p->radius, p->grid_id, gnd_grids); - prev_list_init = true; - } - // move to new grid if (p->grid_id > prev_p->grid_id && ground_cluster.getAverageRadius() > 0.0) { // check if the prev grid have ground point cloud @@ -581,8 +575,6 @@ void ScanGroundFilterComponent::extractObjectPoints( std::memcpy( &out_object_cloud.data[output_data_size], &in_cloud_ptr->data[i * in_cloud_ptr->point_step], in_cloud_ptr->point_step * sizeof(uint8_t)); - *reinterpret_cast(&out_object_cloud.data[output_data_size + intensity_offset_]) = - 1; // set intensity to 1 output_data_size += in_cloud_ptr->point_step; } } @@ -612,7 +604,7 @@ void ScanGroundFilterComponent::faster_filter( output.row_step = no_ground_indices.indices.size() * input->point_step; output.data.resize(output.row_step); output.width = no_ground_indices.indices.size(); - output.fields.assign(input->fields.begin(), input->fields.begin() + 3); + output.fields = input->fields; output.is_dense = true; output.height = input->height; output.is_bigendian = input->is_bigendian; diff --git a/perception/image_projection_based_fusion/config/pointpainting.param.yaml b/perception/image_projection_based_fusion/config/pointpainting.param.yaml old mode 100755 new mode 100644 index 53ac6f4cafc28..30136bc8f47d0 --- a/perception/image_projection_based_fusion/config/pointpainting.param.yaml +++ b/perception/image_projection_based_fusion/config/pointpainting.param.yaml @@ -1,26 +1,10 @@ /**: ros__parameters: - trt_precision: fp16 encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx" encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine" head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx" head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine" - - model_params: - class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] - paint_class_names: ["CAR", "BICYCLE", "PEDESTRIAN"] - point_feature_size: 7 # x, y, z, time-lag and car, pedestrian, bicycle - max_voxel_size: 40000 - point_cloud_range: [-121.6, -76.8, -3.0, 121.6, 76.8, 5.0] - voxel_size: [0.32, 0.32, 8.0] - downsample_factor: 1 - encoder_in_feature_size: 12 - yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] - has_variance: false - has_twist: false - densification_params: - world_frame_id: "map" - num_past_frames: 0 + trt_precision: fp16 post_process_params: # post-process params circle_nms_dist_threshold: 0.3 @@ -28,6 +12,10 @@ iou_nms_search_distance_2d: 10.0 iou_nms_threshold: 0.1 score_threshold: 0.35 + yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] + densification_params: + world_frame_id: "map" + num_past_frames: 1 omp_params: # omp params num_threads: 1 diff --git a/perception/image_projection_based_fusion/config/pointpainting_ml_package.param.yaml b/perception/image_projection_based_fusion/config/pointpainting_ml_package.param.yaml new file mode 100755 index 0000000000000..ca76a8ecf2dac --- /dev/null +++ b/perception/image_projection_based_fusion/config/pointpainting_ml_package.param.yaml @@ -0,0 +1,13 @@ +/**: + ros__parameters: + model_params: + class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] + paint_class_names: ["CAR", "BICYCLE", "PEDESTRIAN"] + point_feature_size: 7 # x, y, z, time-lag and car, pedestrian, bicycle + max_voxel_size: 40000 + point_cloud_range: [-121.6, -76.8, -3.0, 121.6, 76.8, 5.0] + voxel_size: [0.32, 0.32, 8.0] + downsample_factor: 1 + encoder_in_feature_size: 12 + has_twist: false + has_variance: false diff --git a/perception/image_projection_based_fusion/config/roi_pointcloud_fusion.param.yaml b/perception/image_projection_based_fusion/config/roi_pointcloud_fusion.param.yaml index 5b86b8e81d1aa..acf5f75163ffe 100644 --- a/perception/image_projection_based_fusion/config/roi_pointcloud_fusion.param.yaml +++ b/perception/image_projection_based_fusion/config/roi_pointcloud_fusion.param.yaml @@ -2,4 +2,5 @@ ros__parameters: fuse_unknown_only: true min_cluster_size: 2 + max_cluster_size: 20 cluster_2d_tolerance: 0.5 diff --git a/perception/image_projection_based_fusion/docs/pointpainting-fusion.md b/perception/image_projection_based_fusion/docs/pointpainting-fusion.md index d50a3f97390ca..85e740d95ebd0 100644 --- a/perception/image_projection_based_fusion/docs/pointpainting-fusion.md +++ b/perception/image_projection_based_fusion/docs/pointpainting-fusion.md @@ -33,17 +33,22 @@ The lidar points are projected onto the output of an image-only 2d object detect ### Core Parameters -| Name | Type | Default Value | Description | -| ------------------------------- | ------ | ------------- | ----------------------------------------------------------- | -| `score_threshold` | float | `0.4` | detected objects with score less than threshold are ignored | -| `densification_world_frame_id` | string | `map` | the world frame id to fuse multi-frame pointcloud | -| `densification_num_past_frames` | int | `0` | the number of past frames to fuse with the current frame | -| `trt_precision` | string | `fp16` | TensorRT inference precision: `fp32` or `fp16` | -| `encoder_onnx_path` | string | `""` | path to VoxelFeatureEncoder ONNX file | -| `encoder_engine_path` | string | `""` | path to VoxelFeatureEncoder TensorRT Engine file | -| `head_onnx_path` | string | `""` | path to DetectionHead ONNX file | -| `head_engine_path` | string | `""` | path to DetectionHead TensorRT Engine file | -| `build_only` | bool | `false` | shutdown the node after TensorRT engine file is built | +| Name | Type | Default Value | Description | +| ------------------------------------------------ | ------------ | ------------------------- | ----------------------------------------------------------- | +| `encoder_onnx_path` | string | `""` | path to VoxelFeatureEncoder ONNX file | +| `encoder_engine_path` | string | `""` | path to VoxelFeatureEncoder TensorRT Engine file | +| `head_onnx_path` | string | `""` | path to DetectionHead ONNX file | +| `head_engine_path` | string | `""` | path to DetectionHead TensorRT Engine file | +| `build_only` | bool | `false` | shutdown the node after TensorRT engine file is built | +| `trt_precision` | string | `fp16` | TensorRT inference precision: `fp32` or `fp16` | +| `post_process_params.score_threshold` | double | `0.4` | detected objects with score less than threshold are ignored | +| `post_process_params.yaw_norm_thresholds` | list[double] | [0.3, 0.3, 0.3, 0.3, 0.0] | An array of distance threshold values of norm of yaw [rad]. | +| `post_process_params.iou_nms_target_class_names` | list[string] | ["CAR"] | An array of class names to be target in NMS. | +| `post_process_params.iou_nms_search_distance_2d` | double | 10.0 | A maximum distance value to search the nearest objects. | +| `post_process_params.iou_nms_threshold` | double | 0.1 | A threshold value of NMS using IoU score. | +| `post_process_params.has_twist` | boolean | false | Indicates whether the model outputs twist value. | +| `densification_params.world_frame_id` | string | `map` | the world frame id to fuse multi-frame pointcloud | +| `densification_params.num_past_frames` | int | `1` | the number of past frames to fuse with the current frame | ## Assumptions / Known limits diff --git a/perception/image_projection_based_fusion/docs/roi-pointcloud-fusion.md b/perception/image_projection_based_fusion/docs/roi-pointcloud-fusion.md index 5d0b241a578d6..f2ce7662da976 100644 --- a/perception/image_projection_based_fusion/docs/roi-pointcloud-fusion.md +++ b/perception/image_projection_based_fusion/docs/roi-pointcloud-fusion.md @@ -37,6 +37,7 @@ The node `roi_pointcloud_fusion` is to cluster the pointcloud based on Region Of | Name | Type | Description | | ---------------------- | ------ | -------------------------------------------------------------------------------------------- | | `min_cluster_size` | int | the minimum number of points that a cluster needs to contain in order to be considered valid | +| `max_cluster_size` | int | the maximum number of points that a cluster needs to contain in order to be considered valid | | `cluster_2d_tolerance` | double | cluster tolerance measured in radial direction | | `rois_number` | int | the number of input rois | diff --git a/perception/image_projection_based_fusion/include/image_projection_based_fusion/roi_pointcloud_fusion/node.hpp b/perception/image_projection_based_fusion/include/image_projection_based_fusion/roi_pointcloud_fusion/node.hpp index fe685baa0b6e2..4cbc0990352e6 100644 --- a/perception/image_projection_based_fusion/include/image_projection_based_fusion/roi_pointcloud_fusion/node.hpp +++ b/perception/image_projection_based_fusion/include/image_projection_based_fusion/roi_pointcloud_fusion/node.hpp @@ -26,6 +26,7 @@ class RoiPointCloudFusionNode { private: int min_cluster_size_{1}; + int max_cluster_size_{20}; bool fuse_unknown_only_{true}; double cluster_2d_tolerance_; diff --git a/perception/image_projection_based_fusion/include/image_projection_based_fusion/utils/utils.hpp b/perception/image_projection_based_fusion/include/image_projection_based_fusion/utils/utils.hpp index d7fd3c3882046..1851d3faaee6e 100644 --- a/perception/image_projection_based_fusion/include/image_projection_based_fusion/utils/utils.hpp +++ b/perception/image_projection_based_fusion/include/image_projection_based_fusion/utils/utils.hpp @@ -54,6 +54,12 @@ namespace image_projection_based_fusion { using PointCloud = pcl::PointCloud; +using PointCloud2 = sensor_msgs::msg::PointCloud2; +struct PointData +{ + float distance; + size_t orig_index; +}; std::optional getTransformStamped( const tf2_ros::Buffer & tf_buffer, const std::string & target_frame_id, const std::string & source_frame_id, const rclcpp::Time & time); @@ -63,14 +69,15 @@ Eigen::Affine3d transformToEigen(const geometry_msgs::msg::Transform & t); void convertCluster2FeatureObject( const std_msgs::msg::Header & header, const PointCloud & cluster, DetectedObjectWithFeature & feature_obj); -PointCloud closest_cluster( - PointCloud & cluster, const double cluster_2d_tolerance, const int min_cluster_size, - const pcl::PointXYZ & center); +void closest_cluster( + const PointCloud2 & cluster, const double cluster_2d_tolerance, const int min_cluster_size, + const pcl::PointXYZ & center, PointCloud2 & out_cluster); void updateOutputFusedObjects( - std::vector & output_objs, const std::vector & clusters, - const std_msgs::msg::Header & in_cloud_header, const std_msgs::msg::Header & in_roi_header, - const tf2_ros::Buffer & tf_buffer, const int min_cluster_size, const float cluster_2d_tolerance, + std::vector & output_objs, std::vector & clusters, + const std::vector clusters_data_size, const PointCloud2 & in_cloud, + const std_msgs::msg::Header & in_roi_header, const tf2_ros::Buffer & tf_buffer, + const int min_cluster_size, const int max_cluster_size, const float cluster_2d_tolerance, std::vector & output_fused_objects); geometry_msgs::msg::Point getCentroid(const sensor_msgs::msg::PointCloud2 & pointcloud); diff --git a/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml b/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml index 9236d7d789ed1..a22b2c2a13bda 100644 --- a/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml +++ b/perception/image_projection_based_fusion/launch/pointpainting_fusion.launch.xml @@ -21,8 +21,9 @@ - - + + + @@ -48,6 +49,7 @@ + @@ -89,6 +91,7 @@ + diff --git a/perception/image_projection_based_fusion/schema/pointpainting.schema.json b/perception/image_projection_based_fusion/schema/pointpainting.schema.json index bc8f0512263b6..57d8bc500f3c6 100644 --- a/perception/image_projection_based_fusion/schema/pointpainting.schema.json +++ b/perception/image_projection_based_fusion/schema/pointpainting.schema.json @@ -6,71 +6,11 @@ "pointpainting": { "type": "object", "properties": { - "model_params": { - "type": "object", - "description": "Parameters for model configuration.", - "properties": { - "class_names": { - "type": "array", - "description": "An array of class names will be predicted.", - "default": ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"], - "uniqueItems": true - }, - "paint_class_names": { - "type": "array", - "description": "An array of class names will be painted by PointPainting", - "default": ["CAR", "BICYCLE", "PEDESTRIAN"], - "uniqueItems": true - }, - "point_feature_size": { - "type": "integer", - "description": "A number of channels of point feature layer.", - "default": 7 - }, - "max_voxel_size": { - "type": "integer", - "description": "A maximum size of voxel grid.", - "default": 40000 - }, - "point_cloud_range": { - "type": "array", - "description": "An array of distance ranges of each class, this must have same length with `class_names`.", - "default": [-121.6, -76.8, -3.0, 121.6, 76.8, 5.0] - }, - "voxel_size": { - "type": "array", - "description": "An array of voxel grid sizes for PointPainting, this must have same length with `paint_class_names`.", - "default": [0.32, 0.32, 8.0] - }, - "down_sample_factor": { - "type": "integer", - "description": "A scale factor of downsampling points", - "default": 1, - "minimum": 1 - }, - "encoder_in_feature_size": { - "type": "integer", - "description": "A size of encoder input feature channels.", - "default": 12 - }, - "yaw_norm_thresholds": { - "type": "array", - "description": "An array of distance threshold values of norm of yaw [rad].", - "default": [0.3, 0.3, 0.3, 0.3, 0.0], - "minimum": 0.0, - "maximum": 1.0 - }, - "has_variance": { - "type": "boolean", - "description": "Indicates whether the model outputs variance value.", - "default": false - }, - "has_twist": { - "type": "boolean", - "description": "Indicates whether the model outputs twist value.", - "default": false - } - } + "trt_precision": { + "type": "string", + "description": "TensorRT inference precision.", + "default": "fp16", + "enum": ["fp32", "fp16"] }, "densification_params": { "type": "object", @@ -112,7 +52,7 @@ "default": ["CAR"], "uniqueItems": true }, - "iou_search_distance_2d": { + "iou_nms_search_distance_2d": { "type": "number", "description": "A maximum distance value to search the nearest objects.", "default": 10.0, @@ -124,6 +64,23 @@ "default": 0.1, "minimum": 0.0, "maximum": 1.0 + }, + "yaw_norm_thresholds": { + "type": "array", + "description": "An array of distance threshold values of norm of yaw [rad].", + "default": [0.3, 0.3, 0.3, 0.3, 0.0], + "minimum": 0.0, + "maximum": 1.0 + }, + "has_variance": { + "type": "boolean", + "description": "Indicates whether the model outputs variance value.", + "default": false + }, + "has_twist": { + "type": "boolean", + "description": "Indicates whether the model outputs twist value.", + "default": false } } }, @@ -139,7 +96,7 @@ } } }, - "required": ["model_params", "densification_params", "post_process_params", "omp_params"] + "required": [] } }, "properties": { diff --git a/perception/image_projection_based_fusion/schema/pointpainting_ml_package.schema.json b/perception/image_projection_based_fusion/schema/pointpainting_ml_package.schema.json new file mode 100644 index 0000000000000..0f89d050c1828 --- /dev/null +++ b/perception/image_projection_based_fusion/schema/pointpainting_ml_package.schema.json @@ -0,0 +1,74 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Parameters for Point Painting ML model", + "type": "object", + "definitions": { + "pointpainting_ml_package": { + "type": "object", + "properties": { + "model_params": { + "type": "object", + "description": "Parameters for model configuration.", + "properties": { + "class_names": { + "type": "array", + "description": "An array of class names will be predicted.", + "default": ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"], + "uniqueItems": true + }, + "paint_class_names": { + "type": "array", + "description": "An array of class names will be painted by PointPainting", + "default": ["CAR", "BICYCLE", "PEDESTRIAN"], + "uniqueItems": true + }, + "point_feature_size": { + "type": "integer", + "description": "A number of channels of point feature layer.", + "default": 7 + }, + "max_voxel_size": { + "type": "integer", + "description": "A maximum size of voxel grid.", + "default": 40000 + }, + "point_cloud_range": { + "type": "array", + "description": "An array of distance ranges of each class, this must have same length with `class_names`.", + "default": [-121.6, -76.8, -3.0, 121.6, 76.8, 5.0] + }, + "voxel_size": { + "type": "array", + "description": "An array of voxel grid sizes for PointPainting, this must have same length with `paint_class_names`.", + "default": [0.32, 0.32, 8.0] + }, + "down_sample_factor": { + "type": "integer", + "description": "A scale factor of downsampling points", + "default": 1, + "minimum": 1 + }, + "encoder_in_feature_size": { + "type": "integer", + "description": "A size of encoder input feature channels.", + "default": 12 + } + } + } + }, + "required": [] + } + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/definitions/pointpainting_ml_package" + } + }, + "required": ["ros__parameters"] + } + }, + "required": ["/**"] +} diff --git a/perception/image_projection_based_fusion/schema/roi_pointcloud_fusion.schema.json b/perception/image_projection_based_fusion/schema/roi_pointcloud_fusion.schema.json index f39ef257ea789..9dba97a2029ee 100644 --- a/perception/image_projection_based_fusion/schema/roi_pointcloud_fusion.schema.json +++ b/perception/image_projection_based_fusion/schema/roi_pointcloud_fusion.schema.json @@ -16,6 +16,11 @@ "description": "The minimum number of points that a cluster must contain to be considered as valid.", "default": 2 }, + "max_cluster_size": { + "type": "integer", + "description": "The maximum number of points that a cluster must contain to be considered as valid.", + "default": 20 + }, "cluster_2d_tolerance": { "type": "number", "description": "A cluster tolerance measured in radial direction [m]", diff --git a/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp b/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp index c4c5941be5fec..2c33df0b65afc 100644 --- a/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp +++ b/perception/image_projection_based_fusion/src/pointpainting_fusion/node.cpp @@ -102,7 +102,7 @@ PointPaintingFusionNode::PointPaintingFusionNode(const rclcpp::NodeOptions & opt const float circle_nms_dist_threshold = static_cast( this->declare_parameter("post_process_params.circle_nms_dist_threshold")); const auto yaw_norm_thresholds = - this->declare_parameter>("model_params.yaw_norm_thresholds"); + this->declare_parameter>("post_process_params.yaw_norm_thresholds"); // densification param const std::string densification_world_frame_id = this->declare_parameter("densification_params.world_frame_id"); @@ -140,8 +140,8 @@ PointPaintingFusionNode::PointPaintingFusionNode(const rclcpp::NodeOptions & opt isClassTable_.erase(cls); } } - has_variance_ = this->declare_parameter("has_variance"); has_twist_ = this->declare_parameter("model_params.has_twist"); + has_variance_ = this->declare_parameter("model_params.has_variance"); const std::size_t point_feature_size = static_cast( this->declare_parameter("model_params.point_feature_size")); const std::size_t max_voxel_size = diff --git a/perception/image_projection_based_fusion/src/roi_pointcloud_fusion/node.cpp b/perception/image_projection_based_fusion/src/roi_pointcloud_fusion/node.cpp index 421aa3a453451..3f78ee159330f 100644 --- a/perception/image_projection_based_fusion/src/roi_pointcloud_fusion/node.cpp +++ b/perception/image_projection_based_fusion/src/roi_pointcloud_fusion/node.cpp @@ -35,6 +35,7 @@ RoiPointCloudFusionNode::RoiPointCloudFusionNode(const rclcpp::NodeOptions & opt { fuse_unknown_only_ = declare_parameter("fuse_unknown_only"); min_cluster_size_ = declare_parameter("min_cluster_size"); + max_cluster_size_ = declare_parameter("max_cluster_size"); cluster_2d_tolerance_ = declare_parameter("cluster_2d_tolerance"); pub_objects_ptr_ = this->create_publisher("output_clusters", rclcpp::QoS{1}); @@ -114,45 +115,62 @@ void RoiPointCloudFusionNode::fuseOnSingleImage( } transform_stamped = transform_stamped_optional.value(); } + int point_step = input_pointcloud_msg.point_step; + int x_offset = input_pointcloud_msg.fields[pcl::getFieldIndex(input_pointcloud_msg, "x")].offset; + int y_offset = input_pointcloud_msg.fields[pcl::getFieldIndex(input_pointcloud_msg, "y")].offset; + int z_offset = input_pointcloud_msg.fields[pcl::getFieldIndex(input_pointcloud_msg, "z")].offset; sensor_msgs::msg::PointCloud2 transformed_cloud; tf2::doTransform(input_pointcloud_msg, transformed_cloud, transform_stamped); - std::vector clusters; + std::vector clusters; + std::vector clusters_data_size; clusters.resize(output_objs.size()); - - for (sensor_msgs::PointCloud2ConstIterator iter_x(transformed_cloud, "x"), - iter_y(transformed_cloud, "y"), iter_z(transformed_cloud, "z"), - iter_orig_x(input_pointcloud_msg, "x"), iter_orig_y(input_pointcloud_msg, "y"), - iter_orig_z(input_pointcloud_msg, "z"); - iter_x != iter_x.end(); - ++iter_x, ++iter_y, ++iter_z, ++iter_orig_x, ++iter_orig_y, ++iter_orig_z) { - if (*iter_z <= 0.0) { + for (auto & cluster : clusters) { + cluster.point_step = input_pointcloud_msg.point_step; + cluster.height = input_pointcloud_msg.height; + cluster.fields = input_pointcloud_msg.fields; + cluster.data.resize(max_cluster_size_ * input_pointcloud_msg.point_step); + clusters_data_size.push_back(0); + } + for (size_t offset = 0; offset < input_pointcloud_msg.data.size(); offset += point_step) { + const float transformed_x = + *reinterpret_cast(&transformed_cloud.data[offset + x_offset]); + const float transformed_y = + *reinterpret_cast(&transformed_cloud.data[offset + y_offset]); + const float transformed_z = + *reinterpret_cast(&transformed_cloud.data[offset + z_offset]); + if (transformed_z <= 0.0) { continue; } - Eigen::Vector4d projected_point = projection * Eigen::Vector4d(*iter_x, *iter_y, *iter_z, 1.0); + Eigen::Vector4d projected_point = + projection * Eigen::Vector4d(transformed_x, transformed_y, transformed_z, 1.0); Eigen::Vector2d normalized_projected_point = Eigen::Vector2d( projected_point.x() / projected_point.z(), projected_point.y() / projected_point.z()); - for (std::size_t i = 0; i < output_objs.size(); ++i) { auto & feature_obj = output_objs.at(i); const auto & check_roi = feature_obj.feature.roi; auto & cluster = clusters.at(i); + if (clusters_data_size.at(i) >= static_cast(max_cluster_size_ * point_step)) { + continue; + } if ( check_roi.x_offset <= normalized_projected_point.x() && check_roi.y_offset <= normalized_projected_point.y() && check_roi.x_offset + check_roi.width >= normalized_projected_point.x() && check_roi.y_offset + check_roi.height >= normalized_projected_point.y()) { - cluster.push_back(pcl::PointXYZ(*iter_orig_x, *iter_orig_y, *iter_orig_z)); + std::memcpy( + &cluster.data[clusters_data_size.at(i)], &input_pointcloud_msg.data[offset], point_step); + clusters_data_size.at(i) += point_step; } } } // refine and update output_fused_objects_ updateOutputFusedObjects( - output_objs, clusters, input_pointcloud_msg.header, input_roi_msg.header, tf_buffer_, - min_cluster_size_, cluster_2d_tolerance_, output_fused_objects_); + output_objs, clusters, clusters_data_size, input_pointcloud_msg, input_roi_msg.header, + tf_buffer_, min_cluster_size_, max_cluster_size_, cluster_2d_tolerance_, output_fused_objects_); } bool RoiPointCloudFusionNode::out_of_scope(__attribute__((unused)) diff --git a/perception/image_projection_based_fusion/src/utils/utils.cpp b/perception/image_projection_based_fusion/src/utils/utils.cpp index 76cd1e3c61e82..fd25696243951 100644 --- a/perception/image_projection_based_fusion/src/utils/utils.cpp +++ b/perception/image_projection_based_fusion/src/utils/utils.cpp @@ -50,40 +50,67 @@ void convertCluster2FeatureObject( feature_obj.object.existence_probability = 1.0f; } -PointCloud closest_cluster( - PointCloud & cluster, const double cluster_2d_tolerance, const int min_cluster_size, - const pcl::PointXYZ & center) +void closest_cluster( + const PointCloud2 & cluster, const double cluster_2d_tolerance, const int min_cluster_size, + const pcl::PointXYZ & center, PointCloud2 & out_cluster) { // sort point by distance to camera origin - auto func = [center](const pcl::PointXYZ & p1, const pcl::PointXYZ & p2) { - return tier4_autoware_utils::calcDistance2d(center, p1) < - tier4_autoware_utils::calcDistance2d(center, p2); - }; - std::sort(cluster.begin(), cluster.end(), func); - PointCloud out_cluster; - for (auto & point : cluster) { - if (out_cluster.empty()) { - out_cluster.push_back(point); + int x_offset = cluster.fields[pcl::getFieldIndex(cluster, "x")].offset; + int y_offset = cluster.fields[pcl::getFieldIndex(cluster, "y")].offset; + int z_offset = cluster.fields[pcl::getFieldIndex(cluster, "z")].offset; + int point_step = cluster.point_step; + auto func = [](const PointData & p1, const PointData & p2) { return p1.distance < p2.distance; }; + // Create and sort points_data by distance to camera origin + std::vector points_data; + for (size_t i = 0; i < cluster.data.size() / point_step; ++i) { + PointData point_data; + pcl::PointXYZ point; + std::memcpy(&point.x, &cluster.data[i * point_step + x_offset], sizeof(float)); + std::memcpy(&point.y, &cluster.data[i * point_step + y_offset], sizeof(float)); + std::memcpy(&point.z, &cluster.data[i * point_step + z_offset], sizeof(float)); + + point_data.distance = tier4_autoware_utils::calcDistance2d(center, point); + point_data.orig_index = i; + points_data.push_back(point_data); + } + std::sort(points_data.begin(), points_data.end(), func); + // extract closest points as output cluster + out_cluster.data.resize(cluster.data.size()); + out_cluster.point_step = cluster.point_step; + out_cluster.height = cluster.height; + size_t out_cluster_size = 0; + for (size_t i = 0; i < points_data.size(); ++i) { + if (out_cluster_size == 0) { + std::memcpy( + &out_cluster.data[out_cluster_size], + &cluster.data[points_data.at(i).orig_index * point_step], point_step); + out_cluster_size += point_step; continue; } - if (tier4_autoware_utils::calcDistance2d(out_cluster.back(), point) < cluster_2d_tolerance) { - out_cluster.push_back(point); + if (points_data.at(i).distance - points_data.at(i - 1).distance < cluster_2d_tolerance) { + std::memcpy( + &out_cluster.data[out_cluster_size], + &cluster.data[points_data.at(i).orig_index * point_step], point_step); + out_cluster_size += point_step; continue; } - if (out_cluster.size() >= static_cast(min_cluster_size)) { - return out_cluster; + if (i >= static_cast(min_cluster_size)) { + out_cluster.data.resize(out_cluster_size); + return; } - out_cluster.clear(); - out_cluster.push_back(point); + std::memcpy( + &out_cluster.data[0], &cluster.data[points_data.at(i).orig_index * point_step], point_step); + out_cluster_size = point_step; } - return out_cluster; + out_cluster.data.resize(out_cluster_size); } void updateOutputFusedObjects( - std::vector & output_objs, const std::vector & clusters, - const std_msgs::msg::Header & in_cloud_header, const std_msgs::msg::Header & in_roi_header, - const tf2_ros::Buffer & tf_buffer, const int min_cluster_size, const float cluster_2d_tolerance, + std::vector & output_objs, std::vector & clusters, + const std::vector clusters_data_size, const PointCloud2 & in_cloud, + const std_msgs::msg::Header & in_roi_header, const tf2_ros::Buffer & tf_buffer, + const int min_cluster_size, const int max_cluster_size, const float cluster_2d_tolerance, std::vector & output_fused_objects) { if (output_objs.size() != clusters.size()) { @@ -92,6 +119,7 @@ void updateOutputFusedObjects( Eigen::Vector3d orig_camera_frame, orig_point_frame; Eigen::Affine3d camera2lidar_affine; orig_camera_frame << 0.0, 0.0, 0.0; + const std_msgs::msg::Header & in_cloud_header = in_cloud.header; { const auto transform_stamped_optional = getTransformStamped( tf_buffer, in_cloud_header.frame_id, in_roi_header.frame_id, in_roi_header.stamp); @@ -105,25 +133,33 @@ void updateOutputFusedObjects( pcl::PointXYZ(orig_point_frame.x(), orig_point_frame.y(), orig_point_frame.z()); for (std::size_t i = 0; i < output_objs.size(); ++i) { - PointCloud cluster = clusters.at(i); + auto & cluster = clusters.at(i); + cluster.data.resize(clusters_data_size.at(i)); auto & feature_obj = output_objs.at(i); - if (cluster.points.size() < std::size_t(min_cluster_size)) { + if ( + cluster.data.size() < std::size_t(min_cluster_size * cluster.point_step) || + cluster.data.size() >= std::size_t(max_cluster_size * cluster.point_step)) { continue; } // TODO(badai-nguyen): change to interface to select refine criteria like closest, largest // to output refine cluster and centroid - auto refine_cluster = - closest_cluster(cluster, cluster_2d_tolerance, min_cluster_size, camera_orig_point_frame); - if (refine_cluster.points.size() < std::size_t(min_cluster_size)) { + sensor_msgs::msg::PointCloud2 refine_cluster; + closest_cluster( + cluster, cluster_2d_tolerance, min_cluster_size, camera_orig_point_frame, refine_cluster); + if (refine_cluster.data.size() < std::size_t(min_cluster_size * cluster.point_step)) { continue; } - refine_cluster.width = refine_cluster.points.size(); - refine_cluster.height = 1; - refine_cluster.is_dense = false; - // convert cluster to object - convertCluster2FeatureObject(in_cloud_header, refine_cluster, feature_obj); + refine_cluster.width = refine_cluster.data.size() / in_cloud.point_step / in_cloud.height; + refine_cluster.row_step = refine_cluster.data.size() / in_cloud.height; + refine_cluster.is_bigendian = in_cloud.is_bigendian; + refine_cluster.is_dense = in_cloud.is_dense; + refine_cluster.header = in_cloud.header; + refine_cluster.fields = in_cloud.fields; + feature_obj.object.kinematics.pose_with_covariance.pose.position = getCentroid(refine_cluster); + feature_obj.object.existence_probability = 1.0f; + feature_obj.feature.cluster = refine_cluster; output_fused_objects.push_back(feature_obj); } } diff --git a/perception/lidar_centerpoint/README.md b/perception/lidar_centerpoint/README.md index ed71349d5bd7f..09cee5266760c 100644 --- a/perception/lidar_centerpoint/README.md +++ b/perception/lidar_centerpoint/README.md @@ -30,20 +30,22 @@ We trained the models using . ### Core Parameters -| Name | Type | Default Value | Description | -| ------------------------------- | ------------ | ------------- | ------------------------------------------------------------- | -| `score_threshold` | float | `0.4` | detected objects with score less than threshold are ignored | -| `densification_world_frame_id` | string | `map` | the world frame id to fuse multi-frame pointcloud | -| `densification_num_past_frames` | int | `1` | the number of past frames to fuse with the current frame | -| `trt_precision` | string | `fp16` | TensorRT inference precision: `fp32` or `fp16` | -| `encoder_onnx_path` | string | `""` | path to VoxelFeatureEncoder ONNX file | -| `encoder_engine_path` | string | `""` | path to VoxelFeatureEncoder TensorRT Engine file | -| `head_onnx_path` | string | `""` | path to DetectionHead ONNX file | -| `head_engine_path` | string | `""` | path to DetectionHead TensorRT Engine file | -| `nms_iou_target_class_names` | list[string] | - | target classes for IoU-based Non Maximum Suppression | -| `nms_iou_search_distance_2d` | double | - | If two objects are farther than the value, NMS isn't applied. | -| `nms_iou_threshold` | double | - | IoU threshold for the IoU-based Non Maximum Suppression | -| `build_only` | bool | `false` | shutdown the node after TensorRT engine file is built | +| Name | Type | Default Value | Description | +| ------------------------------------------------ | ------------ | ------------------------- | ------------------------------------------------------------- | +| `encoder_onnx_path` | string | `""` | path to VoxelFeatureEncoder ONNX file | +| `encoder_engine_path` | string | `""` | path to VoxelFeatureEncoder TensorRT Engine file | +| `head_onnx_path` | string | `""` | path to DetectionHead ONNX file | +| `head_engine_path` | string | `""` | path to DetectionHead TensorRT Engine file | +| `build_only` | bool | `false` | shutdown the node after TensorRT engine file is built | +| `trt_precision` | string | `fp16` | TensorRT inference precision: `fp32` or `fp16` | +| `post_process_params.score_threshold` | double | `0.4` | detected objects with score less than threshold are ignored | +| `post_process_params.yaw_norm_thresholds` | list[double] | [0.3, 0.3, 0.3, 0.3, 0.0] | An array of distance threshold values of norm of yaw [rad]. | +| `post_process_params.iou_nms_target_class_names` | list[string] | - | target classes for IoU-based Non Maximum Suppression | +| `post_process_params.iou_nms_search_distance_2d` | double | - | If two objects are farther than the value, NMS isn't applied. | +| `post_process_params.iou_nms_threshold` | double | - | IoU threshold for the IoU-based Non Maximum Suppression | +| `post_process_params.has_twist` | boolean | false | Indicates whether the model outputs twist value. | +| `densification_params.world_frame_id` | string | `map` | the world frame id to fuse multi-frame pointcloud | +| `densification_params.num_past_frames` | int | `1` | the number of past frames to fuse with the current frame | ### The `build_only` option diff --git a/perception/lidar_centerpoint/config/centerpoint.param.yaml b/perception/lidar_centerpoint/config/centerpoint.param.yaml index 38c57285e552d..17ed9a447cdb8 100644 --- a/perception/lidar_centerpoint/config/centerpoint.param.yaml +++ b/perception/lidar_centerpoint/config/centerpoint.param.yaml @@ -1,27 +1,19 @@ /**: ros__parameters: - class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] - point_feature_size: 4 - max_voxel_size: 40000 - point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] - voxel_size: [0.32, 0.32, 10.0] - downsample_factor: 1 - encoder_in_feature_size: 9 - # post-process params - circle_nms_dist_threshold: 0.5 - iou_nms_target_class_names: ["CAR"] - iou_nms_search_distance_2d: 10.0 - iou_nms_threshold: 0.1 - yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] - score_threshold: 0.35 - has_variance: false - has_twist: false - trt_precision: fp16 - densification_num_past_frames: 1 - densification_world_frame_id: map - # weight files encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx" encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine" head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx" head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine" + trt_precision: fp16 + post_process_params: + # post-process params + circle_nms_dist_threshold: 0.5 + iou_nms_target_class_names: ["CAR"] + iou_nms_search_distance_2d: 10.0 + iou_nms_threshold: 0.1 + score_threshold: 0.35 + yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] + densification_params: + world_frame_id: map + num_past_frames: 1 diff --git a/perception/lidar_centerpoint/config/centerpoint_ml_package.param.yaml b/perception/lidar_centerpoint/config/centerpoint_ml_package.param.yaml new file mode 100644 index 0000000000000..c8d17890e33be --- /dev/null +++ b/perception/lidar_centerpoint/config/centerpoint_ml_package.param.yaml @@ -0,0 +1,12 @@ +/**: + ros__parameters: + model_params: + class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] + point_feature_size: 4 + max_voxel_size: 40000 + point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] + voxel_size: [0.32, 0.32, 10.0] + downsample_factor: 1 + encoder_in_feature_size: 9 + has_variance: false + has_twist: false diff --git a/perception/lidar_centerpoint/config/centerpoint_sigma.param.yaml b/perception/lidar_centerpoint/config/centerpoint_sigma.param.yaml deleted file mode 100644 index c217f6321381a..0000000000000 --- a/perception/lidar_centerpoint/config/centerpoint_sigma.param.yaml +++ /dev/null @@ -1,27 +0,0 @@ -/**: - ros__parameters: - class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] - point_feature_size: 4 - max_voxel_size: 40000 - point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] - voxel_size: [0.32, 0.32, 10.0] - downsample_factor: 1 - encoder_in_feature_size: 9 - # post-process params - circle_nms_dist_threshold: 0.5 - iou_nms_target_class_names: ["CAR"] - iou_nms_search_distance_2d: 10.0 - iou_nms_threshold: 0.1 - yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] - score_threshold: 0.35 - has_variance: true - has_twist: true - trt_precision: fp16 - densification_num_past_frames: 1 - densification_world_frame_id: map - - # weight files - encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx" - encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine" - head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx" - head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine" diff --git a/perception/lidar_centerpoint/config/centerpoint_sigma_ml_package.param.yaml b/perception/lidar_centerpoint/config/centerpoint_sigma_ml_package.param.yaml new file mode 100644 index 0000000000000..c8d17890e33be --- /dev/null +++ b/perception/lidar_centerpoint/config/centerpoint_sigma_ml_package.param.yaml @@ -0,0 +1,12 @@ +/**: + ros__parameters: + model_params: + class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] + point_feature_size: 4 + max_voxel_size: 40000 + point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] + voxel_size: [0.32, 0.32, 10.0] + downsample_factor: 1 + encoder_in_feature_size: 9 + has_variance: false + has_twist: false diff --git a/perception/lidar_centerpoint/config/centerpoint_tiny.param.yaml b/perception/lidar_centerpoint/config/centerpoint_tiny.param.yaml index 35e11e61e9634..17ed9a447cdb8 100644 --- a/perception/lidar_centerpoint/config/centerpoint_tiny.param.yaml +++ b/perception/lidar_centerpoint/config/centerpoint_tiny.param.yaml @@ -1,27 +1,19 @@ /**: ros__parameters: - class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] - point_feature_size: 4 - max_voxel_size: 40000 - point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] - voxel_size: [0.32, 0.32, 10.0] - downsample_factor: 2 - encoder_in_feature_size: 9 - # post-process params - circle_nms_dist_threshold: 0.5 - iou_nms_target_class_names: ["CAR"] - iou_nms_search_distance_2d: 10.0 - iou_nms_threshold: 0.1 - yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] - score_threshold: 0.35 - has_variance: false - has_twist: false - trt_precision: fp16 - densification_num_past_frames: 1 - densification_world_frame_id: map - # weight files encoder_onnx_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).onnx" encoder_engine_path: "$(var model_path)/pts_voxel_encoder_$(var model_name).engine" head_onnx_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).onnx" head_engine_path: "$(var model_path)/pts_backbone_neck_head_$(var model_name).engine" + trt_precision: fp16 + post_process_params: + # post-process params + circle_nms_dist_threshold: 0.5 + iou_nms_target_class_names: ["CAR"] + iou_nms_search_distance_2d: 10.0 + iou_nms_threshold: 0.1 + score_threshold: 0.35 + yaw_norm_thresholds: [0.3, 0.3, 0.3, 0.3, 0.0] + densification_params: + world_frame_id: map + num_past_frames: 1 diff --git a/perception/lidar_centerpoint/config/centerpoint_tiny_ml_package.param.yaml b/perception/lidar_centerpoint/config/centerpoint_tiny_ml_package.param.yaml new file mode 100644 index 0000000000000..2a3f9c8e75290 --- /dev/null +++ b/perception/lidar_centerpoint/config/centerpoint_tiny_ml_package.param.yaml @@ -0,0 +1,12 @@ +/**: + ros__parameters: + model_params: + class_names: ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"] + point_feature_size: 4 + max_voxel_size: 40000 + point_cloud_range: [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] + voxel_size: [0.32, 0.32, 10.0] + downsample_factor: 2 + encoder_in_feature_size: 9 + has_variance: false + has_twist: false diff --git a/perception/lidar_centerpoint/launch/lidar_centerpoint.launch.xml b/perception/lidar_centerpoint/launch/lidar_centerpoint.launch.xml index 5489af2c8fb60..950dfa7f5b290 100644 --- a/perception/lidar_centerpoint/launch/lidar_centerpoint.launch.xml +++ b/perception/lidar_centerpoint/launch/lidar_centerpoint.launch.xml @@ -6,7 +6,8 @@ - + + @@ -18,6 +19,7 @@ + @@ -30,6 +32,7 @@ + diff --git a/perception/lidar_centerpoint/schema/centerpoint.schemal.json b/perception/lidar_centerpoint/schema/centerpoint.schemal.json new file mode 100644 index 0000000000000..b11c115cc2466 --- /dev/null +++ b/perception/lidar_centerpoint/schema/centerpoint.schemal.json @@ -0,0 +1,98 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Parameters for Lidar Centerpoint Node", + "type": "object", + "definitions": { + "centerpoint": { + "type": "object", + "properties": { + "trt_precision": { + "type": "string", + "description": "TensorRT inference precision.", + "default": "fp16", + "enum": ["fp32", "fp16"] + }, + "post_process_params": { + "type": "object", + "properties": { + "score_threshold": { + "type": "number", + "description": "A threshold value of existence probability score, all of objects with score less than this threshold are ignored.", + "default": 0.35, + "minimum": 0.0, + "maximum": 1.0 + }, + "yaw_norm_thresholds": { + "type": "array", + "description": "An array of distance threshold values of norm of yaw [rad].", + "default": [0.3, 0.3, 0.3, 0.3, 0.0], + "minimum": 0.0, + "maximum": 1.0 + }, + "circle_nms_dist_threshold": { + "type": "number", + "description": "", + "default": 0.5, + "minimum": 0.0, + "maximum": 1.0 + }, + "iou_nms_target_class_names": { + "type": "array", + "description": "An array of class names to be target in NMS.", + "default": ["CAR"], + "uniqueItems": true + }, + "iou_nms_search_distance_2d": { + "type": "number", + "description": "A maximum distance value to search the nearest objects.", + "default": 10.0, + "minimum": 0.0 + }, + "iou_nms_threshold": { + "type": "number", + "description": "A threshold value of NMS using IoU score.", + "default": 0.1, + "minimum": 0.0, + "maximum": 1.0 + }, + "has_twist": { + "type": "boolean", + "description": "Indicates whether the model outputs twist value.", + "default": false + } + } + }, + "densification_params": { + "type": "object", + "description": "Parameters for pointcloud densification.", + "properties": { + "world_frame_id": { + "type": "string", + "description": "A name of frame id where world coordinates system is defined with respect to.", + "default": "map" + }, + "num_past_frames": { + "type": "integer", + "description": "A number of past frames to be considered as same input frame.", + "default": 1, + "minimum": 0 + } + } + } + }, + "required": ["post_process_params", "densification_params"] + } + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/definitions/centerpoint" + } + }, + "required": ["ros__parameters"] + } + }, + "required": ["/**"] +} diff --git a/perception/lidar_centerpoint/schema/centerpoint_ml_package.schema.json b/perception/lidar_centerpoint/schema/centerpoint_ml_package.schema.json new file mode 100644 index 0000000000000..2c5655c6201ed --- /dev/null +++ b/perception/lidar_centerpoint/schema/centerpoint_ml_package.schema.json @@ -0,0 +1,68 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Parameters for Centerpoint ML model", + "type": "object", + "definitions": { + "centerpoint_ml_package": { + "type": "object", + "properties": { + "model_params": { + "type": "object", + "description": "Parameters for model configuration.", + "properties": { + "class_names": { + "type": "array", + "description": "An array of class names will be predicted.", + "default": ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"], + "uniqueItems": true + }, + "point_feature_size": { + "type": "integer", + "description": "A number of channels of point feature layer.", + "default": 4 + }, + "max_voxel_size": { + "type": "integer", + "description": "A maximum size of voxel grid.", + "default": 40000 + }, + "point_cloud_range": { + "type": "array", + "description": "An array of distance ranges of each class, this must have same length with `class_names`.", + "default": [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] + }, + "voxel_size": { + "type": "array", + "description": "An array of voxel grid sizes for PointPainting, this must have same length with `paint_class_names`.", + "default": [0.32, 0.32, 10.0] + }, + "down_sample_factor": { + "type": "integer", + "description": "A scale factor of downsampling points", + "default": 1, + "minimum": 1 + }, + "encoder_in_feature_size": { + "type": "integer", + "description": "A size of encoder input feature channels.", + "default": 9 + } + } + } + }, + "required": ["model_params"] + } + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/definitions/centerpoint_ml_package" + } + }, + "required": ["ros__parameters"] + } + }, + "required": ["/**"] +} diff --git a/perception/lidar_centerpoint/schema/centerpoint_tiny_ml_package.schema.json b/perception/lidar_centerpoint/schema/centerpoint_tiny_ml_package.schema.json new file mode 100644 index 0000000000000..55329e21ea8ab --- /dev/null +++ b/perception/lidar_centerpoint/schema/centerpoint_tiny_ml_package.schema.json @@ -0,0 +1,68 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Parameters for Centerpoint Tiny ML model", + "type": "object", + "definitions": { + "centerpoint_tiny_ml_package": { + "type": "object", + "properties": { + "model_params": { + "type": "object", + "description": "Parameters for model configuration.", + "properties": { + "class_names": { + "type": "array", + "description": "An array of class names will be predicted.", + "default": ["CAR", "TRUCK", "BUS", "BICYCLE", "PEDESTRIAN"], + "uniqueItems": true + }, + "point_feature_size": { + "type": "integer", + "description": "A number of channels of point feature layer.", + "default": 4 + }, + "max_voxel_size": { + "type": "integer", + "description": "A maximum size of voxel grid.", + "default": 40000 + }, + "point_cloud_range": { + "type": "array", + "description": "An array of distance ranges of each class, this must have same length with `class_names`.", + "default": [-76.8, -76.8, -4.0, 76.8, 76.8, 6.0] + }, + "voxel_size": { + "type": "array", + "description": "An array of voxel grid sizes for PointPainting, this must have same length with `paint_class_names`.", + "default": [0.32, 0.32, 10.0] + }, + "down_sample_factor": { + "type": "integer", + "description": "A scale factor of downsampling points", + "default": 2, + "minimum": 1 + }, + "encoder_in_feature_size": { + "type": "integer", + "description": "A size of encoder input feature channels.", + "default": 9 + } + } + } + }, + "required": ["model_params"] + } + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/definitions/centerpoint_tiny_ml_package" + } + }, + "required": ["ros__parameters"] + } + }, + "required": ["/**"] +} diff --git a/perception/lidar_centerpoint/src/node.cpp b/perception/lidar_centerpoint/src/node.cpp index 0606a2ec55c9e..d0abf72d888d3 100644 --- a/perception/lidar_centerpoint/src/node.cpp +++ b/perception/lidar_centerpoint/src/node.cpp @@ -39,34 +39,35 @@ LidarCenterPointNode::LidarCenterPointNode(const rclcpp::NodeOptions & node_opti : Node("lidar_center_point", node_options), tf_buffer_(this->get_clock()) { const float score_threshold = - static_cast(this->declare_parameter("score_threshold", 0.35)); - const float circle_nms_dist_threshold = - static_cast(this->declare_parameter("circle_nms_dist_threshold")); + static_cast(this->declare_parameter("post_process_params.score_threshold")); + const float circle_nms_dist_threshold = static_cast( + this->declare_parameter("post_process_params.circle_nms_dist_threshold")); const auto yaw_norm_thresholds = - this->declare_parameter>("yaw_norm_thresholds"); + this->declare_parameter>("post_process_params.yaw_norm_thresholds"); const std::string densification_world_frame_id = - this->declare_parameter("densification_world_frame_id", "map"); + this->declare_parameter("densification_params.world_frame_id"); const int densification_num_past_frames = - this->declare_parameter("densification_num_past_frames", 1); - const std::string trt_precision = this->declare_parameter("trt_precision", "fp16"); + this->declare_parameter("densification_params.num_past_frames"); + const std::string trt_precision = this->declare_parameter("trt_precision"); const std::string encoder_onnx_path = this->declare_parameter("encoder_onnx_path"); const std::string encoder_engine_path = this->declare_parameter("encoder_engine_path"); const std::string head_onnx_path = this->declare_parameter("head_onnx_path"); const std::string head_engine_path = this->declare_parameter("head_engine_path"); - class_names_ = this->declare_parameter>("class_names"); - has_variance_ = this->declare_parameter("has_variance"); - has_twist_ = this->declare_parameter("has_twist"); - const std::size_t point_feature_size = - static_cast(this->declare_parameter("point_feature_size")); + class_names_ = this->declare_parameter>("model_params.class_names"); + has_twist_ = this->declare_parameter("model_params.has_twist"); + const std::size_t point_feature_size = static_cast( + this->declare_parameter("model_params.point_feature_size")); + has_variance_ = this->declare_parameter("model_params.has_variance"); const std::size_t max_voxel_size = - static_cast(this->declare_parameter("max_voxel_size")); - const auto point_cloud_range = this->declare_parameter>("point_cloud_range"); - const auto voxel_size = this->declare_parameter>("voxel_size"); - const std::size_t downsample_factor = - static_cast(this->declare_parameter("downsample_factor")); - const std::size_t encoder_in_feature_size = - static_cast(this->declare_parameter("encoder_in_feature_size")); + static_cast(this->declare_parameter("model_params.max_voxel_size")); + const auto point_cloud_range = + this->declare_parameter>("model_params.point_cloud_range"); + const auto voxel_size = this->declare_parameter>("model_params.voxel_size"); + const std::size_t downsample_factor = static_cast( + this->declare_parameter("model_params.downsample_factor")); + const std::size_t encoder_in_feature_size = static_cast( + this->declare_parameter("model_params.encoder_in_feature_size")); const auto allow_remapping_by_area_matrix = this->declare_parameter>("allow_remapping_by_area_matrix"); const auto min_area_matrix = this->declare_parameter>("min_area_matrix"); @@ -78,10 +79,11 @@ LidarCenterPointNode::LidarCenterPointNode(const rclcpp::NodeOptions & node_opti { NMSParams p; p.nms_type_ = NMS_TYPE::IoU_BEV; - p.target_class_names_ = - this->declare_parameter>("iou_nms_target_class_names"); - p.search_distance_2d_ = this->declare_parameter("iou_nms_search_distance_2d"); - p.iou_threshold_ = this->declare_parameter("iou_nms_threshold"); + p.target_class_names_ = this->declare_parameter>( + "post_process_params.iou_nms_target_class_names"); + p.search_distance_2d_ = + this->declare_parameter("post_process_params.iou_nms_search_distance_2d"); + p.iou_threshold_ = this->declare_parameter("post_process_params.iou_nms_threshold"); iou_bev_nms_.setParameters(p); } diff --git a/perception/map_based_prediction/config/map_based_prediction.param.yaml b/perception/map_based_prediction/config/map_based_prediction.param.yaml index f8ad371ab92a6..a1b776bdb6393 100644 --- a/perception/map_based_prediction/config/map_based_prediction.param.yaml +++ b/perception/map_based_prediction/config/map_based_prediction.param.yaml @@ -27,6 +27,9 @@ timeout_set_for_no_intention_to_walk: [1.0, 0.0] # [s] values of map # parameter for shoulder lane prediction prediction_time_horizon_rate_for_validate_shoulder_lane_length: 0.8 + use_crosswalk_user_history: + match_lost_and_appeared_users: false + remember_lost_users: false # parameters for lc prediction lane_change_detection: diff --git a/perception/map_based_prediction/include/map_based_prediction/map_based_prediction_node.hpp b/perception/map_based_prediction/include/map_based_prediction/map_based_prediction_node.hpp index 829c4d6e4a114..213f18d63ef3a 100644 --- a/perception/map_based_prediction/include/map_based_prediction/map_based_prediction_node.hpp +++ b/perception/map_based_prediction/include/map_based_prediction/map_based_prediction_node.hpp @@ -48,6 +48,7 @@ #include #include #include +#include #include #include @@ -85,6 +86,12 @@ struct ObjectData Maneuver::UNINITIALIZED}; // output maneuver considering previous one shot maneuvers }; +struct CrosswalkUserData +{ + std_msgs::msg::Header header; + autoware_auto_perception_msgs::msg::TrackedObject tracked_object; +}; + struct LaneletData { lanelet::Lanelet lanelet; @@ -135,8 +142,10 @@ class MapBasedPredictionNode : public rclcpp::Node std::unique_ptr processing_time_publisher_; // Object History - std::unordered_map> objects_history_; + std::unordered_map> road_users_history; std::map, rclcpp::Time> stopped_times_against_green_; + std::unordered_map> crosswalk_users_history_; + std::unordered_map known_matches_; // Lanelet Map Pointers std::shared_ptr lanelet_map_ptr_; @@ -200,6 +209,9 @@ class MapBasedPredictionNode : public rclcpp::Node std::vector distance_set_for_no_intention_to_walk_; std::vector timeout_set_for_no_intention_to_walk_; + bool match_lost_and_appeared_crosswalk_users_; + bool remember_lost_crosswalk_users_; + std::unique_ptr published_time_publisher_; // Member Functions @@ -222,8 +234,7 @@ class MapBasedPredictionNode : public rclcpp::Node PredictedObject getPredictedObjectAsCrosswalkUser(const TrackedObject & object); - void removeOldObjectsHistory( - const double current_time, const TrackedObjects::ConstSharedPtr in_objects); + void removeStaleTrafficLightInfo(const TrackedObjects::ConstSharedPtr in_objects); LaneletsData getCurrentLanelets(const TrackedObject & object); bool checkCloseLaneletCondition( @@ -232,10 +243,14 @@ class MapBasedPredictionNode : public rclcpp::Node const lanelet::Lanelet & current_lanelet, const TrackedObject & object) const; void updateObjectData(TrackedObject & object); - void updateObjectsHistory( + void updateRoadUsersHistory( const std_msgs::msg::Header & header, const TrackedObject & object, const LaneletsData & current_lanelets_data); - + void updateCrosswalkUserHistory( + const std_msgs::msg::Header & header, const TrackedObject & object, + const std::string & object_id); + std::string tryMatchNewObjectToDisappeared( + const std::string & object_id, std::unordered_map & current_users); std::vector getPredictedReferencePath( const TrackedObject & object, const LaneletsData & current_lanelets_data, const double object_detected_time); diff --git a/perception/map_based_prediction/package.xml b/perception/map_based_prediction/package.xml index 8efea9efa1844..ba127ee39d5dd 100644 --- a/perception/map_based_prediction/package.xml +++ b/perception/map_based_prediction/package.xml @@ -5,7 +5,6 @@ 0.1.0 This package implements a map_based_prediction Tomoya Kimura - Shunsuke Miura Yoshi Ri Takayuki Murooka Kyoichi Sugahara @@ -17,9 +16,9 @@ autoware_auto_perception_msgs autoware_perception_msgs + glog interpolation lanelet2_extension - libgoogle-glog-dev motion_utils rclcpp rclcpp_components diff --git a/perception/map_based_prediction/src/map_based_prediction_node.cpp b/perception/map_based_prediction/src/map_based_prediction_node.cpp index 56dc1c2293583..b55ea72402d74 100644 --- a/perception/map_based_prediction/src/map_based_prediction_node.cpp +++ b/perception/map_based_prediction/src/map_based_prediction_node.cpp @@ -585,6 +585,52 @@ bool hasPotentialToReach( return false; } +template +std::unordered_set removeOldObjectsHistory( + const double current_time, const double buffer_time, + std::unordered_map> & target_objects) +{ + std::unordered_set invalid_object_id; + for (auto iter = target_objects.begin(); iter != target_objects.end(); ++iter) { + const std::string object_id = iter->first; + std::deque & object_data = iter->second; + + // If object data is empty, we are going to delete the buffer for the obstacle + if (object_data.empty()) { + invalid_object_id.insert(object_id); + continue; + } + + const double latest_object_time = rclcpp::Time(object_data.back().header.stamp).seconds(); + + // Delete Old Objects + if (current_time - latest_object_time > buffer_time) { + invalid_object_id.insert(object_id); + continue; + } + + // Delete old information + while (!object_data.empty()) { + const double post_object_time = rclcpp::Time(object_data.front().header.stamp).seconds(); + if (current_time - post_object_time <= buffer_time) { + break; + } + object_data.pop_front(); + } + + if (object_data.empty()) { + invalid_object_id.insert(object_id); + continue; + } + } + + for (const auto & key : invalid_object_id) { + target_objects.erase(key); + } + + return invalid_object_id; +} + /** * @brief change label for prediction * @@ -715,8 +761,10 @@ void replaceObjectYawWithLaneletsYaw( MapBasedPredictionNode::MapBasedPredictionNode(const rclcpp::NodeOptions & node_options) : Node("map_based_prediction", node_options), debug_accumulated_time_(0.0) { - google::InitGoogleLogging("map_based_prediction_node"); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging("map_based_prediction_node"); + google::InstallFailureSignalHandler(); + } enable_delay_compensation_ = declare_parameter("enable_delay_compensation"); prediction_time_horizon_ = declare_parameter("prediction_time_horizon"); lateral_control_time_horizon_ = @@ -774,7 +822,10 @@ MapBasedPredictionNode::MapBasedPredictionNode(const rclcpp::NodeOptions & node_ * parameter control the estimated path length = vx * th * (rate) */ prediction_time_horizon_rate_for_validate_lane_length_ = declare_parameter("prediction_time_horizon_rate_for_validate_shoulder_lane_length"); - + match_lost_and_appeared_crosswalk_users_ = + declare_parameter("use_crosswalk_user_history.match_lost_and_appeared_users"); + remember_lost_crosswalk_users_ = + declare_parameter("use_crosswalk_user_history.remember_lost_users"); use_vehicle_acceleration_ = declare_parameter("use_vehicle_acceleration"); speed_limit_multiplier_ = declare_parameter("speed_limit_multiplier"); acceleration_exponential_half_life_ = @@ -916,7 +967,19 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt // Remove old objects information in object history const double objects_detected_time = rclcpp::Time(in_objects->header.stamp).seconds(); - removeOldObjectsHistory(objects_detected_time, in_objects); + removeOldObjectsHistory(objects_detected_time, object_buffer_time_length_, road_users_history); + removeStaleTrafficLightInfo(in_objects); + + auto invalidated_crosswalk_users = removeOldObjectsHistory( + objects_detected_time, object_buffer_time_length_, crosswalk_users_history_); + // delete matches that point to invalid object + for (auto it = known_matches_.begin(); it != known_matches_.end();) { + if (invalidated_crosswalk_users.count(it->second)) { + it = known_matches_.erase(it); + } else { + ++it; + } + } // result output PredictedObjects output; @@ -926,6 +989,20 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt // result debug visualization_msgs::msg::MarkerArray debug_markers; + // get current crosswalk users for later prediction + std::unordered_map current_crosswalk_users; + for (const auto & object : in_objects->objects) { + const auto label_for_prediction = + changeLabelForPrediction(object.classification.front().label, object, lanelet_map_ptr_); + if ( + label_for_prediction == ObjectClassification::PEDESTRIAN || + label_for_prediction == ObjectClassification::BICYCLE) { + const std::string object_id = tier4_autoware_utils::toHexString(object.object_id); + current_crosswalk_users.emplace(object_id, object); + } + } + std::unordered_set predicted_crosswalk_users_ids; + for (const auto & object : in_objects->objects) { std::string object_id = tier4_autoware_utils::toHexString(object.object_id); TrackedObject transformed_object = object; @@ -946,6 +1023,12 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt switch (label) { case ObjectClassification::PEDESTRIAN: case ObjectClassification::BICYCLE: { + std::string object_id = tier4_autoware_utils::toHexString(object.object_id); + if (match_lost_and_appeared_crosswalk_users_) { + object_id = tryMatchNewObjectToDisappeared(object_id, current_crosswalk_users); + } + predicted_crosswalk_users_ids.insert(object_id); + updateCrosswalkUserHistory(output.header, transformed_object, object_id); const auto predicted_object_crosswalk = getPredictedObjectAsCrosswalkUser(transformed_object); output.objects.push_back(predicted_object_crosswalk); @@ -963,7 +1046,7 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt const auto current_lanelets = getCurrentLanelets(transformed_object); // Update Objects History - updateObjectsHistory(output.header, transformed_object, current_lanelets); + updateRoadUsersHistory(output.header, transformed_object, current_lanelets); // For off lane obstacles if (current_lanelets.empty()) { @@ -1111,6 +1194,19 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt } } + // process lost crosswalk users to tackle unstable detection + if (remember_lost_crosswalk_users_) { + for (const auto & [id, crosswalk_user] : crosswalk_users_history_) { + // get a predicted path for crosswalk users in history who didn't get path yet using latest + // message + if (predicted_crosswalk_users_ids.count(id) == 0) { + const auto predicted_object = + getPredictedObjectAsCrosswalkUser(crosswalk_user.back().tracked_object); + output.objects.push_back(predicted_object); + } + } + } + // Publish Results pub_objects_->publish(output); published_time_publisher_->publish_if_subscribed(pub_objects_, output.header.stamp); @@ -1123,6 +1219,79 @@ void MapBasedPredictionNode::objectsCallback(const TrackedObjects::ConstSharedPt "debug/processing_time_ms", processing_time_ms); } +void MapBasedPredictionNode::updateCrosswalkUserHistory( + const std_msgs::msg::Header & header, const TrackedObject & object, const std::string & object_id) +{ + CrosswalkUserData crosswalk_user_data; + crosswalk_user_data.header = header; + crosswalk_user_data.tracked_object = object; + + if (crosswalk_users_history_.count(object_id) == 0) { + crosswalk_users_history_.emplace(object_id, std::deque{crosswalk_user_data}); + return; + } + + crosswalk_users_history_.at(object_id).push_back(crosswalk_user_data); +} + +std::string MapBasedPredictionNode::tryMatchNewObjectToDisappeared( + const std::string & object_id, std::unordered_map & current_users) +{ + const auto known_match_opt = [&]() -> std::optional { + if (!known_matches_.count(object_id)) { + return std::nullopt; + } + + std::string match_id = known_matches_[object_id]; + // object in the history is already matched to something (possibly itself) + if (crosswalk_users_history_.count(match_id)) { + // avoid matching two appeared users to one user in history + current_users[match_id] = crosswalk_users_history_[match_id].back().tracked_object; + return match_id; + } else { + RCLCPP_WARN_STREAM( + get_logger(), "Crosswalk user was " + << object_id << "was matched to " << match_id + << " but history for the crosswalk user was deleted. Rematching"); + } + return std::nullopt; + }(); + // early return if the match is already known + if (known_match_opt.has_value()) { + return known_match_opt.value(); + } + + std::string match_id = object_id; + double best_score = std::numeric_limits::max(); + const auto object_pos = current_users[object_id].kinematics.pose_with_covariance.pose.position; + for (const auto & [user_id, user_history] : crosswalk_users_history_) { + // user present in current_users and will be matched to itself + if (current_users.count(user_id)) { + continue; + } + // TODO(dkoldaev): implement more sophisticated scoring, for now simply dst to last position in + // history + const auto match_candidate_pos = + user_history.back().tracked_object.kinematics.pose_with_covariance.pose.position; + const double score = + std::hypot(match_candidate_pos.x - object_pos.x, match_candidate_pos.y - object_pos.y); + if (score < best_score) { + best_score = score; + match_id = user_id; + } + } + + if (object_id != match_id) { + RCLCPP_INFO_STREAM( + get_logger(), "[Map Based Prediction]: Matched " << object_id << " to " << match_id); + // avoid matching two appeared users to one user in history + current_users[match_id] = crosswalk_users_history_[match_id].back().tracked_object; + } + + known_matches_[object_id] = match_id; + return match_id; +} + bool MapBasedPredictionNode::doesPathCrossAnyFence(const PredictedPath & predicted_path) { const lanelet::ConstLineStrings3d & all_fences = @@ -1139,7 +1308,7 @@ bool MapBasedPredictionNode::doesPathCrossFence( const PredictedPath & predicted_path, const lanelet::ConstLineString3d & fence_line) { // check whether the predicted path cross with fence - for (size_t i = 0; i < predicted_path.path.size(); ++i) { + for (size_t i = 0; i < predicted_path.path.size() - 1; ++i) { for (size_t j = 0; j < fence_line.size() - 1; ++j) { if (isIntersecting( predicted_path.path[i].position, predicted_path.path[i + 1].position, fence_line[j], @@ -1343,49 +1512,9 @@ void MapBasedPredictionNode::updateObjectData(TrackedObject & object) return; } -void MapBasedPredictionNode::removeOldObjectsHistory( - const double current_time, const TrackedObjects::ConstSharedPtr in_objects) +void MapBasedPredictionNode::removeStaleTrafficLightInfo( + const TrackedObjects::ConstSharedPtr in_objects) { - std::vector invalid_object_id; - for (auto iter = objects_history_.begin(); iter != objects_history_.end(); ++iter) { - const std::string object_id = iter->first; - std::deque & object_data = iter->second; - - // If object data is empty, we are going to delete the buffer for the obstacle - if (object_data.empty()) { - invalid_object_id.push_back(object_id); - continue; - } - - const double latest_object_time = rclcpp::Time(object_data.back().header.stamp).seconds(); - - // Delete Old Objects - if (current_time - latest_object_time > object_buffer_time_length_) { - invalid_object_id.push_back(object_id); - continue; - } - - // Delete old information - while (!object_data.empty()) { - const double post_object_time = rclcpp::Time(object_data.front().header.stamp).seconds(); - if (current_time - post_object_time > object_buffer_time_length_) { - // Delete Old Position - object_data.pop_front(); - } else { - break; - } - } - - if (object_data.empty()) { - invalid_object_id.push_back(object_id); - continue; - } - } - - for (const auto & key : invalid_object_id) { - objects_history_.erase(key); - } - for (auto it = stopped_times_against_green_.begin(); it != stopped_times_against_green_.end();) { const bool isDisappeared = std::none_of( in_objects->objects.begin(), in_objects->objects.end(), @@ -1500,9 +1629,9 @@ bool MapBasedPredictionNode::checkCloseLaneletCondition( // If the object is in the objects history, we check if the target lanelet is // inside the current lanelets id or following lanelets const std::string object_id = tier4_autoware_utils::toHexString(object.object_id); - if (objects_history_.count(object_id) != 0) { + if (road_users_history.count(object_id) != 0) { const std::vector & possible_lanelet = - objects_history_.at(object_id).back().future_possible_lanelets; + road_users_history.at(object_id).back().future_possible_lanelets; bool not_in_possible_lanelet = std::find(possible_lanelet.begin(), possible_lanelet.end(), lanelet.second) == @@ -1569,7 +1698,7 @@ float MapBasedPredictionNode::calculateLocalLikelihood( return static_cast(1.0 / dist); } -void MapBasedPredictionNode::updateObjectsHistory( +void MapBasedPredictionNode::updateRoadUsersHistory( const std_msgs::msg::Header & header, const TrackedObject & object, const LaneletsData & current_lanelets_data) { @@ -1593,13 +1722,13 @@ void MapBasedPredictionNode::updateObjectsHistory( single_object_data.lateral_kinematics_set[current_lane] = lateral_kinematics; } - if (objects_history_.count(object_id) == 0) { + if (road_users_history.count(object_id) == 0) { // New Object(Create a new object in object histories) std::deque object_data = {single_object_data}; - objects_history_.emplace(object_id, object_data); + road_users_history.emplace(object_id, object_data); } else { // Object that is already in the object buffer - std::deque & object_data = objects_history_.at(object_id); + std::deque & object_data = road_users_history.at(object_id); // get previous object data and update const auto prev_object_data = object_data.back(); updateLateralKinematicsVector( @@ -1787,10 +1916,10 @@ Maneuver MapBasedPredictionNode::predictObjectManeuver( }(); const std::string object_id = tier4_autoware_utils::toHexString(object.object_id); - if (objects_history_.count(object_id) == 0) { + if (road_users_history.count(object_id) == 0) { return current_maneuver; } - auto & object_info = objects_history_.at(object_id); + auto & object_info = road_users_history.at(object_id); // update maneuver in object history if (!object_info.empty()) { @@ -1826,11 +1955,11 @@ Maneuver MapBasedPredictionNode::predictObjectManeuverByTimeToLaneChange( { // Step1. Check if we have the object in the buffer const std::string object_id = tier4_autoware_utils::toHexString(object.object_id); - if (objects_history_.count(object_id) == 0) { + if (road_users_history.count(object_id) == 0) { return Maneuver::LANE_FOLLOW; } - const std::deque & object_info = objects_history_.at(object_id); + const std::deque & object_info = road_users_history.at(object_id); // Step2. Check if object history length longer than history_time_length const int latest_id = static_cast(object_info.size()) - 1; @@ -1897,11 +2026,11 @@ Maneuver MapBasedPredictionNode::predictObjectManeuverByLatDiffDistance( { // Step1. Check if we have the object in the buffer const std::string object_id = tier4_autoware_utils::toHexString(object.object_id); - if (objects_history_.count(object_id) == 0) { + if (road_users_history.count(object_id) == 0) { return Maneuver::LANE_FOLLOW; } - const std::deque & object_info = objects_history_.at(object_id); + const std::deque & object_info = road_users_history.at(object_id); const double current_time = (this->get_clock()->now()).seconds(); // Step2. Get the previous id @@ -2058,12 +2187,12 @@ void MapBasedPredictionNode::updateFuturePossibleLanelets( const TrackedObject & object, const lanelet::routing::LaneletPaths & paths) { std::string object_id = tier4_autoware_utils::toHexString(object.object_id); - if (objects_history_.count(object_id) == 0) { + if (road_users_history.count(object_id) == 0) { return; } std::vector & possible_lanelets = - objects_history_.at(object_id).back().future_possible_lanelets; + road_users_history.at(object_id).back().future_possible_lanelets; for (const auto & path : paths) { for (const auto & lanelet : path) { bool not_in_buffer = std::find(possible_lanelets.begin(), possible_lanelets.end(), lanelet) == diff --git a/perception/map_based_prediction/src/path_generator.cpp b/perception/map_based_prediction/src/path_generator.cpp index 413a0e233186b..83fbc16feb7fa 100644 --- a/perception/map_based_prediction/src/path_generator.cpp +++ b/perception/map_based_prediction/src/path_generator.cpp @@ -50,14 +50,18 @@ PredictedPath PathGenerator::generatePathToTargetPoint( const auto velocity = std::max(std::hypot(obj_vel.x, obj_vel.y), min_crosswalk_user_velocity_); const auto arrival_time = pedestrian_to_entry_point.norm() / velocity; + const auto pedestrian_to_entry_point_normalized = pedestrian_to_entry_point.normalized(); + const auto pedestrian_to_entry_point_orientation = tier4_autoware_utils::createQuaternionFromYaw( + std::atan2(pedestrian_to_entry_point_normalized.y(), pedestrian_to_entry_point_normalized.x())); + for (double dt = 0.0; dt < arrival_time + ep; dt += sampling_time_interval_) { geometry_msgs::msg::Pose world_frame_pose; world_frame_pose.position.x = - obj_pos.x + velocity * pedestrian_to_entry_point.normalized().x() * dt; + obj_pos.x + velocity * pedestrian_to_entry_point_normalized.x() * dt; world_frame_pose.position.y = - obj_pos.y + velocity * pedestrian_to_entry_point.normalized().y() * dt; + obj_pos.y + velocity * pedestrian_to_entry_point_normalized.y() * dt; world_frame_pose.position.z = obj_pos.z; - world_frame_pose.orientation = object.kinematics.pose_with_covariance.pose.orientation; + world_frame_pose.orientation = pedestrian_to_entry_point_orientation; predicted_path.path.push_back(world_frame_pose); if (predicted_path.path.size() >= predicted_path.path.max_size()) { break; @@ -88,25 +92,32 @@ PredictedPath PathGenerator::generatePathForCrosswalkUser( const auto velocity = std::max(std::hypot(obj_vel.x, obj_vel.y), min_crosswalk_user_velocity_); const auto arrival_time = pedestrian_to_entry_point.norm() / velocity; + const auto pedestrian_to_entry_point_normalized = pedestrian_to_entry_point.normalized(); + const auto pedestrian_to_entry_point_orientation = tier4_autoware_utils::createQuaternionFromYaw( + std::atan2(pedestrian_to_entry_point_normalized.y(), pedestrian_to_entry_point_normalized.x())); + const auto entry_to_exit_point_normalized = entry_to_exit_point.normalized(); + const auto entry_to_exit_point_orientation = tier4_autoware_utils::createQuaternionFromYaw( + std::atan2(entry_to_exit_point_normalized.y(), entry_to_exit_point_normalized.x())); + for (double dt = 0.0; dt < time_horizon_ + ep; dt += sampling_time_interval_) { geometry_msgs::msg::Pose world_frame_pose; if (dt < arrival_time) { world_frame_pose.position.x = - obj_pos.x + velocity * pedestrian_to_entry_point.normalized().x() * dt; + obj_pos.x + velocity * pedestrian_to_entry_point_normalized.x() * dt; world_frame_pose.position.y = - obj_pos.y + velocity * pedestrian_to_entry_point.normalized().y() * dt; + obj_pos.y + velocity * pedestrian_to_entry_point_normalized.y() * dt; world_frame_pose.position.z = obj_pos.z; - world_frame_pose.orientation = object.kinematics.pose_with_covariance.pose.orientation; + world_frame_pose.orientation = pedestrian_to_entry_point_orientation; predicted_path.path.push_back(world_frame_pose); } else { world_frame_pose.position.x = reachable_crosswalk.front_center_point.x() + - velocity * entry_to_exit_point.normalized().x() * (dt - arrival_time); + velocity * entry_to_exit_point_normalized.x() * (dt - arrival_time); world_frame_pose.position.y = reachable_crosswalk.front_center_point.y() + - velocity * entry_to_exit_point.normalized().y() * (dt - arrival_time); + velocity * entry_to_exit_point_normalized.y() * (dt - arrival_time); world_frame_pose.position.z = obj_pos.z; - world_frame_pose.orientation = object.kinematics.pose_with_covariance.pose.orientation; + world_frame_pose.orientation = entry_to_exit_point_orientation; predicted_path.path.push_back(world_frame_pose); } if (predicted_path.path.size() >= predicted_path.path.max_size()) { @@ -114,17 +125,6 @@ PredictedPath PathGenerator::generatePathForCrosswalkUser( } } - // calculate orientation of each point - if (predicted_path.path.size() >= 2) { - for (size_t i = 0; i < predicted_path.path.size() - 1; i++) { - const auto yaw = tier4_autoware_utils::calcAzimuthAngle( - predicted_path.path.at(i).position, predicted_path.path.at(i + 1).position); - predicted_path.path.at(i).orientation = tier4_autoware_utils::createQuaternionFromYaw(yaw); - } - predicted_path.path.back().orientation = - predicted_path.path.at(predicted_path.path.size() - 2).orientation; - } - predicted_path.confidence = 1.0; predicted_path.time_step = rclcpp::Duration::from_seconds(sampling_time_interval_); diff --git a/perception/multi_object_tracker/CMakeLists.txt b/perception/multi_object_tracker/CMakeLists.txt index 41d150ef0ba1b..46af1f9b9a1de 100644 --- a/perception/multi_object_tracker/CMakeLists.txt +++ b/perception/multi_object_tracker/CMakeLists.txt @@ -48,16 +48,13 @@ ament_auto_add_library(multi_object_tracker_node SHARED target_link_libraries(multi_object_tracker_node Eigen3::Eigen + glog::glog ) ament_auto_add_executable(${PROJECT_NAME} src/multi_object_tracker_node.cpp ) -target_link_libraries(${PROJECT_NAME} - multi_object_tracker_node glog -) - ament_auto_package(INSTALL_TO_SHARE launch config diff --git a/perception/multi_object_tracker/package.xml b/perception/multi_object_tracker/package.xml index 4033f85eafb8a..1e4a90d8cc08c 100644 --- a/perception/multi_object_tracker/package.xml +++ b/perception/multi_object_tracker/package.xml @@ -16,8 +16,8 @@ autoware_auto_perception_msgs diagnostic_updater eigen + glog kalman_filter - libgoogle-glog-dev mussp object_recognition_utils rclcpp diff --git a/perception/multi_object_tracker/src/multi_object_tracker_node.cpp b/perception/multi_object_tracker/src/multi_object_tracker_node.cpp index f20aedf16efef..c6eed297c02c4 100644 --- a/perception/multi_object_tracker/src/multi_object_tracker_node.cpp +++ b/perception/multi_object_tracker/src/multi_object_tracker_node.cpp @@ -20,8 +20,10 @@ int main(int argc, char ** argv) { - google::InitGoogleLogging(argv[0]); // NOLINT - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging(argv[0]); // NOLINT + google::InstallFailureSignalHandler(); + } rclcpp::init(argc, argv); rclcpp::NodeOptions options; diff --git a/perception/object_range_splitter/package.xml b/perception/object_range_splitter/package.xml index d2bb2b401fb2b..1705162ff7faf 100644 --- a/perception/object_range_splitter/package.xml +++ b/perception/object_range_splitter/package.xml @@ -5,6 +5,7 @@ 0.1.0 The object_range_splitter package Yukihiro Saito + Yoshi Ri Apache License 2.0 ament_cmake_auto diff --git a/perception/occupancy_grid_map_outlier_filter/include/occupancy_grid_map_outlier_filter/occupancy_grid_map_outlier_filter_nodelet.hpp b/perception/occupancy_grid_map_outlier_filter/include/occupancy_grid_map_outlier_filter/occupancy_grid_map_outlier_filter_nodelet.hpp index 1d7d01bfbab55..0faa40255a1ca 100644 --- a/perception/occupancy_grid_map_outlier_filter/include/occupancy_grid_map_outlier_filter/occupancy_grid_map_outlier_filter_nodelet.hpp +++ b/perception/occupancy_grid_map_outlier_filter/include/occupancy_grid_map_outlier_filter/occupancy_grid_map_outlier_filter_nodelet.hpp @@ -46,18 +46,16 @@ using geometry_msgs::msg::Pose; using nav_msgs::msg::OccupancyGrid; using sensor_msgs::msg::PointCloud2; using std_msgs::msg::Header; -using PclPointCloud = pcl::PointCloud; class RadiusSearch2dFilter { public: explicit RadiusSearch2dFilter(rclcpp::Node & node); void filter( - const PclPointCloud & input, const Pose & pose, PclPointCloud & output, - PclPointCloud & outlier); + const PointCloud2 & input, const Pose & pose, PointCloud2 & output, PointCloud2 & outlier); void filter( - const PclPointCloud & high_conf_input, const PclPointCloud & low_conf_input, const Pose & pose, - PclPointCloud & output, PclPointCloud & outlier); + const PointCloud2 & high_conf_input, const PointCloud2 & low_conf_input, const Pose & pose, + PointCloud2 & output, PointCloud2 & outlier); private: float search_radius_; @@ -79,22 +77,25 @@ class OccupancyGridMapOutlierFilterComponent : public rclcpp::Node const PointCloud2::ConstSharedPtr & input_pointcloud); void filterByOccupancyGridMap( const OccupancyGrid & occupancy_grid_map, const PointCloud2 & pointcloud, - PclPointCloud & high_confidence, PclPointCloud & low_confidence, PclPointCloud & out_ogm); + PointCloud2 & high_confidence, PointCloud2 & low_confidence, PointCloud2 & out_ogm); void splitPointCloudFrontBack( const PointCloud2::ConstSharedPtr & input_pc, PointCloud2 & front_pc, PointCloud2 & behind_pc); + void initializerPointCloud2(const PointCloud2 & input, PointCloud2 & output); + void finalizePointCloud2(const PointCloud2 & input, PointCloud2 & output); + void concatPointCloud2(PointCloud2 & output, const PointCloud2 & input); private: class Debugger { public: explicit Debugger(OccupancyGridMapOutlierFilterComponent & node); - void publishOutlier(const PclPointCloud & input, const Header & header); - void publishHighConfidence(const PclPointCloud & input, const Header & header); - void publishLowConfidence(const PclPointCloud & input, const Header & header); + void publishOutlier(const PointCloud2 & input, const Header & header); + void publishHighConfidence(const PointCloud2 & input, const Header & header); + void publishLowConfidence(const PointCloud2 & input, const Header & header); private: void transformToBaseLink( - const PclPointCloud & input, const Header & header, PointCloud2 & output); + const PointCloud2 & input, const Header & header, PointCloud2 & output); rclcpp::Publisher::SharedPtr outlier_pointcloud_pub_; rclcpp::Publisher::SharedPtr low_confidence_pointcloud_pub_; rclcpp::Publisher::SharedPtr high_confidence_pointcloud_pub_; diff --git a/perception/occupancy_grid_map_outlier_filter/src/occupancy_grid_map_outlier_filter_nodelet.cpp b/perception/occupancy_grid_map_outlier_filter/src/occupancy_grid_map_outlier_filter_nodelet.cpp index 65eb336269fe4..bbd138030d76f 100644 --- a/perception/occupancy_grid_map_outlier_filter/src/occupancy_grid_map_outlier_filter_nodelet.cpp +++ b/perception/occupancy_grid_map_outlier_filter/src/occupancy_grid_map_outlier_filter_nodelet.cpp @@ -116,19 +116,23 @@ RadiusSearch2dFilter::RadiusSearch2dFilter(rclcpp::Node & node) } void RadiusSearch2dFilter::filter( - const PclPointCloud & input, const Pose & pose, PclPointCloud & output, PclPointCloud & outlier) + const PointCloud2 & input, const Pose & pose, PointCloud2 & output, PointCloud2 & outlier) { - const auto & xyz_cloud = input; pcl::PointCloud::Ptr xy_cloud(new pcl::PointCloud); - xy_cloud->points.resize(xyz_cloud.points.size()); - for (size_t i = 0; i < xyz_cloud.points.size(); ++i) { - xy_cloud->points[i].x = xyz_cloud.points[i].x; - xy_cloud->points[i].y = xyz_cloud.points[i].y; + int point_step = input.point_step; + int x_offset = input.fields[pcl::getFieldIndex(input, "x")].offset; + int y_offset = input.fields[pcl::getFieldIndex(input, "y")].offset; + xy_cloud->points.resize(input.data.size() / point_step); + for (size_t i = 0; i < input.data.size() / point_step; ++i) { + std::memcpy(&xy_cloud->points[i].x, &input.data[i * point_step + x_offset], sizeof(float)); + std::memcpy(&xy_cloud->points[i].y, &input.data[i * point_step + y_offset], sizeof(float)); } std::vector k_indices(xy_cloud->points.size()); std::vector k_distances(xy_cloud->points.size()); kd_tree_->setInputCloud(xy_cloud); + size_t output_size = 0; + size_t outlier_size = 0; for (size_t i = 0; i < xy_cloud->points.size(); ++i) { const float distance = std::hypot(xy_cloud->points[i].x - pose.position.x, xy_cloud->points[i].y - pose.position.y); @@ -139,42 +143,57 @@ void RadiusSearch2dFilter::filter( kd_tree_->radiusSearch(i, search_radius_, k_indices, k_distances, min_points_threshold); if (min_points_threshold <= points_num) { - output.points.push_back(xyz_cloud.points.at(i)); + std::memcpy(&output.data[output_size], &input.data[i * point_step], point_step); + output_size += point_step; } else { - outlier.points.push_back(xyz_cloud.points.at(i)); + std::memcpy(&outlier.data[outlier_size], &input.data[i * point_step], point_step); + outlier_size += point_step; } } + output.data.resize(output_size); + outlier.data.resize(outlier_size); } void RadiusSearch2dFilter::filter( - const PclPointCloud & high_conf_input, const PclPointCloud & low_conf_input, const Pose & pose, - PclPointCloud & output, PclPointCloud & outlier) + const PointCloud2 & high_conf_xyz_cloud, const PointCloud2 & low_conf_xyz_cloud, + const Pose & pose, PointCloud2 & output, PointCloud2 & outlier) { - const auto & high_conf_xyz_cloud = high_conf_input; - const auto & low_conf_xyz_cloud = low_conf_input; // check the limit points number - if (low_conf_xyz_cloud.points.size() > max_filter_points_nb_) { + if (low_conf_xyz_cloud.width > max_filter_points_nb_) { RCLCPP_WARN( rclcpp::get_logger("OccupancyGridMapOutlierFilterComponent"), "Skip outlier filter since too much low_confidence pointcloud!"); return; } - + int x_offset = low_conf_xyz_cloud.fields[pcl::getFieldIndex(low_conf_xyz_cloud, "x")].offset; + int y_offset = low_conf_xyz_cloud.fields[pcl::getFieldIndex(low_conf_xyz_cloud, "y")].offset; + int point_step = low_conf_xyz_cloud.point_step; pcl::PointCloud::Ptr xy_cloud(new pcl::PointCloud); - xy_cloud->points.resize(low_conf_xyz_cloud.points.size() + high_conf_xyz_cloud.points.size()); - for (size_t i = 0; i < low_conf_xyz_cloud.points.size(); ++i) { - xy_cloud->points[i].x = low_conf_xyz_cloud.points[i].x; - xy_cloud->points[i].y = low_conf_xyz_cloud.points[i].y; + xy_cloud->points.resize(low_conf_xyz_cloud.width + high_conf_xyz_cloud.width); + for (size_t i = 0; i < low_conf_xyz_cloud.width; ++i) { + std::memcpy( + &xy_cloud->points[i].x, &low_conf_xyz_cloud.data[i * point_step + x_offset], sizeof(float)); + std::memcpy( + &xy_cloud->points[i].y, &low_conf_xyz_cloud.data[i * point_step + y_offset], sizeof(float)); } - for (size_t i = low_conf_xyz_cloud.points.size(); i < xy_cloud->points.size(); ++i) { - xy_cloud->points[i].x = high_conf_xyz_cloud.points[i - low_conf_xyz_cloud.points.size()].x; - xy_cloud->points[i].y = high_conf_xyz_cloud.points[i - low_conf_xyz_cloud.points.size()].y; + + for (size_t i = low_conf_xyz_cloud.width; i < xy_cloud->points.size(); ++i) { + size_t high_conf_xyz_cloud_index = i - low_conf_xyz_cloud.width; + std::memcpy( + &xy_cloud->points[i].x, + &high_conf_xyz_cloud.data[high_conf_xyz_cloud_index * point_step + x_offset], sizeof(float)); + std::memcpy( + &xy_cloud->points[i].y, + &high_conf_xyz_cloud.data[high_conf_xyz_cloud_index * point_step + y_offset], sizeof(float)); } std::vector k_indices(xy_cloud->points.size()); std::vector k_distances(xy_cloud->points.size()); kd_tree_->setInputCloud(xy_cloud); - for (size_t i = 0; i < low_conf_xyz_cloud.points.size(); ++i) { + + size_t output_size = 0; + size_t outlier_size = 0; + for (size_t i = 0; i < low_conf_xyz_cloud.data.size() / low_conf_xyz_cloud.point_step; ++i) { const float distance = std::hypot(xy_cloud->points[i].x - pose.position.x, xy_cloud->points[i].y - pose.position.y); const int min_points_threshold = std::min( @@ -184,11 +203,20 @@ void RadiusSearch2dFilter::filter( kd_tree_->radiusSearch(i, search_radius_, k_indices, k_distances, min_points_threshold); if (min_points_threshold <= points_num) { - output.points.push_back(low_conf_xyz_cloud.points.at(i)); + std::memcpy( + &output.data[output_size], &low_conf_xyz_cloud.data[i * low_conf_xyz_cloud.point_step], + low_conf_xyz_cloud.point_step); + output_size += low_conf_xyz_cloud.point_step; } else { - outlier.points.push_back(low_conf_xyz_cloud.points.at(i)); + std::memcpy( + &outlier.data[outlier_size], &low_conf_xyz_cloud.data[i * low_conf_xyz_cloud.point_step], + low_conf_xyz_cloud.point_step); + outlier_size += low_conf_xyz_cloud.point_step; } } + + output.data.resize(output_size); + outlier.data.resize(outlier_size); } OccupancyGridMapOutlierFilterComponent::OccupancyGridMapOutlierFilterComponent( @@ -234,61 +262,52 @@ OccupancyGridMapOutlierFilterComponent::OccupancyGridMapOutlierFilterComponent( if (enable_debugger) { debugger_ptr_ = std::make_shared(*this); } - published_time_publisher_ = std::make_unique(this); } void OccupancyGridMapOutlierFilterComponent::splitPointCloudFrontBack( const PointCloud2::ConstSharedPtr & input_pc, PointCloud2 & front_pc, PointCloud2 & behind_pc) { + int x_offset = input_pc->fields[pcl::getFieldIndex(*input_pc, "x")].offset; + int point_step = input_pc->point_step; size_t front_count = 0; size_t behind_count = 0; - for (sensor_msgs::PointCloud2ConstIterator x(*input_pc, "x"); x != x.end(); ++x) { - if (*x < 0.0) { + for (size_t global_offset = 0; global_offset < input_pc->data.size(); + global_offset += point_step) { + float x; + std::memcpy(&x, &input_pc->data[global_offset + x_offset], sizeof(float)); + if (x < 0.0) { + std::memcpy( + &behind_pc.data[behind_count * point_step], &input_pc->data[global_offset], + input_pc->point_step); behind_count++; } else { + std::memcpy( + &front_pc.data[front_count * point_step], &input_pc->data[global_offset], + input_pc->point_step); front_count++; } } - - sensor_msgs::PointCloud2Modifier front_pc_modifier(front_pc); - sensor_msgs::PointCloud2Modifier behind_pc_modifier(behind_pc); - front_pc_modifier.setPointCloud2FieldsByString(1, "xyz"); - behind_pc_modifier.setPointCloud2FieldsByString(1, "xyz"); - front_pc_modifier.resize(front_count); - behind_pc_modifier.resize(behind_count); - - sensor_msgs::PointCloud2Iterator fr_iter(front_pc, "x"); - sensor_msgs::PointCloud2Iterator be_iter(behind_pc, "x"); - - for (sensor_msgs::PointCloud2ConstIterator in_iter(*input_pc, "x"); - in_iter != in_iter.end(); ++in_iter) { - if (*in_iter < 0.0) { - *be_iter = in_iter[0]; - be_iter[1] = in_iter[1]; - be_iter[2] = in_iter[2]; - ++be_iter; - } else { - *fr_iter = in_iter[0]; - fr_iter[1] = in_iter[1]; - fr_iter[2] = in_iter[2]; - ++fr_iter; - } - } - - front_pc.header = input_pc->header; - behind_pc.header = input_pc->header; + front_pc.data.resize(front_count * point_step); + behind_pc.data.resize(behind_count * point_step); } void OccupancyGridMapOutlierFilterComponent::onOccupancyGridMapAndPointCloud2( const OccupancyGrid::ConstSharedPtr & input_ogm, const PointCloud2::ConstSharedPtr & input_pc) { stop_watch_ptr_->toc("processing_time", true); // Transform to occupancy grid map frame - PointCloud2 ogm_frame_pc{}; - PointCloud2 input_front_pc{}; + PointCloud2 input_behind_pc{}; - PointCloud2 ogm_frame_input_behind_pc{}; + PointCloud2 input_front_pc{}; + initializerPointCloud2(*input_pc, input_front_pc); + initializerPointCloud2(*input_pc, input_behind_pc); + // Split pointcloud into front and behind of the vehicle to reduce the calculation cost splitPointCloudFrontBack(input_pc, input_front_pc, input_behind_pc); + finalizePointCloud2(*input_pc, input_front_pc); + finalizePointCloud2(*input_pc, input_behind_pc); + + PointCloud2 ogm_frame_pc{}; + PointCloud2 ogm_frame_input_behind_pc{}; if ( !transformPointcloud(input_front_pc, *tf2_, input_ogm->header.frame_id, ogm_frame_pc) || !transformPointcloud( @@ -296,16 +315,22 @@ void OccupancyGridMapOutlierFilterComponent::onOccupancyGridMapAndPointCloud2( return; } // Occupancy grid map based filter - PclPointCloud high_confidence_pc{}; - PclPointCloud low_confidence_pc{}; - PclPointCloud out_ogm_pc{}; - PclPointCloud ogm_frame_behind_pc; - pcl::fromROSMsg(ogm_frame_input_behind_pc, ogm_frame_behind_pc); + PointCloud2 high_confidence_pc{}; + PointCloud2 low_confidence_pc{}; + PointCloud2 out_ogm_pc{}; + initializerPointCloud2(ogm_frame_pc, high_confidence_pc); + initializerPointCloud2(ogm_frame_pc, low_confidence_pc); + initializerPointCloud2(ogm_frame_pc, out_ogm_pc); + // split front pointcloud into high and low confidence and out of map pointcloud filterByOccupancyGridMap( *input_ogm, ogm_frame_pc, high_confidence_pc, low_confidence_pc, out_ogm_pc); // Apply Radius search 2d filter for low confidence pointcloud - PclPointCloud filtered_low_confidence_pc{}; - PclPointCloud outlier_pc{}; + PointCloud2 filtered_low_confidence_pc{}; + PointCloud2 outlier_pc{}; + initializerPointCloud2(low_confidence_pc, outlier_pc); + initializerPointCloud2(low_confidence_pc, filtered_low_confidence_pc); + initializerPointCloud2(low_confidence_pc, outlier_pc); + if (radius_search_2d_filter_ptr_) { auto pc_frame_pose_stamped = getPoseStamped( *tf2_, input_ogm->header.frame_id, input_pc->header.frame_id, input_ogm->header.stamp); @@ -313,26 +338,29 @@ void OccupancyGridMapOutlierFilterComponent::onOccupancyGridMapAndPointCloud2( high_confidence_pc, low_confidence_pc, pc_frame_pose_stamped.pose, filtered_low_confidence_pc, outlier_pc); } else { - outlier_pc = low_confidence_pc; + std::memcpy(&outlier_pc.data[0], &low_confidence_pc.data[0], low_confidence_pc.data.size()); + outlier_pc.data.resize(low_confidence_pc.data.size()); } // Concatenate high confidence pointcloud from occupancy grid map and non-outlier pointcloud - PclPointCloud concat_pc = - high_confidence_pc + filtered_low_confidence_pc + out_ogm_pc + ogm_frame_behind_pc; - // Convert to ros msg + PointCloud2 ogm_frame_filtered_pc{}; + concatPointCloud2(ogm_frame_filtered_pc, high_confidence_pc); + concatPointCloud2(ogm_frame_filtered_pc, filtered_low_confidence_pc); + concatPointCloud2(ogm_frame_filtered_pc, out_ogm_pc); + concatPointCloud2(ogm_frame_filtered_pc, ogm_frame_input_behind_pc); + finalizePointCloud2(ogm_frame_pc, ogm_frame_filtered_pc); { - PointCloud2 ogm_frame_filtered_pc{}; auto base_link_frame_filtered_pc_ptr = std::make_unique(); - pcl::toROSMsg(concat_pc, ogm_frame_filtered_pc); ogm_frame_filtered_pc.header = ogm_frame_pc.header; if (!transformPointcloud( ogm_frame_filtered_pc, *tf2_, base_link_frame_, *base_link_frame_filtered_pc_ptr)) { return; } pointcloud_pub_->publish(std::move(base_link_frame_filtered_pc_ptr)); - published_time_publisher_->publish_if_subscribed( - pointcloud_pub_, ogm_frame_filtered_pc.header.stamp); } if (debugger_ptr_) { + finalizePointCloud2(ogm_frame_pc, high_confidence_pc); + finalizePointCloud2(ogm_frame_pc, filtered_low_confidence_pc); + finalizePointCloud2(ogm_frame_pc, outlier_pc); debugger_ptr_->publishHighConfidence(high_confidence_pc, ogm_frame_pc.header); debugger_ptr_->publishLowConfidence(filtered_low_confidence_pc, ogm_frame_pc.header); debugger_ptr_->publishOutlier(outlier_pc, ogm_frame_pc.header); @@ -349,24 +377,75 @@ void OccupancyGridMapOutlierFilterComponent::onOccupancyGridMapAndPointCloud2( } } +void OccupancyGridMapOutlierFilterComponent::initializerPointCloud2( + const PointCloud2 & input, PointCloud2 & output) +{ + output.point_step = input.point_step; + output.data.resize(input.data.size()); +} + +void OccupancyGridMapOutlierFilterComponent::finalizePointCloud2( + const PointCloud2 & input, PointCloud2 & output) +{ + output.header = input.header; + output.point_step = input.point_step; + output.fields = input.fields; + output.height = input.height; + output.is_bigendian = input.is_bigendian; + output.is_dense = input.is_dense; + output.width = output.data.size() / output.point_step / output.height; + output.row_step = output.data.size() / output.height; +} + +void OccupancyGridMapOutlierFilterComponent::concatPointCloud2( + PointCloud2 & output, const PointCloud2 & input) +{ + size_t output_size = output.data.size(); + output.data.resize(output.data.size() + input.data.size()); + std::memcpy(&output.data[output_size], &input.data[0], input.data.size()); +} void OccupancyGridMapOutlierFilterComponent::filterByOccupancyGridMap( const OccupancyGrid & occupancy_grid_map, const PointCloud2 & pointcloud, - PclPointCloud & high_confidence, PclPointCloud & low_confidence, PclPointCloud & out_ogm) + PointCloud2 & high_confidence, PointCloud2 & low_confidence, PointCloud2 & out_ogm) { - for (sensor_msgs::PointCloud2ConstIterator x(pointcloud, "x"), y(pointcloud, "y"), - z(pointcloud, "z"); - x != x.end(); ++x, ++y, ++z) { - const auto cost = getCost(occupancy_grid_map, *x, *y); + int x_offset = pointcloud.fields[pcl::getFieldIndex(pointcloud, "x")].offset; + int y_offset = pointcloud.fields[pcl::getFieldIndex(pointcloud, "y")].offset; + size_t high_confidence_size = 0; + size_t low_confidence_size = 0; + size_t out_ogm_size = 0; + + for (size_t global_offset = 0; global_offset < pointcloud.data.size(); + global_offset += pointcloud.point_step) { + float x; + float y; + std::memcpy(&x, &pointcloud.data[global_offset + x_offset], sizeof(float)); + std::memcpy(&y, &pointcloud.data[global_offset + y_offset], sizeof(float)); + + const auto cost = getCost(occupancy_grid_map, x, y); if (cost) { if (cost_threshold_ < *cost) { - high_confidence.push_back(pcl::PointXYZ(*x, *y, *z)); + std::memcpy( + &high_confidence.data[high_confidence_size], &pointcloud.data[global_offset], + pointcloud.point_step); + high_confidence_size += pointcloud.point_step; } else { - low_confidence.push_back(pcl::PointXYZ(*x, *y, *z)); + std::memcpy( + &low_confidence.data[low_confidence_size], &pointcloud.data[global_offset], + pointcloud.point_step); + low_confidence_size += pointcloud.point_step; } } else { - out_ogm.push_back(pcl::PointXYZ(*x, *y, *z)); + std::memcpy( + &out_ogm.data[out_ogm_size], &pointcloud.data[global_offset], pointcloud.point_step); + out_ogm_size += pointcloud.point_step; } } + high_confidence.data.resize(high_confidence_size); + low_confidence.data.resize(low_confidence_size); + out_ogm.data.resize(out_ogm_size); + finalizePointCloud2(pointcloud, high_confidence); + finalizePointCloud2(pointcloud, low_confidence); + finalizePointCloud2(pointcloud, out_ogm); } OccupancyGridMapOutlierFilterComponent::Debugger::Debugger( @@ -382,14 +461,14 @@ OccupancyGridMapOutlierFilterComponent::Debugger::Debugger( } void OccupancyGridMapOutlierFilterComponent::Debugger::publishOutlier( - const PclPointCloud & input, const Header & header) + const PointCloud2 & input, const Header & header) { auto output_ptr = std::make_unique(); transformToBaseLink(input, header, *output_ptr); outlier_pointcloud_pub_->publish(std::move(output_ptr)); } void OccupancyGridMapOutlierFilterComponent::Debugger::publishHighConfidence( - const PclPointCloud & input, const Header & header) + const PointCloud2 & input, const Header & header) { auto output_ptr = std::make_unique(); transformToBaseLink(input, header, *output_ptr); @@ -397,7 +476,7 @@ void OccupancyGridMapOutlierFilterComponent::Debugger::publishHighConfidence( } void OccupancyGridMapOutlierFilterComponent::Debugger::publishLowConfidence( - const PclPointCloud & input, const Header & header) + const PointCloud2 & input, const Header & header) { auto output_ptr = std::make_unique(); transformToBaseLink(input, header, *output_ptr); @@ -405,11 +484,8 @@ void OccupancyGridMapOutlierFilterComponent::Debugger::publishLowConfidence( } void OccupancyGridMapOutlierFilterComponent::Debugger::transformToBaseLink( - const PclPointCloud & pcl_input, const Header & header, PointCloud2 & output) + const PointCloud2 & ros_input, [[maybe_unused]] const Header & header, PointCloud2 & output) { - PointCloud2 ros_input{}; - pcl::toROSMsg(pcl_input, ros_input); - ros_input.header = header; transformPointcloud(ros_input, *(node_.tf2_), node_.base_link_frame_, output); } diff --git a/perception/probabilistic_occupancy_grid_map/README.md b/perception/probabilistic_occupancy_grid_map/README.md index 084c55d80d629..97d66bf9f648c 100644 --- a/perception/probabilistic_occupancy_grid_map/README.md +++ b/perception/probabilistic_occupancy_grid_map/README.md @@ -72,6 +72,26 @@ Additional argument is shown below: | `input_obstacle_pointcloud` | `false` | only for laserscan based method. If true, the node subscribe obstacle pointcloud | | `input_obstacle_and_raw_pointcloud` | `true` | only for laserscan based method. If true, the node subscribe both obstacle and raw pointcloud | +### Downsample input pointcloud(Optional) + +If you set `downsample_input_pointcloud` to `true`, the input pointcloud will be downsampled and following topics are also used. This feature is currently only for the pointcloud based occupancy grid map. + +- pointcloud_based_occupancy_grid_map method + +```yaml +# downsampled raw and obstacle pointcloud +/perception/occupancy_grid_map/obstacle/downsample/pointcloud +/perception/occupancy_grid_map/raw/downsample/pointcloud +``` + +- multi_lidar_pointcloud_based_point_cloud + +```yaml +# downsampled raw and obstacle pointcloud +/perception/occupancy_grid_map/obstacle/downsample/pointcloud +/perception/occupancy_grid_map//raw/downsample/pointcloud +``` + ### Test This package provides unit tests using `gtest`. diff --git a/perception/probabilistic_occupancy_grid_map/config/multi_lidar_pointcloud_based_occupancy_grid_map.param.yaml b/perception/probabilistic_occupancy_grid_map/config/multi_lidar_pointcloud_based_occupancy_grid_map.param.yaml index f9a1c4f930001..878bea4cd8ced 100644 --- a/perception/probabilistic_occupancy_grid_map/config/multi_lidar_pointcloud_based_occupancy_grid_map.param.yaml +++ b/perception/probabilistic_occupancy_grid_map/config/multi_lidar_pointcloud_based_occupancy_grid_map.param.yaml @@ -12,6 +12,10 @@ map_length_x: 150.0 # [m] map_length_y: 150.0 # [m] + # downsample input pointcloud + downsample_input_pointcloud: true + downsample_voxel_size: 0.25 # [m] + # each grid map parameters ogm_creation_config: height_filter: @@ -20,7 +24,7 @@ max_height: 2.0 enable_single_frame_mode: true # use sensor pointcloud to filter obstacle pointcloud - filter_obstacle_pointcloud_by_raw_pointcloud: true + filter_obstacle_pointcloud_by_raw_pointcloud: false grid_map_type: "OccupancyGridMapFixedBlindSpot" OccupancyGridMapFixedBlindSpot: diff --git a/perception/probabilistic_occupancy_grid_map/config/pointcloud_based_occupancy_grid_map.param.yaml b/perception/probabilistic_occupancy_grid_map/config/pointcloud_based_occupancy_grid_map.param.yaml index 8077bdec5008e..922d4be6d519f 100644 --- a/perception/probabilistic_occupancy_grid_map/config/pointcloud_based_occupancy_grid_map.param.yaml +++ b/perception/probabilistic_occupancy_grid_map/config/pointcloud_based_occupancy_grid_map.param.yaml @@ -8,6 +8,10 @@ min_height: -1.0 max_height: 2.0 + # downsample input pointcloud + downsample_input_pointcloud: true + downsample_voxel_size: 0.25 # [m] + enable_single_frame_mode: false # use sensor pointcloud to filter obstacle pointcloud filter_obstacle_pointcloud_by_raw_pointcloud: false diff --git a/perception/probabilistic_occupancy_grid_map/launch/multi_lidar_pointcloud_based_occupancy_grid_map.launch.py b/perception/probabilistic_occupancy_grid_map/launch/multi_lidar_pointcloud_based_occupancy_grid_map.launch.py index dccddfbe54196..b112dd0a84b83 100644 --- a/perception/probabilistic_occupancy_grid_map/launch/multi_lidar_pointcloud_based_occupancy_grid_map.launch.py +++ b/perception/probabilistic_occupancy_grid_map/launch/multi_lidar_pointcloud_based_occupancy_grid_map.launch.py @@ -92,6 +92,57 @@ def get_ogm_creation_config(total_config: dict, list_iter: int) -> dict: return ogm_creation_config +# generate downsample node +def get_downsample_filter_node(setting: dict) -> ComposableNode: + plugin_str = setting["plugin"] + voxel_size = setting["voxel_size"] + node_name = setting["node_name"] + return ComposableNode( + package="pointcloud_preprocessor", + plugin=plugin_str, + name=node_name, + remappings=[ + ("input", setting["input_topic"]), + ("output", setting["output_topic"]), + ], + parameters=[ + { + "voxel_size_x": voxel_size, + "voxel_size_y": voxel_size, + "voxel_size_z": voxel_size, + } + ], + extra_arguments=[{"use_intra_process_comms": LaunchConfiguration("use_intra_process")}], + ) + + +def get_downsample_preprocess_nodes(voxel_size: float, raw_pointcloud_topics: list) -> list: + nodes = [] + for i in range(len(raw_pointcloud_topics)): + raw_pointcloud_topic: str = raw_pointcloud_topics[i] + frame_name: str = raw_pointcloud_topic.split("/")[ + -2 + ] # `/sensing/lidar/top/pointcloud` -> `top + processed_pointcloud_topic: str = frame_name + "/raw/downsample/pointcloud" + raw_settings = { + "plugin": "pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent", + "node_name": "raw_pc_downsample_filter_" + frame_name, + "input_topic": raw_pointcloud_topic, + "output_topic": processed_pointcloud_topic, + "voxel_size": voxel_size, + } + nodes.append(get_downsample_filter_node(raw_settings)) + obstacle_settings = { + "plugin": "pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent", + "node_name": "obstacle_pc_downsample_filter", + "input_topic": LaunchConfiguration("input/obstacle_pointcloud"), + "output_topic": "/perception/occupancy_grid_map/obstacle/downsample/pointcloud", + "voxel_size": voxel_size, + } + nodes.append(get_downsample_filter_node(obstacle_settings)) + return nodes + + def launch_setup(context, *args, **kwargs): """Launch fusion based occupancy grid map creation nodes. @@ -118,20 +169,39 @@ def launch_setup(context, *args, **kwargs): LaunchConfiguration("pointcloud_container_name").perform(context), ) + # Down sample settings + downsample_input_pointcloud: bool = total_config["downsample_input_pointcloud"] + downsample_voxel_size: float = total_config["downsample_voxel_size"] + + # get obstacle pointcloud + obstacle_pointcloud_topic: str = ( + "/perception/occupancy_grid_map/obstacle/downsample/pointcloud" + if downsample_input_pointcloud + else LaunchConfiguration("input/obstacle_pointcloud").perform(context) + ) + for i in range(number_of_nodes): # load parameter file ogm_creation_config = get_ogm_creation_config(total_config, i) ogm_creation_config["updater_type"] = LaunchConfiguration("updater_type").perform(context) ogm_creation_config.update(updater_config) + raw_pointcloud_topic: str = fusion_config["raw_pointcloud_topics"][i] + frame_name: str = raw_pointcloud_topic.split("/")[ + -2 + ] # assume `/sensing/lidar/top/pointcloud` -> `top + if downsample_input_pointcloud: + raw_pointcloud_topic = "raw/downsample/pointcloud" + # generate composable node node = ComposableNode( package="probabilistic_occupancy_grid_map", plugin="occupancy_grid_map::PointcloudBasedOccupancyGridMapNode", - name="occupancy_grid_map_node_in_" + str(i), + name="occupancy_grid_map_node", + namespace=frame_name, remappings=[ - ("~/input/obstacle_pointcloud", LaunchConfiguration("input/obstacle_pointcloud")), - ("~/input/raw_pointcloud", fusion_config["raw_pointcloud_topics"][i]), + ("~/input/obstacle_pointcloud", obstacle_pointcloud_topic), + ("~/input/raw_pointcloud", raw_pointcloud_topic), ("~/output/occupancy_grid_map", fusion_config["fusion_input_ogm_topics"][i]), ], parameters=[ogm_creation_config], @@ -139,6 +209,12 @@ def launch_setup(context, *args, **kwargs): ) gridmap_generation_composable_nodes.append(node) + if downsample_input_pointcloud: + downsample_nodes = get_downsample_preprocess_nodes( + downsample_voxel_size, fusion_config["raw_pointcloud_topics"] + ) + gridmap_generation_composable_nodes.extend(downsample_nodes) + # 2. launch occupancy grid map fusion node gridmap_fusion_node = [ ComposableNode( diff --git a/perception/probabilistic_occupancy_grid_map/launch/pointcloud_based_occupancy_grid_map.launch.py b/perception/probabilistic_occupancy_grid_map/launch/pointcloud_based_occupancy_grid_map.launch.py index 29435c4ea8e24..c58e747f84af2 100644 --- a/perception/probabilistic_occupancy_grid_map/launch/pointcloud_based_occupancy_grid_map.launch.py +++ b/perception/probabilistic_occupancy_grid_map/launch/pointcloud_based_occupancy_grid_map.launch.py @@ -26,6 +26,47 @@ import yaml +def get_downsample_filter_node(setting: dict) -> ComposableNode: + plugin_str = setting["plugin"] + voxel_size = setting["voxel_size"] + node_name = setting["node_name"] + return ComposableNode( + package="pointcloud_preprocessor", + plugin=plugin_str, + name=node_name, + remappings=[ + ("input", setting["input_topic"]), + ("output", setting["output_topic"]), + ], + parameters=[ + { + "voxel_size_x": voxel_size, + "voxel_size_y": voxel_size, + "voxel_size_z": voxel_size, + } + ], + extra_arguments=[{"use_intra_process_comms": LaunchConfiguration("use_intra_process")}], + ) + + +def get_downsample_preprocess_nodes(voxel_size: float) -> list: + raw_settings = { + "plugin": "pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent", + "node_name": "raw_pc_downsample_filter", + "input_topic": LaunchConfiguration("input/raw_pointcloud"), + "output_topic": "raw/downsample/pointcloud", + "voxel_size": voxel_size, + } + obstacle_settings = { + "plugin": "pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent", + "node_name": "obstacle_pc_downsample_filter", + "input_topic": LaunchConfiguration("input/obstacle_pointcloud"), + "output_topic": "obstacle/downsample/pointcloud", + "voxel_size": voxel_size, + } + return [get_downsample_filter_node(raw_settings), get_downsample_filter_node(obstacle_settings)] + + def launch_setup(context, *args, **kwargs): # load parameter files param_file = LaunchConfiguration("param_file").perform(context) @@ -38,7 +79,21 @@ def launch_setup(context, *args, **kwargs): with open(updater_param_file, "r") as f: occupancy_grid_map_updater_params = yaml.safe_load(f)["/**"]["ros__parameters"] - composable_nodes = [ + # composable nodes + composable_nodes = [] + + # add downsample process + downsample_input_pointcloud: bool = pointcloud_based_occupancy_grid_map_node_params[ + "downsample_input_pointcloud" + ] + if downsample_input_pointcloud: + voxel_grid_size: float = pointcloud_based_occupancy_grid_map_node_params[ + "downsample_voxel_size" + ] + downsample_preprocess_nodes = get_downsample_preprocess_nodes(voxel_grid_size) + composable_nodes.extend(downsample_preprocess_nodes) + + composable_nodes.append( ComposableNode( package="probabilistic_occupancy_grid_map", plugin="occupancy_grid_map::PointcloudBasedOccupancyGridMapNode", @@ -46,11 +101,15 @@ def launch_setup(context, *args, **kwargs): remappings=[ ( "~/input/obstacle_pointcloud", - LaunchConfiguration("input/obstacle_pointcloud"), + LaunchConfiguration("input/obstacle_pointcloud") + if not downsample_input_pointcloud + else "obstacle/downsample/pointcloud", ), ( "~/input/raw_pointcloud", - LaunchConfiguration("input/raw_pointcloud"), + LaunchConfiguration("input/raw_pointcloud") + if not downsample_input_pointcloud + else "raw/downsample/pointcloud", ), ("~/output/occupancy_grid_map", LaunchConfiguration("output")), ], @@ -60,8 +119,8 @@ def launch_setup(context, *args, **kwargs): {"updater_type": LaunchConfiguration("updater_type")}, ], extra_arguments=[{"use_intra_process_comms": LaunchConfiguration("use_intra_process")}], - ), - ] + ) + ) occupancy_grid_map_container = ComposableNodeContainer( name=LaunchConfiguration("individual_container_name"), diff --git a/perception/probabilistic_occupancy_grid_map/package.xml b/perception/probabilistic_occupancy_grid_map/package.xml index a90ae78b03597..3efed07535504 100644 --- a/perception/probabilistic_occupancy_grid_map/package.xml +++ b/perception/probabilistic_occupancy_grid_map/package.xml @@ -34,6 +34,7 @@ tier4_autoware_utils visualization_msgs + pointcloud_preprocessor pointcloud_to_laserscan ament_cmake_gtest @@ -44,6 +45,7 @@ launch_testing launch_testing_ament_cmake launch_testing_ros + pointcloud_preprocessor ament_cmake diff --git a/perception/probabilistic_occupancy_grid_map/pointcloud-based-occupancy-grid-map.md b/perception/probabilistic_occupancy_grid_map/pointcloud-based-occupancy-grid-map.md index 7d2efb3468f3a..d8d69ed7866b6 100644 --- a/perception/probabilistic_occupancy_grid_map/pointcloud-based-occupancy-grid-map.md +++ b/perception/probabilistic_occupancy_grid_map/pointcloud-based-occupancy-grid-map.md @@ -77,18 +77,34 @@ $$ | ----------------------------- | ------------------------- | ------------------ | | `~/output/occupancy_grid_map` | `nav_msgs::OccupancyGrid` | occupancy grid map | +### Related topics + +If you set `downsample_input_pointcloud` to `true`, the input pointcloud will be downsampled and following topics are also used. + +- pointcloud_based_occupancy_grid_map method + +```yaml +# downsampled raw and obstacle pointcloud +/perception/occupancy_grid_map/obstacle/downsample/pointcloud +/perception/occupancy_grid_map/raw/downsample/pointcloud +``` + ## Parameters ### Node Parameters -| Name | Type | Description | -| ------------------- | ------ | -------------------------------------------------------------------------------------------------------------------------------- | -| `map_frame` | string | map frame | -| `base_link_frame` | string | base_link frame | -| `use_height_filter` | bool | whether to height filter for `~/input/obstacle_pointcloud` and `~/input/raw_pointcloud`? By default, the height is set to -1~2m. | -| `map_length` | double | The length of the map. -100 if it is 50~50[m] | -| `map_resolution` | double | The map cell resolution [m] | -| `grid_map_type` | string | The type of grid map for estimating `UNKNOWN` region behind obstacle point clouds | +| Name | Type | Description | +| ----------------------------- | ------ | -------------------------------------------------------------------------------------------------------------------------------- | +| `map_frame` | string | map frame | +| `base_link_frame` | string | base_link frame | +| `use_height_filter` | bool | whether to height filter for `~/input/obstacle_pointcloud` and `~/input/raw_pointcloud`? By default, the height is set to -1~2m. | +| `map_length` | double | The length of the map. -100 if it is 50~50[m] | +| `map_resolution` | double | The map cell resolution [m] | +| `grid_map_type` | string | The type of grid map for estimating `UNKNOWN` region behind obstacle point clouds | +| `scan_origin` | string | The origin of the scan. It should be a sensor frame. | +| `pub_debug_grid` | bool | Whether to publish debug grid maps | +| `downsample_input_pointcloud` | bool | Whether to downsample the input pointclouds. The downsampled pointclouds are used for the ray tracing. | +| `downsample_voxel_size` | double | The voxel size for the downsampled pointclouds. | ## Assumptions / Known limits diff --git a/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_fixed.cpp b/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_fixed.cpp index 00b3e42fdf392..2722f2ef98249 100644 --- a/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_fixed.cpp +++ b/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_fixed.cpp @@ -71,7 +71,7 @@ void OccupancyGridMapFixedBlindSpot::updateWithPointCloud( utils::transformPointcloud(map_raw_pointcloud, scan2map_pose, scan_raw_pointcloud); utils::transformPointcloud(map_obstacle_pointcloud, scan2map_pose, scan_obstacle_pointcloud); - // Create angle bins + // Create angle bins and sort by distance struct BinInfo { BinInfo() = default; @@ -96,45 +96,43 @@ void OccupancyGridMapFixedBlindSpot::updateWithPointCloud( raw_pointcloud_angle_bins.at(angle_bin_index) .push_back(BinInfo(std::hypot(*iter_y, *iter_x), *iter_wx, *iter_wy)); } + for (auto & raw_pointcloud_angle_bin : raw_pointcloud_angle_bins) { + std::sort(raw_pointcloud_angle_bin.begin(), raw_pointcloud_angle_bin.end(), [](auto a, auto b) { + return a.range < b.range; + }); + } + // create and sort bin for obstacle pointcloud for (PointCloud2ConstIterator iter_x(scan_obstacle_pointcloud, "x"), iter_y(scan_obstacle_pointcloud, "y"), iter_wx(map_obstacle_pointcloud, "x"), iter_wy(map_obstacle_pointcloud, "y"); iter_x != iter_x.end(); ++iter_x, ++iter_y, ++iter_wx, ++iter_wy) { const double angle = atan2(*iter_y, *iter_x); - int angle_bin_index = (angle - min_angle) / angle_increment; + const int angle_bin_index = (angle - min_angle) / angle_increment; + const double range = std::hypot(*iter_y, *iter_x); + // Ignore obstacle points exceed the range of the raw points + if (raw_pointcloud_angle_bins.at(angle_bin_index).empty()) { + continue; // No raw point in this angle bin + } else if (range > raw_pointcloud_angle_bins.at(angle_bin_index).back().range) { + continue; // Obstacle point exceeds the range of the raw points + } obstacle_pointcloud_angle_bins.at(angle_bin_index) - .push_back(BinInfo(std::hypot(*iter_y, *iter_x), *iter_wx, *iter_wy)); + .push_back(BinInfo(range, *iter_wx, *iter_wy)); } - - // Sort by distance for (auto & obstacle_pointcloud_angle_bin : obstacle_pointcloud_angle_bins) { std::sort( obstacle_pointcloud_angle_bin.begin(), obstacle_pointcloud_angle_bin.end(), [](auto a, auto b) { return a.range < b.range; }); } - for (auto & raw_pointcloud_angle_bin : raw_pointcloud_angle_bins) { - std::sort(raw_pointcloud_angle_bin.begin(), raw_pointcloud_angle_bin.end(), [](auto a, auto b) { - return a.range < b.range; - }); - } // First step: Initialize cells to the final point with freespace for (size_t bin_index = 0; bin_index < obstacle_pointcloud_angle_bins.size(); ++bin_index) { - auto & obstacle_pointcloud_angle_bin = obstacle_pointcloud_angle_bins.at(bin_index); auto & raw_pointcloud_angle_bin = raw_pointcloud_angle_bins.at(bin_index); BinInfo end_distance; - if (raw_pointcloud_angle_bin.empty() && obstacle_pointcloud_angle_bin.empty()) { + if (raw_pointcloud_angle_bin.empty()) { continue; - } else if (raw_pointcloud_angle_bin.empty()) { - end_distance = obstacle_pointcloud_angle_bin.back(); - } else if (obstacle_pointcloud_angle_bin.empty()) { - end_distance = raw_pointcloud_angle_bin.back(); } else { - end_distance = obstacle_pointcloud_angle_bin.back().range + distance_margin_ < - raw_pointcloud_angle_bin.back().range - ? raw_pointcloud_angle_bin.back() - : obstacle_pointcloud_angle_bin.back(); + end_distance = raw_pointcloud_angle_bin.back(); } raytrace( scan_origin.position.x, scan_origin.position.y, end_distance.wx, end_distance.wy, diff --git a/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_projective.cpp b/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_projective.cpp index 64b76a2488e24..eae66eb90355b 100644 --- a/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_projective.cpp +++ b/perception/probabilistic_occupancy_grid_map/src/pointcloud_based_occupancy_grid_map/occupancy_grid_map_projective.cpp @@ -72,7 +72,7 @@ void OccupancyGridMapProjectiveBlindSpot::updateWithPointCloud( utils::transformPointcloud(map_raw_pointcloud, scan2map_pose, scan_raw_pointcloud); utils::transformPointcloud(map_obstacle_pointcloud, scan2map_pose, scan_obstacle_pointcloud); - // Create angle bins + // Create angle bins and sort points by range struct BinInfo3D { BinInfo3D( @@ -110,6 +110,12 @@ void OccupancyGridMapProjectiveBlindSpot::updateWithPointCloud( raw_pointcloud_angle_bins.at(angle_bin_index) .emplace_back(std::hypot(*iter_y, *iter_x), *iter_wx, *iter_wy, *iter_wz); } + for (auto & raw_pointcloud_angle_bin : raw_pointcloud_angle_bins) { + std::sort(raw_pointcloud_angle_bin.begin(), raw_pointcloud_angle_bin.end(), [](auto a, auto b) { + return a.range < b.range; + }); + } + // Create obstacle angle bins and sort points by range for (PointCloud2ConstIterator iter_x(scan_obstacle_pointcloud, "x"), iter_y(scan_obstacle_pointcloud, "y"), iter_z(scan_obstacle_pointcloud, "z"), iter_wx(map_obstacle_pointcloud, "x"), iter_wy(map_obstacle_pointcloud, "y"), @@ -121,6 +127,12 @@ void OccupancyGridMapProjectiveBlindSpot::updateWithPointCloud( const double angle = atan2(*iter_y, *iter_x); const int angle_bin_index = (angle - min_angle) / angle_increment; const double range = std::hypot(*iter_x, *iter_y); + // Ignore obstacle points exceed the range of the raw points + if (raw_pointcloud_angle_bins.at(angle_bin_index).empty()) { + continue; // No raw point in this angle bin + } else if (range > raw_pointcloud_angle_bins.at(angle_bin_index).back().range) { + continue; // Obstacle point exceeds the range of the raw points + } if (dz > projection_dz_threshold_) { const double ratio = obstacle_z / dz; const double projection_length = range * ratio; @@ -136,18 +148,11 @@ void OccupancyGridMapProjectiveBlindSpot::updateWithPointCloud( std::numeric_limits::infinity(), std::numeric_limits::infinity()); } } - - // Sort by distance for (auto & obstacle_pointcloud_angle_bin : obstacle_pointcloud_angle_bins) { std::sort( obstacle_pointcloud_angle_bin.begin(), obstacle_pointcloud_angle_bin.end(), [](auto a, auto b) { return a.range < b.range; }); } - for (auto & raw_pointcloud_angle_bin : raw_pointcloud_angle_bins) { - std::sort(raw_pointcloud_angle_bin.begin(), raw_pointcloud_angle_bin.end(), [](auto a, auto b) { - return a.range < b.range; - }); - } grid_map::Costmap2DConverter converter; if (pub_debug_grid_) { @@ -177,22 +182,13 @@ void OccupancyGridMapProjectiveBlindSpot::updateWithPointCloud( // First step: Initialize cells to the final point with freespace for (size_t bin_index = 0; bin_index < obstacle_pointcloud_angle_bins.size(); ++bin_index) { - const auto & obstacle_pointcloud_angle_bin = obstacle_pointcloud_angle_bins.at(bin_index); const auto & raw_pointcloud_angle_bin = raw_pointcloud_angle_bins.at(bin_index); BinInfo3D ray_end; - if (raw_pointcloud_angle_bin.empty() && obstacle_pointcloud_angle_bin.empty()) { + if (raw_pointcloud_angle_bin.empty()) { continue; - } else if (raw_pointcloud_angle_bin.empty()) { - ray_end = obstacle_pointcloud_angle_bin.back(); - } else if (obstacle_pointcloud_angle_bin.empty()) { - ray_end = raw_pointcloud_angle_bin.back(); } else { - const auto & farthest_obstacle_this_bin = obstacle_pointcloud_angle_bin.back(); - const auto & farthest_raw_this_bin = raw_pointcloud_angle_bin.back(); - ray_end = is_visible_beyond_obstacle(farthest_obstacle_this_bin, farthest_raw_this_bin) - ? farthest_raw_this_bin - : farthest_obstacle_this_bin; + ray_end = raw_pointcloud_angle_bin.back(); } raytrace( scan_origin.position.x, scan_origin.position.y, ray_end.wx, ray_end.wy, diff --git a/perception/radar_object_tracker/package.xml b/perception/radar_object_tracker/package.xml index a371d9054966a..3697903e77e41 100644 --- a/perception/radar_object_tracker/package.xml +++ b/perception/radar_object_tracker/package.xml @@ -16,9 +16,9 @@ autoware_auto_perception_msgs eigen + glog kalman_filter lanelet2_extension - libgoogle-glog-dev mussp nlohmann-json-dev object_recognition_utils diff --git a/perception/radar_object_tracker/src/radar_object_tracker_node/radar_object_tracker_node.cpp b/perception/radar_object_tracker/src/radar_object_tracker_node/radar_object_tracker_node.cpp index e4b394256101d..460578699e780 100644 --- a/perception/radar_object_tracker/src/radar_object_tracker_node/radar_object_tracker_node.cpp +++ b/perception/radar_object_tracker/src/radar_object_tracker_node/radar_object_tracker_node.cpp @@ -196,8 +196,10 @@ RadarObjectTrackerNode::RadarObjectTrackerNode(const rclcpp::NodeOptions & node_ tf_listener_(tf_buffer_) { // glog for debug - google::InitGoogleLogging("radar_object_tracker"); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging("radar_object_tracker"); + google::InstallFailureSignalHandler(); + } // Create publishers and subscribers detected_object_sub_ = create_subscription( diff --git a/perception/radar_tracks_msgs_converter/src/radar_tracks_msgs_converter_node/radar_tracks_msgs_converter_node.cpp b/perception/radar_tracks_msgs_converter/src/radar_tracks_msgs_converter_node/radar_tracks_msgs_converter_node.cpp index c7f2bb5bdc60d..084e939ff40a9 100644 --- a/perception/radar_tracks_msgs_converter/src/radar_tracks_msgs_converter_node/radar_tracks_msgs_converter_node.cpp +++ b/perception/radar_tracks_msgs_converter/src/radar_tracks_msgs_converter_node/radar_tracks_msgs_converter_node.cpp @@ -87,7 +87,7 @@ RadarTracksMsgsConverterNode::RadarTracksMsgsConverterNode(const rclcpp::NodeOpt // Subscriber sub_radar_ = create_subscription( - "~/input/radar_objects", rclcpp::QoS{1}, + "~/input/radar_objects", rclcpp::QoS{1}.best_effort(), std::bind(&RadarTracksMsgsConverterNode::onRadarTracks, this, _1)); sub_odometry_ = create_subscription( "~/input/odometry", rclcpp::QoS{1}, diff --git a/perception/raindrop_cluster_filter/CMakeLists.txt b/perception/raindrop_cluster_filter/CMakeLists.txt new file mode 100644 index 0000000000000..a867bc740317b --- /dev/null +++ b/perception/raindrop_cluster_filter/CMakeLists.txt @@ -0,0 +1,31 @@ +cmake_minimum_required(VERSION 3.8) +project(raindrop_cluster_filter) + +if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang") + add_compile_options(-Wall -Wextra -Wpedantic) +endif() +# find dependencies +find_package(autoware_cmake REQUIRED) +autoware_package() + +# Targets +ament_auto_add_library(low_intensity_cluster_filter SHARED + src/low_intensity_cluster_filter.cpp +) + +rclcpp_components_register_node(low_intensity_cluster_filter + PLUGIN "low_intensity_cluster_filter::LowIntensityClusterFilter" + EXECUTABLE low_intensity_cluster_filter_node) + + +if(BUILD_TESTING) + list(APPEND AMENT_LINT_AUTO_EXCLUDE ament_cmake_uncrustify) + find_package(ament_lint_auto REQUIRED) + ament_lint_auto_find_test_dependencies() +endif() + +ament_auto_package( + INSTALL_TO_SHARE + launch + config +) diff --git a/perception/raindrop_cluster_filter/config/low_intensity_cluster_filter.param.yaml b/perception/raindrop_cluster_filter/config/low_intensity_cluster_filter.param.yaml new file mode 100644 index 0000000000000..5c0892aa34721 --- /dev/null +++ b/perception/raindrop_cluster_filter/config/low_intensity_cluster_filter.param.yaml @@ -0,0 +1,17 @@ +/**: + ros__parameters: + intensity_threshold: 1.0 + existence_probability_threshold: 0.2 + max_x: 60.0 + min_x: -20.0 + max_y: 20.0 + min_y: -20.0 + filter_target_label: + UNKNOWN: true + CAR: false + TRUCK: false + BUS: false + TRAILER: false + MOTORCYCLE: false + BICYCLE: false + PEDESTRIAN: false diff --git a/perception/raindrop_cluster_filter/include/raindrop_cluster_filter/low_intensity_cluster_filter/low_intensity_cluster_filter.hpp b/perception/raindrop_cluster_filter/include/raindrop_cluster_filter/low_intensity_cluster_filter/low_intensity_cluster_filter.hpp new file mode 100644 index 0000000000000..86a790e208012 --- /dev/null +++ b/perception/raindrop_cluster_filter/include/raindrop_cluster_filter/low_intensity_cluster_filter/low_intensity_cluster_filter.hpp @@ -0,0 +1,78 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef RAINDROP_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER_HPP_ +#define RAINDROP_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER_HPP_ + +#include "detected_object_validation/utils/utils.hpp" + +#include +#include +#include + +#include + +#include +#include +// #include +#include + +#include +#include + +namespace low_intensity_cluster_filter +{ + +class LowIntensityClusterFilter : public rclcpp::Node +{ +public: + explicit LowIntensityClusterFilter(const rclcpp::NodeOptions & node_options); + +private: + void objectCallback( + const tier4_perception_msgs::msg::DetectedObjectsWithFeature::ConstSharedPtr input_msg); + bool isValidatedCluster(const sensor_msgs::msg::PointCloud2 & cluster); + + rclcpp::Publisher::SharedPtr object_pub_; + rclcpp::Subscription::SharedPtr + object_sub_; + + tf2_ros::Buffer tf_buffer_; + tf2_ros::TransformListener tf_listener_; + double intensity_threshold_; + double existence_probability_threshold_; + double max_x_; + double min_x_; + double max_y_; + double min_y_; + + double max_x_transformed_; + double min_x_transformed_; + double max_y_transformed_; + double min_y_transformed_; + // Eigen::Vector4f min_boundary_transformed_; + // Eigen::Vector4f max_boundary_transformed_; + bool is_validation_range_transformed_ = false; + const std::string base_link_frame_id_ = "base_link"; + utils::FilterTargetLabel filter_target_; + + // debugger + std::unique_ptr> stop_watch_ptr_{ + nullptr}; + std::unique_ptr debug_publisher_ptr_{nullptr}; +}; + +} // namespace low_intensity_cluster_filter + +#endif // RAINDROP_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER__LOW_INTENSITY_CLUSTER_FILTER_HPP_ diff --git a/perception/raindrop_cluster_filter/launch/low_intensity_cluster_filter.launch.xml b/perception/raindrop_cluster_filter/launch/low_intensity_cluster_filter.launch.xml new file mode 100644 index 0000000000000..9af4ad47055f9 --- /dev/null +++ b/perception/raindrop_cluster_filter/launch/low_intensity_cluster_filter.launch.xml @@ -0,0 +1,14 @@ + + + + + + + + + + + + + + diff --git a/perception/raindrop_cluster_filter/package.xml b/perception/raindrop_cluster_filter/package.xml new file mode 100644 index 0000000000000..492b789239d54 --- /dev/null +++ b/perception/raindrop_cluster_filter/package.xml @@ -0,0 +1,36 @@ + + + + raindrop_cluster_filter + 0.1.0 + The ROS 2 filter cluster package + Yukihiro Saito + Dai Nguyen + Yoshi Ri + Apache License 2.0 + Dai Nguyen + + ament_cmake + autoware_cmake + detected_object_validation + lanelet2_extension + message_filters + nav_msgs + pcl_conversions + pcl_ros + rclcpp + rclcpp_components + sensor_msgs + tf2 + tf2_eigen + tf2_ros + tier4_autoware_utils + tier4_perception_msgs + + ament_lint_auto + ament_lint_common + + + ament_cmake + + diff --git a/perception/raindrop_cluster_filter/raindrop_cluster_filter.md b/perception/raindrop_cluster_filter/raindrop_cluster_filter.md new file mode 100644 index 0000000000000..175bbd00a93ea --- /dev/null +++ b/perception/raindrop_cluster_filter/raindrop_cluster_filter.md @@ -0,0 +1,54 @@ +# low_intensity_cluster_filter + +## Purpose + +The `low_intensity_cluster_filter` is a node that filters clusters based on the intensity of their pointcloud. + +Mainly this focuses on filtering out unknown objects with very low intensity pointcloud, such as fail detection of unknown objects caused by raindrop or water splash from ego or other fast moving vehicles. + +## Inner-workings / Algorithms + +## Inputs / Outputs + +### Input + +| Name | Type | Description | +| -------------- | -------------------------------------------------------- | ---------------------- | +| `input/object` | `tier4_perception_msgs::msg::DetectedObjectsWithFeature` | input detected objects | + +### Output + +| Name | Type | Description | +| --------------- | -------------------------------------------------------- | ------------------------- | +| `output/object` | `tier4_perception_msgs::msg::DetectedObjectsWithFeature` | filtered detected objects | + +## Parameters + +### Core Parameters + +| Name | Type | Default Value | Description | +| --------------------------------- | ----- | ------------------------------------------------------- | --------------------------------------------- | +| `filter_target_label.UNKNOWN` | bool | false | If true, unknown objects are filtered. | +| `filter_target_label.CAR` | bool | false | If true, car objects are filtered. | +| `filter_target_label.TRUCK` | bool | false | If true, truck objects are filtered. | +| `filter_target_label.BUS` | bool | false | If true, bus objects are filtered. | +| `filter_target_label.TRAILER` | bool | false | If true, trailer objects are filtered. | +| `filter_target_label.MOTORCYCLE` | bool | false | If true, motorcycle objects are filtered. | +| `filter_target_label.BICYCLE` | bool | false | If true, bicycle objects are filtered. | +| `filter_target_label.PEDESTRIAN` | bool | false | If true, pedestrian objects are filtered. | +| `max_x` | float | 60.00 | Maximum of x of the filter effective range | +| `min_x` | float | -20.00 | Minimum of x of the filter effective range | +| `max_y` | float | 20.00 | Maximum of y of the filter effective range | +| `min_y` | float | -20.00 | Minium of y of the filter effective range | +| `intensity_threshold` | float | 1.0 | The threshold of average intensity for filter | +| `existence_probability_threshold` | float | The existence probability threshold to apply the filter | + +## Assumptions / Known limits + +## (Optional) Error detection and handling + +## (Optional) Performance characterization + +## (Optional) References/External links + +## (Optional) Future extensions / Unimplemented parts diff --git a/perception/raindrop_cluster_filter/src/low_intensity_cluster_filter.cpp b/perception/raindrop_cluster_filter/src/low_intensity_cluster_filter.cpp new file mode 100644 index 0000000000000..5c47b61eaa0a3 --- /dev/null +++ b/perception/raindrop_cluster_filter/src/low_intensity_cluster_filter.cpp @@ -0,0 +1,141 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "raindrop_cluster_filter/low_intensity_cluster_filter/low_intensity_cluster_filter.hpp" + +#include +#include + +#include + +#include +namespace low_intensity_cluster_filter +{ +LowIntensityClusterFilter::LowIntensityClusterFilter(const rclcpp::NodeOptions & node_options) +: Node("low_intensity_cluster_filter_node", node_options), + tf_buffer_(this->get_clock()), + tf_listener_(tf_buffer_) +{ + intensity_threshold_ = declare_parameter("intensity_threshold"); + existence_probability_threshold_ = declare_parameter("existence_probability_threshold"); + max_x_ = declare_parameter("max_x"); + min_x_ = declare_parameter("min_x"); + max_y_ = declare_parameter("max_y"); + min_y_ = declare_parameter("min_y"); + + filter_target_.UNKNOWN = declare_parameter("filter_target_label.UNKNOWN"); + filter_target_.CAR = declare_parameter("filter_target_label.CAR"); + filter_target_.TRUCK = declare_parameter("filter_target_label.TRUCK"); + filter_target_.BUS = declare_parameter("filter_target_label.BUS"); + filter_target_.TRAILER = declare_parameter("filter_target_label.TRAILER"); + filter_target_.MOTORCYCLE = declare_parameter("filter_target_label.MOTORCYCLE"); + filter_target_.BICYCLE = declare_parameter("filter_target_label.BICYCLE"); + filter_target_.PEDESTRIAN = declare_parameter("filter_target_label.PEDESTRIAN"); + + using std::placeholders::_1; + // Set publisher/subscriber + object_sub_ = this->create_subscription( + "input/objects", rclcpp::QoS{1}, + std::bind(&LowIntensityClusterFilter::objectCallback, this, _1)); + object_pub_ = this->create_publisher( + "output/objects", rclcpp::QoS{1}); + // initialize debug tool + { + using tier4_autoware_utils::DebugPublisher; + using tier4_autoware_utils::StopWatch; + stop_watch_ptr_ = std::make_unique>(); + debug_publisher_ptr_ = + std::make_unique(this, "low_intensity_cluster_filter_node"); + stop_watch_ptr_->tic("cyclic_time"); + stop_watch_ptr_->tic("processing_time"); + } +} + +void LowIntensityClusterFilter::objectCallback( + const tier4_perception_msgs::msg::DetectedObjectsWithFeature::ConstSharedPtr input_msg) +{ + // Guard + stop_watch_ptr_->toc("processing_time", true); + if (object_pub_->get_subscription_count() < 1) return; + + tier4_perception_msgs::msg::DetectedObjectsWithFeature output_object_msg; + output_object_msg.header = input_msg->header; + geometry_msgs::msg::TransformStamped transform_stamp; + try { + transform_stamp = tf_buffer_.lookupTransform( + input_msg->header.frame_id, base_link_frame_id_, tf2_ros::fromMsg(input_msg->header.stamp)); + } catch (tf2::TransformException & ex) { + RCLCPP_ERROR(get_logger(), "Failed to lookup transform: %s", ex.what()); + return; + } + geometry_msgs::msg::Pose min_range; + min_range.position.x = min_x_; + min_range.position.y = min_y_; + geometry_msgs::msg::Pose max_pose; + max_pose.position.x = max_x_; + max_pose.position.y = max_y_; + auto min_ranged_transformed = tier4_autoware_utils::transformPose(min_range, transform_stamp); + auto max_range_transformed = tier4_autoware_utils::transformPose(max_pose, transform_stamp); + for (const auto & feature_object : input_msg->feature_objects) { + const auto & object = feature_object.object; + const auto & label = object.classification.front().label; + const auto & feature = feature_object.feature; + const auto & cluster = feature.cluster; + const auto existence_probability = object.existence_probability; + const auto & position = object.kinematics.pose_with_covariance.pose.position; + bool is_inside_validation_range = min_ranged_transformed.position.x < position.x && + position.x < max_range_transformed.position.x && + min_ranged_transformed.position.y < position.x && + position.y < max_range_transformed.position.y; + int intensity_index = pcl::getFieldIndex(cluster, "intensity"); + if ( + intensity_index != -1 && filter_target_.isTarget(label) && is_inside_validation_range && + !isValidatedCluster(cluster) && existence_probability < existence_probability_threshold_) { + continue; + } + output_object_msg.feature_objects.emplace_back(feature_object); + } + object_pub_->publish(output_object_msg); + if (debug_publisher_ptr_ && stop_watch_ptr_) { + const double cyclic_time_ms = stop_watch_ptr_->toc("cyclic_time", true); + const double processing_time_ms = stop_watch_ptr_->toc("processing_time", true); + debug_publisher_ptr_->publish( + "debug/cyclic_time_ms", cyclic_time_ms); + debug_publisher_ptr_->publish( + "debug/processing_time_ms", processing_time_ms); + } +} +bool LowIntensityClusterFilter::isValidatedCluster(const sensor_msgs::msg::PointCloud2 & cluster) +{ + double mean_intensity = 0.0; + if (cluster.point_step < 16) { + RCLCPP_WARN(get_logger(), "Invalid point cloud data. point_step is less than 16."); + return true; + } + for (sensor_msgs::PointCloud2ConstIterator iter(cluster, "intensity"); iter != iter.end(); + ++iter) { + mean_intensity += *iter; + } + const size_t num_points = cluster.width * cluster.height; + mean_intensity /= static_cast(num_points); + if (mean_intensity > intensity_threshold_) { + return true; + } + return false; +} + +} // namespace low_intensity_cluster_filter + +#include +RCLCPP_COMPONENTS_REGISTER_NODE(low_intensity_cluster_filter::LowIntensityClusterFilter) diff --git a/perception/tracking_object_merger/package.xml b/perception/tracking_object_merger/package.xml index 027a7bf26d2c4..5912675c819fc 100644 --- a/perception/tracking_object_merger/package.xml +++ b/perception/tracking_object_merger/package.xml @@ -15,7 +15,7 @@ autoware_auto_perception_msgs eigen - libgoogle-glog-dev + glog mussp object_recognition_utils rclcpp diff --git a/perception/tracking_object_merger/src/decorative_tracker_merger.cpp b/perception/tracking_object_merger/src/decorative_tracker_merger.cpp index 2273ad6504e2a..5ff016379dd18 100644 --- a/perception/tracking_object_merger/src/decorative_tracker_merger.cpp +++ b/perception/tracking_object_merger/src/decorative_tracker_merger.cpp @@ -88,8 +88,10 @@ DecorativeTrackerMergerNode::DecorativeTrackerMergerNode(const rclcpp::NodeOptio tf_listener_(tf_buffer_) { // glog for debug - google::InitGoogleLogging("decorative_object_merger_node"); - google::InstallFailureSignalHandler(); + if (!google::IsGoogleLoggingInitialized()) { + google::InitGoogleLogging("decorative_object_merger_node"); + google::InstallFailureSignalHandler(); + } // Subscriber sub_main_objects_ = create_subscription( diff --git a/perception/traffic_light_classifier/package.xml b/perception/traffic_light_classifier/package.xml index ef04aae7ee3cb..9e460e8ad1a1d 100644 --- a/perception/traffic_light_classifier/package.xml +++ b/perception/traffic_light_classifier/package.xml @@ -6,6 +6,7 @@ The traffic_light_classifier package Yukihiro Saito Shunsuke Miura + Tao Zhong Apache License 2.0 ament_cmake_auto diff --git a/perception/traffic_light_classifier/src/cnn_classifier.cpp b/perception/traffic_light_classifier/src/cnn_classifier.cpp index cd266ac25b822..d6ba81041c6f8 100644 --- a/perception/traffic_light_classifier/src/cnn_classifier.cpp +++ b/perception/traffic_light_classifier/src/cnn_classifier.cpp @@ -108,7 +108,7 @@ bool CNNClassifier::getTrafficSignals( void CNNClassifier::outputDebugImage( cv::Mat & debug_image, const tier4_perception_msgs::msg::TrafficLight & traffic_signal) { - float probability; + float probability = 0.0f; std::string label; for (std::size_t i = 0; i < traffic_signal.elements.size(); i++) { auto light = traffic_signal.elements.at(i); diff --git a/perception/traffic_light_map_based_detector/package.xml b/perception/traffic_light_map_based_detector/package.xml index 4631935fe42fa..6f1befb79b98c 100644 --- a/perception/traffic_light_map_based_detector/package.xml +++ b/perception/traffic_light_map_based_detector/package.xml @@ -6,6 +6,7 @@ The traffic_light_map_based_detector package Yukihiro Saito Shunsuke Miura + Tao Zhong Apache License 2.0 ament_cmake_auto diff --git a/perception/traffic_light_visualization/package.xml b/perception/traffic_light_visualization/package.xml index 276f04762cdea..3d3683a8be6cc 100644 --- a/perception/traffic_light_visualization/package.xml +++ b/perception/traffic_light_visualization/package.xml @@ -5,6 +5,7 @@ 0.1.0 The traffic_light_visualization package Yukihiro Saito + Tao Zhong Apache License 2.0 ament_cmake_auto diff --git a/planning/autoware_remaining_distance_time_calculator/CMakeLists.txt b/planning/autoware_remaining_distance_time_calculator/CMakeLists.txt new file mode 100644 index 0000000000000..d29a153a0ce5d --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/CMakeLists.txt @@ -0,0 +1,21 @@ +cmake_minimum_required(VERSION 3.14) +project(autoware_remaining_distance_time_calculator) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +ament_auto_add_library(${PROJECT_NAME} SHARED + src/remaining_distance_time_calculator_node.cpp +) + +rclcpp_components_register_node(${PROJECT_NAME} + PLUGIN "autoware::remaining_distance_time_calculator::RemainingDistanceTimeCalculatorNode" + EXECUTABLE ${PROJECT_NAME}_node +) + + +ament_auto_package( + INSTALL_TO_SHARE + config + launch +) diff --git a/planning/autoware_remaining_distance_time_calculator/README.md b/planning/autoware_remaining_distance_time_calculator/README.md new file mode 100644 index 0000000000000..694c6764de91c --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/README.md @@ -0,0 +1,39 @@ +## Remaining Distance and Time Calculator + +### Role + +This package aims to provide mission remaining distance and remaining time calculations. + +### Activation and Timing + +- The calculations are activated once we have a route planned for a mission in Autoware. +- The calculations are triggered timely based on the `update_rate` parameter. + +### Module Parameters + +| Name | Type | Default Value | Explanation | +| ------------- | ------ | ------------- | --------------------------- | +| `update_rate` | double | 10.0 | Timer callback period. [Hz] | + +### Inner-workings + +#### Remaining Distance Calculation + +- The remaining distance calculation is based on getting the remaining shortest path between the current vehicle pose and goal pose using `lanelet2` routing APIs. +- The remaining distance is calculated by summing the 2D length of remaining shortest path, with exception to current lanelet and goal lanelet. + - For the current lanelet, the distance is calculated from the current vehicle position to the end of that lanelet. + - For the goal lanelet, the distance is calculated from the start of the lanelet to the goal pose in this lanelet. +- When there is only one lanelet remaining, the distance is calculated by getting the 2D distance between the current vehicle pose and goal pose. +- Checks are added to handle cases when current lanelet, goal lanelet, or routing graph are not valid to prevent node process die. + - In such cases when, last valid remaining distance and time are maintained. + +#### Remaining Time Calculation + +- The remaining time currently depends on a simple equation of motion by getting the maximum velocity limit. +- The remaining distance is calculated by dividing the remaining distance by the maximum velocity limit. +- A check is added to the remaining time calculation to make sure that maximum velocity limit is greater than zero. This prevents division by zero or getting negative time value. + +### Future Work + +- Find a more efficient way for remaining distance calculation instead of regularly searching the graph for finding the remaining shortest path. +- Engage more sophisticated motion models for more accurate remaining time calculations. diff --git a/planning/autoware_remaining_distance_time_calculator/config/remaining_distance_time_calculator.param.yaml b/planning/autoware_remaining_distance_time_calculator/config/remaining_distance_time_calculator.param.yaml new file mode 100644 index 0000000000000..5b8c019de5a20 --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/config/remaining_distance_time_calculator.param.yaml @@ -0,0 +1,3 @@ +/**: + ros__parameters: + update_rate: 10.0 diff --git a/planning/autoware_remaining_distance_time_calculator/launch/remaining_distance_time_calculator.launch.xml b/planning/autoware_remaining_distance_time_calculator/launch/remaining_distance_time_calculator.launch.xml new file mode 100644 index 0000000000000..cfb456c57ca41 --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/launch/remaining_distance_time_calculator.launch.xml @@ -0,0 +1,20 @@ + + + + + + + + + + + + + + + + + + + + diff --git a/planning/autoware_remaining_distance_time_calculator/package.xml b/planning/autoware_remaining_distance_time_calculator/package.xml new file mode 100644 index 0000000000000..4f0324b23f299 --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/package.xml @@ -0,0 +1,35 @@ + + + autoware_remaining_distance_time_calculator + 0.1.0 + Calculates and publishes remaining distance and time of the mission. + + Ahmed Ebrahim + + Apache License 2.0 + + ament_cmake_auto + autoware_cmake + + autoware_internal_msgs + autoware_planning_msgs + geometry_msgs + lanelet2_extension + motion_utils + nav_msgs + planning_test_utils + rclcpp + rclcpp_components + route_handler + std_msgs + tier4_autoware_utils + tier4_planning_msgs + + ament_cmake_ros + ament_lint_auto + autoware_lint_common + + + ament_cmake + + diff --git a/planning/autoware_remaining_distance_time_calculator/schema/remaining_distance_time_calculator.schema.json b/planning/autoware_remaining_distance_time_calculator/schema/remaining_distance_time_calculator.schema.json new file mode 100644 index 0000000000000..4b3bc15432d0d --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/schema/remaining_distance_time_calculator.schema.json @@ -0,0 +1,31 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Remaining Distance Time Calculator Parameters", + "type": "object", + "actual_parameters": { + "type": "object", + "properties": { + "update_rate": { + "type": "number", + "default": 10.0, + "description": "Recalculate remaining distance and time at this rate, Hz" + } + }, + "required": ["update_rate"], + "additionalProperties": false + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/actual_parameters" + } + }, + "required": ["ros__parameters"], + "additionalProperties": false + } + }, + "required": ["/**"], + "additionalProperties": false +} diff --git a/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.cpp b/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.cpp new file mode 100644 index 0000000000000..327bd0ff3b582 --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.cpp @@ -0,0 +1,188 @@ +// Copyright 2022 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "remaining_distance_time_calculator_node.hpp" + +#include +#include +#include +#include +#include +#include + +#include + +#include +#include +#include +#include +#include + +namespace autoware::remaining_distance_time_calculator +{ + +RemainingDistanceTimeCalculatorNode::RemainingDistanceTimeCalculatorNode( + const rclcpp::NodeOptions & options) +: Node("remaining_distance_time_calculator", options), + is_graph_ready_{false}, + has_received_route_{false}, + velocity_limit_{99.99}, + remaining_distance_{0.0}, + remaining_time_{0.0} +{ + using std::placeholders::_1; + + sub_odometry_ = create_subscription( + "~/input/odometry", 1, std::bind(&RemainingDistanceTimeCalculatorNode::on_odometry, this, _1)); + + const auto qos_transient_local = rclcpp::QoS{1}.transient_local(); + + sub_map_ = create_subscription( + "~/input/map", qos_transient_local, + std::bind(&RemainingDistanceTimeCalculatorNode::on_map, this, _1)); + sub_route_ = create_subscription( + "~/input/route", qos_transient_local, + std::bind(&RemainingDistanceTimeCalculatorNode::on_route, this, _1)); + sub_planning_velocity_ = create_subscription( + "/planning/scenario_planning/current_max_velocity", qos_transient_local, + std::bind(&RemainingDistanceTimeCalculatorNode::on_velocity_limit, this, _1)); + + pub_mission_remaining_distance_time_ = create_publisher( + "~/output/mission_remaining_distance_time", + rclcpp::QoS(rclcpp::KeepLast(10)).durability_volatile().reliable()); + + node_param_.update_rate = declare_parameter("update_rate"); + + const auto period_ns = rclcpp::Rate(node_param_.update_rate).period(); + timer_ = rclcpp::create_timer( + this, get_clock(), period_ns, std::bind(&RemainingDistanceTimeCalculatorNode::on_timer, this)); +} + +void RemainingDistanceTimeCalculatorNode::on_map(const HADMapBin::ConstSharedPtr & msg) +{ + route_handler_.setMap(*msg); + lanelet_map_ptr_ = std::make_shared(); + lanelet::utils::conversion::fromBinMsg( + *msg, lanelet_map_ptr_, &traffic_rules_ptr_, &routing_graph_ptr_); + lanelet::ConstLanelets all_lanelets = lanelet::utils::query::laneletLayer(lanelet_map_ptr_); + road_lanelets_ = lanelet::utils::query::roadLanelets(all_lanelets); + is_graph_ready_ = true; +} + +void RemainingDistanceTimeCalculatorNode::on_odometry(const Odometry::ConstSharedPtr & msg) +{ + current_vehicle_pose_ = msg->pose.pose; + current_vehicle_velocity_ = msg->twist.twist.linear; +} + +void RemainingDistanceTimeCalculatorNode::on_route(const LaneletRoute::ConstSharedPtr & msg) +{ + goal_pose_ = msg->goal_pose; + has_received_route_ = true; +} + +void RemainingDistanceTimeCalculatorNode::on_velocity_limit( + const VelocityLimit::ConstSharedPtr & msg) +{ + if (msg->max_velocity > 1e-5) { + velocity_limit_ = msg->max_velocity; + } +} + +void RemainingDistanceTimeCalculatorNode::on_timer() +{ + if (is_graph_ready_ && has_received_route_) { + calculate_remaining_distance(); + calculate_remaining_time(); + publish_mission_remaining_distance_time(); + } +} + +void RemainingDistanceTimeCalculatorNode::calculate_remaining_distance() +{ + size_t index = 0; + + lanelet::ConstLanelet current_lanelet; + if (!lanelet::utils::query::getClosestLanelet( + road_lanelets_, current_vehicle_pose_, ¤t_lanelet)) { + RCLCPP_WARN_STREAM(this->get_logger(), "Failed to find current lanelet."); + + return; + } + + lanelet::ConstLanelet goal_lanelet; + if (!lanelet::utils::query::getClosestLanelet(road_lanelets_, goal_pose_, &goal_lanelet)) { + RCLCPP_WARN_STREAM(this->get_logger(), "Failed to find goal lanelet."); + + return; + } + + const lanelet::Optional optional_route = + routing_graph_ptr_->getRoute(current_lanelet, goal_lanelet, 0); + if (!optional_route) { + RCLCPP_WARN_STREAM(this->get_logger(), "Failed to find proper route."); + + return; + } + + lanelet::routing::LaneletPath remaining_shortest_path; + remaining_shortest_path = optional_route->shortestPath(); + + remaining_distance_ = 0.0; + + for (auto & llt : remaining_shortest_path) { + if (remaining_shortest_path.size() == 1) { + remaining_distance_ += + tier4_autoware_utils::calcDistance2d(current_vehicle_pose_.position, goal_pose_.position); + break; + } + + if (index == 0) { + lanelet::ArcCoordinates arc_coord = + lanelet::utils::getArcCoordinates({llt}, current_vehicle_pose_); + double this_lanelet_length = lanelet::utils::getLaneletLength2d(llt); + + remaining_distance_ += this_lanelet_length - arc_coord.length; + } else if (index == (remaining_shortest_path.size() - 1)) { + lanelet::ArcCoordinates arc_coord = lanelet::utils::getArcCoordinates({llt}, goal_pose_); + remaining_distance_ += arc_coord.length; + } else { + remaining_distance_ += lanelet::utils::getLaneletLength2d(llt); + } + + index++; + } +} + +void RemainingDistanceTimeCalculatorNode::calculate_remaining_time() +{ + if (velocity_limit_ > 0.0) { + remaining_time_ = remaining_distance_ / velocity_limit_; + } +} + +void RemainingDistanceTimeCalculatorNode::publish_mission_remaining_distance_time() +{ + MissionRemainingDistanceTime mission_remaining_distance_time; + + mission_remaining_distance_time.remaining_distance = remaining_distance_; + mission_remaining_distance_time.remaining_time = remaining_time_; + pub_mission_remaining_distance_time_->publish(mission_remaining_distance_time); +} + +} // namespace autoware::remaining_distance_time_calculator + +#include +RCLCPP_COMPONENTS_REGISTER_NODE( + autoware::remaining_distance_time_calculator::RemainingDistanceTimeCalculatorNode) diff --git a/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.hpp b/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.hpp new file mode 100644 index 0000000000000..2a88cdb57abf4 --- /dev/null +++ b/planning/autoware_remaining_distance_time_calculator/src/remaining_distance_time_calculator_node.hpp @@ -0,0 +1,110 @@ +// Copyright 2022 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef REMAINING_DISTANCE_TIME_CALCULATOR_NODE_HPP_ +#define REMAINING_DISTANCE_TIME_CALCULATOR_NODE_HPP_ + +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include +#include + +#include + +namespace autoware::remaining_distance_time_calculator +{ + +struct NodeParam +{ + double update_rate{0.0}; +}; + +class RemainingDistanceTimeCalculatorNode : public rclcpp::Node +{ +public: + explicit RemainingDistanceTimeCalculatorNode(const rclcpp::NodeOptions & options); + +private: + using LaneletRoute = autoware_planning_msgs::msg::LaneletRoute; + using HADMapBin = autoware_auto_mapping_msgs::msg::HADMapBin; + using Odometry = nav_msgs::msg::Odometry; + using VelocityLimit = tier4_planning_msgs::msg::VelocityLimit; + using MissionRemainingDistanceTime = autoware_internal_msgs::msg::MissionRemainingDistanceTime; + + rclcpp::Subscription::SharedPtr sub_route_; + rclcpp::Subscription::SharedPtr sub_map_; + rclcpp::Subscription::SharedPtr sub_odometry_; + rclcpp::Subscription::SharedPtr sub_planning_velocity_; + + rclcpp::Publisher::SharedPtr pub_mission_remaining_distance_time_; + + rclcpp::TimerBase::SharedPtr timer_; + + route_handler::RouteHandler route_handler_; + lanelet::LaneletMapPtr lanelet_map_ptr_; + lanelet::routing::RoutingGraphPtr routing_graph_ptr_; + lanelet::traffic_rules::TrafficRulesPtr traffic_rules_ptr_; + lanelet::ConstLanelets road_lanelets_; + bool is_graph_ready_; + + // Data Buffer + geometry_msgs::msg::Pose current_vehicle_pose_; + geometry_msgs::msg::Vector3 current_vehicle_velocity_; + geometry_msgs::msg::Pose goal_pose_; + bool has_received_route_; + double velocity_limit_; + + double remaining_distance_; + double remaining_time_; + + // Parameter + NodeParam node_param_; + + // Callbacks + void on_timer(); + void on_odometry(const Odometry::ConstSharedPtr & msg); + void on_route(const LaneletRoute::ConstSharedPtr & msg); + void on_map(const HADMapBin::ConstSharedPtr & msg); + void on_velocity_limit(const VelocityLimit::ConstSharedPtr & msg); + + /** + * @brief calculate mission remaining distance + */ + void calculate_remaining_distance(); + + /** + * @brief calculate mission remaining time + */ + void calculate_remaining_time(); + + /** + * @brief publish mission remaining distance and time + */ + void publish_mission_remaining_distance_time(); +}; +} // namespace autoware::remaining_distance_time_calculator +#endif // REMAINING_DISTANCE_TIME_CALCULATOR_NODE_HPP_ diff --git a/planning/behavior_path_avoidance_by_lane_change_module/src/interface.cpp b/planning/behavior_path_avoidance_by_lane_change_module/src/interface.cpp index 3a7c22c84b3e8..a2e26557d9726 100644 --- a/planning/behavior_path_avoidance_by_lane_change_module/src/interface.cpp +++ b/planning/behavior_path_avoidance_by_lane_change_module/src/interface.cpp @@ -57,7 +57,10 @@ void AvoidanceByLaneChangeInterface::updateRTCStatus( return (dir == Direction::LEFT) ? "left" : "right"; }); + const auto state = isWaitingApproval() ? State::WAITING_FOR_EXECUTION : State::RUNNING; + rtc_interface_ptr_map_.at(direction)->updateCooperateStatus( - uuid_map_.at(direction), isExecutionReady(), start_distance, finish_distance, clock_->now()); + uuid_map_.at(direction), isExecutionReady(), state, start_distance, finish_distance, + clock_->now()); } } // namespace behavior_path_planner diff --git a/planning/behavior_path_avoidance_by_lane_change_module/src/scene.cpp b/planning/behavior_path_avoidance_by_lane_change_module/src/scene.cpp index 27c6713adfead..d7d7fa8b60513 100644 --- a/planning/behavior_path_avoidance_by_lane_change_module/src/scene.cpp +++ b/planning/behavior_path_avoidance_by_lane_change_module/src/scene.cpp @@ -125,7 +125,7 @@ AvoidancePlanningData AvoidanceByLaneChange::calcAvoidancePlanningData( // reference pose data.reference_pose = getEgoPose(); - data.reference_path_rough = prev_module_path_; + data.reference_path_rough = prev_module_output_.path; const auto resample_interval = avoidance_parameters_->resample_interval_for_planning; data.reference_path = utils::resamplePathWithSpline(data.reference_path_rough, resample_interval); @@ -145,7 +145,9 @@ void AvoidanceByLaneChange::fillAvoidanceTargetObjects( const auto [object_within_target_lane, object_outside_target_lane] = utils::path_safety_checker::separateObjectsByLanelets( *planner_data_->dynamic_object, data.current_lanelets, - utils::path_safety_checker::isPolygonOverlapLanelet); + [](const auto & obj, const auto & lane) { + return utils::path_safety_checker::isPolygonOverlapLanelet(obj, lane); + }); // Assume that the maximum allocation for data.other object is the sum of // objects_within_target_lane and object_outside_target_lane. The maximum allocation for @@ -164,7 +166,7 @@ void AvoidanceByLaneChange::fillAvoidanceTargetObjects( [](const auto & object) { ObjectData other_object; other_object.object = object; - other_object.reason = "OutOfTargetArea"; + other_object.info = ObjectInfo::OUT_OF_TARGET_AREA; return other_object; }); } @@ -273,12 +275,8 @@ double AvoidanceByLaneChange::calcMinimumLaneChangeLength() const return std::numeric_limits::infinity(); } - // get minimum lane change distance - const auto shift_intervals = - getRouteHandler()->getLateralIntervalsToPreferredLane(current_lanes.back(), direction_); return utils::lane_change::calcMinimumLaneChangeLength( - *lane_change_parameters_, shift_intervals, - lane_change_parameters_->backward_length_buffer_for_end_of_lane); + getRouteHandler(), current_lanes.back(), *lane_change_parameters_, direction_); } double AvoidanceByLaneChange::calcLateralOffset() const diff --git a/planning/behavior_path_avoidance_module/config/avoidance.param.yaml b/planning/behavior_path_avoidance_module/config/avoidance.param.yaml index 5d6044df64b2f..dc42af0412254 100644 --- a/planning/behavior_path_avoidance_module/config/avoidance.param.yaml +++ b/planning/behavior_path_avoidance_module/config/avoidance.param.yaml @@ -132,6 +132,10 @@ th_shiftable_ratio: 0.8 # [-] min_road_shoulder_width: 0.5 # [m] FOR DEVELOPER + # for merging/deviating vehicle + merging_vehicle: + th_overhang_distance: 0.0 # [m] + # params for avoidance of vehicle type objects that are ambiguous as to whether they are parked. avoidance_for_ambiguous_vehicle: enable: true # [-] @@ -290,4 +294,3 @@ # for debug debug: marker: false - console: false diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/data_structs.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/data_structs.hpp index e74b546f31fc4..2e1daed38488f 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/data_structs.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/data_structs.hpp @@ -15,16 +15,12 @@ #ifndef BEHAVIOR_PATH_AVOIDANCE_MODULE__DATA_STRUCTS_HPP_ #define BEHAVIOR_PATH_AVOIDANCE_MODULE__DATA_STRUCTS_HPP_ +#include "behavior_path_avoidance_module/type_alias.hpp" #include "behavior_path_planner_common/data_manager.hpp" #include "behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp" #include "behavior_path_planner_common/utils/path_shifter/path_shifter.hpp" #include -#include - -#include -#include -#include #include #include @@ -38,21 +34,38 @@ namespace behavior_path_planner { -using autoware_auto_perception_msgs::msg::PredictedObject; -using autoware_auto_perception_msgs::msg::PredictedPath; -using autoware_auto_planning_msgs::msg::PathWithLaneId; - -using tier4_autoware_utils::Point2d; -using tier4_autoware_utils::Polygon2d; -using tier4_planning_msgs::msg::AvoidanceDebugMsgArray; - -using geometry_msgs::msg::Point; -using geometry_msgs::msg::Pose; using behavior_path_planner::utils::path_safety_checker::CollisionCheckDebug; - using route_handler::Direction; +enum class ObjectInfo { + NONE = 0, + // ignore reasons + OUT_OF_TARGET_AREA, + FURTHER_THAN_THRESHOLD, + FURTHER_THAN_GOAL, + IS_NOT_TARGET_OBJECT, + IS_NOT_PARKING_OBJECT, + TOO_NEAR_TO_CENTERLINE, + TOO_NEAR_TO_GOAL, + MOVING_OBJECT, + UNSTABLE_OBJECT, + CROSSWALK_USER, + ENOUGH_LATERAL_DISTANCE, + LESS_THAN_EXECUTION_THRESHOLD, + PARALLEL_TO_EGO_LANE, + MERGING_TO_EGO_LANE, + DEVIATING_FROM_EGO_LANE, + // unavoidable reasons + NEED_DECELERATION, + SAME_DIRECTION_SHIFT, + INSUFFICIENT_DRIVABLE_SPACE, + INSUFFICIENT_LONGITUDINAL_DISTANCE, + INVALID_SHIFT_LINE, + // others + AMBIGUOUS_STOPPED_VEHICLE, +}; + struct ObjectParameter { bool is_avoidance_target{false}; @@ -189,6 +202,9 @@ struct AvoidanceParameters double time_threshold_for_ambiguous_vehicle{0.0}; double distance_threshold_for_ambiguous_vehicle{0.0}; + // for merging/deviating vehicle + double th_overhang_distance{0.0}; + // parameters for safety check area bool enable_safety_check{false}; bool check_current_lane{false}; @@ -322,7 +338,6 @@ struct AvoidanceParameters // debug bool publish_debug_marker = false; - bool print_debug_info = false; }; struct ObjectData // avoidance target @@ -421,8 +436,8 @@ struct ObjectData // avoidance target // overhang points (sort by distance) std::vector> overhang_points{}; - // unavoidable reason - std::string reason{}; + // object detail info + ObjectInfo info{ObjectInfo::NONE}; // lateral avoid margin std::optional avoid_margin{std::nullopt}; diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/debug.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/debug.hpp index f49f457ddd066..63cb54d2e3fa1 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/debug.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/debug.hpp @@ -16,25 +16,20 @@ #define BEHAVIOR_PATH_AVOIDANCE_MODULE__DEBUG_HPP_ #include "behavior_path_avoidance_module/data_structs.hpp" - -#include - -#include -#include +#include "behavior_path_avoidance_module/type_alias.hpp" #include -namespace marker_utils::avoidance_marker +namespace behavior_path_planner::utils::avoidance { -using autoware_auto_planning_msgs::msg::PathWithLaneId; + using behavior_path_planner::AvoidancePlanningData; using behavior_path_planner::AvoidLineArray; using behavior_path_planner::DebugData; using behavior_path_planner::ObjectDataArray; +using behavior_path_planner::ObjectInfo; using behavior_path_planner::PathShifter; using behavior_path_planner::ShiftLineArray; -using geometry_msgs::msg::Pose; -using visualization_msgs::msg::MarkerArray; MarkerArray createEgoStatusMarkerArray( const AvoidancePlanningData & data, const Pose & p_ego, std::string && ns); @@ -47,11 +42,11 @@ MarkerArray createPredictedVehiclePositions(const PathWithLaneId & path, std::st MarkerArray createTargetObjectsMarkerArray(const ObjectDataArray & objects, const std::string & ns); -MarkerArray createOtherObjectsMarkerArray(const ObjectDataArray & objects, const std::string & ns); +MarkerArray createOtherObjectsMarkerArray(const ObjectDataArray & objects, const ObjectInfo & info); MarkerArray createDebugMarkerArray( const AvoidancePlanningData & data, const PathShifter & shifter, const DebugData & debug); -} // namespace marker_utils::avoidance_marker +} // namespace behavior_path_planner::utils::avoidance std::string toStrInfo(const behavior_path_planner::ShiftLineArray & sl_arr); diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/helper.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/helper.hpp index 8d95e724045ba..8de39d00af130 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/helper.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/helper.hpp @@ -16,11 +16,10 @@ #define BEHAVIOR_PATH_AVOIDANCE_MODULE__HELPER_HPP_ #include "behavior_path_avoidance_module/data_structs.hpp" +#include "behavior_path_avoidance_module/type_alias.hpp" #include "behavior_path_avoidance_module/utils.hpp" #include "behavior_path_planner_common/utils/utils.hpp" -#include - #include #include #include @@ -32,11 +31,6 @@ namespace behavior_path_planner::helper::avoidance using behavior_path_planner::PathShifter; using behavior_path_planner::PlannerData; -using motion_utils::calcDecelDistWithJerkAndAccConstraints; -using motion_utils::calcLongitudinalOffsetPose; -using motion_utils::calcSignedArcLength; -using motion_utils::findNearestIndex; -using tier4_autoware_utils::getPose; class AvoidanceHelper { @@ -181,14 +175,14 @@ class AvoidanceHelper double getShift(const Point & p) const { validate(); - const auto idx = findNearestIndex(prev_reference_path_.points, p); + const auto idx = motion_utils::findNearestIndex(prev_reference_path_.points, p); return prev_spline_shift_path_.shift_length.at(idx); } double getLinearShift(const Point & p) const { validate(); - const auto idx = findNearestIndex(prev_reference_path_.points, p); + const auto idx = motion_utils::findNearestIndex(prev_reference_path_.points, p); return prev_linear_shift_path_.shift_length.at(idx); } @@ -282,8 +276,8 @@ class AvoidanceHelper } const auto start_idx = data_->findEgoIndex(path.points); - const auto distance = - calcSignedArcLength(path.points, start_idx, max_v_point_.value().first.position); + const auto distance = motion_utils::calcSignedArcLength( + path.points, start_idx, max_v_point_.value().first.position); return std::make_pair(distance, max_v_point_.value().second); } @@ -294,7 +288,7 @@ class AvoidanceHelper const auto & a_now = data_->self_acceleration->accel.accel.linear.x; const auto & a_lim = use_hard_constraints ? p->max_deceleration : p->nominal_deceleration; const auto & j_lim = use_hard_constraints ? p->max_jerk : p->nominal_jerk; - const auto ret = calcDecelDistWithJerkAndAccConstraints( + const auto ret = motion_utils::calcDecelDistWithJerkAndAccConstraints( getEgoSpeed(), target_velocity, a_now, a_lim, j_lim, -1.0 * j_lim); if (!!ret) { @@ -343,6 +337,20 @@ class AvoidanceHelper parameters_->closest_distance_to_wait_and_see_for_ambiguous_vehicle; } + static bool isAbsolutelyNotAvoidable(const ObjectData & object) + { + if (object.is_avoidable) { + return false; + } + + // can avoid it after deceleration. + if (object.info == ObjectInfo::NEED_DECELERATION) { + return false; + } + + return true; + } + bool isReady(const AvoidLineArray & new_shift_lines, const double current_shift_length) const { if (std::abs(current_shift_length) < 1e-3) { @@ -427,14 +435,15 @@ class AvoidanceHelper const auto x_max_accel = v_neg_jerk * t_max_accel + p->max_acceleration * std::pow(t_max_accel, 2.0) / 2.0; - const auto point = - calcLongitudinalOffsetPose(path.points, getEgoPosition(), x_neg_jerk + x_max_accel); + const auto point = motion_utils::calcLongitudinalOffsetPose( + path.points, getEgoPosition(), x_neg_jerk + x_max_accel); if (point.has_value()) { max_v_point_ = std::make_pair(point.value(), v_max); return; } - const auto x_end = calcSignedArcLength(path.points, getEgoPosition(), path.points.size() - 1); + const auto x_end = + motion_utils::calcSignedArcLength(path.points, getEgoPosition(), path.points.size() - 1); const auto t_end = (std::sqrt(v0 * v0 + 2.0 * p->max_acceleration * x_end) - v0) / p->max_acceleration; const auto v_end = v0 + p->max_acceleration * t_end; diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/parameter_helper.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/parameter_helper.hpp index 6dbf52c0425fb..25101537850ae 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/parameter_helper.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/parameter_helper.hpp @@ -131,6 +131,11 @@ AvoidanceParameters getParameter(rclcpp::Node * node) getOrDeclareParameter(*node, ns + "min_road_shoulder_width"); } + { + const std::string ns = "avoidance.target_filtering.merging_vehicle."; + p.th_overhang_distance = getOrDeclareParameter(*node, ns + "th_overhang_distance"); + } + { const std::string ns = "avoidance.target_filtering.avoidance_for_ambiguous_vehicle."; p.enable_avoidance_for_ambiguous_vehicle = getOrDeclareParameter(*node, ns + "enable"); @@ -379,7 +384,6 @@ AvoidanceParameters getParameter(rclcpp::Node * node) { const std::string ns = "avoidance.debug."; p.publish_debug_marker = getOrDeclareParameter(*node, ns + "marker"); - p.print_debug_info = getOrDeclareParameter(*node, ns + "console"); } return p; diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/scene.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/scene.hpp index 899ec99cb0d3b..6b11d490e8c23 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/scene.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/scene.hpp @@ -18,6 +18,7 @@ #include "behavior_path_avoidance_module/data_structs.hpp" #include "behavior_path_avoidance_module/helper.hpp" #include "behavior_path_avoidance_module/shift_line_generator.hpp" +#include "behavior_path_avoidance_module/type_alias.hpp" #include "behavior_path_planner_common/interface/scene_module_interface.hpp" #include "behavior_path_planner_common/interface/scene_module_visitor.hpp" @@ -25,12 +26,6 @@ #include #include -#include -#include -#include -#include -#include - #include #include #include @@ -39,12 +34,8 @@ namespace behavior_path_planner { -using motion_utils::calcSignedArcLength; -using motion_utils::findNearestIndex; - -using tier4_planning_msgs::msg::AvoidanceDebugMsg; - using helper::avoidance::AvoidanceHelper; +using tier4_planning_msgs::msg::AvoidanceDebugMsg; class AvoidanceModule : public SceneModuleInterface { @@ -86,15 +77,17 @@ class AvoidanceModule : public SceneModuleInterface { if (candidate.lateral_shift > 0.0) { rtc_interface_ptr_map_.at("left")->updateCooperateStatus( - uuid_map_.at("left"), isExecutionReady(), candidate.start_distance_to_path_change, - candidate.finish_distance_to_path_change, clock_->now()); + uuid_map_.at("left"), isExecutionReady(), State::WAITING_FOR_EXECUTION, + candidate.start_distance_to_path_change, candidate.finish_distance_to_path_change, + clock_->now()); candidate_uuid_ = uuid_map_.at("left"); return; } if (candidate.lateral_shift < 0.0) { rtc_interface_ptr_map_.at("right")->updateCooperateStatus( - uuid_map_.at("right"), isExecutionReady(), candidate.start_distance_to_path_change, - candidate.finish_distance_to_path_change, clock_->now()); + uuid_map_.at("right"), isExecutionReady(), State::WAITING_FOR_EXECUTION, + candidate.start_distance_to_path_change, candidate.finish_distance_to_path_change, + clock_->now()); candidate_uuid_ = uuid_map_.at("right"); return; } @@ -114,10 +107,10 @@ class AvoidanceModule : public SceneModuleInterface for (const auto & left_shift : left_shift_array_) { const double start_distance = - calcSignedArcLength(path.points, ego_idx, left_shift.start_pose.position); + motion_utils::calcSignedArcLength(path.points, ego_idx, left_shift.start_pose.position); const double finish_distance = start_distance + left_shift.relative_longitudinal; rtc_interface_ptr_map_.at("left")->updateCooperateStatus( - left_shift.uuid, true, start_distance, finish_distance, clock_->now()); + left_shift.uuid, true, State::RUNNING, start_distance, finish_distance, clock_->now()); if (finish_distance > -1.0e-03) { steering_factor_interface_ptr_->updateSteeringFactor( {left_shift.start_pose, left_shift.finish_pose}, {start_distance, finish_distance}, @@ -127,10 +120,10 @@ class AvoidanceModule : public SceneModuleInterface for (const auto & right_shift : right_shift_array_) { const double start_distance = - calcSignedArcLength(path.points, ego_idx, right_shift.start_pose.position); + motion_utils::calcSignedArcLength(path.points, ego_idx, right_shift.start_pose.position); const double finish_distance = start_distance + right_shift.relative_longitudinal; rtc_interface_ptr_map_.at("right")->updateCooperateStatus( - right_shift.uuid, true, start_distance, finish_distance, clock_->now()); + right_shift.uuid, true, State::RUNNING, start_distance, finish_distance, clock_->now()); if (finish_distance > -1.0e-03) { steering_factor_interface_ptr_->updateSteeringFactor( {right_shift.start_pose, right_shift.finish_pose}, {start_distance, finish_distance}, @@ -424,9 +417,6 @@ class AvoidanceModule : public SceneModuleInterface // TODO(Satoshi OTA) create detected object manager. ObjectDataArray registered_objects_; - // TODO(Satoshi OTA) remove mutable. - mutable ObjectDataArray detected_objects_; - // TODO(Satoshi OTA) remove this variable. mutable ObjectDataArray ego_stopped_objects_; diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/shift_line_generator.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/shift_line_generator.hpp index efdda622a664c..e721401207830 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/shift_line_generator.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/shift_line_generator.hpp @@ -17,6 +17,7 @@ #include "behavior_path_avoidance_module/data_structs.hpp" #include "behavior_path_avoidance_module/helper.hpp" +#include "behavior_path_avoidance_module/type_alias.hpp" #include "behavior_path_planner_common/utils/path_shifter/path_shifter.hpp" #include diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/type_alias.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/type_alias.hpp new file mode 100644 index 0000000000000..67bca3099df6f --- /dev/null +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/type_alias.hpp @@ -0,0 +1,74 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef BEHAVIOR_PATH_AVOIDANCE_MODULE__TYPE_ALIAS_HPP_ +#define BEHAVIOR_PATH_AVOIDANCE_MODULE__TYPE_ALIAS_HPP_ + +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include + +namespace behavior_path_planner +{ +// auto msgs +using autoware_auto_perception_msgs::msg::PredictedObject; +using autoware_auto_perception_msgs::msg::PredictedPath; +using autoware_auto_planning_msgs::msg::PathWithLaneId; + +// ROS 2 general msgs +using geometry_msgs::msg::Point; +using geometry_msgs::msg::Pose; +using geometry_msgs::msg::TransformStamped; +using geometry_msgs::msg::Vector3; +using std_msgs::msg::ColorRGBA; +using visualization_msgs::msg::Marker; +using visualization_msgs::msg::MarkerArray; + +// tier4 msgs +using tier4_planning_msgs::msg::AvoidanceDebugMsg; +using tier4_planning_msgs::msg::AvoidanceDebugMsgArray; +using tier4_rtc_msgs::msg::State; + +// tier4 utils functions +using tier4_autoware_utils::appendMarkerArray; +using tier4_autoware_utils::calcDistance2d; +using tier4_autoware_utils::calcLateralDeviation; +using tier4_autoware_utils::calcOffsetPose; +using tier4_autoware_utils::calcYawDeviation; +using tier4_autoware_utils::createDefaultMarker; +using tier4_autoware_utils::createMarkerColor; +using tier4_autoware_utils::createMarkerScale; +using tier4_autoware_utils::createPoint; +using tier4_autoware_utils::createQuaternionFromRPY; +using tier4_autoware_utils::getPoint; +using tier4_autoware_utils::getPose; +using tier4_autoware_utils::Point2d; +using tier4_autoware_utils::Polygon2d; +using tier4_autoware_utils::pose2transform; +using tier4_autoware_utils::toHexString; +} // namespace behavior_path_planner + +#endif // BEHAVIOR_PATH_AVOIDANCE_MODULE__TYPE_ALIAS_HPP_ diff --git a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/utils.hpp b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/utils.hpp index 3f1d3495e51cb..cf68f577ed7c0 100644 --- a/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/utils.hpp +++ b/planning/behavior_path_avoidance_module/include/behavior_path_avoidance_module/utils.hpp @@ -25,12 +25,16 @@ namespace behavior_path_planner::utils::avoidance { + using behavior_path_planner::PlannerData; using behavior_path_planner::utils::path_safety_checker::ExtendedPredictedObject; using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityAndPolygonStamped; using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityStamped; using behavior_path_planner::utils::path_safety_checker::PredictedPathWithPolygon; +static constexpr const char * logger_namespace = + "planning.scenario_planning.lane_driving.behavior_planning.behavior_path_planner.avoidance.utils"; + bool isOnRight(const ObjectData & obj); double calcShiftLength( @@ -112,8 +116,6 @@ void fillObjectStoppableJudge( ObjectData & object_data, const ObjectDataArray & registered_objects, const double feasible_stop_distance, const std::shared_ptr & parameters); -void fillInitialPose(ObjectData & object_data, ObjectDataArray & detected_objects); - void updateRegisteredObject( ObjectDataArray & registered_objects, const ObjectDataArray & now_objects, const std::shared_ptr & parameters); diff --git a/planning/behavior_path_avoidance_module/package.xml b/planning/behavior_path_avoidance_module/package.xml index fc34172bb2ce9..5f0a658735b2f 100644 --- a/planning/behavior_path_avoidance_module/package.xml +++ b/planning/behavior_path_avoidance_module/package.xml @@ -13,6 +13,7 @@ Tomoya Kimura Shumpei Wakabayashi Tomohito Ando + Go Sakayori Apache License 2.0 diff --git a/planning/behavior_path_avoidance_module/schema/avoidance.schema.json b/planning/behavior_path_avoidance_module/schema/avoidance.schema.json index 79882beb805f8..7c0205d2473e5 100644 --- a/planning/behavior_path_avoidance_module/schema/avoidance.schema.json +++ b/planning/behavior_path_avoidance_module/schema/avoidance.schema.json @@ -681,6 +681,18 @@ ], "additionalProperties": false }, + "merging_vehicle": { + "type": "object", + "properties": { + "th_overhang_distance": { + "type": "number", + "description": "Distance threshold to ignore merging/deviating vehicle to/from ego driving lane. The distance represents how the object polygon overlaps ego lane, and it's calculated from polygon overhang point and lane centerline. If the distance is more than this param, the module never avoid the object. (Basically, the ego stops behind of it.)", + "default": 0.5 + } + }, + "required": ["th_overhang_distance"], + "additionalProperties": false + }, "parked_vehicle": { "type": "object", "properties": { @@ -803,6 +815,7 @@ "object_check_return_pose_distance", "max_compensation_time", "detection_area", + "merging_vehicle", "parked_vehicle", "avoidance_for_ambiguous_vehicle", "intersection" @@ -1379,14 +1392,9 @@ "type": "boolean", "description": "Publish debug marker.", "default": "false" - }, - "console": { - "type": "boolean", - "description": "Output debug info on console.", - "default": "false" } }, - "required": ["marker", "console"], + "required": ["marker"], "additionalProperties": false } }, diff --git a/planning/behavior_path_avoidance_module/src/debug.cpp b/planning/behavior_path_avoidance_module/src/debug.cpp index 7d029277fcbc4..65450c143ccda 100644 --- a/planning/behavior_path_avoidance_module/src/debug.cpp +++ b/planning/behavior_path_avoidance_module/src/debug.cpp @@ -19,26 +19,12 @@ #include #include -#include - -#include #include #include -namespace marker_utils::avoidance_marker +namespace behavior_path_planner::utils::avoidance { - -using tier4_autoware_utils::appendMarkerArray; -using tier4_autoware_utils::calcDistance2d; -using tier4_autoware_utils::calcOffsetPose; -using tier4_autoware_utils::createDefaultMarker; -using tier4_autoware_utils::createMarkerColor; -using tier4_autoware_utils::createMarkerScale; -using tier4_autoware_utils::createPoint; -using tier4_autoware_utils::getPose; -using visualization_msgs::msg::Marker; - namespace { @@ -176,7 +162,8 @@ MarkerArray createObjectInfoMarkerArray(const ObjectDataArray & objects, std::st marker.id = uuidToInt32(object.object.object_id); marker.pose.position.z += 2.0; std::ostringstream string_stream; - string_stream << object.reason << (object.is_parked ? "(PARKED)" : ""); + string_stream << magic_enum::enum_name(object.info) << (object.is_parked ? "(PARKED)" : ""); + string_stream << (object.is_ambiguous ? "(WAIT AND SEE)" : ""); marker.text = string_stream.str(); marker.color = createMarkerColor(1.0, 1.0, 1.0, 0.999); marker.scale = createMarkerScale(0.6, 0.6, 0.6); @@ -441,14 +428,12 @@ MarkerArray createTargetObjectsMarkerArray(const ObjectDataArray & objects, cons return msg; } -MarkerArray createOtherObjectsMarkerArray(const ObjectDataArray & objects, const std::string & ns) +MarkerArray createOtherObjectsMarkerArray(const ObjectDataArray & objects, const ObjectInfo & info) { - using behavior_path_planner::utils::convertToSnakeCase; - - const auto filtered_objects = [&objects, &ns]() { + const auto filtered_objects = [&objects, &info]() { ObjectDataArray ret{}; for (const auto & o : objects) { - if (o.reason != ns) { + if (o.info != info) { continue; } ret.push_back(o); @@ -460,18 +445,20 @@ MarkerArray createOtherObjectsMarkerArray(const ObjectDataArray & objects, const MarkerArray msg; msg.markers.reserve(filtered_objects.size() * 2); + std::ostringstream string_stream; + string_stream << magic_enum::enum_name(info); + + std::string ns = string_stream.str(); + transform(ns.begin(), ns.end(), ns.begin(), tolower); + appendMarkerArray( createObjectsCubeMarkerArray( - filtered_objects, "others_" + convertToSnakeCase(ns) + "_cube", - createMarkerScale(3.0, 1.5, 1.5), createMarkerColor(0.0, 1.0, 0.0, 0.8)), - &msg); - appendMarkerArray( - createObjectInfoMarkerArray(filtered_objects, "others_" + convertToSnakeCase(ns) + "_info"), + filtered_objects, "others_" + ns + "_cube", createMarkerScale(3.0, 1.5, 1.5), + createMarkerColor(0.0, 1.0, 0.0, 0.8)), &msg); + appendMarkerArray(createObjectInfoMarkerArray(filtered_objects, "others_" + ns + "_info"), &msg); appendMarkerArray( - createOverhangLaneletMarkerArray( - filtered_objects, "others_" + convertToSnakeCase(ns) + "_overhang_lanelet"), - &msg); + createOverhangLaneletMarkerArray(filtered_objects, "others_" + ns + "_overhang_lanelet"), &msg); return msg; } @@ -528,7 +515,6 @@ MarkerArray createDebugMarkerArray( using marker_utils::showPolygon; using marker_utils::showPredictedPath; using marker_utils::showSafetyCheckInfo; - using tier4_planning_msgs::msg::AvoidanceDebugFactor; const auto current_time = rclcpp::Clock{RCL_ROS_TIME}.now(); MarkerArray msg; @@ -564,23 +550,22 @@ MarkerArray createDebugMarkerArray( // ignore objects { - addObjects(data.other_objects, AvoidanceDebugFactor::OBJECT_IS_BEHIND_THRESHOLD); - addObjects(data.other_objects, AvoidanceDebugFactor::OBJECT_IS_IN_FRONT_THRESHOLD); - addObjects(data.other_objects, AvoidanceDebugFactor::OBJECT_IS_NOT_TYPE); - addObjects(data.other_objects, AvoidanceDebugFactor::OBJECT_BEHIND_PATH_GOAL); - addObjects(data.other_objects, AvoidanceDebugFactor::TOO_NEAR_TO_CENTERLINE); - addObjects(data.other_objects, AvoidanceDebugFactor::NOT_PARKING_OBJECT); - addObjects(data.other_objects, std::string("MovingObject")); - addObjects(data.other_objects, std::string("CrosswalkUser")); - addObjects(data.other_objects, std::string("OutOfTargetArea")); - addObjects(data.other_objects, std::string("NotNeedAvoidance")); - addObjects(data.other_objects, std::string("LessThanExecutionThreshold")); - addObjects(data.other_objects, std::string("TooNearToGoal")); - addObjects(data.other_objects, std::string("ParallelToEgoLane")); - addObjects(data.other_objects, std::string("MergingToEgoLane")); - addObjects(data.other_objects, std::string("UnstableObject")); - addObjects(data.other_objects, std::string("AmbiguousStoppedVehicle")); - addObjects(data.other_objects, std::string("AmbiguousStoppedVehicle(wait-and-see)")); + addObjects(data.other_objects, ObjectInfo::FURTHER_THAN_THRESHOLD); + addObjects(data.other_objects, ObjectInfo::IS_NOT_TARGET_OBJECT); + addObjects(data.other_objects, ObjectInfo::FURTHER_THAN_GOAL); + addObjects(data.other_objects, ObjectInfo::TOO_NEAR_TO_CENTERLINE); + addObjects(data.other_objects, ObjectInfo::IS_NOT_PARKING_OBJECT); + addObjects(data.other_objects, ObjectInfo::MOVING_OBJECT); + addObjects(data.other_objects, ObjectInfo::CROSSWALK_USER); + addObjects(data.other_objects, ObjectInfo::OUT_OF_TARGET_AREA); + addObjects(data.other_objects, ObjectInfo::ENOUGH_LATERAL_DISTANCE); + addObjects(data.other_objects, ObjectInfo::LESS_THAN_EXECUTION_THRESHOLD); + addObjects(data.other_objects, ObjectInfo::TOO_NEAR_TO_GOAL); + addObjects(data.other_objects, ObjectInfo::PARALLEL_TO_EGO_LANE); + addObjects(data.other_objects, ObjectInfo::MERGING_TO_EGO_LANE); + addObjects(data.other_objects, ObjectInfo::DEVIATING_FROM_EGO_LANE); + addObjects(data.other_objects, ObjectInfo::UNSTABLE_OBJECT); + addObjects(data.other_objects, ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE); } // shift line pre-process @@ -653,7 +638,7 @@ MarkerArray createDebugMarkerArray( return msg; } -} // namespace marker_utils::avoidance_marker +} // namespace behavior_path_planner::utils::avoidance std::string toStrInfo(const behavior_path_planner::ShiftLineArray & sl_arr) { diff --git a/planning/behavior_path_avoidance_module/src/manager.cpp b/planning/behavior_path_avoidance_module/src/manager.cpp index e3391f251e55f..7772bd9c2ad35 100644 --- a/planning/behavior_path_avoidance_module/src/manager.cpp +++ b/planning/behavior_path_avoidance_module/src/manager.cpp @@ -124,6 +124,11 @@ void AvoidanceModuleManager::updateModuleParams(const std::vector(parameters, ns + "backward_distance", p->object_check_backward_distance); } + { + const std::string ns = "avoidance.target_filtering.merging_vehicle."; + updateParam(parameters, ns + "th_overhang_distance", p->th_overhang_distance); + } + { const std::string ns = "avoidance.avoidance.lateral.avoidance_for_ambiguous_vehicle."; updateParam(parameters, ns + "enable", p->enable_avoidance_for_ambiguous_vehicle); @@ -257,7 +262,6 @@ void AvoidanceModuleManager::updateModuleParams(const std::vector(parameters, ns + "marker", p->publish_debug_marker); - updateParam(parameters, ns + "console", p->print_debug_info); } std::for_each(observers_.begin(), observers_.end(), [&p](const auto & observer) { diff --git a/planning/behavior_path_avoidance_module/src/scene.cpp b/planning/behavior_path_avoidance_module/src/scene.cpp index b16395f825385..6858b3809a73b 100644 --- a/planning/behavior_path_avoidance_module/src/scene.cpp +++ b/planning/behavior_path_avoidance_module/src/scene.cpp @@ -26,12 +26,6 @@ #include #include -#include -#include -#include - -#include "tier4_planning_msgs/msg/detail/avoidance_debug_msg_array__struct.hpp" -#include #include #include @@ -40,26 +34,8 @@ #include #include -// set as macro so that calling function name will be printed. -// debug print is heavy. turn on only when debugging. -#define DEBUG_PRINT(...) \ - RCLCPP_DEBUG_EXPRESSION(getLogger(), parameters_->print_debug_info, __VA_ARGS__) -#define printShiftLines(p, msg) DEBUG_PRINT("[%s] %s", msg, toStrInfo(p).c_str()) - namespace behavior_path_planner { - -using motion_utils::calcLongitudinalOffsetPose; -using motion_utils::calcSignedArcLength; -using motion_utils::findNearestIndex; -using tier4_autoware_utils::appendMarkerArray; -using tier4_autoware_utils::calcDistance2d; -using tier4_autoware_utils::calcLateralDeviation; -using tier4_autoware_utils::getPoint; -using tier4_autoware_utils::getPose; -using tier4_autoware_utils::toHexString; -using tier4_planning_msgs::msg::AvoidanceDebugFactor; - namespace { bool isDrivingSameLane( @@ -109,7 +85,7 @@ AvoidanceModule::AvoidanceModule( bool AvoidanceModule::isExecutionRequested() const { - DEBUG_PRINT("AVOIDANCE isExecutionRequested"); + RCLCPP_DEBUG(getLogger(), "AVOIDANCE isExecutionRequested"); // Check ego is in preferred lane updateInfoMarker(avoid_data_); @@ -125,23 +101,25 @@ bool AvoidanceModule::isExecutionRequested() const } return std::any_of( - avoid_data_.target_objects.begin(), avoid_data_.target_objects.end(), [](const auto & o) { - return o.is_avoidable || o.reason == AvoidanceDebugFactor::TOO_LARGE_JERK; - }); + avoid_data_.target_objects.begin(), avoid_data_.target_objects.end(), + [this](const auto & o) { return !helper_->isAbsolutelyNotAvoidable(o); }); } bool AvoidanceModule::isExecutionReady() const { - DEBUG_PRINT("AVOIDANCE isExecutionReady"); + RCLCPP_DEBUG_STREAM(getLogger(), "---Avoidance GO/NO-GO status---"); + RCLCPP_DEBUG_STREAM(getLogger(), std::boolalpha << "SAFE:" << avoid_data_.safe); + RCLCPP_DEBUG_STREAM(getLogger(), std::boolalpha << "COMFORTABLE:" << avoid_data_.comfortable); + RCLCPP_DEBUG_STREAM(getLogger(), std::boolalpha << "VALID:" << avoid_data_.valid); + RCLCPP_DEBUG_STREAM(getLogger(), std::boolalpha << "READY:" << avoid_data_.ready); return avoid_data_.safe && avoid_data_.comfortable && avoid_data_.valid && avoid_data_.ready; } bool AvoidanceModule::isSatisfiedSuccessCondition(const AvoidancePlanningData & data) const { - const bool has_avoidance_target = - std::any_of(data.target_objects.begin(), data.target_objects.end(), [](const auto & o) { - return o.is_avoidable || o.reason == AvoidanceDebugFactor::TOO_LARGE_JERK; - }); + const bool has_avoidance_target = std::any_of( + data.target_objects.begin(), data.target_objects.end(), + [this](const auto & o) { return !helper_->isAbsolutelyNotAvoidable(o); }); if (has_avoidance_target) { return false; @@ -287,7 +265,7 @@ void AvoidanceModule::fillFundamentalData(AvoidancePlanningData & data, DebugDat // arclength from ego pose (used in many functions) data.arclength_from_ego = utils::calcPathArcLengthArray( data.reference_path, 0, data.reference_path.points.size(), - calcSignedArcLength(data.reference_path.points, getEgoPosition(), 0)); + motion_utils::calcSignedArcLength(data.reference_path.points, getEgoPosition(), 0)); data.to_return_point = utils::avoidance::calcDistanceToReturnDeadLine( data.current_lanelets, data.reference_path_rough, planner_data_, parameters_); @@ -339,7 +317,7 @@ void AvoidanceModule::fillAvoidanceTargetObjects( for (const auto & object : object_outside_target_lane.objects) { ObjectData other_object = createObjectData(data, object); - other_object.reason = "OutOfTargetArea"; + other_object.info = ObjectInfo::OUT_OF_TARGET_AREA; data.other_objects.push_back(other_object); } @@ -369,8 +347,6 @@ void AvoidanceModule::fillAvoidanceTargetObjects( debug_info.object_id = toHexString(o.object.object_id); debug_info.longitudinal_distance = o.longitudinal; debug_info.lateral_distance_from_centerline = o.to_centerline; - debug_info.allow_avoidance = o.reason == ""; - debug_info.failed_reason = o.reason; debug_info_array.push_back(debug_info); }; @@ -387,7 +363,8 @@ ObjectData AvoidanceModule::createObjectData( const auto & path_points = data.reference_path.points; const auto & object_pose = object.kinematics.initial_pose_with_covariance.pose; - const auto object_closest_index = findNearestIndex(path_points, object_pose.position); + const auto object_closest_index = + motion_utils::findNearestIndex(path_points, object_pose.position); const auto object_closest_pose = path_points.at(object_closest_index).point.pose; const auto object_type = utils::getHighestProbLabel(object.classification); const auto object_parameter = parameters_->object_parameters.at(object_type); @@ -412,9 +389,6 @@ ObjectData AvoidanceModule::createObjectData( // Calc moving time. utils::avoidance::fillObjectMovingTime(object_data, stopped_objects_, parameters_); - // Fill init pose. - utils::avoidance::fillInitialPose(object_data, detected_objects_); - // Calc lateral deviation from path to target object. object_data.direction = calcLateralDeviation(object_closest_pose, object_pose.position) > 0.0 ? Direction::LEFT @@ -435,7 +409,7 @@ bool AvoidanceModule::canYieldManeuver(const AvoidancePlanningData & data) const const auto registered_lines = path_shifter_.getShiftLines(); if (!registered_lines.empty()) { const size_t idx = planner_data_->findEgoIndex(path_shifter_.getReferencePath().points); - const auto to_shift_start_point = calcSignedArcLength( + const auto to_shift_start_point = motion_utils::calcSignedArcLength( path_shifter_.getReferencePath().points, idx, registered_lines.front().start_idx); if (to_shift_start_point < helper_->getMinimumPrepareDistance()) { RCLCPP_DEBUG( @@ -535,12 +509,11 @@ void AvoidanceModule::fillEgoStatus( * if the both of following two conditions are satisfied, the module surely avoid the object. * Condition1: there is risk to collide with object without avoidance. * Condition2: there is enough space to avoid. - * In TOO_LARGE_JERK condition, it is possible to avoid object by deceleration even if the flag + * In NEED_DECELERATION condition, it is possible to avoid object by deceleration even if the flag * is_avoidable is FALSE. So, the module inserts stop point for such a object. */ for (const auto & o : data.target_objects) { - const auto enough_space = o.is_avoidable || o.reason == AvoidanceDebugFactor::TOO_LARGE_JERK; - if (o.avoid_required && enough_space) { + if (o.avoid_required && !helper_->isAbsolutelyNotAvoidable(o)) { data.avoid_required = true; data.stop_target_object = o; data.to_stop_line = o.to_stop_line; @@ -652,7 +625,7 @@ void AvoidanceModule::fillDebugData( const auto prepare_distance = helper_->getNominalPrepareDistance(); const auto total_avoid_distance = prepare_distance + avoidance_distance + constant_distance; - dead_pose_ = calcLongitudinalOffsetPose( + dead_pose_ = motion_utils::calcLongitudinalOffsetPose( data.reference_path.points, getEgoPosition(), o_front.longitudinal - total_avoid_distance); if (!dead_pose_) { @@ -839,8 +812,8 @@ PathWithLaneId AvoidanceModule::extendBackwardLength(const PathWithLaneId & orig return a.start_idx < b.start_idx; }); return std::max( - max_dist, - calcSignedArcLength(previous_path.points, lines.front().start.position, getEgoPosition())); + max_dist, motion_utils::calcSignedArcLength( + previous_path.points, lines.front().start.position, getEgoPosition())); }(); const auto extra_margin = 10.0; // Since distance does not consider arclength, but just line. @@ -857,7 +830,9 @@ PathWithLaneId AvoidanceModule::extendBackwardLength(const PathWithLaneId & orig size_t clip_idx = 0; for (size_t i = 0; i < prev_ego_idx; ++i) { - if (backward_length > calcSignedArcLength(previous_path.points, clip_idx, *prev_ego_idx)) { + if ( + backward_length > + motion_utils::calcSignedArcLength(previous_path.points, clip_idx, *prev_ego_idx)) { break; } clip_idx = i; @@ -1139,7 +1114,7 @@ void AvoidanceModule::addNewShiftLines( const auto new_shift_length = front_new_shift_line.end_shift_length; const auto new_shift_end_idx = front_new_shift_line.end_idx; - DEBUG_PRINT("min_start_idx = %lu", min_start_idx); + RCLCPP_DEBUG(getLogger(), "min_start_idx = %lu", min_start_idx); // Remove shift points that starts later than the new_shift_line from path_shifter. // @@ -1152,8 +1127,9 @@ void AvoidanceModule::addNewShiftLines( // farther avoidance. for (const auto & sl : current_shift_lines) { if (sl.start_idx >= min_start_idx) { - DEBUG_PRINT( - "sl.start_idx = %lu, this sl starts after new proposal. remove this one.", sl.start_idx); + RCLCPP_DEBUG( + getLogger(), "sl.start_idx = %lu, this sl starts after new proposal. remove this one.", + sl.start_idx); continue; } @@ -1171,7 +1147,7 @@ void AvoidanceModule::addNewShiftLines( } } - DEBUG_PRINT("sl.start_idx = %lu, no conflict. keep this one.", sl.start_idx); + RCLCPP_DEBUG(getLogger(), "sl.start_idx = %lu, no conflict. keep this one.", sl.start_idx); future.push_back(sl); } @@ -1374,7 +1350,7 @@ void AvoidanceModule::updateRTCData() void AvoidanceModule::updateInfoMarker(const AvoidancePlanningData & data) const { - using marker_utils::avoidance_marker::createTargetObjectsMarkerArray; + using utils::avoidance::createTargetObjectsMarkerArray; info_marker_.markers.clear(); appendMarkerArray( @@ -1390,7 +1366,7 @@ void AvoidanceModule::updateDebugMarker( return; } - debug_marker_ = marker_utils::avoidance_marker::createDebugMarkerArray(data, shifter, debug); + debug_marker_ = utils::avoidance::createDebugMarkerArray(data, shifter, debug); } void AvoidanceModule::updateAvoidanceDebugData( @@ -1469,7 +1445,7 @@ void AvoidanceModule::insertReturnDeadLine( // Consider the difference in path length between the shifted path and original path (the path // that is shifted inward has a shorter distance to the end of the path than the other one.) const auto & to_reference_path_end = data.arclength_from_ego.back(); - const auto to_shifted_path_end = calcSignedArcLength( + const auto to_shifted_path_end = motion_utils::calcSignedArcLength( shifted_path.path.points, getEgoPosition(), shifted_path.path.points.size() - 1); const auto buffer = std::max(0.0, to_shifted_path_end - to_reference_path_end); @@ -1506,7 +1482,8 @@ void AvoidanceModule::insertReturnDeadLine( const auto start_idx = planner_data_->findEgoIndex(shifted_path.path.points); for (size_t i = start_idx; i < shifted_path.path.points.size(); ++i) { - const auto distance_from_ego = calcSignedArcLength(shifted_path.path.points, start_idx, i); + const auto distance_from_ego = + motion_utils::calcSignedArcLength(shifted_path.path.points, start_idx, i); // slow down speed is inserted only in front of the object. const auto shift_longitudinal_distance = to_stop_line - distance_from_ego; @@ -1600,7 +1577,7 @@ void AvoidanceModule::insertStopPoint( }(); const auto stop_distance = - calcSignedArcLength(shifted_path.path.points, getEgoPosition(), stop_idx); + motion_utils::calcSignedArcLength(shifted_path.path.points, getEgoPosition(), stop_idx); // If we don't need to consider deceleration constraints, insert a deceleration point // and return immediately @@ -1671,9 +1648,7 @@ void AvoidanceModule::insertPrepareVelocity(ShiftedPath & shifted_path) const return; } - const auto enough_space = - object.value().is_avoidable || object.value().reason == AvoidanceDebugFactor::TOO_LARGE_JERK; - if (!enough_space) { + if (helper_->isAbsolutelyNotAvoidable(object.value())) { return; } @@ -1713,7 +1688,8 @@ void AvoidanceModule::insertPrepareVelocity(ShiftedPath & shifted_path) const const auto start_idx = planner_data_->findEgoIndex(shifted_path.path.points); for (size_t i = start_idx; i < shifted_path.path.points.size(); ++i) { - const auto distance_from_ego = calcSignedArcLength(shifted_path.path.points, start_idx, i); + const auto distance_from_ego = + motion_utils::calcSignedArcLength(shifted_path.path.points, start_idx, i); // slow down speed is inserted only in front of the object. const auto shift_longitudinal_distance = distance_to_object - distance_from_ego; @@ -1756,7 +1732,8 @@ void AvoidanceModule::insertAvoidanceVelocity(ShiftedPath & shifted_path) const const auto start_idx = planner_data_->findEgoIndex(shifted_path.path.points); for (size_t i = start_idx; i < shifted_path.path.points.size(); ++i) { - const auto distance_from_ego = calcSignedArcLength(shifted_path.path.points, start_idx, i); + const auto distance_from_ego = + motion_utils::calcSignedArcLength(shifted_path.path.points, start_idx, i); // slow down speed is inserted only in front of the object. const auto accel_distance = distance_to_accel_end_point - distance_from_ego; diff --git a/planning/behavior_path_avoidance_module/src/shift_line_generator.cpp b/planning/behavior_path_avoidance_module/src/shift_line_generator.cpp index 9137048945fa1..84b2b9b61a702 100644 --- a/planning/behavior_path_avoidance_module/src/shift_line_generator.cpp +++ b/planning/behavior_path_avoidance_module/src/shift_line_generator.cpp @@ -17,17 +17,9 @@ #include "behavior_path_avoidance_module/utils.hpp" #include "behavior_path_planner_common/utils/utils.hpp" -#include - -#include - namespace behavior_path_planner::utils::avoidance { -using tier4_autoware_utils::generateUUID; -using tier4_autoware_utils::getPoint; -using tier4_planning_msgs::msg::AvoidanceDebugFactor; - namespace { bool isBestEffort(const std::string & policy) @@ -182,7 +174,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( // prepare distance is not enough. unavoidable. if (avoidance_distance < 1e-3) { - object.reason = AvoidanceDebugFactor::REMAINING_DISTANCE_LESS_THAN_ZERO; + object.info = ObjectInfo::INSUFFICIENT_LONGITUDINAL_DISTANCE; return std::nullopt; } @@ -200,10 +192,10 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( // avoidance distance is not enough. unavoidable. if (!isBestEffort(parameters_->policy_deceleration)) { if (avoidance_distance < helper_->getMinAvoidanceDistance(avoiding_shift) + LON_DIST_BUFFER) { - object.reason = AvoidanceDebugFactor::REMAINING_DISTANCE_LESS_THAN_ZERO; + object.info = ObjectInfo::INSUFFICIENT_LONGITUDINAL_DISTANCE; return std::nullopt; } else { - object.reason = AvoidanceDebugFactor::TOO_LARGE_JERK; + object.info = ObjectInfo::NEED_DECELERATION; return std::nullopt; } } @@ -213,7 +205,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( avoidance_distance, helper_->getLateralMaxJerkLimit(), helper_->getAvoidanceEgoSpeed()); if (std::abs(feasible_relative_shift_length) < parameters_->lateral_execution_threshold) { - object.reason = "LessThanExecutionThreshold"; + object.info = ObjectInfo::LESS_THAN_EXECUTION_THRESHOLD; return std::nullopt; } @@ -224,7 +216,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( if ( avoidance_distance < helper_->getMinAvoidanceDistance(feasible_shift_length) + LON_DIST_BUFFER) { - object.reason = AvoidanceDebugFactor::REMAINING_DISTANCE_LESS_THAN_ZERO; + object.info = ObjectInfo::INSUFFICIENT_LONGITUDINAL_DISTANCE; return std::nullopt; } @@ -238,7 +230,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( 0.5 * data_->parameters.vehicle_width + lateral_hard_margin; if (infeasible) { RCLCPP_DEBUG(rclcpp::get_logger(""), "feasible shift length is not enough to avoid. "); - object.reason = AvoidanceDebugFactor::TOO_LARGE_JERK; + object.info = ObjectInfo::NEED_DECELERATION; return std::nullopt; } @@ -254,7 +246,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( AvoidOutlines outlines; for (auto & o : data.target_objects) { if (!o.avoid_margin.has_value()) { - o.reason = AvoidanceDebugFactor::INSUFFICIENT_LATERAL_MARGIN; + o.info = ObjectInfo::INSUFFICIENT_DRIVABLE_SPACE; if (o.avoid_required && is_forward_object(o)) { break; } else { @@ -266,7 +258,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( const auto desire_shift_length = helper_->getShiftLength(o, is_object_on_right, o.avoid_margin.value()); if (utils::avoidance::isSameDirectionShift(is_object_on_right, desire_shift_length)) { - o.reason = AvoidanceDebugFactor::SAME_DIRECTION_SHIFT; + o.info = ObjectInfo::SAME_DIRECTION_SHIFT; if (o.avoid_required && is_forward_object(o)) { break; } else { @@ -377,7 +369,7 @@ AvoidOutlines ShiftLineGenerator::generateAvoidOutline( } else if (is_valid_shift_line(al_avoid) && is_valid_shift_line(al_return)) { outlines.emplace_back(al_avoid, al_return); } else { - o.reason = "InvalidShiftLine"; + o.info = ObjectInfo::INVALID_SHIFT_LINE; continue; } diff --git a/planning/behavior_path_avoidance_module/src/utils.cpp b/planning/behavior_path_avoidance_module/src/utils.cpp index bef3976be7e1e..7ae5a97b77fff 100644 --- a/planning/behavior_path_avoidance_module/src/utils.cpp +++ b/planning/behavior_path_avoidance_module/src/utils.cpp @@ -20,14 +20,8 @@ #include "behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp" #include "behavior_path_planner_common/utils/path_utils.hpp" #include "behavior_path_planner_common/utils/traffic_light_utils.hpp" -#include "tier4_autoware_utils/geometry/boost_polygon_utils.hpp" #include -#include -#include - -#include -#include #include #include @@ -49,21 +43,6 @@ namespace behavior_path_planner::utils::avoidance using autoware_perception_msgs::msg::TrafficSignalElement; using behavior_path_planner::utils::traffic_light::calcDistanceToRedTrafficLight; using behavior_path_planner::utils::traffic_light::getDistanceToNextTrafficLight; -using geometry_msgs::msg::TransformStamped; -using motion_utils::calcLongitudinalOffsetPoint; -using motion_utils::calcSignedArcLength; -using motion_utils::findNearestIndex; -using motion_utils::findNearestSegmentIndex; -using motion_utils::insertTargetPoint; -using tier4_autoware_utils::calcDistance2d; -using tier4_autoware_utils::calcLateralDeviation; -using tier4_autoware_utils::calcOffsetPose; -using tier4_autoware_utils::calcYawDeviation; -using tier4_autoware_utils::createQuaternionFromRPY; -using tier4_autoware_utils::getPose; -using tier4_autoware_utils::pose2transform; -using tier4_planning_msgs::msg::AvoidanceDebugFactor; -using tier4_planning_msgs::msg::AvoidanceDebugMsg; namespace { @@ -418,33 +397,41 @@ bool isParkedVehicle( bool is_left_side_parked_vehicle = false; if (!isOnRight(object)) { - auto [object_shiftable_distance, sub_type] = [&]() { - const auto most_left_road_lanelet = - route_handler->getMostLeftLanelet(object.overhang_lanelet); - const auto most_left_lanelet_candidates = - route_handler->getLaneletMapPtr()->laneletLayer.findUsages( - most_left_road_lanelet.leftBound()); - - lanelet::ConstLanelet most_left_lanelet = most_left_road_lanelet; - const lanelet::Attribute sub_type = - most_left_lanelet.attribute(lanelet::AttributeName::Subtype); - - for (const auto & ll : most_left_lanelet_candidates) { - const lanelet::Attribute sub_type = ll.attribute(lanelet::AttributeName::Subtype); - if (sub_type.value() == "road_shoulder") { - most_left_lanelet = ll; - } + const auto most_left_lanelet = [&]() { + auto same_direction_lane = + route_handler->getMostLeftLanelet(object.overhang_lanelet, true, true); + const lanelet::Attribute & sub_type = + same_direction_lane.attribute(lanelet::AttributeName::Subtype); + if (sub_type == "road_shoulder") { + return same_direction_lane; } - const auto center_to_left_boundary = distance2d( - to2D(most_left_lanelet.leftBound().basicLineString()), - to2D(toLaneletPoint(centerline_pos)).basicPoint()); + const auto opposite_lanes = route_handler->getLeftOppositeLanelets(same_direction_lane); + if (opposite_lanes.empty()) { + return same_direction_lane; + } - return std::make_pair( - center_to_left_boundary - 0.5 * object.object.shape.dimensions.y, sub_type); + return static_cast(opposite_lanes.front().invert()); }(); - if (sub_type.value() != "road_shoulder") { + const auto center_to_left_boundary = distance2d( + to2D(most_left_lanelet.leftBound().basicLineString()), + to2D(toLaneletPoint(centerline_pos)).basicPoint()); + + double object_shiftable_distance = + center_to_left_boundary - 0.5 * object.object.shape.dimensions.y; + + const lanelet::Attribute & sub_type = + most_left_lanelet.attribute(lanelet::AttributeName::Subtype); + if (sub_type == "road_shoulder") { + // assuming it's parked vehicle if its CoG is within road shoulder lanelet. + if (boost::geometry::within( + to2D(toLaneletPoint(object_pos)).basicPoint(), + most_left_lanelet.polygon2d().basicPolygon())) { + return true; + } + } else { + // assuming there is 0.5m road shoulder even if it's not defined explicitly in HDMap. object_shiftable_distance += parameters->object_check_min_road_shoulder_width; } @@ -458,33 +445,41 @@ bool isParkedVehicle( bool is_right_side_parked_vehicle = false; if (isOnRight(object)) { - auto [object_shiftable_distance, sub_type] = [&]() { - const auto most_right_road_lanelet = - route_handler->getMostRightLanelet(object.overhang_lanelet); - const auto most_right_lanelet_candidates = - route_handler->getLaneletMapPtr()->laneletLayer.findUsages( - most_right_road_lanelet.rightBound()); - - lanelet::ConstLanelet most_right_lanelet = most_right_road_lanelet; - const lanelet::Attribute sub_type = - most_right_lanelet.attribute(lanelet::AttributeName::Subtype); - - for (const auto & ll : most_right_lanelet_candidates) { - const lanelet::Attribute sub_type = ll.attribute(lanelet::AttributeName::Subtype); - if (sub_type.value() == "road_shoulder") { - most_right_lanelet = ll; - } + const auto most_right_lanelet = [&]() { + auto same_direction_lane = + route_handler->getMostRightLanelet(object.overhang_lanelet, true, true); + const lanelet::Attribute & sub_type = + same_direction_lane.attribute(lanelet::AttributeName::Subtype); + if (sub_type == "road_shoulder") { + return same_direction_lane; } - const auto center_to_right_boundary = distance2d( - to2D(most_right_lanelet.rightBound().basicLineString()), - to2D(toLaneletPoint(centerline_pos)).basicPoint()); + const auto opposite_lanes = route_handler->getRightOppositeLanelets(same_direction_lane); + if (opposite_lanes.empty()) { + return same_direction_lane; + } - return std::make_pair( - center_to_right_boundary - 0.5 * object.object.shape.dimensions.y, sub_type); + return static_cast(opposite_lanes.front().invert()); }(); - if (sub_type.value() != "road_shoulder") { + const auto center_to_right_boundary = distance2d( + to2D(most_right_lanelet.rightBound().basicLineString()), + to2D(toLaneletPoint(centerline_pos)).basicPoint()); + + double object_shiftable_distance = + center_to_right_boundary - 0.5 * object.object.shape.dimensions.y; + + const lanelet::Attribute & sub_type = + most_right_lanelet.attribute(lanelet::AttributeName::Subtype); + if (sub_type == "road_shoulder") { + // assuming it's parked vehicle if its CoG is within road shoulder lanelet. + if (boost::geometry::within( + to2D(toLaneletPoint(object_pos)).basicPoint(), + most_right_lanelet.polygon2d().basicPolygon())) { + return true; + } + } else { + // assuming there is 0.5m road shoulder even if it's not defined explicitly in HDMap. object_shiftable_distance += parameters->object_check_min_road_shoulder_width; } @@ -551,25 +546,58 @@ bool isNeverAvoidanceTarget( const std::shared_ptr & planner_data, const std::shared_ptr & parameters) { - const auto & object_pose = object.object.kinematics.initial_pose_with_covariance.pose; - const auto is_moving_distance_longer_than_threshold = - tier4_autoware_utils::calcDistance2d(object.init_pose, object_pose) > - parameters->distance_threshold_for_ambiguous_vehicle; - if (is_moving_distance_longer_than_threshold) { - object.reason = AvoidanceDebugFactor::MOVING_OBJECT; - return true; - } - if (object.is_within_intersection) { if (object.behavior == ObjectData::Behavior::NONE) { - object.reason = "ParallelToEgoLane"; - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object belongs to ego lane. never avoid it."); + object.info = ObjectInfo::PARALLEL_TO_EGO_LANE; + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), "object belongs to ego lane. never avoid it."); return true; } if (object.behavior == ObjectData::Behavior::MERGING) { - object.reason = "MergingToEgoLane"; - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object belongs to ego lane. never avoid it."); + object.info = ObjectInfo::MERGING_TO_EGO_LANE; + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), "object belongs to ego lane. never avoid it."); + return true; + } + } + + if (object.behavior == ObjectData::Behavior::MERGING) { + object.info = ObjectInfo::MERGING_TO_EGO_LANE; + if ( + isOnRight(object) && !object.is_parked && + object.overhang_points.front().first > parameters->th_overhang_distance) { + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), + "merging vehicle. but overhang distance is larger than threshold."); + return true; + } + if ( + !isOnRight(object) && !object.is_parked && + object.overhang_points.front().first < -1.0 * parameters->th_overhang_distance) { + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), + "merging vehicle. but overhang distance is larger than threshold."); + return true; + } + } + + if (object.behavior == ObjectData::Behavior::DEVIATING) { + object.info = ObjectInfo::DEVIATING_FROM_EGO_LANE; + if ( + isOnRight(object) && !object.is_parked && + object.overhang_points.front().first > parameters->th_overhang_distance) { + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), + "deviating vehicle. but overhang distance is larger than threshold."); + return true; + } + if ( + !isOnRight(object) && !object.is_parked && + object.overhang_points.front().first < -1.0 * parameters->th_overhang_distance) { + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), + "deviating vehicle. but overhang distance is larger than threshold."); return true; } } @@ -580,16 +608,18 @@ bool isNeverAvoidanceTarget( const auto left_lane = planner_data->route_handler->getLeftLanelet(object.overhang_lanelet, true, false); if (right_lane.has_value() && left_lane.has_value()) { - object.reason = AvoidanceDebugFactor::NOT_PARKING_OBJECT; - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object isn't on the edge lane. never avoid it."); + object.info = ObjectInfo::IS_NOT_PARKING_OBJECT; + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), "object isn't on the edge lane. never avoid it."); return true; } } if (isCloseToStopFactor(object, data, planner_data, parameters)) { if (object.is_on_ego_lane && !object.is_parked) { - object.reason = AvoidanceDebugFactor::NOT_PARKING_OBJECT; - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object is close to stop factor. never avoid it."); + object.info = ObjectInfo::IS_NOT_PARKING_OBJECT; + RCLCPP_DEBUG( + rclcpp::get_logger(logger_namespace), "object is close to stop factor. never avoid it."); return true; } } @@ -604,22 +634,22 @@ bool isObviousAvoidanceTarget( { if (!object.is_within_intersection) { if (object.is_parked && object.behavior == ObjectData::Behavior::NONE) { - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object is obvious parked vehicle."); + RCLCPP_DEBUG(rclcpp::get_logger(logger_namespace), "object is obvious parked vehicle."); return true; } if (!object.is_on_ego_lane && object.behavior == ObjectData::Behavior::NONE) { - RCLCPP_DEBUG(rclcpp::get_logger(__func__), "object is adjacent vehicle."); + RCLCPP_DEBUG(rclcpp::get_logger(logger_namespace), "object is adjacent vehicle."); return true; } } if (!object.is_parked) { - object.reason = AvoidanceDebugFactor::NOT_PARKING_OBJECT; + object.info = ObjectInfo::IS_NOT_PARKING_OBJECT; } if (object.behavior == ObjectData::Behavior::MERGING) { - object.reason = "MergingToEgoLane"; + object.info = ObjectInfo::MERGING_TO_EGO_LANE; } return false; @@ -632,13 +662,13 @@ bool isSatisfiedWithCommonCondition( { // Step1. filtered by target object type. if (!isAvoidanceTargetObjectType(object.object, parameters)) { - object.reason = AvoidanceDebugFactor::OBJECT_IS_NOT_TYPE; + object.info = ObjectInfo::IS_NOT_TARGET_OBJECT; return false; } // Step2. filtered stopped objects. if (filtering_utils::isMovingObject(object, parameters)) { - object.reason = AvoidanceDebugFactor::MOVING_OBJECT; + object.info = ObjectInfo::MOVING_OBJECT; return false; } @@ -647,12 +677,12 @@ bool isSatisfiedWithCommonCondition( fillLongitudinalAndLengthByClosestEnvelopeFootprint(data.reference_path_rough, ego_pos, object); if (object.longitudinal < -parameters->object_check_backward_distance) { - object.reason = AvoidanceDebugFactor::OBJECT_IS_BEHIND_THRESHOLD; + object.info = ObjectInfo::FURTHER_THAN_THRESHOLD; return false; } if (object.longitudinal > forward_detection_range) { - object.reason = AvoidanceDebugFactor::OBJECT_IS_IN_FRONT_THRESHOLD; + object.info = ObjectInfo::FURTHER_THAN_THRESHOLD; return false; } @@ -663,12 +693,12 @@ bool isSatisfiedWithCommonCondition( const auto ego_idx = planner_data->findEgoIndex(data.reference_path_rough.points); const auto to_goal_distance = rh->isInGoalRouteSection(data.current_lanelets.back()) - ? calcSignedArcLength( + ? motion_utils::calcSignedArcLength( data.reference_path_rough.points, ego_idx, data.reference_path_rough.points.size() - 1) : std::numeric_limits::max(); if (object.longitudinal > to_goal_distance) { - object.reason = AvoidanceDebugFactor::OBJECT_BEHIND_PATH_GOAL; + object.info = ObjectInfo::FURTHER_THAN_GOAL; return false; } @@ -676,7 +706,7 @@ bool isSatisfiedWithCommonCondition( if ( object.longitudinal + object.length / 2 + parameters->object_check_goal_distance > to_goal_distance) { - object.reason = "TooNearToGoal"; + object.info = ObjectInfo::TOO_NEAR_TO_GOAL; return false; } } @@ -691,7 +721,7 @@ bool isSatisfiedWithNonVehicleCondition( { // avoidance module ignore pedestrian and bicycle around crosswalk if (isWithinCrosswalk(object, planner_data->route_handler->getOverallGraphPtr())) { - object.reason = "CrosswalkUser"; + object.info = ObjectInfo::CROSSWALK_USER; return false; } @@ -700,7 +730,7 @@ bool isSatisfiedWithNonVehicleCondition( object.to_centerline = lanelet::utils::getArcCoordinates(data.current_lanelets, object_pose).distance; if (std::abs(object.to_centerline) < parameters->threshold_distance_object_is_on_center) { - object.reason = AvoidanceDebugFactor::TOO_NEAR_TO_CENTERLINE; + object.info = ObjectInfo::TOO_NEAR_TO_CENTERLINE; return false; } @@ -737,32 +767,41 @@ bool isSatisfiedWithVehicleCondition( // from here, filtering for ambiguous vehicle. if (!parameters->enable_avoidance_for_ambiguous_vehicle) { - object.reason = "AmbiguousStoppedVehicle"; + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; return false; } const auto stop_time_longer_than_threshold = object.stop_time > parameters->time_threshold_for_ambiguous_vehicle; if (!stop_time_longer_than_threshold) { - object.reason = "AmbiguousStoppedVehicle(wait-and-see)"; + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; + return false; + } + + const auto & current_pose = object.object.kinematics.initial_pose_with_covariance.pose; + const auto is_moving_distance_longer_than_threshold = + calcDistance2d(object.init_pose, current_pose) > + parameters->distance_threshold_for_ambiguous_vehicle; + if (is_moving_distance_longer_than_threshold) { + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; return false; } if (object.is_within_intersection) { if (object.behavior == ObjectData::Behavior::DEVIATING) { - object.reason = "AmbiguousStoppedVehicle(wait-and-see)"; + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; object.is_ambiguous = true; return true; } } else { if (object.behavior == ObjectData::Behavior::MERGING) { - object.reason = "AmbiguousStoppedVehicle(wait-and-see)"; + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; object.is_ambiguous = true; return true; } if (object.behavior == ObjectData::Behavior::DEVIATING) { - object.reason = "AmbiguousStoppedVehicle(wait-and-see)"; + object.info = ObjectInfo::AMBIGUOUS_STOPPED_VEHICLE; object.is_ambiguous = true; return true; } @@ -773,7 +812,7 @@ bool isSatisfiedWithVehicleCondition( } } - object.reason = AvoidanceDebugFactor::NOT_PARKING_OBJECT; + object.info = ObjectInfo::IS_NOT_PARKING_OBJECT; return false; } @@ -787,12 +826,12 @@ bool isNoNeedAvoidanceBehavior( const auto shift_length = calcShiftLength( isOnRight(object), object.overhang_points.front().first, object.avoid_margin.value()); if (!isShiftNecessary(isOnRight(object), shift_length)) { - object.reason = "NotNeedAvoidance"; + object.info = ObjectInfo::ENOUGH_LATERAL_DISTANCE; return true; } if (std::abs(shift_length) < parameters->lateral_execution_threshold) { - object.reason = "LessThanExecutionThreshold"; + object.info = ObjectInfo::LESS_THAN_EXECUTION_THRESHOLD; return true; } @@ -841,7 +880,7 @@ double getRoadShoulderDistance( const auto & object_pose = object.object.kinematics.initial_pose_with_covariance.pose; const auto object_closest_index = - findNearestIndex(data.reference_path.points, object_pose.position); + motion_utils::findNearestIndex(data.reference_path.points, object_pose.position); const auto object_closest_pose = data.reference_path.points.at(object_closest_index).point.pose; const auto rh = planner_data->route_handler; @@ -1084,7 +1123,7 @@ void fillLongitudinalAndLengthByClosestEnvelopeFootprint( for (const auto & p : obj.envelope_poly.outer()) { const auto point = tier4_autoware_utils::createPoint(p.x(), p.y(), 0.0); // TODO(someone): search around first position where the ego should avoid the object. - const double arc_length = calcSignedArcLength(path.points, ego_pos, point); + const double arc_length = motion_utils::calcSignedArcLength(path.points, ego_pos, point); min_distance = std::min(min_distance, arc_length); max_distance = std::max(max_distance, arc_length); } @@ -1101,7 +1140,7 @@ std::vector> calcEnvelopeOverhangDistance( for (const auto & p : object_data.envelope_poly.outer()) { const auto point = tier4_autoware_utils::createPoint(p.x(), p.y(), 0.0); // TODO(someone): search around first position where the ego should avoid the object. - const auto idx = findNearestIndex(path.points, point); + const auto idx = motion_utils::findNearestIndex(path.points, point); const auto lateral = calcLateralDeviation(getPose(path.points.at(idx)), point); overhang_points.emplace_back(lateral, point); } @@ -1272,15 +1311,16 @@ void insertDecelPoint( const Point & p_src, const double offset, const double velocity, PathWithLaneId & path, std::optional & p_out) { - const auto decel_point = calcLongitudinalOffsetPoint(path.points, p_src, offset); + const auto decel_point = motion_utils::calcLongitudinalOffsetPoint(path.points, p_src, offset); if (!decel_point) { // TODO(Satoshi OTA) Think later the process in the case of no decel point found. return; } - const auto seg_idx = findNearestSegmentIndex(path.points, decel_point.value()); - const auto insert_idx = insertTargetPoint(seg_idx, decel_point.value(), path.points); + const auto seg_idx = motion_utils::findNearestSegmentIndex(path.points, decel_point.value()); + const auto insert_idx = + motion_utils::insertTargetPoint(seg_idx, decel_point.value(), path.points); if (!insert_idx) { // TODO(Satoshi OTA) Think later the process in the case of no decel point found. @@ -1380,6 +1420,7 @@ void fillObjectMovingTime( object_data.last_stop = now; object_data.move_time = 0.0; if (is_new_object) { + object_data.init_pose = object_data.object.kinematics.initial_pose_with_covariance.pose; object_data.stop_time = 0.0; object_data.last_move = now; stopped_objects.push_back(object_data); @@ -1388,11 +1429,13 @@ void fillObjectMovingTime( same_id_obj->last_stop = now; same_id_obj->move_time = 0.0; object_data.stop_time = same_id_obj->stop_time; + object_data.init_pose = same_id_obj->init_pose; } return; } if (is_new_object) { + object_data.init_pose = object_data.object.kinematics.initial_pose_with_covariance.pose; object_data.move_time = std::numeric_limits::infinity(); object_data.stop_time = 0.0; object_data.last_move = now; @@ -1402,6 +1445,7 @@ void fillObjectMovingTime( object_data.last_stop = same_id_obj->last_stop; object_data.move_time = (now - same_id_obj->last_stop).seconds(); object_data.stop_time = 0.0; + object_data.init_pose = object_data.object.kinematics.initial_pose_with_covariance.pose; if (object_data.move_time > object_parameter.moving_time_threshold) { stopped_objects.erase(same_id_obj); @@ -1448,22 +1492,6 @@ void fillAvoidanceNecessity( object_data.avoid_required = check_necessity(parameters->hysteresis_factor_expand_rate); } -void fillInitialPose(ObjectData & object_data, ObjectDataArray & detected_objects) -{ - const auto id = object_data.object.object_id; - const auto same_id_obj = std::find_if( - detected_objects.begin(), detected_objects.end(), - [&id](const auto & o) { return o.object.object_id == id; }); - - if (same_id_obj != detected_objects.end()) { - object_data.init_pose = same_id_obj->init_pose; - return; - } - - object_data.init_pose = object_data.object.kinematics.initial_pose_with_covariance.pose; - detected_objects.push_back(object_data); -} - void fillObjectStoppableJudge( ObjectData & object_data, const ObjectDataArray & registered_objects, const double feasible_stop_distance, const std::shared_ptr & parameters) @@ -1654,7 +1682,7 @@ void filterTargetObjects( constexpr double STOP_TIME_THRESHOLD = 3.0; // [s] if (filtering_utils::isUnknownTypeObject(o)) { if (o.stop_time < STOP_TIME_THRESHOLD) { - o.reason = "UnstableObject"; + o.info = ObjectInfo::UNSTABLE_OBJECT; data.other_objects.push_back(o); continue; } @@ -1713,9 +1741,9 @@ void fillAdditionalInfoFromPoint(const AvoidancePlanningData & data, AvoidLineAr // calc longitudinal for (auto & sl : lines) { - sl.start_idx = findNearestIndex(path.points, sl.start.position); + sl.start_idx = motion_utils::findNearestIndex(path.points, sl.start.position); sl.start_longitudinal = arc.at(sl.start_idx); - sl.end_idx = findNearestIndex(path.points, sl.end.position); + sl.end_idx = motion_utils::findNearestIndex(path.points, sl.end.position); sl.end_longitudinal = arc.at(sl.end_idx); } } @@ -2012,7 +2040,8 @@ std::pair separateObjectsByPath( Pose p_spline_ego_front = spline_path.points.front().point.pose; double next_longitudinal_distance = parameters->resample_interval_for_output; for (size_t i = 0; i < points_size; ++i) { - const auto distance_from_ego = calcSignedArcLength(reference_path.points, ego_idx, i); + const auto distance_from_ego = + motion_utils::calcSignedArcLength(reference_path.points, ego_idx, i); if (distance_from_ego > object_check_forward_distance) { break; } @@ -2187,8 +2216,7 @@ DrivableLanes generateExpandedDrivableLanes( } if (i == max_recursive_search_num - 1) { RCLCPP_ERROR( - rclcpp::get_logger("behavior_path_planner").get_child("avoidance"), - "Drivable area expansion reaches max iteration."); + rclcpp::get_logger(logger_namespace), "Drivable area expansion reaches max iteration."); } } }; @@ -2261,7 +2289,7 @@ double calcDistanceToReturnDeadLine( if (planner_data->route_handler->isInGoalRouteSection(lanelets.back())) { const auto & ego_pos = planner_data->self_odometry->pose.pose.position; const auto to_goal_distance = - calcSignedArcLength(path.points, ego_pos, path.points.size() - 1); + motion_utils::calcSignedArcLength(path.points, ego_pos, path.points.size() - 1); distance_to_return_dead_line = std::min( distance_to_return_dead_line, to_goal_distance - parameters->dead_line_buffer_for_goal); } diff --git a/planning/behavior_path_avoidance_module/test/test_utils.cpp b/planning/behavior_path_avoidance_module/test/test_utils.cpp index 95488daa69cf8..1a114eef9f7f7 100644 --- a/planning/behavior_path_avoidance_module/test/test_utils.cpp +++ b/planning/behavior_path_avoidance_module/test/test_utils.cpp @@ -21,6 +21,7 @@ using behavior_path_planner::ObjectData; using behavior_path_planner::utils::avoidance::isOnRight; using behavior_path_planner::utils::avoidance::isSameDirectionShift; +using behavior_path_planner::utils::avoidance::isShiftNecessary; TEST(BehaviorPathPlanningAvoidanceUtilsTest, shiftLengthDirectionTest) { @@ -37,3 +38,19 @@ TEST(BehaviorPathPlanningAvoidanceUtilsTest, shiftLengthDirectionTest) ASSERT_TRUE(isSameDirectionShift(isOnRight(left_obj), positive_shift_length)); ASSERT_FALSE(isSameDirectionShift(isOnRight(left_obj), negative_shift_length)); } + +TEST(BehaviorPathPlanningAvoidanceUtilsTest, shiftNecessaryTest) +{ + ObjectData right_obj; + right_obj.direction = route_handler::Direction::RIGHT; + const double negative_shift_length = -1.0; + const double positive_shift_length = 1.0; + + ASSERT_TRUE(isShiftNecessary(isOnRight(right_obj), positive_shift_length)); + ASSERT_FALSE(isShiftNecessary(isOnRight(right_obj), negative_shift_length)); + + ObjectData left_obj; + left_obj.direction = route_handler::Direction::LEFT; + ASSERT_TRUE(isShiftNecessary(isOnRight(left_obj), negative_shift_length)); + ASSERT_FALSE(isShiftNecessary(isOnRight(left_obj), positive_shift_length)); +} diff --git a/planning/behavior_path_dynamic_avoidance_module/README.md b/planning/behavior_path_dynamic_avoidance_module/README.md index 89a661d66735e..b8af767afd9a5 100644 --- a/planning/behavior_path_dynamic_avoidance_module/README.md +++ b/planning/behavior_path_dynamic_avoidance_module/README.md @@ -12,7 +12,7 @@ Obstacle Avoidance module modifies the path to be followed so that it fits withi Avoidance functions are also provided by the [Avoidance module](https://autowarefoundation.github.io/autoware.universe/main/planning/behavior_path_avoidance_module/), but these modules have different roles. The Avoidance module performs avoidance through the outside of own lanes but cannot avoid the moving objects. On the other hand, this module can avoid moving objects. -For this reason, the word "dynamic" is used in the modules's name. +For this reason, the word "dynamic" is used in the module's name. The table below lists the avoidance modules that can handle each situation. | | avoid within the own lane | avoid through the outside of own lanes | @@ -23,7 +23,7 @@ The table below lists the avoidance modules that can handle each situation. ## Policy of algorithms Here, we describe the policy of inner algorithms. -The inner algorithms can be separated into two parts: The first decide whether to avoid the obstacles and the second cuts off the drivable area against the corresponding obstacle. +The inner algorithms can be separated into two parts: The first decides whether to avoid the obstacles and the second cuts off the drivable area against the corresponding obstacle. ### Select obstacles to avoid @@ -36,7 +36,7 @@ The other, _can be avoided_ denotes whether it can be avoided without risk to th For this purpose, the module judges whether the obstacle can be avoided with satisfying the constraints of lateral acceleration and lateral jerk. For example, the module decides not to avoid an object that is too close or fast in the lateral direction. -### Cuts off the drivable area against the selected obstacles +### Cuts off the drivable area against the selected vehicles For the selected obstacles to be avoided, the module cuts off the drivable area. As inputs to decide the shapes of cut-off polygons, poses of the obstacles are mainly used, assuming they move in parallel to the ego's path, instead of its predicted path. @@ -45,7 +45,7 @@ Furthermore, the output drivable area shape is designed as a rectangular cutout #### Determination of lateral dimension -Lateral dimensions of the polygon is calculated as follows. +The lateral dimensions of the polygon are calculated as follows. The polygon's width to extract from the drivable area is the obstacle width and `drivable_area_generation.lat_offset_from_obstacle`. We can limit the lateral shift length by `drivable_area_generation.max_lat_offset_to_avoid`. @@ -55,7 +55,7 @@ We can limit the lateral shift length by `drivable_area_generation.max_lat_offse Then, extracting the same directional and opposite directional obstacles from the drivable area will work as follows considering TTC (time to collision). -Regarding the same directional obstacles, obstacles whose TTC is negative will be ignored (e.g. The obstacle is in front of the ego, and the obstacle's velocity is larger than the ego's velocity.). +Regarding the same directional obstacles, obstacles whose TTC is negative will be ignored (e.g., The obstacle is in front of the ego, and the obstacle's velocity is larger than the ego's velocity.). Same directional obstacles (Parameter names may differ from implementation) ![same_directional_object](./image/same_directional_object.svg) @@ -63,6 +63,26 @@ Same directional obstacles (Parameter names may differ from implementation) Opposite directional obstacles (Parameter names may differ from implementation) ![opposite_directional_object](./image/opposite_directional_object.svg) +### Cuts off the drivable area against the selected pedestrians + +Then, we describe the logic to generate the drivable areas against pedestrians to be avoided. +Objects of this type are considered to have priority right of way over the ego's vehicle while ensuring a minimum safety of the ego's vehicle. +In other words, the module assigns a drivable area to an obstacle with a specific margin based on the predicted paths with specific confidences for a specific time interval, as shown in the following figure. + +
+ +
Restriction areas are generated from each pedestrian's predicted paths
+
+ +Apart from polygons for objects, the module also generates another polygon to ensure the ego's safety, i.e., to avoid abrupt steering or significant changes from the path. +This is similar to avoidance against the vehicles and takes precedence over keeping a safe distance from the object to be avoided. +As a result, as shown in the figure below, the polygons around the objects reduced by the secured polygon of the ego are subtracted from the ego's drivable area. + +
+ +
Ego's minimum requirements are prioritized against object margin
+
+ ## Example
diff --git a/planning/behavior_path_dynamic_avoidance_module/config/dynamic_avoidance.param.yaml b/planning/behavior_path_dynamic_avoidance_module/config/dynamic_avoidance.param.yaml index 371f7da2fadf5..c1f4646ef7736 100644 --- a/planning/behavior_path_dynamic_avoidance_module/config/dynamic_avoidance.param.yaml +++ b/planning/behavior_path_dynamic_avoidance_module/config/dynamic_avoidance.param.yaml @@ -12,9 +12,9 @@ bus: true trailer: true unknown: false - bicycle: false + bicycle: true motorcycle: true - pedestrian: false + pedestrian: true max_obstacle_vel: 100.0 # [m/s] min_obstacle_vel: 0.0 # [m/s] @@ -38,8 +38,9 @@ crossing_object: min_overtaking_object_vel: 1.0 max_overtaking_object_angle: 1.05 - min_oncoming_object_vel: 0.0 + min_oncoming_object_vel: 1.0 max_oncoming_object_angle: 0.523 + max_pedestrian_crossing_vel: 0.8 front_object: max_object_angle: 0.785 @@ -54,7 +55,11 @@ object_path_base: min_longitudinal_polygon_margin: 3.0 # [m] - lat_offset_from_obstacle: 0.8 # [m] + lat_offset_from_obstacle: 1.0 # [m] + margin_distance_around_pedestrian: 2.0 # [m] + predicted_path: + end_time_to_consider: 3.0 # [s] + threshold_confidence: 0.0 # [] not probability max_lat_offset_to_avoid: 0.5 # [m] max_time_for_object_lat_shift: 0.0 # [s] lpf_gain_for_lat_avoid_to_offset: 0.9 # [-] @@ -66,12 +71,12 @@ # for same directional object overtaking_object: max_time_to_collision: 40.0 # [s] - start_duration_to_avoid: 2.0 # [s] - end_duration_to_avoid: 4.0 # [s] + start_duration_to_avoid: 1.0 # [s] + end_duration_to_avoid: 1.0 # [s] duration_to_hold_avoidance: 3.0 # [s] # for opposite directional object oncoming_object: max_time_to_collision: 40.0 # [s] This value should be the same as overtaking_object's one to suppress chattering of this value for parked vehicles - start_duration_to_avoid: 12.0 # [s] + start_duration_to_avoid: 1.0 # [s] end_duration_to_avoid: 0.0 # [s] diff --git a/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-13-01.png b/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-13-01.png new file mode 100644 index 0000000000000..719636ed295c0 Binary files /dev/null and b/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-13-01.png differ diff --git a/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-32-03.png b/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-32-03.png new file mode 100644 index 0000000000000..934c495bbb9f1 Binary files /dev/null and b/planning/behavior_path_dynamic_avoidance_module/image/2024-04-18_15-32-03.png differ diff --git a/planning/behavior_path_dynamic_avoidance_module/include/behavior_path_dynamic_avoidance_module/scene.hpp b/planning/behavior_path_dynamic_avoidance_module/include/behavior_path_dynamic_avoidance_module/scene.hpp index bdcd1d7424d37..353a5fab92032 100644 --- a/planning/behavior_path_dynamic_avoidance_module/include/behavior_path_dynamic_avoidance_module/scene.hpp +++ b/planning/behavior_path_dynamic_avoidance_module/include/behavior_path_dynamic_avoidance_module/scene.hpp @@ -16,6 +16,7 @@ #define BEHAVIOR_PATH_DYNAMIC_AVOIDANCE_MODULE__SCENE_HPP_ #include "behavior_path_planner_common/interface/scene_module_interface.hpp" +#include "tier4_autoware_utils/system/stop_watch.hpp" #include #include @@ -54,12 +55,21 @@ std::vector getAllKeys(const std::unordered_map & map) namespace behavior_path_planner { using autoware_auto_perception_msgs::msg::PredictedPath; +using autoware_auto_planning_msgs::msg::PathWithLaneId; using tier4_autoware_utils::Polygon2d; struct MinMaxValue { double min_value{0.0}; double max_value{0.0}; + MinMaxValue operator+(const double scalar) const + { + MinMaxValue ret; + ret.min_value = min_value + scalar; + ret.max_value = max_value + scalar; + return ret; + }; + void swap() { std::swap(min_value, max_value); } }; enum class PolygonGenerationMethod { @@ -67,6 +77,16 @@ enum class PolygonGenerationMethod { OBJECT_PATH_BASE, }; +enum class ObjectType { + OUT_OF_SCOPE = 0, // The module do not care about this type of objects. + REGULATED, // The module assumes this type of objects move in parallel against lanes. Drivable + // areas are divided proportionately with the ego. Typically, cars, bus and trucks + // are classified to this type. + UNREGULATED, // The module does not assume the objects move in parallel against lanes and + // assigns drivable area with priority to ego. Typically, pedestrians should be + // classified to this type. +}; + struct DynamicAvoidanceParameters { // common @@ -103,12 +123,18 @@ struct DynamicAvoidanceParameters double max_overtaking_crossing_object_angle{0.0}; double min_oncoming_crossing_object_vel{0.0}; double max_oncoming_crossing_object_angle{0.0}; + double max_pedestrian_crossing_vel{0.0}; double max_stopped_object_vel{0.0}; // drivable area generation PolygonGenerationMethod polygon_generation_method{}; double min_obj_path_based_lon_polygon_margin{0.0}; double lat_offset_from_obstacle{0.0}; + double margin_distance_around_pedestrian{0.0}; + + double end_time_to_consider{0.0}; + double threshold_confidence{0.0}; + double max_lat_offset_to_avoid{0.0}; double max_time_for_lat_shift{0.0}; double lpf_gain_for_lat_avoid_to_offset{0.0}; @@ -148,6 +174,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface const bool arg_is_object_on_ego_path, const std::optional & arg_latest_time_inside_ego_path) : uuid(tier4_autoware_utils::toHexString(predicted_object.object_id)), + label(predicted_object.classification.front().label), pose(predicted_object.kinematics.initial_pose_with_covariance.pose), shape(predicted_object.shape), vel(arg_vel), @@ -161,6 +188,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface } std::string uuid{}; + uint8_t label{}; geometry_msgs::msg::Pose pose{}; autoware_auto_perception_msgs::msg::Shape shape; double vel{0.0}; @@ -178,6 +206,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface std::vector ref_path_points_for_obj_poly; LatFeasiblePaths ego_lat_feasible_paths; + // add additional information (not update to the latest data) void update( const MinMaxValue & arg_lon_offset_to_avoid, const MinMaxValue & arg_lat_offset_to_avoid, const bool arg_is_collision_left, const bool arg_should_be_avoided, @@ -216,7 +245,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface // increase counter if (counter_map_.count(uuid) != 0) { - counter_map_.at(uuid) = std::min(max_count_ + 1, std::max(1, counter_map_.at(uuid) + 1)); + counter_map_.at(uuid) = std::min(max_count_, std::max(1, counter_map_.at(uuid) + 1)); } else { counter_map_.emplace(uuid, 1); } @@ -236,7 +265,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface } for (const auto & uuid : not_updated_uuids) { if (counter_map_.count(uuid) != 0) { - counter_map_.at(uuid) = std::max(min_count_ - 1, std::min(-1, counter_map_.at(uuid) - 1)); + counter_map_.at(uuid) = std::max(0, counter_map_.at(uuid) - 1); } else { counter_map_.emplace(uuid, -1); } @@ -253,7 +282,7 @@ class DynamicAvoidanceModule : public SceneModuleInterface std::remove_if( valid_object_uuids_.begin(), valid_object_uuids_.end(), [&](const auto & uuid) { - return counter_map_.count(uuid) == 0 || counter_map_.at(uuid) < max_count_; + return counter_map_.count(uuid) == 0 || counter_map_.at(uuid) < min_count_; }), valid_object_uuids_.end()); @@ -340,13 +369,23 @@ class DynamicAvoidanceModule : public SceneModuleInterface const double max_lon_offset; const double min_lon_offset; }; + struct EgoPathReservePoly + { + const tier4_autoware_utils::Polygon2d left_avoid; + const tier4_autoware_utils::Polygon2d right_avoid; + }; bool canTransitSuccessState() override; bool canTransitFailureState() override { return false; } - bool isLabelTargetObstacle(const uint8_t label) const; - void updateTargetObjects(); + ObjectType getObjectType(const uint8_t label) const; + void registerRegulatedObjects(const std::vector & prev_objects); + void registerUnregulatedObjects(const std::vector & prev_objects); + void determineWhetherToAvoidAgainstRegulatedObjects( + const std::vector & prev_objects); + void determineWhetherToAvoidAgainstUnregulatedObjects( + const std::vector & prev_objects); LatFeasiblePaths generateLateralFeasiblePaths( const geometry_msgs::msg::Pose & ego_pose, const double ego_vel) const; void updateRefPathBeforeLaneChange(const std::vector & ego_ref_path_points); @@ -378,18 +417,24 @@ class DynamicAvoidanceModule : public SceneModuleInterface const geometry_msgs::msg::Pose & obj_pose, const Polygon2d & obj_points, const double obj_vel, const PredictedPath & obj_path, const autoware_auto_perception_msgs::msg::Shape & obj_shape, const TimeWhileCollision & time_while_collision) const; - std::optional calcMinMaxLateralOffsetToAvoid( + std::optional calcMinMaxLateralOffsetToAvoidRegulatedObject( const std::vector & ref_path_points_for_obj_poly, const Polygon2d & obj_points, const geometry_msgs::msg::Point & obj_pos, const double obj_vel, const bool is_collision_left, const double obj_normal_vel, const std::optional & prev_object) const; - + std::optional calcMinMaxLateralOffsetToAvoidUnregulatedObject( + const std::vector & ref_path_points_for_obj_poly, + const std::optional & prev_object, + const DynamicAvoidanceObject & object) const; std::pair getAdjacentLanes( const double forward_distance, const double backward_distance) const; std::optional calcEgoPathBasedDynamicObstaclePolygon( const DynamicAvoidanceObject & object) const; std::optional calcObjectPathBasedDynamicObstaclePolygon( const DynamicAvoidanceObject & object) const; + std::optional calcPredictedPathBasedDynamicObstaclePolygon( + const DynamicAvoidanceObject & object, const EgoPathReservePoly & ego_path_poly) const; + EgoPathReservePoly calcEgoPathReservePoly(const PathWithLaneId & ego_path) const; void printIgnoreReason(const std::string & obj_uuid, const std::string & reason) { @@ -406,6 +451,10 @@ class DynamicAvoidanceModule : public SceneModuleInterface std::shared_ptr parameters_; TargetObjectsManager target_objects_manager_; + + mutable tier4_autoware_utils::StopWatch< + std::chrono::milliseconds, std::chrono::microseconds, std::chrono::steady_clock> + stop_watch_; }; } // namespace behavior_path_planner diff --git a/planning/behavior_path_dynamic_avoidance_module/src/manager.cpp b/planning/behavior_path_dynamic_avoidance_module/src/manager.cpp index 569c6a17b5b32..baa1c631df8da 100644 --- a/planning/behavior_path_dynamic_avoidance_module/src/manager.cpp +++ b/planning/behavior_path_dynamic_avoidance_module/src/manager.cpp @@ -99,6 +99,8 @@ void DynamicAvoidanceModuleManager::init(rclcpp::Node * node) node->declare_parameter(ns + "crossing_object.min_oncoming_object_vel"); p.max_oncoming_crossing_object_angle = node->declare_parameter(ns + "crossing_object.max_oncoming_object_angle"); + p.max_pedestrian_crossing_vel = + node->declare_parameter(ns + "crossing_object.max_pedestrian_crossing_vel"); p.max_stopped_object_vel = node->declare_parameter(ns + "stopped_object.max_object_vel"); @@ -111,6 +113,12 @@ void DynamicAvoidanceModuleManager::init(rclcpp::Node * node) p.min_obj_path_based_lon_polygon_margin = node->declare_parameter(ns + "object_path_base.min_longitudinal_polygon_margin"); p.lat_offset_from_obstacle = node->declare_parameter(ns + "lat_offset_from_obstacle"); + p.margin_distance_around_pedestrian = + node->declare_parameter(ns + "margin_distance_around_pedestrian"); + p.end_time_to_consider = + node->declare_parameter(ns + "predicted_path.end_time_to_consider"); + p.threshold_confidence = + node->declare_parameter(ns + "predicted_path.threshold_confidence"); p.max_lat_offset_to_avoid = node->declare_parameter(ns + "max_lat_offset_to_avoid"); p.max_time_for_lat_shift = node->declare_parameter(ns + "max_time_for_object_lat_shift"); @@ -214,6 +222,9 @@ void DynamicAvoidanceModuleManager::updateModuleParams( updateParam( parameters, ns + "crossing_object.max_oncoming_object_angle", p->max_oncoming_crossing_object_angle); + updateParam( + parameters, ns + "crossing_object.max_pedestrian_crossing_vel", + p->max_pedestrian_crossing_vel); updateParam( parameters, ns + "stopped_object.max_object_vel", p->max_stopped_object_vel); @@ -231,6 +242,12 @@ void DynamicAvoidanceModuleManager::updateModuleParams( parameters, ns + "object_path_base.min_longitudinal_polygon_margin", p->min_obj_path_based_lon_polygon_margin); updateParam(parameters, ns + "lat_offset_from_obstacle", p->lat_offset_from_obstacle); + updateParam( + parameters, ns + "margin_distance_around_pedestrian", p->margin_distance_around_pedestrian); + updateParam( + parameters, ns + "predicted_path.end_time_to_consider", p->end_time_to_consider); + updateParam( + parameters, ns + "predicted_path.threshold_confidence", p->threshold_confidence); updateParam(parameters, ns + "max_lat_offset_to_avoid", p->max_lat_offset_to_avoid); updateParam( parameters, ns + "max_time_for_object_lat_shift", p->max_time_for_lat_shift); diff --git a/planning/behavior_path_dynamic_avoidance_module/src/scene.cpp b/planning/behavior_path_dynamic_avoidance_module/src/scene.cpp index c6b7b2e0e8031..a5368732ef3bb 100644 --- a/planning/behavior_path_dynamic_avoidance_module/src/scene.cpp +++ b/planning/behavior_path_dynamic_avoidance_module/src/scene.cpp @@ -18,12 +18,15 @@ #include "behavior_path_planner_common/utils/utils.hpp" #include "object_recognition_utils/predicted_path_utils.hpp" #include "signal_processing/lowpass_filter_1d.hpp" +#include "tier4_autoware_utils/geometry/boost_polygon_utils.hpp" -#include #include -#include +#include +#include #include +#include +#include #include #include @@ -55,6 +58,11 @@ MinMaxValue getMinMaxValues(const std::vector & vec) return MinMaxValue{vec.at(min_idx), vec.at(max_idx)}; } +MinMaxValue combineMinMaxValues(const MinMaxValue & r1, const MinMaxValue & r2) +{ + return MinMaxValue{std::min(r1.min_value, r2.min_value), std::max(r1.max_value, r2.max_value)}; +} + void appendObjectMarker(MarkerArray & marker_array, const geometry_msgs::msg::Pose & obj_pose) { auto marker = tier4_autoware_utils::createDefaultMarker( @@ -339,11 +347,24 @@ bool DynamicAvoidanceModule::isExecutionReady() const void DynamicAvoidanceModule::updateData() { + // stop_watch_.tic(std::string(__func__)); + info_marker_.markers.clear(); debug_marker_.markers.clear(); - // calculate target objects - updateTargetObjects(); + const auto prev_objects = target_objects_manager_.getValidObjects(); + target_objects_manager_.initialize(); + + // 1. Rough filtering of target objects with small computing cost + registerRegulatedObjects(prev_objects); + registerUnregulatedObjects(prev_objects); + + const auto & ego_lat_feasible_paths = generateLateralFeasiblePaths(getEgoPose(), getEgoSpeed()); + target_objects_manager_.finalize(ego_lat_feasible_paths); + + // 2. Precise filtering of target objects and check if they should be avoided + determineWhetherToAvoidAgainstRegulatedObjects(prev_objects); + determineWhetherToAvoidAgainstUnregulatedObjects(prev_objects); const auto target_objects_candidate = target_objects_manager_.getValidObjects(); target_objects_.clear(); @@ -352,6 +373,11 @@ void DynamicAvoidanceModule::updateData() target_objects_.push_back(target_object_candidate); } } + + // const double calculation_time = stop_watch_.toc(std::string(__func__)); + // RCLCPP_INFO_STREAM_EXPRESSION( + // getLogger(), parameters_->enable_debug_info, __func__ << ":=" << calculation_time << " + // [ms]"); } bool DynamicAvoidanceModule::canTransitSuccessState() @@ -361,12 +387,23 @@ bool DynamicAvoidanceModule::canTransitSuccessState() BehaviorModuleOutput DynamicAvoidanceModule::plan() { + // stop_watch_.tic(std::string(__func__)); + const auto & input_path = getPreviousModuleOutput().path; + if (input_path.points.empty()) { + throw std::runtime_error("input path is empty"); + } + + const auto ego_path_reserve_poly = calcEgoPathReservePoly(input_path); // create obstacles to avoid (= extract from the drivable area) std::vector obstacles_for_drivable_area; for (const auto & object : target_objects_) { const auto obstacle_poly = [&]() { + if (getObjectType(object.label) == ObjectType::UNREGULATED) { + return calcPredictedPathBasedDynamicObstaclePolygon(object, ego_path_reserve_poly); + } + if (parameters_->polygon_generation_method == PolygonGenerationMethod::EGO_PATH_BASE) { return calcEgoPathBasedDynamicObstaclePolygon(object); } @@ -399,6 +436,11 @@ BehaviorModuleOutput DynamicAvoidanceModule::plan() output.turn_signal_info = getPreviousModuleOutput().turn_signal_info; output.modified_goal = getPreviousModuleOutput().modified_goal; + // const double calculation_time = stop_watch_.toc(std::string(__func__)); + // RCLCPP_INFO_STREAM_EXPRESSION( + // getLogger(), parameters_->enable_debug_info, __func__ << ":=" << calculation_time << " + // [ms]"); + return output; } @@ -414,53 +456,43 @@ BehaviorModuleOutput DynamicAvoidanceModule::planWaitingApproval() return out; } -bool DynamicAvoidanceModule::isLabelTargetObstacle(const uint8_t label) const +ObjectType DynamicAvoidanceModule::getObjectType(const uint8_t label) const { using autoware_auto_perception_msgs::msg::ObjectClassification; if (label == ObjectClassification::CAR && parameters_->avoid_car) { - return true; + return ObjectType::REGULATED; } if (label == ObjectClassification::TRUCK && parameters_->avoid_truck) { - return true; + return ObjectType::REGULATED; } if (label == ObjectClassification::BUS && parameters_->avoid_bus) { - return true; + return ObjectType::REGULATED; } if (label == ObjectClassification::TRAILER && parameters_->avoid_trailer) { - return true; + return ObjectType::REGULATED; } if (label == ObjectClassification::UNKNOWN && parameters_->avoid_unknown) { - return true; + return ObjectType::UNREGULATED; } if (label == ObjectClassification::BICYCLE && parameters_->avoid_bicycle) { - return true; + return ObjectType::UNREGULATED; } if (label == ObjectClassification::MOTORCYCLE && parameters_->avoid_motorcycle) { - return true; + return ObjectType::REGULATED; } if (label == ObjectClassification::PEDESTRIAN && parameters_->avoid_pedestrian) { - return true; + return ObjectType::UNREGULATED; } - return false; + return ObjectType::OUT_OF_SCOPE; } -void DynamicAvoidanceModule::updateTargetObjects() +void DynamicAvoidanceModule::registerRegulatedObjects( + const std::vector & prev_objects) { const auto input_path = getPreviousModuleOutput().path; const auto & predicted_objects = planner_data_->dynamic_object->objects; - const auto input_ref_path_points = getPreviousModuleOutput().reference_path.points; - const auto prev_objects = target_objects_manager_.getValidObjects(); - - updateRefPathBeforeLaneChange(input_ref_path_points); - - const auto & ego_pose = getEgoPose(); - const double ego_vel = getEgoSpeed(); - const auto ego_lat_feasible_paths = generateLateralFeasiblePaths(ego_pose, ego_vel); - - // 1. Rough filtering of target objects - target_objects_manager_.initialize(); for (const auto & predicted_object : predicted_objects) { const auto obj_uuid = tier4_autoware_utils::toHexString(predicted_object.object_id); const auto & obj_pose = predicted_object.kinematics.initial_pose_with_covariance.pose; @@ -474,9 +506,7 @@ void DynamicAvoidanceModule::updateTargetObjects() [](const PredictedPath & a, const PredictedPath & b) { return a.confidence < b.confidence; }); // 1.a. check label - const bool is_label_target_obstacle = - isLabelTargetObstacle(predicted_object.classification.front().label); - if (!is_label_target_obstacle) { + if (getObjectType(predicted_object.classification.front().label) != ObjectType::REGULATED) { continue; } @@ -543,10 +573,92 @@ void DynamicAvoidanceModule::updateTargetObjects() latest_time_inside_ego_path); target_objects_manager_.updateObject(obj_uuid, target_object); } - target_objects_manager_.finalize(ego_lat_feasible_paths); +} + +void DynamicAvoidanceModule::registerUnregulatedObjects( + const std::vector & prev_objects) +{ + const auto input_path = getPreviousModuleOutput().path; + const auto & predicted_objects = planner_data_->dynamic_object->objects; + + for (const auto & predicted_object : predicted_objects) { + const auto obj_uuid = tier4_autoware_utils::toHexString(predicted_object.object_id); + const auto & obj_pose = predicted_object.kinematics.initial_pose_with_covariance.pose; + const double obj_vel_norm = std::hypot( + predicted_object.kinematics.initial_twist_with_covariance.twist.linear.x, + predicted_object.kinematics.initial_twist_with_covariance.twist.linear.y); + const auto prev_object = getObstacleFromUuid(prev_objects, obj_uuid); + const auto obj_path = *std::max_element( + predicted_object.kinematics.predicted_paths.begin(), + predicted_object.kinematics.predicted_paths.end(), + [](const PredictedPath & a, const PredictedPath & b) { return a.confidence < b.confidence; }); + + // 1.a. Check if the obstacle is labeled as pedestrians, bicycle or similar. + if (getObjectType(predicted_object.classification.front().label) != ObjectType::UNREGULATED) { + continue; + } + + // 1.b. Check if the object's velocity is within the module's coverage range. + const auto [obj_tangent_vel, obj_normal_vel] = + projectObstacleVelocityToTrajectory(input_path.points, predicted_object); + if ( + obj_vel_norm < parameters_->min_obstacle_vel || + obj_vel_norm > parameters_->max_obstacle_vel) { + continue; + } + + // 1.c. Check if object' lateral velocity is small enough to be avoid. + if (std::abs(obj_normal_vel) > parameters_->max_pedestrian_crossing_vel) { + RCLCPP_INFO_EXPRESSION( + getLogger(), parameters_->enable_debug_info, + "[DynamicAvoidance] Ignore obstacle (%s) since it crosses the ego's path with its normal " + "vel (%5.2f) m/s.", + obj_uuid.c_str(), obj_normal_vel); + continue; + } + + // Blocks for compatibility with existing code + // 1.e. check if object lateral distance to ego's path is small enough + // 1.f. calculate the object is on ego's path or not + + const double dist_obj_center_to_path = + std::abs(motion_utils::calcLateralOffset(input_path.points, obj_pose.position)); + const bool is_object_on_ego_path = + dist_obj_center_to_path < + planner_data_->parameters.vehicle_width / 2.0 + parameters_->min_obj_lat_offset_to_ego_path; + + // 1.g. calculate last time inside ego's path + const auto latest_time_inside_ego_path = [&]() -> std::optional { + if (!prev_object || !prev_object->latest_time_inside_ego_path) { + if (is_object_on_ego_path) { + return clock_->now(); + } + return std::nullopt; + } + if (is_object_on_ego_path) { + return clock_->now(); + } + return *prev_object->latest_time_inside_ego_path; + }(); + + // register the object + const auto target_object = DynamicAvoidanceObject( + predicted_object, obj_tangent_vel, obj_normal_vel, is_object_on_ego_path, + latest_time_inside_ego_path); + target_objects_manager_.updateObject(obj_uuid, target_object); + } +} + +void DynamicAvoidanceModule::determineWhetherToAvoidAgainstRegulatedObjects( + const std::vector & prev_objects) +{ + const auto & input_path = getPreviousModuleOutput().path; - // 2. Precise filtering of target objects and check if they should be avoided for (const auto & object : target_objects_manager_.getValidObjects()) { + if (getObjectType(object.label) != ObjectType::REGULATED) { + continue; + } + const auto obj_uuid = object.uuid; const auto prev_object = getObstacleFromUuid(prev_objects, obj_uuid); const auto obj_path = *std::max_element( @@ -651,7 +763,7 @@ void DynamicAvoidanceModule::updateTargetObjects() const double signed_dist_ego_to_obj = [&]() { const size_t ego_seg_idx = planner_data_->findEgoSegmentIndex(input_path.points); const double lon_offset_ego_to_obj = motion_utils::calcSignedArcLength( - input_path.points, ego_pose.position, ego_seg_idx, lat_lon_offset.nearest_idx); + input_path.points, getEgoPose().position, ego_seg_idx, lat_lon_offset.nearest_idx); if (0 < lon_offset_ego_to_obj) { return std::max( 0.0, lon_offset_ego_to_obj - planner_data_->parameters.front_overhang + @@ -676,9 +788,10 @@ void DynamicAvoidanceModule::updateTargetObjects() const auto lon_offset_to_avoid = calcMinMaxLongitudinalOffsetToAvoid( ref_path_points_for_obj_poly, object.pose, obj_points, object.vel, obj_path, object.shape, time_while_collision); - const auto lat_offset_to_avoid = calcMinMaxLateralOffsetToAvoid( + const auto lat_offset_to_avoid = calcMinMaxLateralOffsetToAvoidRegulatedObject( ref_path_points_for_obj_poly, obj_points, object.pose.position, object.vel, is_collision_left, object.lat_vel, prev_object); + if (!lat_offset_to_avoid) { RCLCPP_INFO_EXPRESSION( getLogger(), parameters_->enable_debug_info, @@ -693,8 +806,68 @@ void DynamicAvoidanceModule::updateTargetObjects() obj_uuid, lon_offset_to_avoid, *lat_offset_to_avoid, is_collision_left, should_be_avoided, ref_path_points_for_obj_poly); } + // prev_input_ref_path_points_ = input_ref_path_points; +} + +void DynamicAvoidanceModule::determineWhetherToAvoidAgainstUnregulatedObjects( + const std::vector & prev_objects) +{ + const auto & input_path = getPreviousModuleOutput().path; + + for (const auto & object : target_objects_manager_.getValidObjects()) { + if (getObjectType(object.label) != ObjectType::UNREGULATED) { + continue; + } + + const auto obj_uuid = object.uuid; + const auto & ref_path_points_for_obj_poly = input_path.points; + + // 2.g. check if the ego is not ahead of the object. + const auto lat_lon_offset = + getLateralLongitudinalOffset(input_path.points, object.pose, object.shape); + const double signed_dist_ego_to_obj = [&]() { + const size_t ego_seg_idx = planner_data_->findEgoSegmentIndex(input_path.points); + const double lon_offset_ego_to_obj = motion_utils::calcSignedArcLength( + input_path.points, getEgoPose().position, ego_seg_idx, lat_lon_offset.nearest_idx); + if (0 < lon_offset_ego_to_obj) { + return std::max( + 0.0, lon_offset_ego_to_obj - planner_data_->parameters.front_overhang + + lat_lon_offset.min_lon_offset); + } + return std::min( + 0.0, lon_offset_ego_to_obj + planner_data_->parameters.rear_overhang + + lat_lon_offset.max_lon_offset); + }(); + if (signed_dist_ego_to_obj < 0) { + RCLCPP_INFO_EXPRESSION( + getLogger(), parameters_->enable_debug_info, + "[DynamicAvoidance] Ignore obstacle (%s) since distance from ego to object (%f) is less " + "than 0.", + obj_uuid.c_str(), signed_dist_ego_to_obj); + continue; + } + + // 2.h. calculate longitudinal and lateral offset to avoid to generate object polygon by + // "ego_path_base" + const auto lat_offset_to_avoid = calcMinMaxLateralOffsetToAvoidUnregulatedObject( + ref_path_points_for_obj_poly, getObstacleFromUuid(prev_objects, obj_uuid), object); + if (!lat_offset_to_avoid) { + RCLCPP_INFO_EXPRESSION( + getLogger(), parameters_->enable_debug_info, + "[DynamicAvoidance] Ignore obstacle (%s) since the object will intersects the ego's path " + "enough", + obj_uuid.c_str()); + continue; + } - prev_input_ref_path_points_ = input_ref_path_points; + const bool is_collision_left = (lat_offset_to_avoid.value().max_value > 0.0); + const auto lon_offset_to_avoid = MinMaxValue{0.0, 1.0}; // not used. dummy value + + const bool should_be_avoided = true; + target_objects_manager_.updateObjectVariables( + obj_uuid, lon_offset_to_avoid, *lat_offset_to_avoid, is_collision_left, should_be_avoided, + ref_path_points_for_obj_poly); + } } LatFeasiblePaths DynamicAvoidanceModule::generateLateralFeasiblePaths( @@ -706,6 +879,7 @@ LatFeasiblePaths DynamicAvoidanceModule::generateLateralFeasiblePaths( LatFeasiblePaths ego_lat_feasible_paths; for (double t = 0; t < 10.0; t += 1.0) { + // maybe this equation does not have physical meaning (takagi) const double feasible_lat_offset = lat_acc * std::pow(std::max(t - delay_time, 0.0), 2) / 2.0 + lat_jerk * std::pow(std::max(t - delay_time, 0.0), 3) / 6.0 - planner_data_->parameters.vehicle_width / 2.0; @@ -733,7 +907,7 @@ LatFeasiblePaths DynamicAvoidanceModule::generateLateralFeasiblePaths( return ego_lat_feasible_paths; } -void DynamicAvoidanceModule::updateRefPathBeforeLaneChange( +[[maybe_unused]] void DynamicAvoidanceModule::updateRefPathBeforeLaneChange( const std::vector & ego_ref_path_points) { if (ref_path_before_lane_change_) { @@ -1204,7 +1378,8 @@ double DynamicAvoidanceModule::calcValidLengthToAvoid( return motion_utils::calcSignedArcLength(obj_path.path, 0, valid_obj_path_end_idx); } -std::optional DynamicAvoidanceModule::calcMinMaxLateralOffsetToAvoid( +// min value denotes near side, max value denotes far side +std::optional DynamicAvoidanceModule::calcMinMaxLateralOffsetToAvoidRegulatedObject( const std::vector & ref_path_points_for_obj_poly, const Polygon2d & obj_points, const geometry_msgs::msg::Point & obj_pos, const double obj_vel, const bool is_collision_left, const double obj_normal_vel, @@ -1297,6 +1472,89 @@ std::optional DynamicAvoidanceModule::calcMinMaxLateralOffsetToAvoi return MinMaxValue{filtered_min_bound_lat_offset, max_bound_lat_offset}; } +// min value denotes near side, max value denotes far side +std::optional DynamicAvoidanceModule::calcMinMaxLateralOffsetToAvoidUnregulatedObject( + const std::vector & ref_path_points_for_obj_poly, + const std::optional & prev_object, + const DynamicAvoidanceObject & object) const +{ + const bool enable_lowpass_filter = [&]() { + if ( + !prev_object || prev_object->ref_path_points_for_obj_poly.size() < 2 || + ref_path_points_for_obj_poly.size() < 2) { + return true; + } + const size_t obj_point_idx = + motion_utils::findNearestIndex(ref_path_points_for_obj_poly, object.pose.position); + const double paths_lat_diff = std::abs(motion_utils::calcLateralOffset( + prev_object->ref_path_points_for_obj_poly, + ref_path_points_for_obj_poly.at(obj_point_idx).point.pose.position)); + + constexpr double min_paths_lat_diff = 0.3; + if (paths_lat_diff < min_paths_lat_diff) { + return true; + } + // NOTE: When the input reference path laterally changes, the low-pass filter is disabled not to + // shift the obstacle polygon suddenly. + return false; + }(); + + const auto obj_occupancy_region = [&]() { + const auto obj_points = tier4_autoware_utils::toPolygon2d(object.pose, object.shape); + std::vector lat_pos_vec; + for (size_t i = 0; i < obj_points.outer().size(); ++i) { + const auto geom_obj_point = toGeometryPoint(obj_points.outer().at(i)); + const double obj_point_lat_offset = motion_utils::calcLateralOffset( + ref_path_points_for_obj_poly, geom_obj_point, + motion_utils::findNearestSegmentIndex(ref_path_points_for_obj_poly, geom_obj_point)); + lat_pos_vec.push_back(obj_point_lat_offset); + } + const auto current_pos_area = getMinMaxValues(lat_pos_vec); + return combineMinMaxValues(current_pos_area, current_pos_area + object.lat_vel * 3.0); + }(); + + if ( + obj_occupancy_region.min_value * obj_occupancy_region.max_value < 0.0 || + obj_occupancy_region.max_value - obj_occupancy_region.min_value < 1e-3) { + return std::nullopt; + } + + // calculate bound pos + const auto bound_pos = [&]() { + auto temp_bound_pos = obj_occupancy_region; + temp_bound_pos.max_value += parameters_->lat_offset_from_obstacle; + temp_bound_pos.min_value -= parameters_->lat_offset_from_obstacle; + if (std::abs(temp_bound_pos.max_value) < std::abs(temp_bound_pos.min_value)) { + temp_bound_pos.swap(); // From here, min denotes near bound, max denotes far bound. + } + + const double near_bound_limit = + planner_data_->parameters.vehicle_width / 2.0 - parameters_->max_lat_offset_to_avoid; + if (temp_bound_pos.max_value > 0.0) { + temp_bound_pos.min_value = std::max(temp_bound_pos.min_value, near_bound_limit); + } else { + temp_bound_pos.min_value = std::min(temp_bound_pos.min_value, -near_bound_limit); + } + return temp_bound_pos; + }(); + + // low pass filter for min_bound + const auto prev_min_lat_avoid_to_offset = [&]() -> std::optional { + if (!prev_object || !prev_object->lat_offset_to_avoid) { + return std::nullopt; + } + return prev_object->lat_offset_to_avoid->min_value; + }(); + const double filtered_min_bound_pos = + (prev_min_lat_avoid_to_offset.has_value() & enable_lowpass_filter) + ? signal_processing::lowpassFilter( + bound_pos.min_value, *prev_min_lat_avoid_to_offset, + parameters_->lpf_gain_for_lat_avoid_to_offset) + : bound_pos.min_value; + + return MinMaxValue{filtered_min_bound_pos, bound_pos.max_value}; +} + // NOTE: object does not have const only to update min_bound_lat_offset. std::optional DynamicAvoidanceModule::calcEgoPathBasedDynamicObstaclePolygon( @@ -1310,7 +1568,7 @@ DynamicAvoidanceModule::calcEgoPathBasedDynamicObstaclePolygon( const size_t obj_seg_idx = motion_utils::findNearestSegmentIndex(ref_path_points_for_obj_poly, object.pose.position); - const auto obj_points = tier4_autoware_utils::toPolygon2d(object.pose, object.shape); + // const auto obj_points = tier4_autoware_utils::toPolygon2d(object.pose, object.shape); const auto lon_bound_start_idx_opt = motion_utils::insertTargetPoint( obj_seg_idx, object.lon_offset_to_avoid->min_value, ref_path_points_for_obj_poly); @@ -1403,6 +1661,7 @@ DynamicAvoidanceModule::calcEgoPathBasedDynamicObstaclePolygon( return obj_poly; } +// should be replace by the function calcPredictedPathBasedDynamicObstaclePolygon() (takagi) std::optional DynamicAvoidanceModule::calcObjectPathBasedDynamicObstaclePolygon( const DynamicAvoidanceObject & object) const @@ -1458,4 +1717,145 @@ DynamicAvoidanceModule::calcObjectPathBasedDynamicObstaclePolygon( boost::geometry::correct(obj_poly); return obj_poly; } + +// Calculate polygons according to predicted_path with certain confidence, +// except for the area required for ego safety. +// input: an object, the minimum area required for ego safety, and some global params +std::optional +DynamicAvoidanceModule::calcPredictedPathBasedDynamicObstaclePolygon( + const DynamicAvoidanceObject & object, const EgoPathReservePoly & ego_path_poly) const +{ + std::vector obj_poses; + for (const auto & predicted_path : object.predicted_paths) { + if (predicted_path.confidence < parameters_->threshold_confidence) continue; + + double time_count = 0.0; + for (const auto & pose : predicted_path.path) { + obj_poses.push_back(pose); + time_count += predicted_path.time_step.sec + predicted_path.time_step.nanosec * 1e-9; + if (time_count > parameters_->end_time_to_consider + 1e-3) break; + } + } + + tier4_autoware_utils::Polygon2d obj_points_as_poly; + for (const auto pose : obj_poses) { + boost::geometry::append( + obj_points_as_poly, tier4_autoware_utils::toFootprint( + pose, object.shape.dimensions.x * 0.5, object.shape.dimensions.x * 0.5, + object.shape.dimensions.y * 0.5) + .outer()); + } + boost::geometry::correct(obj_points_as_poly); + Polygon2d obj_poly; + boost::geometry::convex_hull(obj_points_as_poly, obj_poly); + + tier4_autoware_utils::MultiPolygon2d expanded_poly; + namespace strategy = boost::geometry::strategy::buffer; + boost::geometry::buffer( + obj_poly, expanded_poly, + strategy::distance_symmetric(parameters_->margin_distance_around_pedestrian), + strategy::side_straight(), strategy::join_round(), strategy::end_flat(), + strategy::point_circle()); + if (expanded_poly.empty()) return {}; + + tier4_autoware_utils::MultiPolygon2d output_poly; + boost::geometry::difference( + expanded_poly[0], + object.is_collision_left ? ego_path_poly.right_avoid : ego_path_poly.left_avoid, output_poly); + + if (output_poly.empty()) { + RCLCPP_INFO_EXPRESSION( + getLogger(), parameters_->enable_debug_info, + "[DynamicAvoidance] Ignore obstacle (%s) because it stay inside the ego's path.", + object.uuid.c_str()); + return {}; + } else if (output_poly.size() >= 2) { + RCLCPP_INFO_EXPRESSION( + getLogger(), parameters_->enable_debug_info, + "[DynamicAvoidance] Ignore obstacle (%s) because it covers the ego's path.", + object.uuid.c_str()); + return {}; + } + + return output_poly[0]; +} + +// Calculate the driving area required to ensure the safety of the own vehicle. +// It is assumed that this area will not be clipped. +// input: ego's reference path, ego's pose, ego's speed, and some global params +DynamicAvoidanceModule::EgoPathReservePoly DynamicAvoidanceModule::calcEgoPathReservePoly( + const PathWithLaneId & ego_path) const +{ + // This function require almost 0.5 ms. Should be refactored in the future + // double calculation_time; + // stop_watch_.tic(std::string(__func__)); + + namespace strategy = boost::geometry::strategy::buffer; + + assert(!ego_path.points.empty()); + + tier4_autoware_utils::LineString2d ego_path_lines; + for (const auto & path_point : ego_path.points) { + ego_path_lines.push_back(tier4_autoware_utils::fromMsg(path_point.point.pose.position).to_2d()); + } + + auto calcReservePoly = [&ego_path_lines]( + const strategy::distance_asymmetric path_expand_strategy, + const strategy::distance_asymmetric steer_expand_strategy, + const std::vector & outer_body_path) + -> tier4_autoware_utils::Polygon2d { + // reserve area based on the reference path + tier4_autoware_utils::MultiPolygon2d path_poly; + boost::geometry::buffer( + ego_path_lines, path_poly, path_expand_strategy, strategy::side_straight(), + strategy::join_round(), strategy::end_flat(), strategy::point_circle()); + + // reserve area steer to the avoidance path + tier4_autoware_utils::LineString2d steer_lines; + for (const auto & point : outer_body_path) { + const auto bg_point = tier4_autoware_utils::fromMsg(point).to_2d(); + if (boost::geometry::within(bg_point, path_poly)) { + if (steer_lines.size() != 0) { + ; + // boost::geometry::append(steer_lines, bg_point); + } + break; + } + // boost::geometry::append(steer_lines, bg_point); + } + tier4_autoware_utils::MultiPolygon2d steer_poly; + boost::geometry::buffer( + steer_lines, steer_poly, steer_expand_strategy, strategy::side_straight(), + strategy::join_round(), strategy::end_flat(), strategy::point_circle()); + + tier4_autoware_utils::MultiPolygon2d output_poly; + boost::geometry::union_(path_poly, steer_poly, output_poly); + if (output_poly.size() != 1) { + assert(false); + } + return output_poly[0]; + }; + + const auto motion_saturated_outer_paths = + generateLateralFeasiblePaths(getEgoPose(), getEgoSpeed()); + + const double vehicle_half_width = planner_data_->parameters.vehicle_width * 0.5; + const double reserve_width_obj_side = vehicle_half_width - parameters_->max_lat_offset_to_avoid; + + const tier4_autoware_utils::Polygon2d left_avoid_poly = calcReservePoly( + strategy::distance_asymmetric(vehicle_half_width, reserve_width_obj_side), + strategy::distance_asymmetric(vehicle_half_width, 0.0), + motion_saturated_outer_paths.right_path); + const tier4_autoware_utils::Polygon2d right_avoid_poly = calcReservePoly( + strategy::distance_asymmetric(reserve_width_obj_side, vehicle_half_width), + strategy::distance_asymmetric(0.0, vehicle_half_width), + motion_saturated_outer_paths.left_path); + + // calculation_time = stop_watch_.toc(std::string(__func__)); + // RCLCPP_INFO_STREAM_EXPRESSION( + // getLogger(), parameters_->enable_debug_info, __func__ << ":=" << calculation_time << "[ms]"); + + return {left_avoid_poly, right_avoid_poly}; +} + } // namespace behavior_path_planner diff --git a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/geometric_pull_over.hpp b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/geometric_pull_over.hpp index 6de1a726d4d4e..e67d458874d17 100644 --- a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/geometric_pull_over.hpp +++ b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/geometric_pull_over.hpp @@ -16,7 +16,6 @@ #define BEHAVIOR_PATH_GOAL_PLANNER_MODULE__GEOMETRIC_PULL_OVER_HPP_ #include "behavior_path_goal_planner_module/pull_over_planner_base.hpp" -#include "behavior_path_planner_common/utils/occupancy_grid_based_collision_detector/occupancy_grid_based_collision_detector.hpp" #include "behavior_path_planner_common/utils/parking_departure/geometric_parallel_parking.hpp" #include @@ -34,9 +33,7 @@ class GeometricPullOver : public PullOverPlannerBase public: GeometricPullOver( rclcpp::Node & node, const GoalPlannerParameters & parameters, - const LaneDepartureChecker & lane_departure_checker, - const std::shared_ptr occupancy_grid_map, - const bool is_forward); + const LaneDepartureChecker & lane_departure_checker, const bool is_forward); PullOverPlannerType getPlannerType() const override { @@ -61,7 +58,6 @@ class GeometricPullOver : public PullOverPlannerBase protected: ParallelParkingParameters parallel_parking_parameters_; LaneDepartureChecker lane_departure_checker_{}; - std::shared_ptr occupancy_grid_map_; bool is_forward_{true}; bool left_side_parking_{true}; diff --git a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_planner_module.hpp b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_planner_module.hpp index 21ea06531c2f4..8f456a57e4c78 100644 --- a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_planner_module.hpp +++ b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_planner_module.hpp @@ -91,6 +91,33 @@ public: \ DEFINE_SETTER_WITH_MUTEX(TYPE, NAME) \ DEFINE_GETTER_WITH_MUTEX(TYPE, NAME) +enum class DecidingPathStatus { + NOT_DECIDED, + DECIDING, + DECIDED, +}; +using DecidingPathStatusWithStamp = std::pair; + +struct PreviousPullOverData +{ + struct SafetyStatus + { + std::optional safe_start_time{}; + bool is_safe{false}; + }; + + void reset() + { + found_path = false; + safety_status = SafetyStatus{}; + deciding_path_status = DecidingPathStatusWithStamp{}; + } + + bool found_path{false}; + SafetyStatus safety_status{}; + DecidingPathStatusWithStamp deciding_path_status{}; +}; + class ThreadSafeData { public: @@ -145,6 +172,9 @@ class ThreadSafeData void set(const std::shared_ptr & arg) { set_pull_over_path(arg); } void set(const PullOverPath & arg) { set_pull_over_path(arg); } void set(const GoalCandidate & arg) { set_modified_goal_pose(arg); } + void set(const BehaviorModuleOutput & arg) { set_last_previous_module_output(arg); } + void set(const PreviousPullOverData & arg) { set_prev_data(arg); } + void set(const CollisionCheckDebugMap & arg) { set_collision_check(arg); } void clearPullOverPath() { @@ -182,6 +212,8 @@ class ThreadSafeData last_path_update_time_ = std::nullopt; last_path_idx_increment_time_ = std::nullopt; closest_start_pose_ = std::nullopt; + last_previous_module_output_ = std::nullopt; + prev_data_.reset(); } DEFINE_GETTER_WITH_MUTEX(std::shared_ptr, pull_over_path) @@ -193,6 +225,9 @@ class ThreadSafeData DEFINE_SETTER_GETTER_WITH_MUTEX(GoalCandidates, goal_candidates) DEFINE_SETTER_GETTER_WITH_MUTEX(std::optional, modified_goal_pose) DEFINE_SETTER_GETTER_WITH_MUTEX(std::optional, closest_start_pose) + DEFINE_SETTER_GETTER_WITH_MUTEX(std::optional, last_previous_module_output) + DEFINE_SETTER_GETTER_WITH_MUTEX(PreviousPullOverData, prev_data) + DEFINE_SETTER_GETTER_WITH_MUTEX(CollisionCheckDebugMap, collision_check) private: std::shared_ptr pull_over_path_{nullptr}; @@ -203,6 +238,9 @@ class ThreadSafeData std::optional last_path_update_time_; std::optional last_path_idx_increment_time_; std::optional closest_start_pose_{}; + std::optional last_previous_module_output_{}; + PreviousPullOverData prev_data_{}; + CollisionCheckDebugMap collision_check_{}; std::recursive_mutex & mutex_; rclcpp::Clock::SharedPtr clock_; @@ -234,33 +272,6 @@ struct LastApprovalData Pose pose{}; }; -enum class DecidingPathStatus { - NOT_DECIDED, - DECIDING, - DECIDED, -}; -using DecidingPathStatusWithStamp = std::pair; - -struct PreviousPullOverData -{ - struct SafetyStatus - { - std::optional safe_start_time{}; - bool is_safe{false}; - }; - - void reset() - { - found_path = false; - safety_status = SafetyStatus{}; - deciding_path_status = DecidingPathStatusWithStamp{}; - } - - bool found_path{false}; - SafetyStatus safety_status{}; - DecidingPathStatusWithStamp deciding_path_status{}; -}; - // store stop_pose_ pointer with reason string struct PoseWithString { @@ -363,6 +374,50 @@ class GoalPlannerModule : public SceneModuleInterface CandidateOutput planCandidate() const override { return CandidateOutput{}; } private: + /** + * @brief shared data for onTimer(onTimer/onFreespaceParkingTimer just read this) + */ + struct GoalPlannerData + { + GoalPlannerData(const PlannerData & planner_data, const GoalPlannerParameters & parameters) + { + initializeOccupancyGridMap(planner_data, parameters); + }; + GoalPlannerParameters parameters; + std::shared_ptr ego_predicted_path_params; + std::shared_ptr objects_filtering_params; + std::shared_ptr safety_check_params; + tier4_autoware_utils::LinearRing2d vehicle_footprint; + + PlannerData planner_data; + ModuleStatus current_status; + BehaviorModuleOutput previous_module_output; + // collision detector + // need to be shared_ptr to be used in planner and goal searcher + std::shared_ptr occupancy_grid_map; + std::shared_ptr goal_searcher; + + const BehaviorModuleOutput & getPreviousModuleOutput() const { return previous_module_output; } + const ModuleStatus & getCurrentStatus() const { return current_status; } + void updateOccupancyGrid(); + GoalPlannerData clone() const; + void update( + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params_, + const std::shared_ptr & objects_filtering_params_, + const std::shared_ptr & safety_check_params_, + const PlannerData & planner_data, const ModuleStatus & current_status, + const BehaviorModuleOutput & previous_module_output, + const std::shared_ptr goal_searcher_, + const tier4_autoware_utils::LinearRing2d & vehicle_footprint); + + private: + void initializeOccupancyGridMap( + const PlannerData & planner_data, const GoalPlannerParameters & parameters); + }; + std::optional gp_planner_data_{std::nullopt}; + std::mutex gp_planner_data_mutex_; + // Flag class for managing whether a certain callback is running in multi-threading class ScopedFlag { @@ -420,9 +475,10 @@ class GoalPlannerModule : public SceneModuleInterface // goal searcher std::shared_ptr goal_searcher_; - // collision detector - // need to be shared_ptr to be used in planner and goal searcher - std::shared_ptr occupancy_grid_map_; + // NOTE: this is latest occupancy_grid_map pointer which the local planner_data on + // onFreespaceParkingTimer thread storage may point to while calculation. + // onTimer/onFreespaceParkingTimer and their callees MUST NOT use this + std::shared_ptr occupancy_grid_map_{nullptr}; // check stopped and stuck state std::deque odometry_buffer_stopped_; @@ -431,10 +487,10 @@ class GoalPlannerModule : public SceneModuleInterface tier4_autoware_utils::LinearRing2d vehicle_footprint_; std::recursive_mutex mutex_; - ThreadSafeData thread_safe_data_; + // TODO(Mamoru Sobue): isSafePath() modifies ThreadSafeData::check_collision, avoid this mutable + mutable ThreadSafeData thread_safe_data_; std::unique_ptr last_approval_data_{nullptr}; - PreviousPullOverData prev_data_{}; // approximate distance from the start point to the end point of pull_over. // this is used as an assumed value to decelerate, etc., before generating the actual path. @@ -460,11 +516,12 @@ class GoalPlannerModule : public SceneModuleInterface mutable PoseWithString debug_stop_pose_with_info_; // collision check - void initializeOccupancyGridMap(); - void updateOccupancyGrid(); - bool checkOccupancyGridCollision(const PathWithLaneId & path) const; + bool checkOccupancyGridCollision( + const PathWithLaneId & path, + const std::shared_ptr occupancy_grid_map) const; bool checkObjectsCollision( - const PathWithLaneId & path, const double collision_check_margin, + const PathWithLaneId & path, const std::shared_ptr planner_data, + const GoalPlannerParameters & parameters, const double collision_check_margin, const bool extract_static_objects, const bool update_debug_data = false) const; // goal seach @@ -487,19 +544,46 @@ class GoalPlannerModule : public SceneModuleInterface bool isStopped( std::deque & odometry_buffer, const double time); bool hasFinishedCurrentPath(); - bool isOnModifiedGoal() const; + bool isOnModifiedGoal(const Pose & current_pose, const GoalPlannerParameters & parameters) const; double calcModuleRequestLength() const; - bool needPathUpdate(const double path_update_duration) const; - bool isStuck(); - bool hasDecidedPath() const; - bool hasNotDecidedPath() const; - DecidingPathStatusWithStamp checkDecidingPathStatus() const; + bool needPathUpdate( + const Pose & current_pose, const double path_update_duration, + const GoalPlannerParameters & parameters) const; + bool isStuck( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters); + bool hasDecidedPath( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const; + bool hasNotDecidedPath( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const; + DecidingPathStatusWithStamp checkDecidingPathStatus( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const; void decideVelocity(); bool foundPullOverPath() const; void updateStatus(const BehaviorModuleOutput & output); // validation - bool hasEnoughDistance(const PullOverPath & pull_over_path) const; + bool hasEnoughDistance( + const PullOverPath & pull_over_path, const PathWithLaneId & long_tail_reference_path) const; bool isCrossingPossible( const lanelet::ConstLanelet & start_lane, const lanelet::ConstLanelet & end_lane) const; bool isCrossingPossible( @@ -508,7 +592,10 @@ class GoalPlannerModule : public SceneModuleInterface bool hasEnoughTimePassedSincePathUpdate(const double duration) const; // freespace parking - bool planFreespacePath(); + bool planFreespacePath( + std::shared_ptr planner_data, + const std::shared_ptr goal_searcher, + const std::shared_ptr occupancy_grid_map); bool canReturnToLaneParking(); // plan pull over path @@ -537,10 +624,12 @@ class GoalPlannerModule : public SceneModuleInterface TurnSignalInfo calcTurnSignalInfo(); std::optional ignore_signal_{std::nullopt}; - std::optional last_previous_module_output_{}; - bool hasPreviousModulePathShapeChanged() const; - bool hasDeviatedFromLastPreviousModulePath() const; - bool hasDeviatedFromCurrentPreviousModulePath() const; + bool hasPreviousModulePathShapeChanged(const BehaviorModuleOutput & previous_module_output) const; + bool hasDeviatedFromLastPreviousModulePath( + const std::shared_ptr planner_data) const; + bool hasDeviatedFromCurrentPreviousModulePath( + const std::shared_ptr planner_data, + const BehaviorModuleOutput & previous_module_output) const; // timer for generating pull over path candidates in a separate thread void onTimer(); @@ -556,16 +645,22 @@ class GoalPlannerModule : public SceneModuleInterface // safety check void initializeSafetyCheckParameters(); SafetyCheckParams createSafetyCheckParams() const; + /* void updateSafetyCheckTargetObjectsData( const PredictedObjects & filtered_objects, const TargetObjectsOnLane & target_objects_on_lane, const std::vector & ego_predicted_path) const; + */ /** * @brief Checks if the current path is safe. * @return std::pair * first: If the path is safe for a certain period of time, true. * second: If the path is safe in the current state, true. */ - std::pair isSafePath() const; + std::pair isSafePath( + const std::shared_ptr planner_data, const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params) const; // debug void setDebugData(); diff --git a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher.hpp b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher.hpp index f228ecc378c28..89f4086874183 100644 --- a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher.hpp +++ b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher.hpp @@ -29,33 +29,45 @@ using BasicPolygons2d = std::vector; class GoalSearcher : public GoalSearcherBase { public: - GoalSearcher( - const GoalPlannerParameters & parameters, const LinearRing2d & vehicle_footprint, - const std::shared_ptr & occupancy_grid_map); + GoalSearcher(const GoalPlannerParameters & parameters, const LinearRing2d & vehicle_footprint); - GoalCandidates search() override; - void update(GoalCandidates & goal_candidates) const override; + GoalCandidates search( + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) override; + void update( + GoalCandidates & goal_candidates, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const override; // todo(kosuke55): Functions for this specific use should not be in the interface, // so it is better to consider interface design when we implement other goal searchers. GoalCandidate getClosetGoalCandidateAlongLanes( - const GoalCandidates & goal_candidates) const override; + const GoalCandidates & goal_candidates, + const std::shared_ptr & planner_data) const override; bool isSafeGoalWithMarginScaleFactor( - const GoalCandidate & goal_candidate, const double margin_scale_factor) const override; + const GoalCandidate & goal_candidate, const double margin_scale_factor, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const override; private: void countObjectsToAvoid( - GoalCandidates & goal_candidates, const PredictedObjects & objects) const; - void createAreaPolygons(std::vector original_search_poses); - bool checkCollision(const Pose & pose, const PredictedObjects & objects) const; + GoalCandidates & goal_candidates, const PredictedObjects & objects, + const std::shared_ptr & planner_data) const; + void createAreaPolygons( + std::vector original_search_poses, + const std::shared_ptr & planner_data); + bool checkCollision( + const Pose & pose, const PredictedObjects & objects, + const std::shared_ptr occupancy_grid_map) const; bool checkCollisionWithLongitudinalDistance( - const Pose & ego_pose, const PredictedObjects & objects) const; + const Pose & ego_pose, const PredictedObjects & objects, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const; BasicPolygons2d getNoParkingAreaPolygons(const lanelet::ConstLanelets & lanes) const; BasicPolygons2d getNoStoppingAreaPolygons(const lanelet::ConstLanelets & lanes) const; bool isInAreas(const LinearRing2d & footprint, const BasicPolygons2d & areas) const; LinearRing2d vehicle_footprint_{}; - std::shared_ptr occupancy_grid_map_{}; bool left_side_parking_{true}; }; } // namespace behavior_path_planner diff --git a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher_base.hpp b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher_base.hpp index 2ddacc0aac46d..f5d879358cd38 100644 --- a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher_base.hpp +++ b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/goal_searcher_base.hpp @@ -17,6 +17,7 @@ #include "behavior_path_goal_planner_module/goal_planner_parameters.hpp" #include "behavior_path_planner_common/data_manager.hpp" +#include "behavior_path_planner_common/utils/occupancy_grid_based_collision_detector/occupancy_grid_based_collision_detector.hpp" #include @@ -49,23 +50,29 @@ class GoalSearcherBase { reference_goal_pose_ = reference_goal_pose; } + const Pose & getReferenceGoal() const { return reference_goal_pose_; } - void setPlannerData(const std::shared_ptr & planner_data) + MultiPolygon2d getAreaPolygons() const { return area_polygons_; } + virtual GoalCandidates search( + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) = 0; + virtual void update( + [[maybe_unused]] GoalCandidates & goal_candidates, + [[maybe_unused]] const std::shared_ptr occupancy_grid_map, + [[maybe_unused]] const std::shared_ptr & planner_data) const { - planner_data_ = planner_data; + return; } - - MultiPolygon2d getAreaPolygons() { return area_polygons_; } - virtual GoalCandidates search() = 0; - virtual void update([[maybe_unused]] GoalCandidates & goal_candidates) const { return; } virtual GoalCandidate getClosetGoalCandidateAlongLanes( - const GoalCandidates & goal_candidates) const = 0; + const GoalCandidates & goal_candidates, + const std::shared_ptr & planner_data) const = 0; virtual bool isSafeGoalWithMarginScaleFactor( - const GoalCandidate & goal_candidate, const double margin_scale_factor) const = 0; + const GoalCandidate & goal_candidate, const double margin_scale_factor, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const = 0; protected: GoalPlannerParameters parameters_{}; - std::shared_ptr planner_data_{nullptr}; Pose reference_goal_pose_{}; MultiPolygon2d area_polygons_{}; }; diff --git a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/shift_pull_over.hpp b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/shift_pull_over.hpp index 892ef7d5dd303..d0b0aee83e20c 100644 --- a/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/shift_pull_over.hpp +++ b/planning/behavior_path_goal_planner_module/include/behavior_path_goal_planner_module/shift_pull_over.hpp @@ -16,7 +16,6 @@ #define BEHAVIOR_PATH_GOAL_PLANNER_MODULE__SHIFT_PULL_OVER_HPP_ #include "behavior_path_goal_planner_module/pull_over_planner_base.hpp" -#include "behavior_path_planner_common/utils/occupancy_grid_based_collision_detector/occupancy_grid_based_collision_detector.hpp" #include @@ -34,9 +33,7 @@ class ShiftPullOver : public PullOverPlannerBase public: ShiftPullOver( rclcpp::Node & node, const GoalPlannerParameters & parameters, - const LaneDepartureChecker & lane_departure_checker, - const std::shared_ptr & occupancy_grid_map); - + const LaneDepartureChecker & lane_departure_checker); PullOverPlannerType getPlannerType() const override { return PullOverPlannerType::SHIFT; }; std::optional plan(const Pose & goal_pose) override; @@ -57,7 +54,6 @@ class ShiftPullOver : public PullOverPlannerBase const Pose & start_pose, const Pose & end_pose, const double resample_interval); LaneDepartureChecker lane_departure_checker_{}; - std::shared_ptr occupancy_grid_map_{}; bool left_side_parking_{true}; }; diff --git a/planning/behavior_path_goal_planner_module/src/geometric_pull_over.cpp b/planning/behavior_path_goal_planner_module/src/geometric_pull_over.cpp index b7d1c240d032a..0779002690f8f 100644 --- a/planning/behavior_path_goal_planner_module/src/geometric_pull_over.cpp +++ b/planning/behavior_path_goal_planner_module/src/geometric_pull_over.cpp @@ -27,13 +27,10 @@ namespace behavior_path_planner { GeometricPullOver::GeometricPullOver( rclcpp::Node & node, const GoalPlannerParameters & parameters, - const LaneDepartureChecker & lane_departure_checker, - const std::shared_ptr occupancy_grid_map, - const bool is_forward) + const LaneDepartureChecker & lane_departure_checker, const bool is_forward) : PullOverPlannerBase{node, parameters}, parallel_parking_parameters_{parameters.parallel_parking_parameters}, lane_departure_checker_{lane_departure_checker}, - occupancy_grid_map_{occupancy_grid_map}, is_forward_{is_forward}, left_side_parking_{parameters.parking_policy == ParkingPolicy::LEFT_SIDE} { diff --git a/planning/behavior_path_goal_planner_module/src/goal_planner_module.cpp b/planning/behavior_path_goal_planner_module/src/goal_planner_module.cpp index a890cfc21ed13..9bfef90668e8e 100644 --- a/planning/behavior_path_goal_planner_module/src/goal_planner_module.cpp +++ b/planning/behavior_path_goal_planner_module/src/goal_planner_module.cpp @@ -78,14 +78,14 @@ GoalPlannerModule::GoalPlannerModule( for (const std::string & planner_type : parameters_->efficient_path_order) { if (planner_type == "SHIFT" && parameters_->enable_shift_parking) { - pull_over_planners_.push_back(std::make_shared( - node, *parameters, lane_departure_checker, occupancy_grid_map_)); + pull_over_planners_.push_back( + std::make_shared(node, *parameters, lane_departure_checker)); } else if (planner_type == "ARC_FORWARD" && parameters_->enable_arc_forward_parking) { pull_over_planners_.push_back(std::make_shared( - node, *parameters, lane_departure_checker, occupancy_grid_map_, /*is_forward*/ true)); + node, *parameters, lane_departure_checker, /*is_forward*/ true)); } else if (planner_type == "ARC_BACKWARD" && parameters_->enable_arc_backward_parking) { pull_over_planners_.push_back(std::make_shared( - node, *parameters, lane_departure_checker, occupancy_grid_map_, /*is_forward*/ false)); + node, *parameters, lane_departure_checker, /*is_forward*/ false)); } } @@ -97,8 +97,7 @@ GoalPlannerModule::GoalPlannerModule( // currently there is only one goal_searcher_type const auto vehicle_info = vehicle_info_util::VehicleInfoUtil(node).getVehicleInfo(); vehicle_footprint_ = vehicle_info.createFootprint(); - goal_searcher_ = - std::make_shared(*parameters, vehicle_footprint_, occupancy_grid_map_); + goal_searcher_ = std::make_shared(*parameters, vehicle_footprint_); // timer callback for generating lane parking candidate paths const auto lane_parking_period_ns = rclcpp::Rate(1.0).period(); @@ -123,51 +122,44 @@ GoalPlannerModule::GoalPlannerModule( // Initialize safety checker if (parameters_->safety_check_params.enable_safety_check) { initializeSafetyCheckParameters(); - utils::parking_departure::initializeCollisionCheckDebugMap(goal_planner_data_.collision_check); } - - prev_data_.reset(); -} - -// This function is needed for waiting for planner_data_ -void GoalPlannerModule::updateOccupancyGrid() -{ - if (!planner_data_->occupancy_grid) { - RCLCPP_WARN_THROTTLE(getLogger(), *clock_, 5000, "occupancy_grid is not ready"); - return; - } - occupancy_grid_map_->setMap(*(planner_data_->occupancy_grid)); } -bool GoalPlannerModule::hasPreviousModulePathShapeChanged() const +bool GoalPlannerModule::hasPreviousModulePathShapeChanged( + const BehaviorModuleOutput & previous_module_output) const { - if (!last_previous_module_output_) { + const auto last_previous_module_output = thread_safe_data_.get_last_previous_module_output(); + if (!last_previous_module_output) { return true; } - const auto current_path = getPreviousModuleOutput().path; + const auto current_path = previous_module_output.path; // the terminal distance is far return calcDistance2d( - last_previous_module_output_->path.points.back().point, + last_previous_module_output->path.points.back().point, current_path.points.back().point) > 0.3; } -bool GoalPlannerModule::hasDeviatedFromLastPreviousModulePath() const +bool GoalPlannerModule::hasDeviatedFromLastPreviousModulePath( + const std::shared_ptr planner_data) const { - if (!last_previous_module_output_) { + const auto last_previous_module_output = thread_safe_data_.get_last_previous_module_output(); + if (!last_previous_module_output) { return true; } return std::abs(motion_utils::calcLateralOffset( - last_previous_module_output_->path.points, - planner_data_->self_odometry->pose.pose.position)) > 0.3; + last_previous_module_output->path.points, + planner_data->self_odometry->pose.pose.position)) > 0.3; } -bool GoalPlannerModule::hasDeviatedFromCurrentPreviousModulePath() const +bool GoalPlannerModule::hasDeviatedFromCurrentPreviousModulePath( + const std::shared_ptr planner_data, + const BehaviorModuleOutput & previous_module_output) const { return std::abs(motion_utils::calcLateralOffset( - getPreviousModuleOutput().path.points, - planner_data_->self_odometry->pose.pose.position)) > 0.3; + previous_module_output.path.points, planner_data->self_odometry->pose.pose.position)) > + 0.3; } // generate pull over candidate paths @@ -175,7 +167,50 @@ void GoalPlannerModule::onTimer() { const ScopedFlag flag(is_lane_parking_cb_running_); - if (getCurrentStatus() == ModuleStatus::IDLE) { + std::shared_ptr local_planner_data{nullptr}; + std::optional current_status_opt{std::nullopt}; + std::optional previous_module_output_opt{std::nullopt}; + std::shared_ptr occupancy_grid_map{nullptr}; + std::optional parameters_opt{std::nullopt}; + std::shared_ptr ego_predicted_path_params{nullptr}; + std::shared_ptr objects_filtering_params{nullptr}; + std::shared_ptr safety_check_params{nullptr}; + std::shared_ptr goal_searcher{nullptr}; + + // begin of critical section + { + std::lock_guard guard(gp_planner_data_mutex_); + if (gp_planner_data_) { + const auto & gp_planner_data = gp_planner_data_.value(); + local_planner_data = std::make_shared(gp_planner_data.planner_data); + current_status_opt = gp_planner_data.current_status; + previous_module_output_opt = gp_planner_data.previous_module_output; + occupancy_grid_map = gp_planner_data.occupancy_grid_map; + parameters_opt = gp_planner_data.parameters; + ego_predicted_path_params = gp_planner_data.ego_predicted_path_params; + objects_filtering_params = gp_planner_data.objects_filtering_params; + safety_check_params = gp_planner_data.safety_check_params; + goal_searcher = gp_planner_data.goal_searcher; + } + } + // end of critical section + if ( + !local_planner_data || !current_status_opt || !previous_module_output_opt || + !occupancy_grid_map || !parameters_opt || !ego_predicted_path_params || + !objects_filtering_params || !safety_check_params || !goal_searcher) { + RCLCPP_ERROR( + getLogger(), + "failed to get valid " + "local_planner_data/current_status/previous_module_output/occupancy_grid_map/parameters_opt/" + "ego_predicted_path_params/objects_filtering_params/safety_check_params/goal_searcher in " + "onTimer"); + return; + } + const auto & current_status = current_status_opt.value(); + const auto & previous_module_output = previous_module_output_opt.value(); + const auto & parameters = parameters_opt.value(); + + if (current_status == ModuleStatus::IDLE) { return; } @@ -184,27 +219,31 @@ void GoalPlannerModule::onTimer() return; } - if (!planner_data_ || !utils::isAllowedGoalModification(planner_data_->route_handler)) { + if (!utils::isAllowedGoalModification(local_planner_data->route_handler)) { return; } // check if new pull over path candidates are needed to be generated const bool need_update = std::invoke([&]() { - if (isOnModifiedGoal()) { + if (isOnModifiedGoal(local_planner_data->self_odometry->pose.pose, parameters)) { return false; } - if (hasDeviatedFromCurrentPreviousModulePath()) { + if (hasDeviatedFromCurrentPreviousModulePath(local_planner_data, previous_module_output)) { RCLCPP_DEBUG(getLogger(), "has deviated from current previous module path"); return false; } if (thread_safe_data_.get_pull_over_path_candidates().empty()) { return true; } - if (hasPreviousModulePathShapeChanged()) { + if (hasPreviousModulePathShapeChanged(previous_module_output)) { RCLCPP_DEBUG(getLogger(), "has previous module path shape changed"); return true; } - if (hasDeviatedFromLastPreviousModulePath() && !hasDecidedPath()) { + if ( + hasDeviatedFromLastPreviousModulePath(local_planner_data) && + !hasDecidedPath( + local_planner_data, occupancy_grid_map, parameters, ego_predicted_path_params, + objects_filtering_params, safety_check_params, goal_searcher)) { RCLCPP_DEBUG(getLogger(), "has deviated from last previous module path"); return true; } @@ -214,13 +253,12 @@ void GoalPlannerModule::onTimer() return; } - const auto previous_module_output = getPreviousModuleOutput(); const auto goal_candidates = thread_safe_data_.get_goal_candidates(); // generate valid pull over path candidates and calculate closest start pose const auto current_lanes = utils::getExtendedCurrentLanes( - planner_data_, parameters_->backward_goal_search_length, - parameters_->forward_goal_search_length, + local_planner_data, parameters.backward_goal_search_length, + parameters.forward_goal_search_length, /*forward_only_in_route*/ false); std::vector path_candidates{}; std::optional closest_start_pose{}; @@ -228,7 +266,7 @@ void GoalPlannerModule::onTimer() const auto planCandidatePaths = [&]( const std::shared_ptr & planner, const GoalCandidate & goal_candidate) { - planner->setPlannerData(planner_data_); + planner->setPlannerData(local_planner_data); planner->setPreviousModuleOutput(previous_module_output); auto pull_over_path = planner->plan(goal_candidate.goal_pose); if (pull_over_path) { @@ -254,7 +292,7 @@ void GoalPlannerModule::onTimer() is_center_line_input_path); // plan candidate paths and set them to the member variable - if (parameters_->path_priority == "efficient_path") { + if (parameters.path_priority == "efficient_path") { for (const auto & planner : pull_over_planners_) { // todo: temporary skip NON SHIFT planner when input path is not center line if (!is_center_line_input_path && planner->getPlannerType() != PullOverPlannerType::SHIFT) { @@ -264,7 +302,7 @@ void GoalPlannerModule::onTimer() planCandidatePaths(planner, goal_candidate); } } - } else if (parameters_->path_priority == "close_goal") { + } else if (parameters.path_priority == "close_goal") { for (const auto & goal_candidate : goal_candidates) { for (const auto & planner : pull_over_planners_) { // todo: temporary skip NON SHIFT planner when input path is not center line @@ -277,49 +315,76 @@ void GoalPlannerModule::onTimer() } else { RCLCPP_ERROR( getLogger(), "path_priority should be efficient_path or close_goal, but %s is given.", - parameters_->path_priority.c_str()); + parameters.path_priority.c_str()); throw std::domain_error("[pull_over] invalid path_priority"); } // set member variables - { - const std::lock_guard lock(mutex_); - thread_safe_data_.set_pull_over_path_candidates(path_candidates); - thread_safe_data_.set_closest_start_pose(closest_start_pose); - RCLCPP_INFO(getLogger(), "generated %lu pull over path candidates", path_candidates.size()); - } + thread_safe_data_.set_pull_over_path_candidates(path_candidates); + thread_safe_data_.set_closest_start_pose(closest_start_pose); + RCLCPP_INFO(getLogger(), "generated %lu pull over path candidates", path_candidates.size()); - last_previous_module_output_ = previous_module_output; + thread_safe_data_.set_last_previous_module_output(previous_module_output); } void GoalPlannerModule::onFreespaceParkingTimer() { const ScopedFlag flag(is_freespace_parking_cb_running_); - if (getCurrentStatus() == ModuleStatus::IDLE) { + std::shared_ptr local_planner_data{nullptr}; + std::optional current_status_opt{std::nullopt}; + std::shared_ptr occupancy_grid_map{nullptr}; + std::optional parameters_opt{std::nullopt}; + std::shared_ptr goal_searcher{nullptr}; + + // begin of critical section + { + std::lock_guard guard(gp_planner_data_mutex_); + if (gp_planner_data_) { + const auto & gp_planner_data = gp_planner_data_.value(); + local_planner_data = std::make_shared(gp_planner_data.planner_data); + current_status_opt = gp_planner_data.current_status; + occupancy_grid_map = gp_planner_data.occupancy_grid_map; + parameters_opt = gp_planner_data.parameters; + goal_searcher = gp_planner_data.goal_searcher; + } + } + // end of critical section + if (!local_planner_data || !current_status_opt || !parameters_opt || !goal_searcher) { + RCLCPP_ERROR( + getLogger(), + "failed to get valid planner_data/current_status/parameters/goal_searcher in " + "onFreespaceParkingTimer"); return; } - if (!planner_data_) { + const auto & current_status = current_status_opt.value(); + const auto & parameters = parameters_opt.value(); + + if (current_status == ModuleStatus::IDLE) { return; } - if (!planner_data_->costmap) { + + if (!local_planner_data->costmap) { return; } // fixed goal planner do not use freespace planner - if (!utils::isAllowedGoalModification(planner_data_->route_handler)) { + if (!utils::isAllowedGoalModification(local_planner_data->route_handler)) { return; } - if (isOnModifiedGoal()) { + if (isOnModifiedGoal(local_planner_data->self_odometry->pose.pose, parameters)) { return; } const bool is_new_costmap = - (clock_->now() - planner_data_->costmap->header.stamp).seconds() < 1.0; + (clock_->now() - local_planner_data->costmap->header.stamp).seconds() < 1.0; constexpr double path_update_duration = 1.0; - if (isStuck() && is_new_costmap && needPathUpdate(path_update_duration)) { - planFreespacePath(); + if ( + isStuck(local_planner_data, occupancy_grid_map, parameters) && is_new_costmap && + needPathUpdate( + local_planner_data->self_odometry->pose.pose, path_update_duration, parameters)) { + planFreespacePath(local_planner_data, goal_searcher, occupancy_grid_map); } } @@ -349,28 +414,64 @@ void GoalPlannerModule::updateObjectsFilteringParams( void GoalPlannerModule::updateData() { + // In PlannerManager::run(), it calls SceneModuleInterface::setData and + // SceneModuleInterface::setPreviousModuleOutput before module_ptr->run(). + // Then module_ptr->run() invokes GoalPlannerModule::updateData and then + // planWaitingApproval()/plan(), so we can copy latest current_status/previous_module_output to + // gp_planner_data_ here + + // NOTE: onTimer/onFreespaceParkingTimer copies gp_planner_data_ to their local clone, so we need + // to lock gp_planner_data_ here to avoid data race. But the following clone process is + // lightweight because most of the member variables of PlannerData/RouteHandler is + // shared_ptrs/bool + // begin of critical section + { + std::lock_guard guard(gp_planner_data_mutex_); + if (!gp_planner_data_) { + gp_planner_data_ = GoalPlannerData(*planner_data_, *parameters_); + } + auto & gp_planner_data = gp_planner_data_.value(); + // NOTE: for the above reasons, PlannerManager/behavior_path_planner_node ensure that + // planner_data_ is not nullptr, so it is OK to copy as value + // By copying PlannerData as value, the internal shared member variables are also copied + // (reference count is incremented), so `gp_planner_data_.foo` is now thread-safe from the + // **re-pointing** by `planner_data_->foo = msg` in behavior_path_planner::onCallbackFor(msg) + // and if these two coincided, only the reference count is affected + gp_planner_data.update( + *parameters_, ego_predicted_path_params_, objects_filtering_params_, safety_check_params_, + *planner_data_, getCurrentStatus(), getPreviousModuleOutput(), goal_searcher_, + vehicle_footprint_); + // NOTE: RouteHandler holds several shared pointers in it, so just copying PlannerData as + // value does not adds the reference counts of RouteHandler.lanelet_map_ptr_ and others. Since + // behavior_path_planner::run() updates + // planner_data_->route_handler->lanelet_map_ptr_/routing_graph_ptr_ especially, we also have + // to copy route_handler as value to use lanelet_map_ptr_/routing_graph_ptr_ thread-safely in + // onTimer/onFreespaceParkingTimer + // TODO(Mamoru Sobue): If the copy of RouteHandler.road_lanelets/shoulder_lanelets is not + // lightweight, we should update gp_planner_data_.route_handler only when + // `planner_data_.is_route_handler_updated` variable is set true by behavior_path_planner + // (although this flag is not implemented yet). In that case, gp_planner_data members except + // for route_handler should be copied from planner_data_ + + // GoalPlannerModule::occupancy_grid_map_ and gp_planner_data.occupancy_grid_map share the + // ownership, and gp_planner_data.occupancy_grid_map maybe also shared by the local + // planner_data on onFreespaceParkingTimer thread local memory space. So following operation + // is thread-safe because gp_planner_data.occupancy_grid_map is only re-pointed here and its + // prior resource is still owned by the onFreespaceParkingTimer thread locally. + occupancy_grid_map_ = gp_planner_data.occupancy_grid_map; + } + // end of critical section + if (getCurrentStatus() == ModuleStatus::IDLE && !isExecutionRequested()) { return; } - // Initialize Occupancy Grid Map - // This operation requires waiting for `planner_data_`, hence it is executed here instead of in - // the constructor. Ideally, this operation should only need to be performed once. - if ( - parameters_->use_occupancy_grid_for_goal_search || - parameters_->use_occupancy_grid_for_path_collision_check) { - initializeOccupancyGridMap(); - } - resetPathCandidate(); resetPathReference(); path_reference_ = std::make_shared(getPreviousModuleOutput().reference_path); - updateOccupancyGrid(); - // update goal searcher and generate goal candidates if (thread_safe_data_.get_goal_candidates().empty()) { - goal_searcher_->setPlannerData(planner_data_); goal_searcher_->setReferenceGoal( calcRefinedGoal(planner_data_->route_handler->getOriginalGoalPose())); thread_safe_data_.set_goal_candidates(generateGoalCandidates()); @@ -391,21 +492,6 @@ void GoalPlannerModule::updateData() } } -void GoalPlannerModule::initializeOccupancyGridMap() -{ - OccupancyGridMapParam occupancy_grid_map_param{}; - const double margin = parameters_->occupancy_grid_collision_check_margin; - occupancy_grid_map_param.vehicle_shape.length = - planner_data_->parameters.vehicle_length + 2 * margin; - occupancy_grid_map_param.vehicle_shape.width = - planner_data_->parameters.vehicle_width + 2 * margin; - occupancy_grid_map_param.vehicle_shape.base2back = - planner_data_->parameters.base_link2rear + margin; - occupancy_grid_map_param.theta_size = parameters_->theta_size; - occupancy_grid_map_param.obstacle_threshold = parameters_->obstacle_threshold; - occupancy_grid_map_->setParam(occupancy_grid_map_param); -} - void GoalPlannerModule::initializeSafetyCheckParameters() { updateEgoPredictedPathParams(ego_predicted_path_params_, parameters_); @@ -418,7 +504,7 @@ void GoalPlannerModule::processOnExit() resetPathCandidate(); resetPathReference(); debug_marker_.markers.clear(); - prev_data_.reset(); + thread_safe_data_.reset(); last_approval_data_.reset(); } @@ -447,12 +533,10 @@ bool GoalPlannerModule::isExecutionRequested() const // check that goal is in current neighbor shoulder lane const bool goal_is_in_current_shoulder_lanes = std::invoke([&]() { - lanelet::ConstLanelet neighbor_shoulder_lane{}; for (const auto & lane : current_lanes) { - const bool has_shoulder_lane = - left_side_parking_ ? route_handler->getLeftShoulderLanelet(lane, &neighbor_shoulder_lane) - : route_handler->getRightShoulderLanelet(lane, &neighbor_shoulder_lane); - if (has_shoulder_lane && lanelet::utils::isInLanelet(goal_pose, neighbor_shoulder_lane)) { + const auto shoulder_lane = left_side_parking_ ? route_handler->getLeftShoulderLanelet(lane) + : route_handler->getRightShoulderLanelet(lane); + if (shoulder_lane && lanelet::utils::isInLanelet(goal_pose, *shoulder_lane)) { return true; } } @@ -501,7 +585,10 @@ bool GoalPlannerModule::isExecutionRequested() const bool GoalPlannerModule::isExecutionReady() const { if (parameters_->safety_check_params.enable_safety_check && isWaitingApproval()) { - if (!isSafePath().first) { + if (!isSafePath( + planner_data_, *parameters_, ego_predicted_path_params_, objects_filtering_params_, + safety_check_params_) + .first) { RCLCPP_ERROR_THROTTLE(getLogger(), *clock_, 5000, "Path is not safe against dynamic objects"); return false; } @@ -584,18 +671,17 @@ Pose GoalPlannerModule::calcRefinedGoal(const Pose & goal_pose) const return refined_goal_pose; } -bool GoalPlannerModule::planFreespacePath() +bool GoalPlannerModule::planFreespacePath( + std::shared_ptr planner_data, + const std::shared_ptr goal_searcher, + const std::shared_ptr occupancy_grid_map) { GoalCandidates goal_candidates{}; - { - const std::lock_guard lock(mutex_); - goal_searcher_->setPlannerData(planner_data_); - goal_candidates = thread_safe_data_.get_goal_candidates(); - goal_searcher_->update(goal_candidates); - thread_safe_data_.set_goal_candidates(goal_candidates); - debug_data_.freespace_planner.num_goal_candidates = goal_candidates.size(); - debug_data_.freespace_planner.is_planning = true; - } + goal_candidates = thread_safe_data_.get_goal_candidates(); + goal_searcher->update(goal_candidates, occupancy_grid_map, planner_data); + thread_safe_data_.set_goal_candidates(goal_candidates); + debug_data_.freespace_planner.num_goal_candidates = goal_candidates.size(); + debug_data_.freespace_planner.is_planning = true; for (size_t i = 0; i < goal_candidates.size(); i++) { const auto goal_candidate = goal_candidates.at(i); @@ -607,7 +693,7 @@ bool GoalPlannerModule::planFreespacePath() if (!goal_candidate.is_safe) { continue; } - freespace_planner_->setPlannerData(planner_data_); + freespace_planner_->setPlannerData(planner_data); auto freespace_path = freespace_planner_->plan(goal_candidate.goal_pose); freespace_path->goal_id = goal_candidate.id; if (!freespace_path) { @@ -645,13 +731,15 @@ bool GoalPlannerModule::canReturnToLaneParking() if ( parameters_->use_object_recognition && checkObjectsCollision( - path, parameters_->object_recognition_collision_check_hard_margins.back(), + path, planner_data_, *parameters_, + parameters_->object_recognition_collision_check_hard_margins.back(), /*extract_static_objects=*/false)) { return false; } if ( - parameters_->use_occupancy_grid_for_path_collision_check && checkOccupancyGridCollision(path)) { + parameters_->use_occupancy_grid_for_path_collision_check && + checkOccupancyGridCollision(path, occupancy_grid_map_)) { return false; } @@ -671,7 +759,7 @@ GoalCandidates GoalPlannerModule::generateGoalCandidates() const // calculate goal candidates const auto & route_handler = planner_data_->route_handler; if (utils::isAllowedGoalModification(route_handler)) { - return goal_searcher_->search(); + return goal_searcher_->search(occupancy_grid_map_, planner_data_); } // NOTE: @@ -778,7 +866,7 @@ std::vector GoalPlannerModule::sortPullOverPathCandidatesByGoalPri utils::resamplePathWithSpline(pull_over_path.getParkingPath(), 0.5); for (const auto & margin : margins) { if (!checkObjectsCollision( - resampled_path, margin, + resampled_path, planner_data_, *parameters_, margin, /*extract_static_objects=*/true)) { return margin; } @@ -848,6 +936,26 @@ std::optional> GoalPlannerModule::selectP const std::vector & pull_over_path_candidates, const GoalCandidates & goal_candidates, const double collision_check_margin) const { + const auto & goal_pose = planner_data_->route_handler->getOriginalGoalPose(); + const double backward_length = + parameters_->backward_goal_search_length + parameters_->decide_path_distance; + const auto & prev_module_output_path = getPreviousModuleOutput().path; + const double prev_path_front_to_goal_dist = calcSignedArcLength( + prev_module_output_path.points, prev_module_output_path.points.front().point.pose.position, + goal_pose.position); + const auto & long_tail_reference_path = [&]() { + if (prev_path_front_to_goal_dist > backward_length) { + return prev_module_output_path; + } + // get road lanes which is at least backward_length[m] behind the goal + const auto road_lanes = utils::getExtendedCurrentLanesFromPath( + prev_module_output_path, planner_data_, backward_length, 0.0, + /*forward_only_in_route*/ false); + const auto goal_pose_length = lanelet::utils::getArcCoordinates(road_lanes, goal_pose).length; + return planner_data_->route_handler->getCenterLinePath( + road_lanes, std::max(0.0, goal_pose_length - backward_length), + goal_pose_length + parameters_->forward_goal_search_length); + }(); for (const auto & pull_over_path : pull_over_path_candidates) { // check if goal is safe const auto goal_candidate_it = std::find_if( @@ -859,22 +967,23 @@ std::optional> GoalPlannerModule::selectP continue; } - if (!hasEnoughDistance(pull_over_path)) { + if (!hasEnoughDistance(pull_over_path, long_tail_reference_path)) { continue; } const auto resampled_path = utils::resamplePathWithSpline(pull_over_path.getParkingPath(), 0.5); if ( - parameters_->use_object_recognition && checkObjectsCollision( - resampled_path, collision_check_margin, - /*extract_static_objects=*/true, - /*update_debug_data=*/true)) { + parameters_->use_object_recognition && + checkObjectsCollision( + resampled_path, planner_data_, *parameters_, collision_check_margin, + /*extract_static_objects=*/true, + /*update_debug_data=*/true)) { continue; } if ( parameters_->use_occupancy_grid_for_path_collision_check && - checkOccupancyGridCollision(resampled_path)) { + checkOccupancyGridCollision(resampled_path, occupancy_grid_map_)) { continue; } @@ -910,7 +1019,12 @@ void GoalPlannerModule::setOutput(BehaviorModuleOutput & output) } if ( - parameters_->safety_check_params.enable_safety_check && !isSafePath().first && isActivated()) { + parameters_->safety_check_params.enable_safety_check && + !isSafePath( + planner_data_, *parameters_, ego_predicted_path_params_, objects_filtering_params_, + safety_check_params_) + .first && + isActivated()) { // situation : not safe against dynamic objects after approval // insert stop point in current path if ego is able to stop with acceleration and jerk // constraints @@ -933,7 +1047,11 @@ void GoalPlannerModule::setOutput(BehaviorModuleOutput & output) setDrivableAreaInfo(output); // set hazard and turn signal - if (hasDecidedPath() && isActivated()) { + if ( + hasDecidedPath( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_) && + isActivated()) { setTurnSignalInfo(output); } } @@ -997,20 +1115,47 @@ void GoalPlannerModule::updateSteeringFactor( pose, distance, PlanningBehavior::GOAL_PLANNER, steering_factor_direction, type, ""); } -bool GoalPlannerModule::hasDecidedPath() const -{ - return checkDecidingPathStatus().first == DecidingPathStatus::DECIDED; -} - -bool GoalPlannerModule::hasNotDecidedPath() const -{ - return checkDecidingPathStatus().first == DecidingPathStatus::NOT_DECIDED; -} - -DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const -{ - const auto & prev_status = prev_data_.deciding_path_status; - const bool enable_safety_check = parameters_->safety_check_params.enable_safety_check; +bool GoalPlannerModule::hasDecidedPath( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const +{ + return checkDecidingPathStatus( + planner_data, occupancy_grid_map, parameters, ego_predicted_path_params, + objects_filtering_params, safety_check_params, goal_searcher) + .first == DecidingPathStatus::DECIDED; +} + +bool GoalPlannerModule::hasNotDecidedPath( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const +{ + return checkDecidingPathStatus( + planner_data, occupancy_grid_map, parameters, ego_predicted_path_params, + objects_filtering_params, safety_check_params, goal_searcher) + .first == DecidingPathStatus::NOT_DECIDED; +} + +DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params, + const std::shared_ptr goal_searcher) const +{ + const auto & prev_status = thread_safe_data_.get_prev_data().deciding_path_status; + const bool enable_safety_check = parameters.safety_check_params.enable_safety_check; // Once this function returns true, it will continue to return true thereafter if (prev_status.first == DecidingPathStatus::DECIDED) { @@ -1024,7 +1169,13 @@ DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const // If it is dangerous against dynamic objects before approval, do not determine the path. // This eliminates a unsafe path to be approved - if (enable_safety_check && !isSafePath().first && !isActivated()) { + if ( + enable_safety_check && + !isSafePath( + planner_data, parameters, ego_predicted_path_params, objects_filtering_params, + safety_check_params) + .first && + !isActivated()) { RCLCPP_DEBUG( getLogger(), "[DecidingPathStatus]: NOT_DECIDED. path is not safe against dynamic objects before " @@ -1040,11 +1191,11 @@ DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const const double hysteresis_factor = 0.9; // check goal pose collision - goal_searcher_->setPlannerData(planner_data_); const auto modified_goal_opt = thread_safe_data_.get_modified_goal_pose(); if ( - modified_goal_opt && !goal_searcher_->isSafeGoalWithMarginScaleFactor( - modified_goal_opt.value(), hysteresis_factor)) { + modified_goal_opt && + !goal_searcher->isSafeGoalWithMarginScaleFactor( + modified_goal_opt.value(), hysteresis_factor, occupancy_grid_map, planner_data)) { RCLCPP_DEBUG(getLogger(), "[DecidingPathStatus]: DECIDING->NOT_DECIDED. goal is not safe"); return {DecidingPathStatus::NOT_DECIDED, clock_->now()}; } @@ -1052,15 +1203,20 @@ DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const // check current parking path collision const auto parking_path = utils::resamplePathWithSpline(pull_over_path->getParkingPath(), 0.5); const double margin = - parameters_->object_recognition_collision_check_hard_margins.back() * hysteresis_factor; - if (checkObjectsCollision(parking_path, margin, /*extract_static_objects=*/false)) { + parameters.object_recognition_collision_check_hard_margins.back() * hysteresis_factor; + if (checkObjectsCollision( + parking_path, planner_data, parameters, margin, /*extract_static_objects=*/false)) { RCLCPP_DEBUG( getLogger(), "[DecidingPathStatus]: DECIDING->NOT_DECIDED. path has collision with objects"); return {DecidingPathStatus::NOT_DECIDED, clock_->now()}; } - if (enable_safety_check && !isSafePath().first) { + if ( + enable_safety_check && !isSafePath( + planner_data, parameters, ego_predicted_path_params, + objects_filtering_params, safety_check_params) + .first) { RCLCPP_DEBUG( getLogger(), "[DecidingPathStatus]: DECIDING->NOT_DECIDED. path is not safe against dynamic objects"); @@ -1084,7 +1240,7 @@ DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const } // if ego is sufficiently close to the start of the nearest candidate path, the path is decided - const auto & current_pose = planner_data_->self_odometry->pose.pose; + const auto & current_pose = planner_data->self_odometry->pose.pose; const size_t ego_segment_idx = motion_utils::findNearestSegmentIndex(current_path.points, current_pose.position); @@ -1093,13 +1249,13 @@ DecidingPathStatusWithStamp GoalPlannerModule::checkDecidingPathStatus() const const double dist_to_parking_start_pose = calcSignedArcLength( current_path.points, current_pose.position, ego_segment_idx, pull_over_path->start_pose.position, start_pose_segment_idx); - if (dist_to_parking_start_pose > parameters_->decide_path_distance) { + if (dist_to_parking_start_pose > parameters.decide_path_distance) { return {DecidingPathStatus::NOT_DECIDED, clock_->now()}; } // if object recognition for path collision check is enabled, transition to DECIDING to check // collision for a certain period of time. Otherwise, transition to DECIDED directly. - if (parameters_->use_object_recognition) { + if (parameters.use_object_recognition) { RCLCPP_DEBUG( getLogger(), "[DecidingPathStatus]: NOT_DECIDED->DECIDING. start checking collision for certain " @@ -1124,7 +1280,9 @@ void GoalPlannerModule::decideVelocity() BehaviorModuleOutput GoalPlannerModule::planPullOver() { - if (!hasDecidedPath()) { + if (!hasDecidedPath( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_)) { return planPullOverAsCandidate(); } @@ -1168,7 +1326,12 @@ BehaviorModuleOutput GoalPlannerModule::planPullOverAsOutput() return getPreviousModuleOutput(); } - if (hasNotDecidedPath() && needPathUpdate(1.0 /*path_update_duration*/)) { + if ( + hasNotDecidedPath( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_) && + needPathUpdate( + planner_data_->self_odometry->pose.pose, 1.0 /*path_update_duration*/, *parameters_)) { // if the final path is not decided and enough time has passed since last path update, // select safe path from lane parking pull over path candidates // and set it to thread_safe_data_ @@ -1177,9 +1340,8 @@ BehaviorModuleOutput GoalPlannerModule::planPullOverAsOutput() thread_safe_data_.clearPullOverPath(); // update goal candidates - goal_searcher_->setPlannerData(planner_data_); auto goal_candidates = thread_safe_data_.get_goal_candidates(); - goal_searcher_->update(goal_candidates); + goal_searcher_->update(goal_candidates, occupancy_grid_map_, planner_data_); // update pull over path candidates const auto pull_over_path_candidates = sortPullOverPathCandidatesByGoalPriority( @@ -1240,9 +1402,14 @@ void GoalPlannerModule::postProcess() return; } - const bool has_decided_path = hasDecidedPath(); const auto distance_to_path_change = calcDistanceToPathChange(); + // TODO(Mamoru Sobue): repetitive call to checkDecidingPathStatus() in the main thread is a + // waste of time because it gives same result throughout the main thread. + const bool has_decided_path = hasDecidedPath( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_); + if (has_decided_path) { updateRTCStatus(distance_to_path_change.first, distance_to_path_change.second); } @@ -1260,27 +1427,35 @@ void GoalPlannerModule::updatePreviousData() { // for the next loop setOutput(). // this is used to determine whether to generate a new stop path or keep the current stop path. - prev_data_.found_path = thread_safe_data_.foundPullOverPath(); + // TODO(Mamoru Sobue): put prev_data_ out of ThreadSafeData + auto prev_data = thread_safe_data_.get_prev_data(); + prev_data.found_path = thread_safe_data_.foundPullOverPath(); - prev_data_.deciding_path_status = checkDecidingPathStatus(); + prev_data.deciding_path_status = checkDecidingPathStatus( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_); // This is related to safety check, so if it is disabled, return here. if (!parameters_->safety_check_params.enable_safety_check) { - prev_data_.safety_status.is_safe = true; - return; - } - - // Even if the current path is safe, it will not be safe unless it stands for a certain period of - // time. Record the time when the current path has become safe - const auto [is_safe, current_is_safe] = isSafePath(); - if (current_is_safe) { - if (!prev_data_.safety_status.safe_start_time) { - prev_data_.safety_status.safe_start_time = clock_->now(); - } + prev_data.safety_status.is_safe = true; } else { - prev_data_.safety_status.safe_start_time = std::nullopt; + // Even if the current path is safe, it will not be safe unless it stands for a certain period + // of time. Record the time when the current path has become safe + const auto [is_safe, current_is_safe] = isSafePath( + planner_data_, *parameters_, ego_predicted_path_params_, objects_filtering_params_, + safety_check_params_); + if (current_is_safe) { + if (!prev_data.safety_status.safe_start_time) { + prev_data.safety_status.safe_start_time = clock_->now(); + } + } else { + prev_data.safety_status.safe_start_time = std::nullopt; + } + prev_data.safety_status.is_safe = is_safe; } - prev_data_.safety_status.is_safe = is_safe; + + // commit the change + thread_safe_data_.set_prev_data(prev_data); } BehaviorModuleOutput GoalPlannerModule::planWaitingApproval() @@ -1357,8 +1532,8 @@ PathWithLaneId GoalPlannerModule::generateStopPath() const // calculate search start offset pose from the closest goal candidate pose with // approximate_pull_over_distance_ ego vehicle decelerates to this position. or if no feasible // stop point is found, stop at this position. - const auto closest_goal_candidate = - goal_searcher_->getClosetGoalCandidateAlongLanes(thread_safe_data_.get_goal_candidates()); + const auto closest_goal_candidate = goal_searcher_->getClosetGoalCandidateAlongLanes( + thread_safe_data_.get_goal_candidates(), planner_data_); const auto decel_pose = calcLongitudinalOffsetPose( extended_prev_path.points, closest_goal_candidate.goal_pose.position, -approximate_pull_over_distance_); @@ -1486,10 +1661,13 @@ bool GoalPlannerModule::isStopped() return isStopped(odometry_buffer_stopped_, parameters_->th_stopped_time); } -bool GoalPlannerModule::isStuck() +bool GoalPlannerModule::isStuck( + const std::shared_ptr planner_data, + const std::shared_ptr occupancy_grid_map, + const GoalPlannerParameters & parameters) { const std::lock_guard lock(mutex_); - if (isOnModifiedGoal()) { + if (isOnModifiedGoal(planner_data->self_odometry->pose.pose, parameters)) { return false; } @@ -1509,17 +1687,18 @@ bool GoalPlannerModule::isStuck() } if ( - parameters_->use_object_recognition && + parameters.use_object_recognition && checkObjectsCollision( - thread_safe_data_.get_pull_over_path()->getCurrentPath(), + thread_safe_data_.get_pull_over_path()->getCurrentPath(), planner_data, parameters, /*extract_static_objects=*/false, - parameters_->object_recognition_collision_check_hard_margins.back())) { + parameters.object_recognition_collision_check_hard_margins.back())) { return true; } if ( - parameters_->use_occupancy_grid_for_path_collision_check && - checkOccupancyGridCollision(thread_safe_data_.get_pull_over_path()->getCurrentPath())) { + parameters.use_occupancy_grid_for_path_collision_check && + checkOccupancyGridCollision( + thread_safe_data_.get_pull_over_path()->getCurrentPath(), occupancy_grid_map)) { return true; } @@ -1565,15 +1744,15 @@ bool GoalPlannerModule::hasFinishedCurrentPath() parameters_->th_arrived_distance; } -bool GoalPlannerModule::isOnModifiedGoal() const +bool GoalPlannerModule::isOnModifiedGoal( + const Pose & current_pose, const GoalPlannerParameters & parameters) const { if (!thread_safe_data_.get_modified_goal_pose()) { return false; } - const Pose current_pose = planner_data_->self_odometry->pose.pose; return calcDistance2d(current_pose, thread_safe_data_.get_modified_goal_pose()->goal_pose) < - parameters_->th_arrived_distance; + parameters.th_arrived_distance; } TurnSignalInfo GoalPlannerModule::calcTurnSignalInfo() @@ -1642,31 +1821,34 @@ TurnSignalInfo GoalPlannerModule::calcTurnSignalInfo() return new_signal; } -bool GoalPlannerModule::checkOccupancyGridCollision(const PathWithLaneId & path) const +bool GoalPlannerModule::checkOccupancyGridCollision( + const PathWithLaneId & path, + const std::shared_ptr occupancy_grid_map) const { - if (!occupancy_grid_map_) { + if (!occupancy_grid_map) { return false; } const bool check_out_of_range = false; - return occupancy_grid_map_->hasObstacleOnPath(path, check_out_of_range); + return occupancy_grid_map->hasObstacleOnPath(path, check_out_of_range); } bool GoalPlannerModule::checkObjectsCollision( - const PathWithLaneId & path, const double collision_check_margin, + const PathWithLaneId & path, const std::shared_ptr planner_data, + const GoalPlannerParameters & parameters, const double collision_check_margin, const bool extract_static_objects, const bool update_debug_data) const { const auto target_objects = std::invoke([&]() { - const auto & p = parameters_; - const auto & rh = *(planner_data_->route_handler); - const auto objects = *(planner_data_->dynamic_object); + const auto & p = parameters; + const auto & rh = *(planner_data->route_handler); + const auto objects = *(planner_data->dynamic_object); if (extract_static_objects) { return goal_planner_utils::extractStaticObjectsInExpandedPullOverLanes( - rh, left_side_parking_, p->backward_goal_search_length, p->forward_goal_search_length, - p->detection_bound_offset, objects, p->th_moving_object_velocity); + rh, left_side_parking_, p.backward_goal_search_length, p.forward_goal_search_length, + p.detection_bound_offset, objects, p.th_moving_object_velocity); } return goal_planner_utils::extractObjectsInExpandedPullOverLanes( - rh, left_side_parking_, p->backward_goal_search_length, p->forward_goal_search_length, - p->detection_bound_offset, objects); + rh, left_side_parking_, p.backward_goal_search_length, p.forward_goal_search_length, + p.detection_bound_offset, objects); }); std::vector obj_polygons; @@ -1685,8 +1867,8 @@ bool GoalPlannerModule::checkObjectsCollision( const auto p = path.points.at(i); const double extra_stopping_margin = std::min( - std::pow(p.point.longitudinal_velocity_mps, 2) * 0.5 / parameters_->maximum_deceleration, - parameters_->object_recognition_collision_check_max_extra_stopping_margin); + std::pow(p.point.longitudinal_velocity_mps, 2) * 0.5 / parameters.maximum_deceleration, + parameters.object_recognition_collision_check_max_extra_stopping_margin); // The square is meant to imply centrifugal force, but it is not a very well-founded formula. // TODO(kosuke55): It is needed to consider better way because there is an inherently different @@ -1697,9 +1879,9 @@ bool GoalPlannerModule::checkObjectsCollision( const auto ego_polygon = tier4_autoware_utils::toFootprint( p.point.pose, - planner_data_->parameters.base_link2front + collision_check_margin + extra_stopping_margin, - planner_data_->parameters.base_link2rear + collision_check_margin, - planner_data_->parameters.vehicle_width + collision_check_margin * 2.0 + + planner_data->parameters.base_link2front + collision_check_margin + extra_stopping_margin, + planner_data->parameters.base_link2rear + collision_check_margin, + planner_data->parameters.vehicle_width + collision_check_margin * 2.0 + extra_lateral_margin * 2.0); ego_polygons_expanded.push_back(ego_polygon); } @@ -1711,7 +1893,8 @@ bool GoalPlannerModule::checkObjectsCollision( return utils::path_safety_checker::checkPolygonsIntersects(ego_polygons_expanded, obj_polygons); } -bool GoalPlannerModule::hasEnoughDistance(const PullOverPath & pull_over_path) const +bool GoalPlannerModule::hasEnoughDistance( + const PullOverPath & pull_over_path, const PathWithLaneId & long_tail_reference_path) const { const Pose & current_pose = planner_data_->self_odometry->pose.pose; const double current_vel = planner_data_->self_odometry->twist.twist.linear.x; @@ -1723,7 +1906,7 @@ bool GoalPlannerModule::hasEnoughDistance(const PullOverPath & pull_over_path) c // otherwise, the goal would change immediately after departure. const bool is_separated_path = pull_over_path.partial_paths.size() > 1; const double distance_to_start = calcSignedArcLength( - pull_over_path.getFullPath().points, current_pose.position, pull_over_path.start_pose.position); + long_tail_reference_path.points, current_pose.position, pull_over_path.start_pose.position); const double distance_to_restart = parameters_->decide_path_distance / 2; const double eps_vel = 0.01; const bool is_stopped = std::abs(current_vel) < eps_vel; @@ -1782,8 +1965,8 @@ double GoalPlannerModule::calcSignedArcLengthFromEgo( void GoalPlannerModule::deceleratePath(PullOverPath & pull_over_path) const { // decelerate before the search area start - const auto closest_goal_candidate = - goal_searcher_->getClosetGoalCandidateAlongLanes(thread_safe_data_.get_goal_candidates()); + const auto closest_goal_candidate = goal_searcher_->getClosetGoalCandidateAlongLanes( + thread_safe_data_.get_goal_candidates(), planner_data_); const auto decel_pose = calcLongitudinalOffsetPose( pull_over_path.getFullPath().points, closest_goal_candidate.goal_pose.position, -approximate_pull_over_distance_); @@ -1897,20 +2080,11 @@ bool GoalPlannerModule::isCrossingPossible( // Lambda function to get the neighboring lanelet based on left_side_parking_ auto getNeighboringLane = [&](const lanelet::ConstLanelet & lane) -> std::optional { - lanelet::ConstLanelet neighboring_lane{}; - if (left_side_parking_) { - if (route_handler->getLeftShoulderLanelet(lane, &neighboring_lane)) { - return neighboring_lane; - } else { - return route_handler->getLeftLanelet(lane); - } - } else { - if (route_handler->getRightShoulderLanelet(lane, &neighboring_lane)) { - return neighboring_lane; - } else { - return route_handler->getRightLanelet(lane); - } - } + const auto neighboring_lane = left_side_parking_ ? route_handler->getLeftShoulderLanelet(lane) + : route_handler->getRightShoulderLanelet(lane); + if (neighboring_lane) return neighboring_lane; + return left_side_parking_ ? route_handler->getLeftLanelet(lane) + : route_handler->getRightLanelet(lane); }; // Iterate through start_lane_sequence to find a path to end_lane_sequence @@ -1964,6 +2138,7 @@ bool GoalPlannerModule::isCrossingPossible(const PullOverPath & pull_over_path) return isCrossingPossible(start_pose, end_pose, lanes); } +/* void GoalPlannerModule::updateSafetyCheckTargetObjectsData( const PredictedObjects & filtered_objects, const TargetObjectsOnLane & target_objects_on_lane, const std::vector & ego_predicted_path) const @@ -1972,6 +2147,7 @@ void GoalPlannerModule::updateSafetyCheckTargetObjectsData( goal_planner_data_.target_objects_on_lane = target_objects_on_lane; goal_planner_data_.ego_predicted_path = ego_predicted_path; } +*/ static std::vector filterObjectsByWithinPolicy( const std::shared_ptr & objects, @@ -2017,26 +2193,29 @@ static std::vector filterOb return refined_filtered_objects; } -std::pair GoalPlannerModule::isSafePath() const +std::pair GoalPlannerModule::isSafePath( + const std::shared_ptr planner_data, const GoalPlannerParameters & parameters, + const std::shared_ptr & ego_predicted_path_params, + const std::shared_ptr & objects_filtering_params, + const std::shared_ptr & safety_check_params) const { if (!thread_safe_data_.get_pull_over_path()) { return {false, false}; } const auto pull_over_path = thread_safe_data_.get_pull_over_path()->getCurrentPath(); - const auto & current_pose = planner_data_->self_odometry->pose.pose; + const auto & current_pose = planner_data->self_odometry->pose.pose; const double current_velocity = std::hypot( - planner_data_->self_odometry->twist.twist.linear.x, - planner_data_->self_odometry->twist.twist.linear.y); - const auto & dynamic_object = planner_data_->dynamic_object; - const auto & route_handler = planner_data_->route_handler; + planner_data->self_odometry->twist.twist.linear.x, + planner_data->self_odometry->twist.twist.linear.y); + const auto & dynamic_object = planner_data->dynamic_object; + const auto & route_handler = planner_data->route_handler; const lanelet::ConstLanelets current_lanes = utils::getExtendedCurrentLanes( - planner_data_, parameters_->backward_goal_search_length, - parameters_->forward_goal_search_length, + planner_data, parameters.backward_goal_search_length, parameters.forward_goal_search_length, /*forward_only_in_route*/ false); const auto pull_over_lanes = goal_planner_utils::getPullOverLanes( - *route_handler, left_side_parking_, parameters_->backward_goal_search_length, - parameters_->forward_goal_search_length); - const size_t ego_seg_idx = planner_data_->findEgoSegmentIndex(pull_over_path.points); + *route_handler, left_side_parking_, parameters.backward_goal_search_length, + parameters.forward_goal_search_length); + const size_t ego_seg_idx = planner_data->findEgoSegmentIndex(pull_over_path.points); const std::pair terminal_velocity_and_accel = utils::parking_departure::getPairsTerminalVelocityAndAccel( thread_safe_data_.get_pull_over_path()->pairs_terminal_velocity_and_accel, @@ -2044,15 +2223,15 @@ std::pair GoalPlannerModule::isSafePath() const RCLCPP_DEBUG( getLogger(), "pairs_terminal_velocity_and_accel for goal_planner: %f, %f", terminal_velocity_and_accel.first, terminal_velocity_and_accel.second); - utils::parking_departure::updatePathProperty( - ego_predicted_path_params_, terminal_velocity_and_accel); + auto temp_param = std::make_shared(*ego_predicted_path_params); + utils::parking_departure::updatePathProperty(temp_param, terminal_velocity_and_accel); // TODO(Sugahara): shoule judge is_object_front properly const bool is_object_front = true; const bool limit_to_max_velocity = true; const auto ego_predicted_path = behavior_path_planner::utils::path_safety_checker::createPredictedPath( - ego_predicted_path_params_, pull_over_path.points, current_pose, current_velocity, - ego_seg_idx, is_object_front, limit_to_max_velocity); + ego_predicted_path_params, pull_over_path.points, current_pose, current_velocity, ego_seg_idx, + is_object_front, limit_to_max_velocity); // ========================================================================================== // if ego is before the entry of pull_over_lanes, the beginning of the safety check area @@ -2094,36 +2273,38 @@ std::pair GoalPlannerModule::isSafePath() const const auto expanded_pull_over_lanes_between_ego = goal_planner_utils::generateBetweenEgoAndExpandedPullOverLanes( pull_over_lanes, left_side_parking_, ego_pose_for_expand, - planner_data_->parameters.vehicle_info, parameters_->outer_road_detection_offset, - parameters_->inner_road_detection_offset); + planner_data->parameters.vehicle_info, parameters.outer_road_detection_offset, + parameters.inner_road_detection_offset); const auto merged_expanded_pull_over_lanes = lanelet::utils::combineLaneletsShape(expanded_pull_over_lanes_between_ego); debug_data_.expanded_pull_over_lane_between_ego = merged_expanded_pull_over_lanes; const auto filtered_objects = filterObjectsByWithinPolicy( - dynamic_object, {merged_expanded_pull_over_lanes}, objects_filtering_params_); + dynamic_object, {merged_expanded_pull_over_lanes}, objects_filtering_params); + const auto prev_data = thread_safe_data_.get_prev_data(); const double hysteresis_factor = - prev_data_.safety_status.is_safe ? 1.0 : parameters_->hysteresis_factor_expand_rate; + prev_data.safety_status.is_safe ? 1.0 : parameters.hysteresis_factor_expand_rate; + CollisionCheckDebugMap collision_check{}; const bool current_is_safe = std::invoke([&]() { - if (parameters_->safety_check_params.method == "RSS") { + if (parameters.safety_check_params.method == "RSS") { return behavior_path_planner::utils::path_safety_checker::checkSafetyWithRSS( - pull_over_path, ego_predicted_path, filtered_objects, goal_planner_data_.collision_check, - planner_data_->parameters, safety_check_params_->rss_params, - objects_filtering_params_->use_all_predicted_path, hysteresis_factor); - } else if (parameters_->safety_check_params.method == "integral_predicted_polygon") { + pull_over_path, ego_predicted_path, filtered_objects, collision_check, + planner_data->parameters, safety_check_params->rss_params, + objects_filtering_params->use_all_predicted_path, hysteresis_factor); + } else if (parameters.safety_check_params.method == "integral_predicted_polygon") { return utils::path_safety_checker::checkSafetyWithIntegralPredictedPolygon( ego_predicted_path, vehicle_info_, filtered_objects, - objects_filtering_params_->check_all_predicted_path, - parameters_->safety_check_params.integral_predicted_polygon_params, - goal_planner_data_.collision_check); + objects_filtering_params->check_all_predicted_path, + parameters.safety_check_params.integral_predicted_polygon_params, collision_check); } RCLCPP_ERROR( getLogger(), " [pull_over] invalid safety check method: %s", - parameters_->safety_check_params.method.c_str()); + parameters.safety_check_params.method.c_str()); throw std::domain_error("[pull_over] invalid safety check method"); }); + thread_safe_data_.set_collision_check(collision_check); /* * ==== is_safe @@ -2140,9 +2321,9 @@ std::pair GoalPlannerModule::isSafePath() const */ if (current_is_safe) { if ( - prev_data_.safety_status.safe_start_time && - (clock_->now() - prev_data_.safety_status.safe_start_time.value()).seconds() > - parameters_->safety_check_params.keep_unsafe_time) { + prev_data.safety_status.safe_start_time && + (clock_->now() - prev_data.safety_status.safe_start_time.value()).seconds() > + parameters.safety_check_params.keep_unsafe_time) { return {true /*is_safe*/, true /*current_is_safe*/}; } } @@ -2176,8 +2357,12 @@ void GoalPlannerModule::setDebugData() }; if (utils::isAllowedGoalModification(planner_data_->route_handler)) { // Visualize pull over areas - const auto color = hasDecidedPath() ? createMarkerColor(1.0, 1.0, 0.0, 0.999) // yellow - : createMarkerColor(0.0, 1.0, 0.0, 0.999); // green + const auto color = + hasDecidedPath( + planner_data_, occupancy_grid_map_, *parameters_, ego_predicted_path_params_, + objects_filtering_params_, safety_check_params_, goal_searcher_) + ? createMarkerColor(1.0, 1.0, 0.0, 0.999) // yellow + : createMarkerColor(0.0, 1.0, 0.0, 0.999); // green const double z = planner_data_->route_handler->getGoalPose().position.z; add(goal_planner_utils::createPullOverAreaMarkerArray( goal_searcher_->getAreaPolygons(), header, color, z)); @@ -2190,9 +2375,11 @@ void GoalPlannerModule::setDebugData() // Visualize previous module output add(createPathMarkerArray( getPreviousModuleOutput().path, "previous_module_path", 0, 1.0, 0.0, 0.0)); - if (last_previous_module_output_.has_value()) { + + const auto last_previous_module_output = thread_safe_data_.get_last_previous_module_output(); + if (last_previous_module_output.has_value()) { add(createPathMarkerArray( - last_previous_module_output_.value().path, "last_previous_module_path", 0, 0.0, 1.0, 1.0)); + last_previous_module_output.value().path, "last_previous_module_path", 0, 0.0, 1.0, 1.0)); } // Visualize path and related pose @@ -2249,6 +2436,7 @@ void GoalPlannerModule::setDebugData() } } + auto collision_check = thread_safe_data_.get_collision_check(); // safety check if (parameters_->safety_check_params.enable_safety_check) { if (goal_planner_data_.ego_predicted_path.size() > 0) { @@ -2263,33 +2451,35 @@ void GoalPlannerModule::setDebugData() } if (parameters_->safety_check_params.method == "RSS") { - add(showSafetyCheckInfo(goal_planner_data_.collision_check, "object_debug_info")); + add(showSafetyCheckInfo(collision_check, "object_debug_info")); } - add(showPredictedPath(goal_planner_data_.collision_check, "ego_predicted_path")); - add(showPolygon(goal_planner_data_.collision_check, "ego_and_target_polygon_relation")); + add(showPredictedPath(collision_check, "ego_predicted_path")); + add(showPolygon(collision_check, "ego_and_target_polygon_relation")); // set objects of interest - for (const auto & [uuid, data] : goal_planner_data_.collision_check) { + for (const auto & [uuid, data] : collision_check) { const auto color = data.is_safe ? ColorName::GREEN : ColorName::RED; setObjectsOfInterestData(data.current_obj_pose, data.obj_shape, color); } - utils::parking_departure::initializeCollisionCheckDebugMap(goal_planner_data_.collision_check); + // TODO(Mamoru Sobue): it is not clear where ThreadSafeData::collision_check should be cleared + utils::parking_departure::initializeCollisionCheckDebugMap(collision_check); // visualize safety status maker { + const auto prev_data = thread_safe_data_.get_prev_data(); visualization_msgs::msg::MarkerArray marker_array{}; - const auto color = prev_data_.safety_status.is_safe ? createMarkerColor(1.0, 1.0, 1.0, 0.99) - : createMarkerColor(1.0, 0.0, 0.0, 0.99); + const auto color = prev_data.safety_status.is_safe ? createMarkerColor(1.0, 1.0, 1.0, 0.99) + : createMarkerColor(1.0, 0.0, 0.0, 0.99); auto marker = createDefaultMarker( header.frame_id, header.stamp, "safety_status", 0, visualization_msgs::msg::Marker::TEXT_VIEW_FACING, createMarkerScale(0.0, 0.0, 1.0), color); marker.pose = planner_data_->self_odometry->pose.pose; - marker.text += "is_safe: " + std::to_string(prev_data_.safety_status.is_safe) + "\n"; - if (prev_data_.safety_status.safe_start_time) { + marker.text += "is_safe: " + std::to_string(prev_data.safety_status.is_safe) + "\n"; + if (prev_data.safety_status.safe_start_time) { const double elapsed_time_from_safe_start = - (clock_->now() - prev_data_.safety_status.safe_start_time.value()).seconds(); + (clock_->now() - prev_data.safety_status.safe_start_time.value()).seconds(); marker.text += "elapsed_time_from_safe_start: " + std::to_string(elapsed_time_from_safe_start) + "\n"; } @@ -2317,7 +2507,7 @@ void GoalPlannerModule::setDebugData() std::to_string(thread_safe_data_.get_pull_over_path()->partial_paths.size() - 1); } - if (isStuck()) { + if (isStuck(planner_data_, occupancy_grid_map_, *parameters_)) { marker.text += " stuck"; } else if (isStopped()) { marker.text += " stopped"; @@ -2367,9 +2557,12 @@ void GoalPlannerModule::printParkingPositionError() const distance_from_real_shoulder); } -bool GoalPlannerModule::needPathUpdate(const double path_update_duration) const +bool GoalPlannerModule::needPathUpdate( + const Pose & current_pose, const double path_update_duration, + const GoalPlannerParameters & parameters) const { - return !isOnModifiedGoal() && hasEnoughTimePassedSincePathUpdate(path_update_duration); + return !isOnModifiedGoal(current_pose, parameters) && + hasEnoughTimePassedSincePathUpdate(path_update_duration); } bool GoalPlannerModule::hasEnoughTimePassedSincePathUpdate(const double duration) const @@ -2380,4 +2573,58 @@ bool GoalPlannerModule::hasEnoughTimePassedSincePathUpdate(const double duration return (clock_->now() - *thread_safe_data_.get_last_path_update_time()).seconds() > duration; } + +void GoalPlannerModule::GoalPlannerData::initializeOccupancyGridMap( + const PlannerData & planner_data, const GoalPlannerParameters & parameters) +{ + OccupancyGridMapParam occupancy_grid_map_param{}; + const double margin = parameters.occupancy_grid_collision_check_margin; + occupancy_grid_map_param.vehicle_shape.length = + planner_data.parameters.vehicle_length + 2 * margin; + occupancy_grid_map_param.vehicle_shape.width = planner_data.parameters.vehicle_width + 2 * margin; + occupancy_grid_map_param.vehicle_shape.base2back = + planner_data.parameters.base_link2rear + margin; + occupancy_grid_map_param.theta_size = parameters.theta_size; + occupancy_grid_map_param.obstacle_threshold = parameters.obstacle_threshold; + occupancy_grid_map = std::make_shared(); + occupancy_grid_map->setParam(occupancy_grid_map_param); +} + +GoalPlannerModule::GoalPlannerData GoalPlannerModule::GoalPlannerData::clone() const +{ + GoalPlannerModule::GoalPlannerData gp_planner_data(planner_data, parameters); + gp_planner_data.update( + parameters, ego_predicted_path_params, objects_filtering_params, safety_check_params, + planner_data, current_status, previous_module_output, goal_searcher, vehicle_footprint); + return gp_planner_data; +} + +void GoalPlannerModule::GoalPlannerData::update( + const GoalPlannerParameters & parameters_, + const std::shared_ptr & ego_predicted_path_params_, + const std::shared_ptr & objects_filtering_params_, + const std::shared_ptr & safety_check_params_, + const PlannerData & planner_data_, const ModuleStatus & current_status_, + const BehaviorModuleOutput & previous_module_output_, + const std::shared_ptr goal_searcher_, + const tier4_autoware_utils::LinearRing2d & vehicle_footprint_) +{ + parameters = parameters_; + ego_predicted_path_params = ego_predicted_path_params_; + objects_filtering_params = objects_filtering_params_; + safety_check_params = safety_check_params_; + vehicle_footprint = vehicle_footprint_; + + planner_data = planner_data_; + planner_data.route_handler = std::make_shared(*(planner_data_.route_handler)); + current_status = current_status_; + previous_module_output = previous_module_output_; + occupancy_grid_map->setMap(*(planner_data.occupancy_grid)); + // to create a deepcopy of GoalPlanner(not GoalPlannerBase), goal_searcher_ is not enough, so + // recreate it here + goal_searcher = std::make_shared(parameters, vehicle_footprint); + // and then copy the reference goal + goal_searcher->setReferenceGoal(goal_searcher_->getReferenceGoal()); +} + } // namespace behavior_path_planner diff --git a/planning/behavior_path_goal_planner_module/src/goal_searcher.cpp b/planning/behavior_path_goal_planner_module/src/goal_searcher.cpp index bd19871c482fc..df91687622349 100644 --- a/planning/behavior_path_goal_planner_module/src/goal_searcher.cpp +++ b/planning/behavior_path_goal_planner_module/src/goal_searcher.cpp @@ -90,35 +90,35 @@ struct SortByWeightedDistance }; GoalSearcher::GoalSearcher( - const GoalPlannerParameters & parameters, const LinearRing2d & vehicle_footprint, - const std::shared_ptr & occupancy_grid_map) + const GoalPlannerParameters & parameters, const LinearRing2d & vehicle_footprint) : GoalSearcherBase{parameters}, vehicle_footprint_{vehicle_footprint}, - occupancy_grid_map_{occupancy_grid_map}, left_side_parking_{parameters.parking_policy == ParkingPolicy::LEFT_SIDE} { } -GoalCandidates GoalSearcher::search() +GoalCandidates GoalSearcher::search( + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) { GoalCandidates goal_candidates{}; - const auto & route_handler = planner_data_->route_handler; + const auto & route_handler = planner_data->route_handler; const double forward_length = parameters_.forward_goal_search_length; const double backward_length = parameters_.backward_goal_search_length; const double margin_from_boundary = parameters_.margin_from_boundary; const double lateral_offset_interval = parameters_.lateral_offset_interval; const double max_lateral_offset = parameters_.max_lateral_offset; const double ignore_distance_from_lane_start = parameters_.ignore_distance_from_lane_start; - const double vehicle_width = planner_data_->parameters.vehicle_width; - const double base_link2front = planner_data_->parameters.base_link2front; - const double base_link2rear = planner_data_->parameters.base_link2rear; + const double vehicle_width = planner_data->parameters.vehicle_width; + const double base_link2front = planner_data->parameters.base_link2front; + const double base_link2rear = planner_data->parameters.base_link2rear; const auto pull_over_lanes = goal_planner_utils::getPullOverLanes( *route_handler, left_side_parking_, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length); auto lanes = utils::getExtendedCurrentLanes( - planner_data_, backward_length, forward_length, + planner_data, backward_length, forward_length, /*forward_only_in_route*/ false); lanes.insert(lanes.end(), pull_over_lanes.begin(), pull_over_lanes.end()); @@ -193,17 +193,18 @@ GoalCandidates GoalSearcher::search() goal_candidates.push_back(goal_candidate); } } - createAreaPolygons(original_search_poses); + createAreaPolygons(original_search_poses, planner_data); - update(goal_candidates); + update(goal_candidates, occupancy_grid_map, planner_data); return goal_candidates; } void GoalSearcher::countObjectsToAvoid( - GoalCandidates & goal_candidates, const PredictedObjects & objects) const + GoalCandidates & goal_candidates, const PredictedObjects & objects, + const std::shared_ptr & planner_data) const { - const auto & route_handler = planner_data_->route_handler; + const auto & route_handler = planner_data->route_handler; const double forward_length = parameters_.forward_goal_search_length; const double backward_length = parameters_.backward_goal_search_length; @@ -225,7 +226,7 @@ void GoalSearcher::countObjectsToAvoid( // generate current lane center line path to check collision with objects const auto current_lanes = utils::getExtendedCurrentLanes( - planner_data_, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, + planner_data, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, /*forward_only_in_route*/ false); const auto current_center_line_path = std::invoke([&]() -> PathWithLaneId { const double s_start = @@ -264,16 +265,19 @@ void GoalSearcher::countObjectsToAvoid( } } -void GoalSearcher::update(GoalCandidates & goal_candidates) const +void GoalSearcher::update( + GoalCandidates & goal_candidates, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const { const auto pull_over_lane_stop_objects = goal_planner_utils::extractStaticObjectsInExpandedPullOverLanes( - *(planner_data_->route_handler), left_side_parking_, parameters_.backward_goal_search_length, + *(planner_data->route_handler), left_side_parking_, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, parameters_.detection_bound_offset, - *(planner_data_->dynamic_object), parameters_.th_moving_object_velocity); + *(planner_data->dynamic_object), parameters_.th_moving_object_velocity); if (parameters_.prioritize_goals_before_objects) { - countObjectsToAvoid(goal_candidates, pull_over_lane_stop_objects); + countObjectsToAvoid(goal_candidates, pull_over_lane_stop_objects, planner_data); } if (parameters_.goal_priority == "minimum_weighted_distance") { @@ -293,7 +297,7 @@ void GoalSearcher::update(GoalCandidates & goal_candidates) const const Pose goal_pose = goal_candidate.goal_pose; // check collision with footprint - if (checkCollision(goal_pose, pull_over_lane_stop_objects)) { + if (checkCollision(goal_pose, pull_over_lane_stop_objects, occupancy_grid_map)) { goal_candidate.is_safe = false; continue; } @@ -301,9 +305,10 @@ void GoalSearcher::update(GoalCandidates & goal_candidates) const // check longitudinal margin with pull over lane objects constexpr bool filter_inside = true; const auto target_objects = goal_planner_utils::filterObjectsByLateralDistance( - goal_pose, planner_data_->parameters.vehicle_width, pull_over_lane_stop_objects, + goal_pose, planner_data->parameters.vehicle_width, pull_over_lane_stop_objects, parameters_.object_recognition_collision_check_hard_margins.back(), filter_inside); - if (checkCollisionWithLongitudinalDistance(goal_pose, target_objects)) { + if (checkCollisionWithLongitudinalDistance( + goal_pose, target_objects, occupancy_grid_map, planner_data)) { goal_candidate.is_safe = false; continue; } @@ -316,7 +321,9 @@ void GoalSearcher::update(GoalCandidates & goal_candidates) const // current planner_data_ and margin scale factor. // And is_safe is not updated in this function. bool GoalSearcher::isSafeGoalWithMarginScaleFactor( - const GoalCandidate & goal_candidate, const double margin_scale_factor) const + const GoalCandidate & goal_candidate, const double margin_scale_factor, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const { if (!parameters_.use_object_recognition) { return true; @@ -326,9 +333,9 @@ bool GoalSearcher::isSafeGoalWithMarginScaleFactor( const auto pull_over_lane_stop_objects = goal_planner_utils::extractStaticObjectsInExpandedPullOverLanes( - *(planner_data_->route_handler), left_side_parking_, parameters_.backward_goal_search_length, + *(planner_data->route_handler), left_side_parking_, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, parameters_.detection_bound_offset, - *(planner_data_->dynamic_object), parameters_.th_moving_object_velocity); + *(planner_data->dynamic_object), parameters_.th_moving_object_velocity); const double margin = parameters_.object_recognition_collision_check_hard_margins.back() * margin_scale_factor; @@ -341,23 +348,26 @@ bool GoalSearcher::isSafeGoalWithMarginScaleFactor( // check longitudinal margin with pull over lane objects constexpr bool filter_inside = true; const auto target_objects = goal_planner_utils::filterObjectsByLateralDistance( - goal_pose, planner_data_->parameters.vehicle_width, pull_over_lane_stop_objects, margin, + goal_pose, planner_data->parameters.vehicle_width, pull_over_lane_stop_objects, margin, filter_inside); - if (checkCollisionWithLongitudinalDistance(goal_pose, target_objects)) { + if (checkCollisionWithLongitudinalDistance( + goal_pose, target_objects, occupancy_grid_map, planner_data)) { return false; } return true; } -bool GoalSearcher::checkCollision(const Pose & pose, const PredictedObjects & objects) const +bool GoalSearcher::checkCollision( + const Pose & pose, const PredictedObjects & objects, + const std::shared_ptr occupancy_grid_map) const { if (parameters_.use_occupancy_grid_for_goal_search) { - const Pose pose_grid_coords = global2local(occupancy_grid_map_->getMap(), pose); + const Pose pose_grid_coords = global2local(occupancy_grid_map->getMap(), pose); const auto idx = pose2index( - occupancy_grid_map_->getMap(), pose_grid_coords, occupancy_grid_map_->getParam().theta_size); + occupancy_grid_map->getMap(), pose_grid_coords, occupancy_grid_map->getParam().theta_size); const bool check_out_of_range = false; - if (occupancy_grid_map_->detectCollision(idx, check_out_of_range)) { + if (occupancy_grid_map->detectCollision(idx, check_out_of_range)) { return true; } } @@ -373,7 +383,9 @@ bool GoalSearcher::checkCollision(const Pose & pose, const PredictedObjects & ob } bool GoalSearcher::checkCollisionWithLongitudinalDistance( - const Pose & ego_pose, const PredictedObjects & objects) const + const Pose & ego_pose, const PredictedObjects & objects, + const std::shared_ptr occupancy_grid_map, + const std::shared_ptr & planner_data) const { if ( parameters_.use_occupancy_grid_for_goal_search && @@ -385,22 +397,22 @@ bool GoalSearcher::checkCollisionWithLongitudinalDistance( // check forward collision const Pose ego_pose_moved_forward = calcOffsetPose(ego_pose, offset, 0, 0); const Pose forward_pose_grid_coords = - global2local(occupancy_grid_map_->getMap(), ego_pose_moved_forward); + global2local(occupancy_grid_map->getMap(), ego_pose_moved_forward); const auto forward_idx = pose2index( - occupancy_grid_map_->getMap(), forward_pose_grid_coords, - occupancy_grid_map_->getParam().theta_size); - if (occupancy_grid_map_->detectCollision(forward_idx, check_out_of_range)) { + occupancy_grid_map->getMap(), forward_pose_grid_coords, + occupancy_grid_map->getParam().theta_size); + if (occupancy_grid_map->detectCollision(forward_idx, check_out_of_range)) { return true; } // check backward collision const Pose ego_pose_moved_backward = calcOffsetPose(ego_pose, -offset, 0, 0); const Pose backward_pose_grid_coords = - global2local(occupancy_grid_map_->getMap(), ego_pose_moved_backward); + global2local(occupancy_grid_map->getMap(), ego_pose_moved_backward); const auto backward_idx = pose2index( - occupancy_grid_map_->getMap(), backward_pose_grid_coords, - occupancy_grid_map_->getParam().theta_size); - if (occupancy_grid_map_->detectCollision(backward_idx, check_out_of_range)) { + occupancy_grid_map->getMap(), backward_pose_grid_coords, + occupancy_grid_map->getParam().theta_size); + if (occupancy_grid_map->detectCollision(backward_idx, check_out_of_range)) { return true; } } @@ -408,23 +420,24 @@ bool GoalSearcher::checkCollisionWithLongitudinalDistance( if (parameters_.use_object_recognition) { if ( utils::calcLongitudinalDistanceFromEgoToObjects( - ego_pose, planner_data_->parameters.base_link2front, - planner_data_->parameters.base_link2rear, objects) < parameters_.longitudinal_margin) { + ego_pose, planner_data->parameters.base_link2front, planner_data->parameters.base_link2rear, + objects) < parameters_.longitudinal_margin) { return true; } } return false; } -void GoalSearcher::createAreaPolygons(std::vector original_search_poses) +void GoalSearcher::createAreaPolygons( + std::vector original_search_poses, const std::shared_ptr & planner_data) { using tier4_autoware_utils::MultiPolygon2d; using tier4_autoware_utils::Point2d; using tier4_autoware_utils::Polygon2d; - const double vehicle_width = planner_data_->parameters.vehicle_width; - const double base_link2front = planner_data_->parameters.base_link2front; - const double base_link2rear = planner_data_->parameters.base_link2rear; + const double vehicle_width = planner_data->parameters.vehicle_width; + const double base_link2front = planner_data->parameters.base_link2front; + const double base_link2rear = planner_data->parameters.base_link2rear; const double max_lateral_offset = parameters_.max_lateral_offset; const auto appendPointToPolygon = @@ -506,10 +519,11 @@ bool GoalSearcher::isInAreas(const LinearRing2d & footprint, const BasicPolygons } GoalCandidate GoalSearcher::getClosetGoalCandidateAlongLanes( - const GoalCandidates & goal_candidates) const + const GoalCandidates & goal_candidates, + const std::shared_ptr & planner_data) const { const auto current_lanes = utils::getExtendedCurrentLanes( - planner_data_, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, + planner_data, parameters_.backward_goal_search_length, parameters_.forward_goal_search_length, /*forward_only_in_route*/ false); // Define a lambda function to compute the arc length for a given goal candidate. diff --git a/planning/behavior_path_goal_planner_module/src/shift_pull_over.cpp b/planning/behavior_path_goal_planner_module/src/shift_pull_over.cpp index b168da61e6239..8fba7f760ab9d 100644 --- a/planning/behavior_path_goal_planner_module/src/shift_pull_over.cpp +++ b/planning/behavior_path_goal_planner_module/src/shift_pull_over.cpp @@ -28,11 +28,9 @@ namespace behavior_path_planner { ShiftPullOver::ShiftPullOver( rclcpp::Node & node, const GoalPlannerParameters & parameters, - const LaneDepartureChecker & lane_departure_checker, - const std::shared_ptr & occupancy_grid_map) + const LaneDepartureChecker & lane_departure_checker) : PullOverPlannerBase{node, parameters}, lane_departure_checker_{lane_departure_checker}, - occupancy_grid_map_{occupancy_grid_map}, left_side_parking_{parameters.parking_policy == ParkingPolicy::LEFT_SIDE} { } @@ -220,11 +218,6 @@ std::optional ShiftPullOver::generatePullOverPath( shifted_path.path.points.push_back(p); } - // set the same z as the goal - for (auto & p : shifted_path.path.points) { - p.point.pose.position.z = goal_pose.position.z; - } - // set lane_id and velocity to shifted_path for (size_t i = path_shifter.getShiftLines().front().start_idx; i < shifted_path.path.points.size() - 1; ++i) { diff --git a/planning/behavior_path_goal_planner_module/src/util.cpp b/planning/behavior_path_goal_planner_module/src/util.cpp index a43592deb3c4e..72ae0143783ea 100644 --- a/planning/behavior_path_goal_planner_module/src/util.cpp +++ b/planning/behavior_path_goal_planner_module/src/util.cpp @@ -55,12 +55,11 @@ lanelet::ConstLanelets getPullOverLanes( // todo(kosuek55): automatically calculates this distance. const double backward_distance_with_buffer = backward_distance + 100; - lanelet::ConstLanelet target_shoulder_lane{}; - if (route_handler::RouteHandler::getPullOverTarget( - route_handler.getShoulderLanelets(), goal_pose, &target_shoulder_lane)) { + const auto target_shoulder_lane = route_handler.getPullOverTarget(goal_pose); + if (target_shoulder_lane) { // pull over on shoulder lane return route_handler.getShoulderLaneletSequence( - target_shoulder_lane, goal_pose, backward_distance_with_buffer, forward_distance); + *target_shoulder_lane, goal_pose, backward_distance_with_buffer, forward_distance); } lanelet::ConstLanelet closest_lane{}; @@ -145,7 +144,9 @@ PredictedObjects extractObjectsInExpandedPullOverLanes( route_handler, left_side, backward_distance, forward_distance, bound_offset); const auto [objects_in_lanes, others] = utils::path_safety_checker::separateObjectsByLanelets( - objects, lanes, utils::path_safety_checker::isPolygonOverlapLanelet); + objects, lanes, [](const auto & obj, const auto & lanelet) { + return utils::path_safety_checker::isPolygonOverlapLanelet(obj, lanelet); + }); return objects_in_lanes; } diff --git a/planning/behavior_path_lane_change_module/README.md b/planning/behavior_path_lane_change_module/README.md index 62f35a053958a..9cbd864be9dbb 100644 --- a/planning/behavior_path_lane_change_module/README.md +++ b/planning/behavior_path_lane_change_module/README.md @@ -319,6 +319,171 @@ The detection area for the target lane can be expanded beyond its original bound +##### Object filtering + +```plantuml +@startuml +skinparam defaultTextAlignment center +skinparam backgroundColor #WHITE + +title NormalLaneChange::filterObjects Method Execution Flow + +start + +group "Filter Objects by Class" { +:Iterate through each object in objects list; +while (has not finished iterating through object list) is (TRUE) + if (current object type != param.object_types_to_check?) then (TRUE) + #LightPink:Remove current object; +else (FALSE) + :Keep current object; +endif +end while +end group + +if (object list is empty?) then (TRUE) + :Return empty result; + stop +else (FALSE) +endif + +group "Filter Oncoming Objects" #PowderBlue { +:Iterate through each object in target lane objects list; +while (has not finished iterating through object list?) is (TRUE) +:check object's yaw with reference to ego's yaw.; +if (yaw difference < 90 degree?) then (TRUE) + :Keep current object; +else (FALSE) +if (object is stopping?) then (TRUE) + :Keep current object; +else (FALSE) + #LightPink:Remove current object; +endif +endif +endwhile +end group + +if (object list is empty?) then (TRUE) + :Return empty result; + stop +else (FALSE) +endif + +group "Filter Objects Ahead Terminal" #Beige { +:Calculate lateral distance from ego to current lanes center; + +:Iterate through each object in objects list; +while (has not finished iterating through object list) is (TRUE) + :Get current object's polygon; + :Initialize distance to terminal from object to max; + while (has not finished iterating through object polygon's vertices) is (TRUE) + :Calculate object's lateral distance to end of lane; + :Update minimum distance to terminal from object; + end while + if (Is object's distance to terminal exceeds minimum lane change length?) then (TRUE) + #LightPink:Remove current object; + else (FALSE) + endif +end while +end group + +if (object list is empty?) then (TRUE) + :Return empty result; + stop +else (FALSE) +endif + +group "Filter Objects By Lanelets" #LightGreen { + +:Iterate through each object in objects list; +while (has not finished iterating through object list) is (TRUE) + :lateral distance diff = difference between object's lateral distance and ego's lateral distance to the current lanes' centerline.; + if (Object in target lane polygon, and lateral distance diff is more than half of ego's width?) then (TRUE) + :Add to target_lane_objects; + else (FALSE) + if (Object overlaps with backward target lanes?) then (TRUE) + :Add to target_lane_objects; + else (FALSE) + if (Object in current lane polygon?) then (TRUE) + :Add to current_lane_objects; + else (FALSE) + :Add to other_lane_objects; + endif + endif + endif +end while + +:Return target lanes object, current lanes object and other lanes object; +end group + +:Generate path from current lanes; + +if (path empty?) then (TRUE) + :Return empty result; + stop +else (FALSE) +endif + +group "Filter Target Lanes' objects" #LightCyan { + +:Iterate through each object in target lane objects list; +while (has not finished iterating through object list) is (TRUE) + :check object's velocity; + if(velocity is within threshold?) then (TRUE) + :Keep current object; + else (FALSE) + :check whether object is ahead of ego; + if(object is ahead of ego?) then (TRUE) + :keep current object; + else (FALSE) + #LightPink:remove current object; + endif + endif +endwhile +end group + +group "Filter Current Lanes' objects" #LightYellow { + +:Iterate through each object in current lane objects list; +while (has not finished iterating through object list) is (TRUE) + :check object's velocity; + if(velocity is within threshold?) then (TRUE) + :check whether object is ahead of ego; + if(object is ahead of ego?) then (TRUE) + :keep current object; + else (FALSE) + #LightPink:remove current object; + endif + else (FALSE) + #LightPink:remove current object; + endif +endwhile +end group + +group "Filter Other Lanes' objects" #Lavender { + +:Iterate through each object in other lane objects list; +while (has not finished iterating through object list) is (TRUE) + :check object's velocity; + if(velocity is within threshold?) then (TRUE) + :check whether object is ahead of ego; + if(object is ahead of ego?) then (TRUE) + :keep current object; + else (FALSE) + #LightPink:remove current object; + endif + else (FALSE) + #LightPink:remove current object; + endif +endwhile +end group + +:Trasform the objects into extended predicted object and return them as lane_change_target_objects; +stop + +@enduml +``` + ##### Collision check in prepare phase The ego vehicle may need to secure ample inter-vehicle distance ahead of the target vehicle before attempting a lane change. The flag `enable_collision_check_at_prepare_phase` can be enabled to gain this behavior. The following image illustrates the differences between the `false` and `true` cases. diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/interface.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/interface.hpp index 757ccd3a3116d..6e40f880467fd 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/interface.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/interface.hpp @@ -67,7 +67,7 @@ class LaneChangeInterface : public SceneModuleInterface bool isExecutionReady() const override; - bool isRootLaneletToBeUpdated() const override + bool isCurrentRouteLaneletToBeReset() const override { return getCurrentStatus() == ModuleStatus::SUCCESS; } @@ -93,9 +93,6 @@ class LaneChangeInterface : public SceneModuleInterface MarkerArray getModuleVirtualWall() override; - TurnSignalInfo getCurrentTurnSignalInfo( - const PathWithLaneId & path, const TurnSignalInfo & original_turn_signal_info); - // TODO(someone): remove this, and use base class function [[deprecated]] BehaviorModuleOutput run() override { diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/scene.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/scene.hpp index 7a76daff4bc55..76181f2195a84 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/scene.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/scene.hpp @@ -30,10 +30,12 @@ using behavior_path_planner::utils::path_safety_checker::ExtendedPredictedObject using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityAndPolygonStamped; using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityStamped; using behavior_path_planner::utils::path_safety_checker::PredictedPathWithPolygon; +using data::lane_change::LanesPolygon; using geometry_msgs::msg::Point; using geometry_msgs::msg::Pose; using geometry_msgs::msg::Twist; using route_handler::Direction; +using utils::path_safety_checker::ExtendedPredictedObjects; class NormalLaneChange : public LaneChangeBase { @@ -99,6 +101,8 @@ class NormalLaneChange : public LaneChangeBase bool isStoppedAtRedTrafficLight() const override; + TurnSignalInfo get_current_turn_signal_info() override; + protected: lanelet::ConstLanelets getCurrentLanes() const override; @@ -115,10 +119,26 @@ class NormalLaneChange : public LaneChangeBase const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes) const; - LaneChangeTargetObjects getTargetObjects( + ExtendedPredictedObjects getTargetObjects( + const LaneChangeLanesFilteredObjects & predicted_objects, + const lanelet::ConstLanelets & current_lanes) const; + + LaneChangeLanesFilteredObjects filterObjects( const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes) const; + void filterOncomingObjects(PredictedObjects & objects) const; + + void filterAheadTerminalObjects( + PredictedObjects & objects, const lanelet::ConstLanelets & current_lanes) const; + + void filterObjectsByLanelets( + const PredictedObjects & objects, const lanelet::ConstLanelets & current_lanes, + const lanelet::ConstLanelets & target_lanes, + std::vector & current_lane_objects, + std::vector & target_lane_objects, + std::vector & other_lane_objects) const; + PathWithLaneId getPrepareSegment( const lanelet::ConstLanelets & current_lanes, const double backward_path_length, const double prepare_length) const override; @@ -154,18 +174,11 @@ class NormalLaneChange : public LaneChangeBase bool isValidPath(const PathWithLaneId & path) const override; PathSafetyStatus isLaneChangePathSafe( - const LaneChangePath & lane_change_path, const LaneChangeTargetObjects & target_objects, - const utils::path_safety_checker::RSSparams & rss_params, const bool is_stuck, + const LaneChangePath & lane_change_path, + const ExtendedPredictedObjects & collision_check_objects, + const utils::path_safety_checker::RSSparams & rss_params, CollisionCheckDebugMap & debug_data) const; - LaneChangeTargetObjectIndices filterObject( - const PredictedObjects & objects, const lanelet::ConstLanelets & current_lanes, - const lanelet::ConstLanelets & target_lanes, - const lanelet::ConstLanelets & target_backward_lanes) const; - - std::vector filterObjectsInTargetLane( - const LaneChangeTargetObjects & objects, const lanelet::ConstLanelets & target_lanes) const; - //! @brief Check if the ego vehicle is in stuck by a stationary obstacle. //! @param obstacle_check_distance Distance to check ahead for any objects that might be //! obstructing ego path. It makes sense to use values like the maximum lane change distance. diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/base_class.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/base_class.hpp index 3efc0c9dd61dc..792e8924e5df6 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/base_class.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/base_class.hpp @@ -111,25 +111,9 @@ class LaneChangeBase virtual bool specialExpiredCheck() const { return false; } - virtual void setPreviousModulePaths( - const PathWithLaneId & prev_module_reference_path, const PathWithLaneId & prev_module_path) + void setPreviousModuleOutput(const BehaviorModuleOutput & prev_module_output) { - if (!prev_module_reference_path.points.empty()) { - prev_module_reference_path_ = prev_module_reference_path; - } - if (!prev_module_path.points.empty()) { - prev_module_path_ = prev_module_path; - } - }; - - virtual void setPreviousDrivableAreaInfo(const DrivableAreaInfo & prev_drivable_area_info) - { - prev_drivable_area_info_ = prev_drivable_area_info; - } - - virtual void setPreviousTurnSignalInfo(const TurnSignalInfo & prev_turn_signal_info) - { - prev_turn_signal_info_ = prev_turn_signal_info; + prev_module_output_ = prev_module_output; } virtual void updateSpecialData() {} @@ -203,6 +187,8 @@ class LaneChangeBase void resetStopPose() { lane_change_stop_pose_ = std::nullopt; } + virtual TurnSignalInfo get_current_turn_signal_info() = 0; + protected: virtual lanelet::ConstLanelets getCurrentLanes() const = 0; @@ -233,10 +219,7 @@ class LaneChangeBase std::shared_ptr lane_change_parameters_{}; std::shared_ptr abort_path_{}; std::shared_ptr planner_data_{}; - PathWithLaneId prev_module_reference_path_{}; - PathWithLaneId prev_module_path_{}; - DrivableAreaInfo prev_drivable_area_info_{}; - TurnSignalInfo prev_turn_signal_info_{}; + BehaviorModuleOutput prev_module_output_{}; std::optional lane_change_stop_pose_{std::nullopt}; PathWithLaneId prev_approved_path_{}; diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/data_structs.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/data_structs.hpp index fdaa15ff9bef9..0947f0e5aff94 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/data_structs.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/data_structs.hpp @@ -20,6 +20,7 @@ #include #include +#include #include #include @@ -195,11 +196,11 @@ struct LaneChangeTargetObjectIndices std::vector other_lane{}; }; -struct LaneChangeTargetObjects +struct LaneChangeLanesFilteredObjects { - std::vector current_lane{}; - std::vector target_lane{}; - std::vector other_lane{}; + utils::path_safety_checker::ExtendedPredictedObjects current_lane{}; + utils::path_safety_checker::ExtendedPredictedObjects target_lane{}; + utils::path_safety_checker::ExtendedPredictedObjects other_lane{}; }; enum class LaneChangeModuleType { @@ -216,6 +217,13 @@ struct PathSafetyStatus bool is_safe{true}; bool is_object_coming_from_rear{false}; }; + +struct LanesPolygon +{ + std::optional current; + std::optional target; + std::vector target_backward; +}; } // namespace behavior_path_planner::data::lane_change #endif // BEHAVIOR_PATH_LANE_CHANGE_MODULE__UTILS__DATA_STRUCTS_HPP_ diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/debug_structs.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/debug_structs.hpp index 37d436f9949a2..fbdd742a8457b 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/debug_structs.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/debug_structs.hpp @@ -35,7 +35,7 @@ struct Debug LaneChangePaths valid_paths; CollisionCheckDebugMap collision_check_objects; CollisionCheckDebugMap collision_check_objects_after_approval; - LaneChangeTargetObjects filtered_objects; + LaneChangeLanesFilteredObjects filtered_objects; geometry_msgs::msg::Polygon execution_area; geometry_msgs::msg::Pose ego_pose; lanelet::ConstLanelets current_lanes; diff --git a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/utils.hpp b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/utils.hpp index 76331bd98eb9c..2d427213141b4 100644 --- a/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/utils.hpp +++ b/planning/behavior_path_lane_change_module/include/behavior_path_lane_change_module/utils/utils.hpp @@ -46,6 +46,7 @@ using behavior_path_planner::utils::path_safety_checker::ExtendedPredictedObject using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityAndPolygonStamped; using behavior_path_planner::utils::path_safety_checker::PoseWithVelocityStamped; using behavior_path_planner::utils::path_safety_checker::PredictedPathWithPolygon; +using data::lane_change::LanesPolygon; using data::lane_change::PathSafetyStatus; using geometry_msgs::msg::Point; using geometry_msgs::msg::Pose; @@ -58,8 +59,11 @@ double calcLaneChangeResampleInterval( const double lane_changing_length, const double lane_changing_velocity); double calcMinimumLaneChangeLength( - const LaneChangeParameters & lane_change_parameters, const std::vector & shift_intervals, - const double length_to_intersection = 0.0); + const LaneChangeParameters & lane_change_parameters, const std::vector & shift_intervals); + +double calcMinimumLaneChangeLength( + const std::shared_ptr & route_handler, const lanelet::ConstLanelet & lane, + const LaneChangeParameters & lane_change_parameters, Direction direction); double calcMaximumLaneChangeLength( const double current_velocity, const LaneChangeParameters & lane_change_parameters, @@ -139,7 +143,7 @@ std::vector generateDrivableLanes( double getLateralShift(const LaneChangePath & path); bool hasEnoughLengthToLaneChangeAfterAbort( - const RouteHandler & route_handler, const lanelet::ConstLanelets & current_lanes, + const std::shared_ptr & route_handler, const lanelet::ConstLanelets & current_lanes, const Pose & curent_pose, const double abort_return_dist, const LaneChangeParameters & lane_change_parameters, const Direction direction); @@ -289,6 +293,10 @@ bool isWithinTurnDirectionLanes(const lanelet::ConstLanelet & lanelet, const Pol double calcPhaseLength( const double velocity, const double maximum_velocity, const double acceleration, const double time); + +LanesPolygon createLanesPolygon( + const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes, + const std::vector & target_backward_lanes); } // namespace behavior_path_planner::utils::lane_change namespace behavior_path_planner::utils::lane_change::debug diff --git a/planning/behavior_path_lane_change_module/src/interface.cpp b/planning/behavior_path_lane_change_module/src/interface.cpp index af2ccb807d989..2567787a3f2e4 100644 --- a/planning/behavior_path_lane_change_module/src/interface.cpp +++ b/planning/behavior_path_lane_change_module/src/interface.cpp @@ -76,10 +76,7 @@ bool LaneChangeInterface::isExecutionReady() const void LaneChangeInterface::updateData() { - module_type_->setPreviousModulePaths( - getPreviousModuleOutput().reference_path, getPreviousModuleOutput().path); - module_type_->setPreviousDrivableAreaInfo(getPreviousModuleOutput().drivable_area_info); - module_type_->setPreviousTurnSignalInfo(getPreviousModuleOutput().turn_signal_info); + module_type_->setPreviousModuleOutput(getPreviousModuleOutput()); module_type_->updateSpecialData(); if (isWaitingApproval()) { @@ -138,8 +135,7 @@ BehaviorModuleOutput LaneChangeInterface::planWaitingApproval() BehaviorModuleOutput out = getPreviousModuleOutput(); module_type_->insertStopPoint(module_type_->getLaneChangeStatus().current_lanes, out.path); - out.turn_signal_info = - getCurrentTurnSignalInfo(out.path, getPreviousModuleOutput().turn_signal_info); + out.turn_signal_info = module_type_->get_current_turn_signal_info(); const auto & lane_change_debug = module_type_->getDebugData(); for (const auto & [uuid, data] : lane_change_debug.collision_check_objects) { @@ -370,81 +366,4 @@ void LaneChangeInterface::updateSteeringFactorPtr( {output.start_distance_to_path_change, output.finish_distance_to_path_change}, PlanningBehavior::LANE_CHANGE, steering_factor_direction, SteeringFactor::APPROACHING, ""); } - -TurnSignalInfo LaneChangeInterface::getCurrentTurnSignalInfo( - const PathWithLaneId & path, const TurnSignalInfo & original_turn_signal_info) -{ - const auto & current_lanes = module_type_->getLaneChangeStatus().current_lanes; - const auto & is_valid = module_type_->getLaneChangeStatus().is_valid_path; - const auto & lane_change_path = module_type_->getLaneChangeStatus().lane_change_path; - const auto & lane_change_param = module_type_->getLaneChangeParam(); - - if ( - module_type_->getModuleType() != LaneChangeModuleType::NORMAL || current_lanes.empty() || - !is_valid) { - return original_turn_signal_info; - } - - // check direction - TurnSignalInfo current_turn_signal_info; - const auto & current_pose = module_type_->getEgoPose(); - const auto direction = module_type_->getDirection(); - if (direction == Direction::LEFT) { - current_turn_signal_info.turn_signal.command = TurnIndicatorsCommand::ENABLE_LEFT; - } else if (direction == Direction::RIGHT) { - current_turn_signal_info.turn_signal.command = TurnIndicatorsCommand::ENABLE_RIGHT; - } - - if (path.points.empty()) { - current_turn_signal_info.desired_start_point = current_pose; - current_turn_signal_info.required_start_point = current_pose; - current_turn_signal_info.desired_end_point = lane_change_path.info.lane_changing_end; - current_turn_signal_info.required_end_point = lane_change_path.info.lane_changing_end; - return current_turn_signal_info; - } - - const auto & min_length_for_turn_signal_activation = - lane_change_param.min_length_for_turn_signal_activation; - const auto & route_handler = module_type_->getRouteHandler(); - const auto & common_parameter = module_type_->getCommonParam(); - const auto shift_intervals = - route_handler->getLateralIntervalsToPreferredLane(current_lanes.back()); - const double next_lane_change_buffer = - utils::lane_change::calcMinimumLaneChangeLength(lane_change_param, shift_intervals); - const double & nearest_dist_threshold = common_parameter.ego_nearest_dist_threshold; - const double & nearest_yaw_threshold = common_parameter.ego_nearest_yaw_threshold; - const double & base_to_front = common_parameter.base_link2front; - - const double buffer = - next_lane_change_buffer + min_length_for_turn_signal_activation + base_to_front; - const double path_length = motion_utils::calcArcLength(path.points); - const size_t & current_nearest_seg_idx = - motion_utils::findFirstNearestSegmentIndexWithSoftConstraints( - path.points, current_pose, nearest_dist_threshold, nearest_yaw_threshold); - const double dist_to_terminal = utils::getDistanceToEndOfLane(current_pose, current_lanes); - const auto start_pose = - motion_utils::calcLongitudinalOffsetPose(path.points, 0, std::max(path_length - buffer, 0.0)); - if (dist_to_terminal - base_to_front < buffer && start_pose) { - // modify turn signal - current_turn_signal_info.desired_start_point = *start_pose; - current_turn_signal_info.desired_end_point = lane_change_path.info.lane_changing_end; - current_turn_signal_info.required_start_point = current_turn_signal_info.desired_start_point; - current_turn_signal_info.required_end_point = current_turn_signal_info.desired_end_point; - - const auto & original_command = original_turn_signal_info.turn_signal.command; - if ( - original_command == TurnIndicatorsCommand::DISABLE || - original_command == TurnIndicatorsCommand::NO_COMMAND) { - return current_turn_signal_info; - } - - // check the priority of turn signals - return module_type_->getTurnSignalDecider().use_prior_turn_signal( - path, current_pose, current_nearest_seg_idx, original_turn_signal_info, - current_turn_signal_info, nearest_dist_threshold, nearest_yaw_threshold); - } - - // not in the vicinity of the end of the path. return original - return original_turn_signal_info; -} } // namespace behavior_path_planner diff --git a/planning/behavior_path_lane_change_module/src/scene.cpp b/planning/behavior_path_lane_change_module/src/scene.cpp index db96f7c83d72a..1052a283efc47 100644 --- a/planning/behavior_path_lane_change_module/src/scene.cpp +++ b/planning/behavior_path_lane_change_module/src/scene.cpp @@ -38,6 +38,9 @@ namespace behavior_path_planner { using motion_utils::calcSignedArcLength; +using utils::lane_change::calcMinimumLaneChangeLength; +using utils::lane_change::createLanesPolygon; +using utils::path_safety_checker::isPolygonOverlapLanelet; using utils::traffic_light::getDistanceToNextTrafficLight; NormalLaneChange::NormalLaneChange( @@ -133,6 +136,83 @@ bool NormalLaneChange::isStoppedAtRedTrafficLight() const status_.lane_change_path.info.length.sum()); } +TurnSignalInfo NormalLaneChange::get_current_turn_signal_info() +{ + const auto original_turn_signal_info = prev_module_output_.turn_signal_info; + + const auto & current_lanes = getLaneChangeStatus().current_lanes; + const auto is_valid = getLaneChangeStatus().is_valid_path; + const auto & lane_change_path = getLaneChangeStatus().lane_change_path; + const auto & lane_change_param = getLaneChangeParam(); + + if (getModuleType() != LaneChangeModuleType::NORMAL || current_lanes.empty() || !is_valid) { + return original_turn_signal_info; + } + + // check direction + TurnSignalInfo current_turn_signal_info; + const auto & current_pose = getEgoPose(); + const auto direction = getDirection(); + if (direction == Direction::LEFT) { + current_turn_signal_info.turn_signal.command = TurnIndicatorsCommand::ENABLE_LEFT; + } else if (direction == Direction::RIGHT) { + current_turn_signal_info.turn_signal.command = TurnIndicatorsCommand::ENABLE_RIGHT; + } + + const auto & path = prev_module_output_.path; + if (path.points.empty()) { + current_turn_signal_info.desired_start_point = current_pose; + current_turn_signal_info.required_start_point = current_pose; + current_turn_signal_info.desired_end_point = lane_change_path.info.lane_changing_end; + current_turn_signal_info.required_end_point = lane_change_path.info.lane_changing_end; + return current_turn_signal_info; + } + + const auto min_length_for_turn_signal_activation = + lane_change_param.min_length_for_turn_signal_activation; + const auto & route_handler = getRouteHandler(); + const auto & common_parameter = getCommonParam(); + const auto shift_intervals = + route_handler->getLateralIntervalsToPreferredLane(current_lanes.back()); + const double next_lane_change_buffer = + utils::lane_change::calcMinimumLaneChangeLength(lane_change_param, shift_intervals); + const double nearest_dist_threshold = common_parameter.ego_nearest_dist_threshold; + const double nearest_yaw_threshold = common_parameter.ego_nearest_yaw_threshold; + const double base_to_front = common_parameter.base_link2front; + + const double buffer = + next_lane_change_buffer + min_length_for_turn_signal_activation + base_to_front; + const double path_length = motion_utils::calcArcLength(path.points); + const size_t current_nearest_seg_idx = + motion_utils::findFirstNearestSegmentIndexWithSoftConstraints( + path.points, current_pose, nearest_dist_threshold, nearest_yaw_threshold); + const double dist_to_terminal = utils::getDistanceToEndOfLane(current_pose, current_lanes); + const auto start_pose = + motion_utils::calcLongitudinalOffsetPose(path.points, 0, std::max(path_length - buffer, 0.0)); + if (dist_to_terminal - base_to_front < buffer && start_pose) { + // modify turn signal + current_turn_signal_info.desired_start_point = *start_pose; + current_turn_signal_info.desired_end_point = lane_change_path.info.lane_changing_end; + current_turn_signal_info.required_start_point = current_turn_signal_info.desired_start_point; + current_turn_signal_info.required_end_point = current_turn_signal_info.desired_end_point; + + const auto & original_command = original_turn_signal_info.turn_signal.command; + if ( + original_command == TurnIndicatorsCommand::DISABLE || + original_command == TurnIndicatorsCommand::NO_COMMAND) { + return current_turn_signal_info; + } + + // check the priority of turn signals + return getTurnSignalDecider().use_prior_turn_signal( + path, current_pose, current_nearest_seg_idx, original_turn_signal_info, + current_turn_signal_info, nearest_dist_threshold, nearest_yaw_threshold); + } + + // not in the vicinity of the end of the path. return original + return original_turn_signal_info; +} + LaneChangePath NormalLaneChange::getLaneChangePath() const { return status_.lane_change_path; @@ -140,52 +220,41 @@ LaneChangePath NormalLaneChange::getLaneChangePath() const BehaviorModuleOutput NormalLaneChange::getTerminalLaneChangePath() const { - BehaviorModuleOutput output; + auto output = prev_module_output_; if (isAbortState() && abort_path_) { output.path = abort_path_->path; - output.reference_path = prev_module_reference_path_; - output.turn_signal_info = prev_turn_signal_info_; extendOutputDrivableArea(output); const auto current_seg_idx = planner_data_->findEgoSegmentIndex(output.path.points); output.turn_signal_info = planner_data_->turn_signal_decider.use_prior_turn_signal( - output.path, getEgoPose(), current_seg_idx, prev_turn_signal_info_, output.turn_signal_info, - planner_data_->parameters.ego_nearest_dist_threshold, + output.path, getEgoPose(), current_seg_idx, prev_module_output_.turn_signal_info, + output.turn_signal_info, planner_data_->parameters.ego_nearest_dist_threshold, planner_data_->parameters.ego_nearest_yaw_threshold); return output; } const auto current_lanes = getCurrentLanes(); if (current_lanes.empty()) { - RCLCPP_WARN(logger_, "Current lanes not found!!! Something wrong."); - output.path = prev_module_path_; - output.reference_path = prev_module_reference_path_; - output.drivable_area_info = prev_drivable_area_info_; - output.turn_signal_info = prev_turn_signal_info_; - return output; + RCLCPP_DEBUG(logger_, "Current lanes not found. Returning previous module's path as output."); + return prev_module_output_; } const auto terminal_path = calcTerminalLaneChangePath(current_lanes, getLaneChangeLanes(current_lanes, direction_)); if (!terminal_path) { - RCLCPP_DEBUG(logger_, "Terminal path not found!!!"); - output.path = prev_module_path_; - output.reference_path = prev_module_reference_path_; - output.drivable_area_info = prev_drivable_area_info_; - output.turn_signal_info = prev_turn_signal_info_; - return output; + RCLCPP_DEBUG(logger_, "Terminal path not found. Returning previous module's path as output."); + return prev_module_output_; } output.path = terminal_path->path; - output.reference_path = prev_module_reference_path_; output.turn_signal_info = updateOutputTurnSignal(); extendOutputDrivableArea(output); const auto current_seg_idx = planner_data_->findEgoSegmentIndex(output.path.points); output.turn_signal_info = planner_data_->turn_signal_decider.use_prior_turn_signal( - output.path, getEgoPose(), current_seg_idx, prev_turn_signal_info_, output.turn_signal_info, - planner_data_->parameters.ego_nearest_dist_threshold, + output.path, getEgoPose(), current_seg_idx, prev_module_output_.turn_signal_info, + output.turn_signal_info, planner_data_->parameters.ego_nearest_dist_threshold, planner_data_->parameters.ego_nearest_yaw_threshold); return output; @@ -193,20 +262,14 @@ BehaviorModuleOutput NormalLaneChange::getTerminalLaneChangePath() const BehaviorModuleOutput NormalLaneChange::generateOutput() { - BehaviorModuleOutput output; - if (!status_.is_valid_path) { - output.path = prev_module_path_; - output.reference_path = prev_module_reference_path_; - output.drivable_area_info = prev_drivable_area_info_; - output.turn_signal_info = prev_turn_signal_info_; - return output; + RCLCPP_DEBUG(logger_, "No valid path found. Returning previous module's path as output."); + return prev_module_output_; } + auto output = prev_module_output_; if (isAbortState() && abort_path_) { output.path = abort_path_->path; - output.reference_path = prev_module_reference_path_; - output.turn_signal_info = prev_turn_signal_info_; insertStopPoint(status_.current_lanes, output.path); } else { output.path = getLaneChangePath().path; @@ -235,8 +298,8 @@ BehaviorModuleOutput NormalLaneChange::generateOutput() const auto current_seg_idx = planner_data_->findEgoSegmentIndex(output.path.points); output.turn_signal_info = planner_data_->turn_signal_decider.use_prior_turn_signal( - output.path, getEgoPose(), current_seg_idx, prev_turn_signal_info_, output.turn_signal_info, - planner_data_->parameters.ego_nearest_dist_threshold, + output.path, getEgoPose(), current_seg_idx, prev_module_output_.turn_signal_info, + output.turn_signal_info, planner_data_->parameters.ego_nearest_dist_threshold, planner_data_->parameters.ego_nearest_yaw_threshold); return output; @@ -256,8 +319,8 @@ void NormalLaneChange::extendOutputDrivableArea(BehaviorModuleOutput & output) c // for new architecture DrivableAreaInfo current_drivable_area_info; current_drivable_area_info.drivable_lanes = expanded_lanes; - output.drivable_area_info = - utils::combineDrivableAreaInfo(current_drivable_area_info, prev_drivable_area_info_); + output.drivable_area_info = utils::combineDrivableAreaInfo( + current_drivable_area_info, prev_module_output_.drivable_area_info); } void NormalLaneChange::insertStopPoint( @@ -274,8 +337,8 @@ void NormalLaneChange::insertStopPoint( } const auto shift_intervals = route_handler->getLateralIntervalsToPreferredLane(lanelets.back()); - const double lane_change_buffer = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals, 0.0); + const auto lane_change_buffer = + calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals); const auto getDistanceAlongLanelet = [&](const geometry_msgs::msg::Pose & target) { return utils::getSignedDistance(path.points.front().point.pose, target, lanelets); @@ -292,7 +355,7 @@ void NormalLaneChange::insertStopPoint( } const double stop_point_buffer = lane_change_parameters_->backward_length_buffer_for_end_of_lane; - const auto target_objects = getTargetObjects(status_.current_lanes, status_.target_lanes); + const auto target_objects = filterObjects(status_.current_lanes, status_.target_lanes); double stopping_distance = distance_to_terminal - lane_change_buffer - stop_point_buffer; const auto is_valid_start_point = std::invoke([&]() -> bool { @@ -404,7 +467,7 @@ void NormalLaneChange::insertStopPoint( PathWithLaneId NormalLaneChange::getReferencePath() const { - return utils::getCenterLinePathFromRootLanelet( + return utils::getCenterLinePathFromLanelet( status_.lane_change_path.info.target_lanes.front(), planner_data_); } @@ -506,7 +569,7 @@ TurnSignalInfo NormalLaneChange::updateOutputTurnSignal() const lanelet::ConstLanelets NormalLaneChange::getCurrentLanes() const { - return utils::getCurrentLanesFromPath(prev_module_path_, planner_data_); + return utils::getCurrentLanesFromPath(prev_module_output_.path, planner_data_); } lanelet::ConstLanelets NormalLaneChange::getLaneChangeLanes( @@ -562,10 +625,8 @@ bool NormalLaneChange::isNearEndOfCurrentLanes( const auto & route_handler = getRouteHandler(); const auto & current_pose = getEgoPose(); - const auto shift_intervals = - route_handler->getLateralIntervalsToPreferredLane(current_lanes.back()); - const auto lane_change_buffer = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals); + const auto lane_change_buffer = calcMinimumLaneChangeLength( + route_handler, current_lanes.back(), *lane_change_parameters_, Direction::NONE); const auto distance_to_lane_change_end = std::invoke([&]() { auto distance_to_end = utils::getDistanceToEndOfLane(current_pose, current_lanes); @@ -738,10 +799,10 @@ std::pair NormalLaneChange::calcCurrentMinMaxAcceleration() cons const auto vehicle_max_acc = std::min(p.max_acc, lane_change_parameters_->max_longitudinal_acc); const auto ego_seg_idx = motion_utils::findFirstNearestSegmentIndexWithSoftConstraints( - prev_module_path_.points, getEgoPose(), p.ego_nearest_dist_threshold, + prev_module_output_.path.points, getEgoPose(), p.ego_nearest_dist_threshold, p.ego_nearest_yaw_threshold); const auto max_path_velocity = - prev_module_path_.points.at(ego_seg_idx).point.longitudinal_velocity_mps; + prev_module_output_.path.points.at(ego_seg_idx).point.longitudinal_velocity_mps; // calculate minimum and maximum acceleration const auto min_acc = utils::lane_change::calcMinimumAcceleration( @@ -765,7 +826,7 @@ double NormalLaneChange::calcMaximumLaneChangeLength( std::vector NormalLaneChange::sampleLongitudinalAccValues( const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes) const { - if (prev_module_path_.points.empty()) { + if (prev_module_output_.path.points.empty()) { return {}; } @@ -852,7 +913,7 @@ PathWithLaneId NormalLaneChange::getPrepareSegment( return PathWithLaneId(); } - auto prepare_segment = prev_module_path_; + auto prepare_segment = prev_module_output_.path; const size_t current_seg_idx = motion_utils::findFirstNearestSegmentIndexWithSoftConstraints( prepare_segment.points, getEgoPose(), 3.0, 1.0); utils::clipPathLength(prepare_segment, current_seg_idx, prepare_length, backward_path_length); @@ -860,228 +921,270 @@ PathWithLaneId NormalLaneChange::getPrepareSegment( return prepare_segment; } -LaneChangeTargetObjects NormalLaneChange::getTargetObjects( +ExtendedPredictedObjects NormalLaneChange::getTargetObjects( + const LaneChangeLanesFilteredObjects & filtered_objects, + const lanelet::ConstLanelets & current_lanes) const +{ + ExtendedPredictedObjects target_objects = filtered_objects.target_lane; + const auto is_stuck = isVehicleStuck(current_lanes); + const auto chk_obj_in_curr_lanes = lane_change_parameters_->check_objects_on_current_lanes; + if (chk_obj_in_curr_lanes || is_stuck) { + target_objects.insert( + target_objects.end(), filtered_objects.current_lane.begin(), + filtered_objects.current_lane.end()); + } + + const auto chk_obj_in_other_lanes = lane_change_parameters_->check_objects_on_other_lanes; + if (chk_obj_in_other_lanes) { + target_objects.insert( + target_objects.end(), filtered_objects.other_lane.begin(), filtered_objects.other_lane.end()); + } + + return target_objects; +} + +LaneChangeLanesFilteredObjects NormalLaneChange::filterObjects( const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes) const { - const auto current_pose = getEgoPose(); - const auto & route_handler = *getRouteHandler(); + const auto & current_pose = getEgoPose(); + const auto & route_handler = getRouteHandler(); const auto & common_parameters = planner_data_->parameters; auto objects = *planner_data_->dynamic_object; utils::path_safety_checker::filterObjectsByClass( objects, lane_change_parameters_->object_types_to_check); - // get backward lanes - const auto backward_length = lane_change_parameters_->backward_lane_length; - const auto target_backward_lanes = behavior_path_planner::utils::getBackwardLanelets( - route_handler, target_lanes, current_pose, backward_length); + if (objects.objects.empty()) { + return {}; + } - lane_change_debug_.current_lanes = current_lanes; - lane_change_debug_.target_lanes = target_lanes; - lane_change_debug_.target_backward_lanes = target_backward_lanes; + filterOncomingObjects(objects); - // filter objects to get target object index - const auto target_obj_index = - filterObject(objects, current_lanes, target_lanes, target_backward_lanes); + if (objects.objects.empty()) { + return {}; + } - LaneChangeTargetObjects target_objects; - target_objects.current_lane.reserve(target_obj_index.current_lane.size()); - target_objects.target_lane.reserve(target_obj_index.target_lane.size()); - target_objects.other_lane.reserve(target_obj_index.other_lane.size()); + filterAheadTerminalObjects(objects, current_lanes); - // objects in current lane - const auto is_check_prepare_phase = check_prepare_phase(); - for (const auto & obj_idx : target_obj_index.current_lane) { - const auto extended_object = utils::lane_change::transform( - objects.objects.at(obj_idx), common_parameters, *lane_change_parameters_, - is_check_prepare_phase); - target_objects.current_lane.push_back(extended_object); + if (objects.objects.empty()) { + return {}; } - // objects in target lane - for (const auto & obj_idx : target_obj_index.target_lane) { - const auto extended_object = utils::lane_change::transform( - objects.objects.at(obj_idx), common_parameters, *lane_change_parameters_, - is_check_prepare_phase); - target_objects.target_lane.push_back(extended_object); - } + std::vector target_lane_objects; + std::vector current_lane_objects; + std::vector other_lane_objects; + + filterObjectsByLanelets( + objects, current_lanes, target_lanes, current_lane_objects, target_lane_objects, + other_lane_objects); + + const auto is_within_vel_th = [](const auto & object) -> bool { + constexpr double min_vel_th = 1.0; + constexpr double max_vel_th = std::numeric_limits::max(); + return utils::path_safety_checker::filter::velocity_filter(object, min_vel_th, max_vel_th); + }; + + const auto path = + route_handler->getCenterLinePath(current_lanes, 0.0, std::numeric_limits::max()); - // objects in other lane - for (const auto & obj_idx : target_obj_index.other_lane) { - const auto extended_object = utils::lane_change::transform( - objects.objects.at(obj_idx), common_parameters, *lane_change_parameters_, - is_check_prepare_phase); - target_objects.other_lane.push_back(extended_object); + if (path.points.empty()) { + return {}; } - return target_objects; + const auto is_ahead_of_ego = [&path, ¤t_pose](const auto & object) { + const auto obj_polygon = tier4_autoware_utils::toPolygon2d(object).outer(); + + double max_dist_ego_to_obj = std::numeric_limits::lowest(); + for (const auto & polygon_p : obj_polygon) { + const auto obj_p = tier4_autoware_utils::createPoint(polygon_p.x(), polygon_p.y(), 0.0); + const auto dist_ego_to_obj = calcSignedArcLength(path.points, current_pose.position, obj_p); + max_dist_ego_to_obj = std::max(dist_ego_to_obj, max_dist_ego_to_obj); + } + return max_dist_ego_to_obj >= 0.0; + }; + + utils::path_safety_checker::filterObjects( + target_lane_objects, [&](const PredictedObject & object) { + return (is_within_vel_th(object) || is_ahead_of_ego(object)); + }); + + utils::path_safety_checker::filterObjects( + other_lane_objects, [&](const PredictedObject & object) { + return is_within_vel_th(object) && is_ahead_of_ego(object); + }); + + utils::path_safety_checker::filterObjects( + current_lane_objects, [&](const PredictedObject & object) { + return is_within_vel_th(object) && is_ahead_of_ego(object); + }); + + LaneChangeLanesFilteredObjects lane_change_target_objects; + + const auto is_check_prepare_phase = check_prepare_phase(); + std::for_each(target_lane_objects.begin(), target_lane_objects.end(), [&](const auto & object) { + auto extended_predicted_object = utils::lane_change::transform( + object, common_parameters, *lane_change_parameters_, is_check_prepare_phase); + lane_change_target_objects.target_lane.push_back(extended_predicted_object); + }); + + std::for_each(current_lane_objects.begin(), current_lane_objects.end(), [&](const auto & object) { + auto extended_predicted_object = utils::lane_change::transform( + object, common_parameters, *lane_change_parameters_, is_check_prepare_phase); + lane_change_target_objects.current_lane.push_back(extended_predicted_object); + }); + + std::for_each(other_lane_objects.begin(), other_lane_objects.end(), [&](const auto & object) { + auto extended_predicted_object = utils::lane_change::transform( + object, common_parameters, *lane_change_parameters_, is_check_prepare_phase); + lane_change_target_objects.other_lane.push_back(extended_predicted_object); + }); + + lane_change_debug_.filtered_objects = lane_change_target_objects; + + return lane_change_target_objects; } -LaneChangeTargetObjectIndices NormalLaneChange::filterObject( +void NormalLaneChange::filterOncomingObjects(PredictedObjects & objects) const +{ + const auto & current_pose = getEgoPose(); + + const auto is_same_direction = [&](const PredictedObject & object) { + const auto & object_pose = object.kinematics.initial_pose_with_covariance.pose; + return !utils::path_safety_checker::isTargetObjectOncoming(current_pose, object_pose); + }; + + // Perception noise could make stationary objects seem opposite the ego vehicle; check the + // velocity to prevent this. + const auto is_stopped_object = [](const auto & object) -> bool { + constexpr double min_vel_th = -0.5; + constexpr double max_vel_th = 0.5; + return utils::path_safety_checker::filter::velocity_filter(object, min_vel_th, max_vel_th); + }; + + utils::path_safety_checker::filterObjects(objects, [&](const PredictedObject & object) { + const auto same_direction = is_same_direction(object); + if (same_direction) { + return true; + } + + return is_stopped_object(object); + }); +} + +void NormalLaneChange::filterAheadTerminalObjects( + PredictedObjects & objects, const lanelet::ConstLanelets & current_lanes) const +{ + const auto & current_pose = getEgoPose(); + const auto & route_handler = getRouteHandler(); + const auto minimum_lane_change_length = utils::lane_change::calcMinimumLaneChangeLength( + route_handler, current_lanes.back(), *lane_change_parameters_, direction_); + + const auto dist_ego_to_current_lanes_center = + lanelet::utils::getLateralDistanceToClosestLanelet(current_lanes, current_pose); + + // ignore object that are ahead of terminal lane change start + utils::path_safety_checker::filterObjects(objects, [&](const PredictedObject & object) { + const auto obj_polygon = tier4_autoware_utils::toPolygon2d(object).outer(); + // ignore object that are ahead of terminal lane change start + auto distance_to_terminal_from_object = std::numeric_limits::max(); + for (const auto & polygon_p : obj_polygon) { + const auto obj_p = tier4_autoware_utils::createPoint(polygon_p.x(), polygon_p.y(), 0.0); + Pose polygon_pose; + polygon_pose.position = obj_p; + polygon_pose.orientation = object.kinematics.initial_pose_with_covariance.pose.orientation; + const auto dist = utils::getDistanceToEndOfLane(polygon_pose, current_lanes); + distance_to_terminal_from_object = std::min(dist_ego_to_current_lanes_center, dist); + } + + return (minimum_lane_change_length > distance_to_terminal_from_object); + }); +} + +void NormalLaneChange::filterObjectsByLanelets( const PredictedObjects & objects, const lanelet::ConstLanelets & current_lanes, - const lanelet::ConstLanelets & target_lanes, - const lanelet::ConstLanelets & target_backward_lanes) const + const lanelet::ConstLanelets & target_lanes, std::vector & current_lane_objects, + std::vector & target_lane_objects, + std::vector & other_lane_objects) const { - const auto current_pose = getEgoPose(); - const auto & route_handler = *getRouteHandler(); + const auto & current_pose = getEgoPose(); + const auto & route_handler = getRouteHandler(); const auto & common_parameters = planner_data_->parameters; - const auto shift_intervals = - route_handler.getLateralIntervalsToPreferredLane(current_lanes.back(), direction_); - const double minimum_lane_change_length = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals); + const auto check_optional_polygon = [](const auto & object, const auto & polygon) { + return polygon && isPolygonOverlapLanelet(object, *polygon); + }; - // Guard - if (objects.objects.empty()) { - return {}; - } + // get backward lanes + const auto backward_length = lane_change_parameters_->backward_lane_length; + const auto target_backward_lanes = + utils::getPrecedingLanelets(*route_handler, target_lanes, current_pose, backward_length); - // Get path - const auto path = - route_handler.getCenterLinePath(current_lanes, 0.0, std::numeric_limits::max()); - const auto target_path = - route_handler.getCenterLinePath(target_lanes, 0.0, std::numeric_limits::max()); + { + lane_change_debug_.current_lanes = current_lanes; + lane_change_debug_.target_lanes = target_lanes; + + // TODO(Azu) change the type to std::vector + lane_change_debug_.target_backward_lanes.clear(); + std::for_each( + target_backward_lanes.begin(), target_backward_lanes.end(), + [&](const lanelet::ConstLanelets & target_backward_lane) { + lane_change_debug_.target_backward_lanes.insert( + lane_change_debug_.target_backward_lanes.end(), target_backward_lane.begin(), + target_backward_lane.end()); + }); + } - const auto current_polygon = - utils::lane_change::createPolygon(current_lanes, 0.0, std::numeric_limits::max()); const auto expanded_target_lanes = utils::lane_change::generateExpandedLanelets( target_lanes, direction_, lane_change_parameters_->lane_expansion_left_offset, lane_change_parameters_->lane_expansion_right_offset); - const auto target_polygon = utils::lane_change::createPolygon( - expanded_target_lanes, 0.0, std::numeric_limits::max()); + + const auto lanes_polygon = + createLanesPolygon(current_lanes, expanded_target_lanes, target_backward_lanes); const auto dist_ego_to_current_lanes_center = lanelet::utils::getLateralDistanceToClosestLanelet(current_lanes, current_pose); - std::vector> target_backward_polygons; - for (const auto & target_backward_lane : target_backward_lanes) { - // Check to see is target_backward_lane is in current_lanes - // Without this check, current lane object might be treated as target lane object - const auto is_current_lane = [&](const lanelet::ConstLanelet & current_lane) { - return current_lane.id() == target_backward_lane.id(); - }; - - if (std::any_of(current_lanes.begin(), current_lanes.end(), is_current_lane)) { - continue; - } - lanelet::ConstLanelets lanelet{target_backward_lane}; - auto lane_polygon = - utils::lane_change::createPolygon(lanelet, 0.0, std::numeric_limits::max()); - target_backward_polygons.push_back(lane_polygon); + { + const auto reserve_size = objects.objects.size(); + current_lane_objects.reserve(reserve_size); + target_lane_objects.reserve(reserve_size); + other_lane_objects.reserve(reserve_size); } - LaneChangeTargetObjectIndices filtered_obj_indices; - for (size_t i = 0; i < objects.objects.size(); ++i) { - const auto & object = objects.objects.at(i); - const auto obj_velocity_norm = std::hypot( - object.kinematics.initial_twist_with_covariance.twist.linear.x, - object.kinematics.initial_twist_with_covariance.twist.linear.y); - const auto extended_object = utils::lane_change::transform( - object, common_parameters, *lane_change_parameters_, check_prepare_phase()); - - const auto obj_polygon = tier4_autoware_utils::toPolygon2d(object); - - // calc distance from the current ego position - double max_dist_ego_to_obj = std::numeric_limits::lowest(); - double min_dist_ego_to_obj = std::numeric_limits::max(); - const auto obj_polygon_outer = obj_polygon.outer(); - for (const auto & polygon_p : obj_polygon_outer) { - const auto obj_p = tier4_autoware_utils::createPoint(polygon_p.x(), polygon_p.y(), 0.0); - const double dist_ego_to_obj = calcSignedArcLength(path.points, current_pose.position, obj_p); - max_dist_ego_to_obj = std::max(dist_ego_to_obj, max_dist_ego_to_obj); - min_dist_ego_to_obj = std::min(dist_ego_to_obj, min_dist_ego_to_obj); - } - - const auto is_lateral_far = [&]() { + for (const auto & object : objects.objects) { + const auto is_lateral_far = std::invoke([&]() -> bool { const auto dist_object_to_current_lanes_center = lanelet::utils::getLateralDistanceToClosestLanelet( current_lanes, object.kinematics.initial_pose_with_covariance.pose); const auto lateral = dist_object_to_current_lanes_center - dist_ego_to_current_lanes_center; return std::abs(lateral) > (common_parameters.vehicle_width / 2); - }; - - // ignore object that are ahead of terminal lane change start - { - double distance_to_terminal_from_object = std::numeric_limits::max(); - for (const auto & polygon_p : obj_polygon_outer) { - const auto obj_p = tier4_autoware_utils::createPoint(polygon_p.x(), polygon_p.y(), 0.0); - Pose polygon_pose; - polygon_pose.position = obj_p; - polygon_pose.orientation = object.kinematics.initial_pose_with_covariance.pose.orientation; - const double dist = utils::getDistanceToEndOfLane(polygon_pose, current_lanes); - if (dist < distance_to_terminal_from_object) { - distance_to_terminal_from_object = dist; - } - } - if (minimum_lane_change_length > distance_to_terminal_from_object) { - continue; - } - } + }); - // ignore static object that are behind the ego vehicle - if (obj_velocity_norm < 1.0 && max_dist_ego_to_obj < 0.0) { + if (check_optional_polygon(object, lanes_polygon.target) && is_lateral_far) { + target_lane_objects.push_back(object); continue; } - // check if the object intersects with target lanes - if (target_polygon && boost::geometry::intersects(target_polygon.value(), obj_polygon)) { - // TODO(watanabe): ignore static parked object that are in front of the ego vehicle in target - // lanes - - if (max_dist_ego_to_obj >= 0 || is_lateral_far()) { - filtered_obj_indices.target_lane.push_back(i); - continue; - } - } - - const auto check_backward_polygon = [&obj_polygon](const auto & target_backward_polygon) { - return target_backward_polygon && - boost::geometry::intersects(target_backward_polygon.value(), obj_polygon); - }; + const auto is_overlap_target_backward = std::invoke([&]() -> bool { + const auto check_backward_polygon = [&object](const auto & target_backward_polygon) { + return isPolygonOverlapLanelet(object, target_backward_polygon); + }; + return std::any_of( + lanes_polygon.target_backward.begin(), lanes_polygon.target_backward.end(), + check_backward_polygon); + }); // check if the object intersects with target backward lanes - if ( - !target_backward_polygons.empty() && - std::any_of( - target_backward_polygons.begin(), target_backward_polygons.end(), check_backward_polygon)) { - filtered_obj_indices.target_lane.push_back(i); + if (is_overlap_target_backward) { + target_lane_objects.push_back(object); continue; } - // check if the object intersects with current lanes - if ( - current_polygon && boost::geometry::intersects(current_polygon.value(), obj_polygon) && - max_dist_ego_to_obj >= 0.0) { + if (check_optional_polygon(object, lanes_polygon.current)) { // check only the objects that are in front of the ego vehicle - filtered_obj_indices.current_lane.push_back(i); - continue; - } - - // ignore all objects that are behind the ego vehicle and not on the current and target - // lanes - if (max_dist_ego_to_obj < 0.0) { + current_lane_objects.push_back(object); continue; } - filtered_obj_indices.other_lane.push_back(i); - } - - return filtered_obj_indices; -} - -std::vector NormalLaneChange::filterObjectsInTargetLane( - const LaneChangeTargetObjects & objects, const lanelet::ConstLanelets & target_lanes) const -{ - const auto target_polygon = - utils::lane_change::createPolygon(target_lanes, 0.0, std::numeric_limits::max()); - std::vector filtered_objects{}; - if (target_polygon) { - for (auto & obj : objects.target_lane) { - const auto obj_polygon = tier4_autoware_utils::toPolygon2d(obj.initial_pose.pose, obj.shape); - if (boost::geometry::intersects(target_polygon.value(), obj_polygon)) { - filtered_objects.push_back(obj); - } - } + other_lane_objects.push_back(object); } - - return filtered_objects; } PathWithLaneId NormalLaneChange::getTargetSegment( @@ -1125,32 +1228,30 @@ bool NormalLaneChange::hasEnoughLength( const LaneChangePath & path, const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes, const Direction direction) const { + if (target_lanes.empty()) { + return false; + } + const auto current_pose = getEgoPose(); - const auto & route_handler = *getRouteHandler(); - const auto overall_graphs_ptr = route_handler.getOverallGraphPtr(); - const double lane_change_length = path.info.length.sum(); - const auto shift_intervals = - route_handler.getLateralIntervalsToPreferredLane(target_lanes.back(), direction); - double minimum_lane_change_length_to_preferred_lane = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals); + const auto & route_handler = getRouteHandler(); + const auto overall_graphs_ptr = route_handler->getOverallGraphPtr(); + const auto minimum_lane_change_length_to_preferred_lane = calcMinimumLaneChangeLength( + route_handler, target_lanes.back(), *lane_change_parameters_, direction); + const double lane_change_length = path.info.length.sum(); if (lane_change_length > utils::getDistanceToEndOfLane(current_pose, current_lanes)) { return false; } - const auto goal_pose = route_handler.getGoalPose(); + const auto goal_pose = route_handler->getGoalPose(); if ( - route_handler.isInGoalRouteSection(current_lanes.back()) && + route_handler->isInGoalRouteSection(current_lanes.back()) && lane_change_length + minimum_lane_change_length_to_preferred_lane > utils::getSignedDistance(current_pose, goal_pose, current_lanes)) { return false; } // return if there are no target lanes - if (target_lanes.empty()) { - return true; - } - if ( lane_change_length + minimum_lane_change_length_to_preferred_lane > utils::getDistanceToEndOfLane(current_pose, target_lanes)) { @@ -1263,8 +1364,8 @@ bool NormalLaneChange::getLaneChangePaths( return false; } - const auto target_objects = getTargetObjects(current_lanes, target_lanes); - lane_change_debug_.filtered_objects = target_objects; + const auto filtered_objects = filterObjects(current_lanes, target_lanes); + const auto target_objects = getTargetObjects(filtered_objects, current_lanes); const auto prepare_durations = calcPrepareDuration(current_lanes, target_lanes); @@ -1488,13 +1589,11 @@ bool NormalLaneChange::getLaneChangePaths( } candidate_paths->push_back(*candidate_path); - std::vector filtered_objects = - filterObjectsInTargetLane(target_objects, target_lanes); if ( - !is_stuck && - utils::lane_change::passParkedObject( - route_handler, *candidate_path, filtered_objects, lane_change_buffer, is_goal_in_route, - *lane_change_parameters_, lane_change_debug_.collision_check_objects)) { + !is_stuck && utils::lane_change::passParkedObject( + route_handler, *candidate_path, filtered_objects.target_lane, + lane_change_buffer, is_goal_in_route, *lane_change_parameters_, + lane_change_debug_.collision_check_objects)) { debug_print( "Reject: parking vehicle exists in the target lane, and the ego is not in stuck. Skip " "lane change."); @@ -1507,8 +1606,7 @@ bool NormalLaneChange::getLaneChangePaths( } const auto [is_safe, is_object_coming_from_rear] = isLaneChangePathSafe( - *candidate_path, target_objects, rss_params, is_stuck, - lane_change_debug_.collision_check_objects); + *candidate_path, target_objects, rss_params, lane_change_debug_.collision_check_objects); if (is_safe) { debug_print("ACCEPT!!!: it is valid and safe!"); @@ -1570,7 +1668,7 @@ std::optional NormalLaneChange::calcTerminalLaneChangePath( } const auto lane_changing_start_pose = motion_utils::calcLongitudinalOffsetPose( - prev_module_path_.points, current_lane_terminal_point, + prev_module_output_.path.points, current_lane_terminal_point, -(lane_change_buffer + next_lane_change_buffer + distance_to_terminal_from_goal)); if (!lane_changing_start_pose) { @@ -1653,7 +1751,7 @@ std::optional NormalLaneChange::calcTerminalLaneChangePath( lane_changing_start_pose.value(), target_segment.points.front().point.pose, target_lane_reference_path, shift_length); - auto reference_segment = prev_module_path_; + auto reference_segment = prev_module_output_.path; const double length_to_lane_changing_start = motion_utils::calcSignedArcLength( reference_segment.points, reference_segment.points.front().point.pose.position, lane_changing_start_pose->position); @@ -1675,13 +1773,12 @@ PathSafetyStatus NormalLaneChange::isApprovedPathSafe() const const auto & current_lanes = status_.current_lanes; const auto & target_lanes = status_.target_lanes; - const auto target_objects = getTargetObjects(current_lanes, target_lanes); - lane_change_debug_.filtered_objects = target_objects; + const auto filtered_objects = filterObjects(current_lanes, target_lanes); + const auto target_objects = getTargetObjects(filtered_objects, current_lanes); CollisionCheckDebugMap debug_data; - const bool is_stuck = isVehicleStuck(current_lanes); const auto safety_status = isLaneChangePathSafe( - path, target_objects, lane_change_parameters_->rss_params_for_abort, is_stuck, debug_data); + path, target_objects, lane_change_parameters_->rss_params_for_abort, debug_data); { // only for debug purpose lane_change_debug_.collision_check_objects.clear(); @@ -1787,10 +1884,8 @@ bool NormalLaneChange::calcAbortPath() const auto ego_nearest_yaw_threshold = common_param.ego_nearest_yaw_threshold; const auto direction = getDirection(); - const auto shift_intervals = route_handler->getLateralIntervalsToPreferredLane( - selected_path.info.current_lanes.back(), direction); - const double minimum_lane_change_length = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals); + const auto minimum_lane_change_length = utils::lane_change::calcMinimumLaneChangeLength( + route_handler, selected_path.info.current_lanes.back(), *lane_change_parameters_, direction); const auto & lane_changing_path = selected_path.path; const auto lane_changing_end_pose_idx = std::invoke([&]() { @@ -1837,7 +1932,7 @@ bool NormalLaneChange::calcAbortPath() } if (!utils::lane_change::hasEnoughLengthToLaneChangeAfterAbort( - *route_handler, reference_lanelets, current_pose, abort_return_dist, + route_handler, reference_lanelets, current_pose, abort_return_dist, *lane_change_parameters_, direction)) { RCLCPP_ERROR(logger_, "insufficient distance to abort."); return false; @@ -1877,7 +1972,7 @@ bool NormalLaneChange::calcAbortPath() RCLCPP_ERROR(logger_, "failed to generate abort shifted path."); } - PathWithLaneId reference_lane_segment = prev_module_path_; + auto reference_lane_segment = prev_module_output_.path; { const auto terminal_path = calcTerminalLaneChangePath(reference_lanelets, selected_path.info.target_lanes); @@ -1915,12 +2010,17 @@ bool NormalLaneChange::calcAbortPath() } PathSafetyStatus NormalLaneChange::isLaneChangePathSafe( - const LaneChangePath & lane_change_path, const LaneChangeTargetObjects & target_objects, - const utils::path_safety_checker::RSSparams & rss_params, const bool is_stuck, + const LaneChangePath & lane_change_path, const ExtendedPredictedObjects & collision_check_objects, + const utils::path_safety_checker::RSSparams & rss_params, CollisionCheckDebugMap & debug_data) const { PathSafetyStatus path_safety_status; + if (collision_check_objects.empty()) { + RCLCPP_DEBUG(logger_, "There is nothing to check."); + return path_safety_status; + } + const auto & path = lane_change_path.path; const auto & common_parameters = planner_data_->parameters; const auto current_pose = getEgoPose(); @@ -1939,21 +2039,8 @@ PathSafetyStatus NormalLaneChange::isLaneChangePathSafe( const auto debug_predicted_path = utils::path_safety_checker::convertToPredictedPath(ego_predicted_path, time_resolution); - auto collision_check_objects = target_objects.target_lane; const auto current_lanes = getCurrentLanes(); - if (lane_change_parameters_->check_objects_on_current_lanes || is_stuck) { - collision_check_objects.insert( - collision_check_objects.end(), target_objects.current_lane.begin(), - target_objects.current_lane.end()); - } - - if (lane_change_parameters_->check_objects_on_other_lanes) { - collision_check_objects.insert( - collision_check_objects.end(), target_objects.other_lane.begin(), - target_objects.other_lane.end()); - } - const auto expanded_target_lanes = utils::lane_change::generateExpandedLanelets( lane_change_path.info.target_lanes, direction_, lane_change_parameters_->lane_expansion_left_offset, @@ -2044,10 +2131,8 @@ bool NormalLaneChange::isVehicleStuck( route_handler->isInGoalRouteSection(current_lanes.back()) ? utils::getSignedDistance(getEgoPose(), route_handler->getGoalPose(), current_lanes) : utils::getDistanceToEndOfLane(getEgoPose(), current_lanes); - const auto shift_intervals = - route_handler->getLateralIntervalsToPreferredLane(current_lanes.back()); - const double lane_change_buffer = - utils::lane_change::calcMinimumLaneChangeLength(*lane_change_parameters_, shift_intervals, 0.0); + const auto lane_change_buffer = calcMinimumLaneChangeLength( + route_handler, current_lanes.back(), *lane_change_parameters_, Direction::NONE); const double stop_point_buffer = lane_change_parameters_->backward_length_buffer_for_end_of_lane; const double terminal_judge_buffer = lane_change_buffer + stop_point_buffer + 1.0; if (distance_to_terminal < terminal_judge_buffer) { @@ -2163,5 +2248,4 @@ bool NormalLaneChange::check_prepare_phase() const return check_in_intersection || check_in_turns || check_in_general_lanes; } - } // namespace behavior_path_planner diff --git a/planning/behavior_path_lane_change_module/src/utils/utils.cpp b/planning/behavior_path_lane_change_module/src/utils/utils.cpp index 97fcc841a546e..ab9a0b7176fdb 100644 --- a/planning/behavior_path_lane_change_module/src/utils/utils.cpp +++ b/planning/behavior_path_lane_change_module/src/utils/utils.cpp @@ -49,6 +49,8 @@ #include #include #include +#include +#include #include #include #include @@ -67,6 +69,12 @@ using tier4_autoware_utils::Polygon2d; using autoware_auto_planning_msgs::msg::PathPointWithLaneId; using lanelet::ArcCoordinates; +rclcpp::Logger get_logger() +{ + constexpr const char * name{"lane_change.utils"}; + return rclcpp::get_logger(name); +} + double calcLaneChangeResampleInterval( const double lane_changing_length, const double lane_changing_velocity) { @@ -77,29 +85,40 @@ double calcLaneChangeResampleInterval( } double calcMinimumLaneChangeLength( - const LaneChangeParameters & lane_change_parameters, const std::vector & shift_intervals, - const double length_to_intersection) + const LaneChangeParameters & lane_change_parameters, const std::vector & shift_intervals) { if (shift_intervals.empty()) { return 0.0; } - const double & vel = lane_change_parameters.minimum_lane_changing_velocity; - const auto lat_acc = lane_change_parameters.lane_change_lat_acc_map.find(vel); - const double & max_lateral_acc = lat_acc.second; - const double & lateral_jerk = lane_change_parameters.lane_changing_lateral_jerk; - const double & finish_judge_buffer = lane_change_parameters.lane_change_finish_judge_buffer; - const double & backward_buffer = lane_change_parameters.backward_length_buffer_for_end_of_lane; - - double accumulated_length = length_to_intersection; - for (const auto & shift_interval : shift_intervals) { - const double t = - PathShifter::calcShiftTimeFromJerk(shift_interval, lateral_jerk, max_lateral_acc); - accumulated_length += vel * t + finish_judge_buffer; + const auto min_vel = lane_change_parameters.minimum_lane_changing_velocity; + const auto [min_lat_acc, max_lat_acc] = + lane_change_parameters.lane_change_lat_acc_map.find(min_vel); + const auto lat_jerk = lane_change_parameters.lane_changing_lateral_jerk; + const auto finish_judge_buffer = lane_change_parameters.lane_change_finish_judge_buffer; + + const auto calc_sum = [&](double sum, double shift_interval) { + const auto t = PathShifter::calcShiftTimeFromJerk(shift_interval, lat_jerk, max_lat_acc); + return sum + (min_vel * t + finish_judge_buffer); + }; + + const auto total_length = + std::accumulate(shift_intervals.begin(), shift_intervals.end(), 0.0, calc_sum); + + const auto backward_buffer = lane_change_parameters.backward_length_buffer_for_end_of_lane; + return total_length + backward_buffer * (static_cast(shift_intervals.size()) - 1.0); +} + +double calcMinimumLaneChangeLength( + const std::shared_ptr & route_handler, const lanelet::ConstLanelet & lane, + const LaneChangeParameters & lane_change_parameters, Direction direction) +{ + if (!route_handler) { + return std::numeric_limits::max(); } - accumulated_length += backward_buffer * (shift_intervals.size() - 1.0); - return accumulated_length; + const auto shift_intervals = route_handler->getLateralIntervalsToPreferredLane(lane, direction); + return utils::lane_change::calcMinimumLaneChangeLength(lane_change_parameters, shift_intervals); } double calcMaximumLaneChangeLength( @@ -110,31 +129,34 @@ double calcMaximumLaneChangeLength( return 0.0; } - const double & finish_judge_buffer = lane_change_parameters.lane_change_finish_judge_buffer; - const double & lateral_jerk = lane_change_parameters.lane_changing_lateral_jerk; - const double & t_prepare = lane_change_parameters.lane_change_prepare_duration; + const auto finish_judge_buffer = lane_change_parameters.lane_change_finish_judge_buffer; + const auto lat_jerk = lane_change_parameters.lane_changing_lateral_jerk; + const auto t_prepare = lane_change_parameters.lane_change_prepare_duration; + + auto vel = current_velocity; - double vel = current_velocity; - double accumulated_length = 0.0; - for (const auto & shift_interval : shift_intervals) { + const auto calc_sum = [&](double sum, double shift_interval) { // prepare section - const double prepare_length = vel * t_prepare + 0.5 * max_acc * t_prepare * t_prepare; + const auto prepare_length = vel * t_prepare + 0.5 * max_acc * t_prepare * t_prepare; vel = vel + max_acc * t_prepare; // lane changing section - const auto lat_acc = lane_change_parameters.lane_change_lat_acc_map.find(vel); - const double t_lane_changing = - PathShifter::calcShiftTimeFromJerk(shift_interval, lateral_jerk, lat_acc.second); - const double lane_changing_length = + const auto [min_lat_acc, max_lat_acc] = + lane_change_parameters.lane_change_lat_acc_map.find(vel); + const auto t_lane_changing = + PathShifter::calcShiftTimeFromJerk(shift_interval, lat_jerk, max_lat_acc); + const auto lane_changing_length = vel * t_lane_changing + 0.5 * max_acc * t_lane_changing * t_lane_changing; - accumulated_length += prepare_length + lane_changing_length + finish_judge_buffer; vel = vel + max_acc * t_lane_changing; - } - accumulated_length += - lane_change_parameters.backward_length_buffer_for_end_of_lane * (shift_intervals.size() - 1.0); + return sum + (prepare_length + lane_changing_length + finish_judge_buffer); + }; + + const auto total_length = + std::accumulate(shift_intervals.begin(), shift_intervals.end(), 0.0, calc_sum); - return accumulated_length; + const auto backward_buffer = lane_change_parameters.backward_length_buffer_for_end_of_lane; + return total_length + backward_buffer * (static_cast(shift_intervals.size()) - 1.0); } double calcMinimumAcceleration( @@ -318,7 +340,6 @@ std::optional constructCandidatePath( const auto terminal_lane_changing_velocity = lane_change_info.terminal_lane_changing_velocity; const auto longitudinal_acceleration = lane_change_info.longitudinal_acceleration; const auto lane_change_velocity = lane_change_info.velocity; - const auto lane_change_length = lane_change_info.length; PathShifter path_shifter; path_shifter.setPath(target_lane_reference_path); @@ -334,40 +355,24 @@ std::optional constructCandidatePath( path_shifter.setLateralAccelerationLimit(std::abs(lane_change_info.lateral_acceleration)); if (!path_shifter.generate(&shifted_path, offset_back)) { - RCLCPP_DEBUG( - rclcpp::get_logger("behavior_path_planner").get_child("util").get_child("lane_change"), - "failed to generate shifted path."); + RCLCPP_DEBUG(get_logger(), "Failed to generate shifted path."); } // TODO(Zulfaqar Azmi): have to think of a more feasible solution for points being remove by path // shifter. if (shifted_path.path.points.size() < shift_line.end_idx + 1) { - RCLCPP_DEBUG( - rclcpp::get_logger("behavior_path_planner").get_child("utils").get_child(__func__), - "path points are removed by PathShifter."); + RCLCPP_DEBUG(get_logger(), "Path points are removed by PathShifter."); return std::nullopt; } - const auto & prepare_length = lane_change_length.prepare; - const auto & lane_changing_length = lane_change_length.lane_changing; - LaneChangePath candidate_path; candidate_path.info = lane_change_info; - RCLCPP_DEBUG( - rclcpp::get_logger("behavior_path_planner") - .get_child("lane_change") - .get_child("util") - .get_child("constructCandidatePath"), - "prepare_length: %f, lane_change: %f", prepare_length, lane_changing_length); - const auto lane_change_end_idx = motion_utils::findNearestIndex(shifted_path.path.points, candidate_path.info.lane_changing_end); if (!lane_change_end_idx) { - RCLCPP_ERROR_STREAM( - rclcpp::get_logger("behavior_path_planner").get_child("util").get_child("lane_change"), - "lane change end idx not found on target path."); + RCLCPP_DEBUG(get_logger(), "Lane change end idx not found on target path."); return std::nullopt; } @@ -403,6 +408,9 @@ std::optional constructCandidatePath( tf2::getYaw(prepare_segment_second_last_point.orientation) - tf2::getYaw(lane_change_start_from_shifted.orientation))); if (yaw_diff2 > tier4_autoware_utils::deg2rad(5.0)) { + RCLCPP_DEBUG( + get_logger(), "Excessive yaw difference %.3f which exceeds the 5 degrees threshold.", + tier4_autoware_utils::rad2deg(yaw_diff2)); return std::nullopt; } } @@ -434,13 +442,6 @@ PathWithLaneId getReferencePathFromTargetLane( return std::min(dist_from_lc_start, target_lane_length - next_lane_change_buffer); }); - RCLCPP_DEBUG( - rclcpp::get_logger("behavior_path_planner") - .get_child("lane_change") - .get_child("util") - .get_child("getReferencePathFromTargetLane"), - "start: %f, end: %f", s_start, s_end); - constexpr double epsilon = 1e-4; if (s_end - s_start + epsilon < lane_changing_length) { return PathWithLaneId(); @@ -477,12 +478,6 @@ ShiftLine getLaneChangingShiftLine( shift_line.end_idx = motion_utils::findNearestIndex(reference_path.points, lane_changing_end_pose.position); - RCLCPP_DEBUG( - rclcpp::get_logger("behavior_path_planner") - .get_child("lane_change") - .get_child("util") - .get_child("getLaneChangingShiftLine"), - "shift_line distance: %f", shift_length); return shift_line; } @@ -658,23 +653,24 @@ double getLateralShift(const LaneChangePath & path) } bool hasEnoughLengthToLaneChangeAfterAbort( - const RouteHandler & route_handler, const lanelet::ConstLanelets & current_lanes, + const std::shared_ptr & route_handler, const lanelet::ConstLanelets & current_lanes, const Pose & current_pose, const double abort_return_dist, const LaneChangeParameters & lane_change_parameters, const Direction direction) { - const auto shift_intervals = - route_handler.getLateralIntervalsToPreferredLane(current_lanes.back(), direction); - const double minimum_lane_change_length = - calcMinimumLaneChangeLength(lane_change_parameters, shift_intervals); + if (current_lanes.empty()) { + return false; + } + + const auto minimum_lane_change_length = calcMinimumLaneChangeLength( + route_handler, current_lanes.back(), lane_change_parameters, direction); const auto abort_plus_lane_change_length = abort_return_dist + minimum_lane_change_length; if (abort_plus_lane_change_length > utils::getDistanceToEndOfLane(current_pose, current_lanes)) { return false; } if ( - route_handler.isInGoalRouteSection(current_lanes.back()) && abort_plus_lane_change_length > - utils::getSignedDistance(current_pose, route_handler.getGoalPose(), current_lanes)) { + utils::getSignedDistance(current_pose, route_handler->getGoalPose(), current_lanes)) { return false; } @@ -1095,12 +1091,7 @@ ExtendedPredictedObject transform( [[maybe_unused]] const BehaviorPathPlannerParameters & common_parameters, const LaneChangeParameters & lane_change_parameters, const bool check_at_prepare_phase) { - ExtendedPredictedObject extended_object; - extended_object.uuid = object.object_id; - extended_object.initial_pose = object.kinematics.initial_pose_with_covariance; - extended_object.initial_twist = object.kinematics.initial_twist_with_covariance; - extended_object.initial_acceleration = object.kinematics.initial_acceleration_with_covariance; - extended_object.shape = object.shape; + ExtendedPredictedObject extended_object(object); const auto & time_resolution = lane_change_parameters.prediction_time_resolution; const auto & prepare_duration = lane_change_parameters.lane_change_prepare_duration; @@ -1207,6 +1198,28 @@ double calcPhaseLength( const auto length_with_max_velocity = maximum_velocity * duration; return std::min(length_with_acceleration, length_with_max_velocity); } + +LanesPolygon createLanesPolygon( + const lanelet::ConstLanelets & current_lanes, const lanelet::ConstLanelets & target_lanes, + const std::vector & target_backward_lanes) +{ + LanesPolygon lanes_polygon; + + lanes_polygon.current = + utils::lane_change::createPolygon(current_lanes, 0.0, std::numeric_limits::max()); + lanes_polygon.target = + utils::lane_change::createPolygon(target_lanes, 0.0, std::numeric_limits::max()); + + for (const auto & target_backward_lane : target_backward_lanes) { + auto lane_polygon = utils::lane_change::createPolygon( + target_backward_lane, 0.0, std::numeric_limits::max()); + + if (lane_polygon) { + lanes_polygon.target_backward.push_back(*lane_polygon); + } + } + return lanes_polygon; +} } // namespace behavior_path_planner::utils::lane_change namespace behavior_path_planner::utils::lane_change::debug diff --git a/planning/behavior_path_planner/config/behavior_path_planner.param.yaml b/planning/behavior_path_planner/config/behavior_path_planner.param.yaml index f3f6870085e02..2c181489ba4c2 100644 --- a/planning/behavior_path_planner/config/behavior_path_planner.param.yaml +++ b/planning/behavior_path_planner/config/behavior_path_planner.param.yaml @@ -1,6 +1,5 @@ /**: ros__parameters: - verbose: false max_iteration_num: 100 traffic_light_signal_timeout: 1.0 planning_hz: 10.0 diff --git a/planning/behavior_path_planner/docs/behavior_path_planner_manager_design.md b/planning/behavior_path_planner/docs/behavior_path_planner_manager_design.md index 5af70a4f98e29..7188c03bd2604 100644 --- a/planning/behavior_path_planner/docs/behavior_path_planner_manager_design.md +++ b/planning/behavior_path_planner/docs/behavior_path_planner_manager_design.md @@ -532,67 +532,33 @@ When the manager removes succeeded modules, the last added module's output is us ## Reference path generation -The root reference path is generated from the centerline of the **lanelet sequence** that obtained from the **root lanelet**, and it is not only used as an input to the first added module of approved modules stack, but also used as the output of `behavior_path_planner` if none of the modules are running. +The reference path is generated from the centerline of the **lanelet sequence** obtained from the **current route lanelet**, and it is not only used as an input to the first added module of approved modules stack, but also used as the output of `behavior_path_planner` if none of the modules are running.
![root_generation](../image/manager/root_generation.svg){width=500}
root reference path generation
-The root lanelet is the closest lanelet within the route, and the update timing is based on Ego's operation mode state. +The **current route lanelet** keeps track of the route lanelet currently followed by the planner. +It is initialized as the closest lanelet within the route. +It is then updated as ego travels along the route such that (1) it follows the previous **current route lanelet** and (2) it is the closest lanelet within the route. -- the state is `OperationModeState::AUTONOMOUS`: Update only when the ego moves to right or left lane by lane change module. -- the state is **NOT** `OperationModeState::AUTONOMOUS`: Update at the beginning of every planning cycle. +The **current route lanelet** can be reset to the closest lanelet within the route, ignoring whether it follows the previous **current route lanelet** . -![root_lanelet](../image/manager/root_lanelet.svg) +![current_route_lanelet](../image/manager/current_route_lanelet.svg) The manager needs to know the ego behavior and then generate a root reference path from the lanes that Ego should follow. -For example, during autonomous driving, even if Ego moves into the next lane in order to avoid a parked vehicle, the target lanes that Ego should follow will **NOT** change because Ego will return to the original lane after the avoidance maneuver. Therefore, the manager does **NOT** update **root lanelet** even if the avoidance maneuver is finished. +For example, during autonomous driving, even if Ego moves into the next lane in order to avoid a parked vehicle, the target lanes that Ego should follow will **NOT** change because Ego will return to the original lane after the avoidance maneuver. Therefore, the manager does **NOT** reset the **current route lanelet**, even if the avoidance maneuver is finished. ![avoidance](../image/manager/avoidance.svg) -On the other hand, if the lane change is successful, the manager updates **root lanelet** because the lane that Ego should follow changes. +On the other hand, if the lane change is successful, the manager resets the **current route lanelet** because the lane that Ego should follow changes. ![lane_change](../image/manager/lane_change.svg) -In addition, while manual driving, the manager always updates **root lanelet** because the pilot may move to an adjacent lane regardless of the decision of the autonomous driving system. - -```c++ - /** - * @brief get reference path from root_lanelet_ centerline. - * @param planner data. - * @return reference path. - */ - BehaviorModuleOutput getReferencePath(const std::shared_ptr & data) const - { - const auto & route_handler = data->route_handler; - const auto & pose = data->self_odometry->pose.pose; - const auto p = data->parameters; - - constexpr double extra_margin = 10.0; - const auto backward_length = - std::max(p.backward_path_length, p.backward_path_length + extra_margin); - - const auto lanelet_sequence = route_handler->getLaneletSequence( - root_lanelet_.value(), pose, backward_length, std::numeric_limits::max()); - - lanelet::ConstLanelet closest_lane{}; - if (lanelet::utils::query::getClosestLaneletWithConstrains( - lanelet_sequence, pose, &closest_lane, p.ego_nearest_dist_threshold, - p.ego_nearest_yaw_threshold)) { - return utils::getReferencePath(closest_lane, data); - } - - if (lanelet::utils::query::getClosestLanelet(lanelet_sequence, pose, &closest_lane)) { - return utils::getReferencePath(closest_lane, data); - } - - return {}; // something wrong. - } -``` - -Code is [here](https://github.com/autowarefoundation/autoware.universe/blob/b1734916e3efd9786507a271e0fe829dd37476c8/planning/behavior_path_planner/include/behavior_path_planner/planner_manager.hpp#L202-L227) +In addition, while manually driving (i.e., either the `OperationModeState` is different from `AUTONOMOUS` or the Autoware control is not engaged), the manager resets the **current route lanelet** at each iteration because the ego vehicle may move to an adjacent lane regardless of the decision of the autonomous driving system. +The only exception is when a module is already approved, allowing testing the module's behavior while manually driving. ## Drivable area generation diff --git a/planning/behavior_path_planner/image/manager/avoidance.svg b/planning/behavior_path_planner/image/manager/avoidance.svg index b61231aa69b17..ea69166abee5f 100644 --- a/planning/behavior_path_planner/image/manager/avoidance.svg +++ b/planning/behavior_path_planner/image/manager/avoidance.svg @@ -1,80 +1,373 @@ + - - - - - - - - - -
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-
- - lanelet sequence - - - - - - - - - - Text is not SVG - cannot display - - - diff --git a/planning/behavior_path_planner/include/behavior_path_planner/planner_manager.hpp b/planning/behavior_path_planner/include/behavior_path_planner/planner_manager.hpp index 5e773eba96aee..877a8c62cbb63 100644 --- a/planning/behavior_path_planner/include/behavior_path_planner/planner_manager.hpp +++ b/planning/behavior_path_planner/include/behavior_path_planner/planner_manager.hpp @@ -96,7 +96,7 @@ struct SceneModuleStatus class PlannerManager { public: - PlannerManager(rclcpp::Node & node, const size_t max_iteration_num, const bool verbose); + PlannerManager(rclcpp::Node & node, const size_t max_iteration_num); /** * @brief run all candidate and approved modules. @@ -137,7 +137,7 @@ class PlannerManager std::for_each(manager_ptrs_.begin(), manager_ptrs_.end(), [](const auto & m) { m->reset(); }); approved_module_ptrs_.clear(); candidate_module_ptrs_.clear(); - root_lanelet_ = std::nullopt; + current_route_lanelet_ = std::nullopt; resetProcessingTime(); } @@ -239,13 +239,6 @@ class PlannerManager */ bool hasCandidateModules() const { return !candidate_module_ptrs_.empty(); } - /** - * @brief reset root lanelet. if there are approved modules, don't reset root lanelet. - * @param planner data. - * @details this function is called only when it is in disengage and drive by manual. - */ - void resetRootLanelet(const std::shared_ptr & data); - /** * @brief show planner manager internal condition. */ @@ -261,6 +254,18 @@ class PlannerManager */ std::shared_ptr getDebugMsg(); + /** + * @brief reset the current route lanelet to be the closest lanelet within the route + * @param planner data. + */ + void resetCurrentRouteLanelet(const std::shared_ptr & data) + { + lanelet::ConstLanelet ret{}; + data->route_handler->getClosestLaneletWithinRoute(data->self_odometry->pose.pose, &ret); + RCLCPP_DEBUG(logger_, "update current route lanelet. id:%ld", ret.id()); + current_route_lanelet_ = ret; + } + private: /** * @brief run the module and publish RTC status. @@ -285,8 +290,6 @@ class PlannerManager module_ptr->updateCurrentState(); - module_ptr->publishRTCStatus(); - module_ptr->publishSteeringFactor(); module_ptr->publishObjectsOfInterestMarker(); @@ -300,11 +303,16 @@ class PlannerManager BehaviorModuleOutput & output, const std::shared_ptr & data) const; /** - * @brief get reference path from root_lanelet_ centerline. + * @brief get reference path from current_route_lanelet_ centerline. * @param planner data. * @return reference path. */ - BehaviorModuleOutput getReferencePath(const std::shared_ptr & data) const; + BehaviorModuleOutput getReferencePath(const std::shared_ptr & data); + + /** + * @brief publish the root reference path and current route lanelet + */ + void publishDebugRootReferencePath(const BehaviorModuleOutput & reference_path); /** * @brief stop and unregister the module from manager. @@ -313,7 +321,6 @@ class PlannerManager void deleteExpiredModules(SceneModulePtr & module_ptr) const { module_ptr->onExit(); - module_ptr->publishRTCStatus(); module_ptr->publishObjectsOfInterestMarker(); module_ptr.reset(); } @@ -361,19 +368,6 @@ class PlannerManager candidate_module_ptrs_.clear(); } - /** - * @brief get current root lanelet. the lanelet is used for reference path generation. - * @param planner data. - * @return root lanelet. - */ - lanelet::ConstLanelet updateRootLanelet(const std::shared_ptr & data) const - { - lanelet::ConstLanelet ret{}; - data->route_handler->getClosestLaneletWithinRoute(data->self_odometry->pose.pose, &ret); - RCLCPP_DEBUG(logger_, "update start lanelet. id:%ld", ret.id()); - return ret; - } - /** * @brief get manager pointer from module name. * @param module pointer. @@ -447,7 +441,7 @@ class PlannerManager static std::string getNames(const std::vector & modules); - std::optional root_lanelet_{std::nullopt}; + std::optional current_route_lanelet_{std::nullopt}; std::vector manager_ptrs_; @@ -474,8 +468,6 @@ class PlannerManager mutable std::shared_ptr debug_msg_ptr_; size_t max_iteration_num_{100}; - - bool verbose_{false}; }; } // namespace behavior_path_planner diff --git a/planning/behavior_path_planner/package.xml b/planning/behavior_path_planner/package.xml index 7f50c61a8343a..f6bd82430c389 100644 --- a/planning/behavior_path_planner/package.xml +++ b/planning/behavior_path_planner/package.xml @@ -20,6 +20,7 @@ Kosuke Takeuchi Kyoichi Sugahara Takayuki Murooka + Go Sakayori Apache License 2.0 diff --git a/planning/behavior_path_planner/src/behavior_path_planner_node.cpp b/planning/behavior_path_planner/src/behavior_path_planner_node.cpp index d250fd97c3aec..b56d1a207f76d 100644 --- a/planning/behavior_path_planner/src/behavior_path_planner_node.cpp +++ b/planning/behavior_path_planner/src/behavior_path_planner_node.cpp @@ -133,7 +133,7 @@ BehaviorPathPlannerNode::BehaviorPathPlannerNode(const rclcpp::NodeOptions & nod const std::lock_guard lock(mutex_manager_); // for planner_manager_ const auto & p = planner_data_->parameters; - planner_manager_ = std::make_shared(*this, p.max_iteration_num, p.verbose); + planner_manager_ = std::make_shared(*this, p.max_iteration_num); for (const auto & name : declare_parameter>("launch_modules")) { // workaround: Since ROS 2 can't get empty list, launcher set [''] on the parameter. @@ -208,7 +208,6 @@ BehaviorPathPlannerParameters BehaviorPathPlannerNode::getCommonParam() { BehaviorPathPlannerParameters p{}; - p.verbose = declare_parameter("verbose"); p.max_iteration_num = declare_parameter("max_iteration_num"); p.traffic_light_signal_timeout = declare_parameter("traffic_light_signal_timeout"); @@ -372,10 +371,8 @@ void BehaviorPathPlannerNode::run() const bool is_first_time = !(planner_data_->route_handler->isHandlerReady()); if (route_ptr) { planner_data_->route_handler->setRoute(*route_ptr); - planner_manager_->resetRootLanelet(planner_data_); - // uuid is not changed when rerouting with modified goal, - // in this case do not need to rest modules. + // in this case do not need to reset modules. const bool has_same_route_id = planner_data_->prev_route_id && route_ptr->uuid == planner_data_->prev_route_id; // Reset behavior tree when new route is received, @@ -385,14 +382,13 @@ void BehaviorPathPlannerNode::run() planner_manager_->reset(); planner_data_->prev_modified_goal.reset(); } + planner_manager_->resetCurrentRouteLanelet(planner_data_); } - const auto controlled_by_autoware_autonomously = planner_data_->operation_mode->mode == OperationModeState::AUTONOMOUS && planner_data_->operation_mode->is_autoware_control_enabled; - if (!controlled_by_autoware_autonomously) { - planner_manager_->resetRootLanelet(planner_data_); - } + if (!controlled_by_autoware_autonomously && !planner_manager_->hasApprovedModules()) + planner_manager_->resetCurrentRouteLanelet(planner_data_); // run behavior planner const auto output = planner_manager_->run(planner_data_); diff --git a/planning/behavior_path_planner/src/planner_manager.cpp b/planning/behavior_path_planner/src/planner_manager.cpp index 5ec34ebbab6e3..6cb2fccb31117 100644 --- a/planning/behavior_path_planner/src/planner_manager.cpp +++ b/planning/behavior_path_planner/src/planner_manager.cpp @@ -30,13 +30,11 @@ namespace behavior_path_planner { -PlannerManager::PlannerManager( - rclcpp::Node & node, const size_t max_iteration_num, const bool verbose) +PlannerManager::PlannerManager(rclcpp::Node & node, const size_t max_iteration_num) : plugin_loader_("behavior_path_planner", "behavior_path_planner::SceneModuleManagerInterface"), logger_(node.get_logger().get_child("planner_manager")), clock_(*node.get_clock()), - max_iteration_num_{max_iteration_num}, - verbose_{verbose} + max_iteration_num_{max_iteration_num} { processing_time_.emplace("total_time", 0.0); debug_publisher_ptr_ = std::make_unique(&node, "~/debug"); @@ -89,9 +87,7 @@ BehaviorModuleOutput PlannerManager::run(const std::shared_ptr & da stop_watch_.tic("total_time"); debug_info_.clear(); - if (!root_lanelet_) { - root_lanelet_ = updateRootLanelet(data); - } + if (!current_route_lanelet_) resetCurrentRouteLanelet(data); std::for_each( manager_ptrs_.begin(), manager_ptrs_.end(), [&data](const auto & m) { m->setData(data); }); @@ -195,8 +191,10 @@ BehaviorModuleOutput PlannerManager::run(const std::shared_ptr & da return BehaviorModuleOutput{}; // something wrong. }(); - std::for_each( - manager_ptrs_.begin(), manager_ptrs_.end(), [](const auto & m) { m->updateObserver(); }); + std::for_each(manager_ptrs_.begin(), manager_ptrs_.end(), [](const auto & m) { + m->updateObserver(); + m->publishRTCStatus(); + }); generateCombinedDrivableArea(result_output, data); @@ -416,8 +414,7 @@ BehaviorModuleOutput PlannerManager::runKeepLastModules( return output; } -BehaviorModuleOutput PlannerManager::getReferencePath( - const std::shared_ptr & data) const +BehaviorModuleOutput PlannerManager::getReferencePath(const std::shared_ptr & data) { const auto & route_handler = data->route_handler; const auto & pose = data->self_odometry->pose.pose; @@ -428,20 +425,41 @@ BehaviorModuleOutput PlannerManager::getReferencePath( std::max(p.backward_path_length, p.backward_path_length + extra_margin); const auto lanelet_sequence = route_handler->getLaneletSequence( - root_lanelet_.value(), pose, backward_length, std::numeric_limits::max()); + current_route_lanelet_.value(), pose, backward_length, p.forward_path_length); lanelet::ConstLanelet closest_lane{}; - if (lanelet::utils::query::getClosestLaneletWithConstrains( - lanelet_sequence, pose, &closest_lane, p.ego_nearest_dist_threshold, - p.ego_nearest_yaw_threshold)) { - return utils::getReferencePath(closest_lane, data); - } - - if (lanelet::utils::query::getClosestLanelet(lanelet_sequence, pose, &closest_lane)) { - return utils::getReferencePath(closest_lane, data); - } + const auto could_calculate_closest_lanelet = + lanelet::utils::query::getClosestLaneletWithConstrains( + lanelet_sequence, pose, &closest_lane, p.ego_nearest_dist_threshold, + p.ego_nearest_yaw_threshold) || + lanelet::utils::query::getClosestLanelet(lanelet_sequence, pose, &closest_lane); + + if (could_calculate_closest_lanelet) + current_route_lanelet_ = closest_lane; + else + resetCurrentRouteLanelet(data); + + const auto reference_path = utils::getReferencePath(*current_route_lanelet_, data); + publishDebugRootReferencePath(reference_path); + return reference_path; +} - return {}; // something wrong. +void PlannerManager::publishDebugRootReferencePath(const BehaviorModuleOutput & reference_path) +{ + using visualization_msgs::msg::Marker; + MarkerArray array; + Marker m = tier4_autoware_utils::createDefaultMarker( + "map", clock_.now(), "root_reference_path", 0UL, Marker::LINE_STRIP, + tier4_autoware_utils::createMarkerScale(1.0, 1.0, 1.0), + tier4_autoware_utils::createMarkerColor(1.0, 0.0, 0.0, 1.0)); + for (const auto & p : reference_path.path.points) m.points.push_back(p.point.pose.position); + array.markers.push_back(m); + m.points.clear(); + m.id = 1UL; + for (const auto & p : current_route_lanelet_->polygon3d().basicPolygon()) + m.points.emplace_back().set__x(p.x()).set__y(p.y()).set__z(p.z()); + array.markers.push_back(m); + debug_publisher_ptr_->publish("root_reference_path", array); } SceneModulePtr PlannerManager::selectHighestPriorityModule( @@ -770,7 +788,8 @@ BehaviorModuleOutput PlannerManager::runApprovedModules(const std::shared_ptrisRootLaneletToBeUpdated(); - })) { - root_lanelet_ = updateRootLanelet(data); - } + return m->isCurrentRouteLaneletToBeReset(); + })) + resetCurrentRouteLanelet(data); std::for_each(itr, approved_module_ptrs_.end(), [&](auto & m) { debug_info_.emplace_back(m, Action::DELETE, "From Approved"); @@ -875,62 +893,6 @@ void PlannerManager::updateCandidateModules( sortByPriority(candidate_module_ptrs_); } -void PlannerManager::resetRootLanelet(const std::shared_ptr & data) -{ - if (!root_lanelet_) { - root_lanelet_ = updateRootLanelet(data); - return; - } - - // when lane change module is running, don't update root lanelet. - const bool is_lane_change_running = std::invoke([&]() { - const auto lane_change_itr = std::find_if( - approved_module_ptrs_.begin(), approved_module_ptrs_.end(), - [](const auto & m) { return m->isRootLaneletToBeUpdated(); }); - return lane_change_itr != approved_module_ptrs_.end(); - }); - if (is_lane_change_running) { - return; - } - - const auto root_lanelet = updateRootLanelet(data); - - // if root_lanelet is not route lanelets, reset root lanelet. - // this can be caused by rerouting. - const auto & route_handler = data->route_handler; - if (!route_handler->isRouteLanelet(root_lanelet_.value())) { - root_lanelet_ = root_lanelet; - return; - } - - // check ego is in same lane - if (root_lanelet_.value().id() == root_lanelet.id()) { - return; - } - - // check ego is in next lane - const auto next_lanelets = route_handler->getRoutingGraphPtr()->following(root_lanelet_.value()); - for (const auto & next : next_lanelets) { - if (next.id() == root_lanelet.id()) { - return; - } - } - - if (!approved_module_ptrs_.empty()) { - return; - } - - for (const auto & m : candidate_module_ptrs_) { - if (m->isLockedNewModuleLaunch()) { - return; - } - } - - root_lanelet_ = root_lanelet; - - RCLCPP_INFO_EXPRESSION(logger_, verbose_, "change ego's following lane. reset."); -} - void PlannerManager::print() const { const auto get_status = [](const auto & m) { @@ -984,11 +946,7 @@ void PlannerManager::print() const state_publisher_ptr_->publish("internal_state", string_stream.str()); - if (!verbose_) { - return; - } - - RCLCPP_INFO_STREAM(logger_, string_stream.str()); + RCLCPP_DEBUG_STREAM(logger_, string_stream.str()); } void PlannerManager::publishProcessingTime() const diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_interface.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_interface.hpp index 73f7448133ee7..b4e1ffce8104a 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_interface.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_interface.hpp @@ -41,6 +41,7 @@ #include #include #include +#include #include #include @@ -67,6 +68,7 @@ using tier4_planning_msgs::msg::AvoidanceDebugMsgArray; using tier4_planning_msgs::msg::StopFactor; using tier4_planning_msgs::msg::StopReason; using tier4_planning_msgs::msg::StopReasonArray; +using tier4_rtc_msgs::msg::State; using unique_identifier_msgs::msg::UUID; using visualization_msgs::msg::MarkerArray; using PlanResult = PathWithLaneId::SharedPtr; @@ -141,7 +143,13 @@ class SceneModuleInterface virtual BehaviorModuleOutput run() { updateData(); - return isWaitingApproval() ? planWaitingApproval() : plan(); + const auto output = isWaitingApproval() ? planWaitingApproval() : plan(); + try { + motion_utils::validateNonEmpty(output.path.points); + } catch (const std::exception & ex) { + throw std::invalid_argument("[" + name_ + "]" + ex.what()); + } + return output; } /** @@ -180,7 +188,6 @@ class SceneModuleInterface clearWaitingApproval(); removeRTCStatus(); - publishRTCStatus(); unlockNewModuleLaunch(); unlockOutputPath(); steering_factor_interface_ptr_->clearSteeringFactors(); @@ -190,18 +197,6 @@ class SceneModuleInterface processOnExit(); } - /** - * @brief Publish status if the module is requested to run - */ - void publishRTCStatus() - { - for (const auto & [module_name, ptr] : rtc_interface_ptr_map_) { - if (ptr) { - ptr->publishCooperateStatus(clock_->now()); - } - } - } - void publishObjectsOfInterestMarker() { for (const auto & [module_name, ptr] : objects_of_interest_marker_interface_ptr_map_) { @@ -259,7 +254,7 @@ class SceneModuleInterface return is_waiting_approval_ || current_state_ == ModuleStatus::WAITING_APPROVAL; } - virtual bool isRootLaneletToBeUpdated() const { return false; } + virtual bool isCurrentRouteLaneletToBeReset() const { return false; } bool isLockedNewModuleLaunch() const { return is_locked_new_module_launch_; } @@ -497,8 +492,9 @@ class SceneModuleInterface { for (const auto & [module_name, ptr] : rtc_interface_ptr_map_) { if (ptr) { + const auto state = isWaitingApproval() ? State::WAITING_FOR_EXECUTION : State::RUNNING; ptr->updateCooperateStatus( - uuid_map_.at(module_name), isExecutionReady(), start_distance, finish_distance, + uuid_map_.at(module_name), isExecutionReady(), state, start_distance, finish_distance, clock_->now()); } } diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_manager_interface.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_manager_interface.hpp index e8a28ee684ce6..0bea7c08c6601 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_manager_interface.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/interface/scene_module_manager_interface.hpp @@ -99,6 +99,15 @@ class SceneModuleManagerInterface observers_.erase(itr, observers_.end()); } + void publishRTCStatus() + { + for (const auto & [module_name, ptr] : rtc_interface_ptr_map_) { + if (ptr) { + ptr->publishCooperateStatus(rclcpp::Clock(RCL_ROS_TIME).now()); + } + } + } + void publishVirtualWall() const { using tier4_autoware_utils::appendMarkerArray; @@ -235,7 +244,6 @@ class SceneModuleManagerInterface std::for_each(observers_.begin(), observers_.end(), [](const auto & observer) { if (!observer.expired()) { observer.lock()->onExit(); - observer.lock()->publishRTCStatus(); } }); @@ -243,7 +251,6 @@ class SceneModuleManagerInterface if (idle_module_ptr_ != nullptr) { idle_module_ptr_->onExit(); - idle_module_ptr_->publishRTCStatus(); idle_module_ptr_.reset(); } diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/parameters.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/parameters.hpp index 1eae4a1c4c345..1241f98daa747 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/parameters.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/parameters.hpp @@ -30,7 +30,6 @@ struct ModuleConfigParameters struct BehaviorPathPlannerParameters { - bool verbose; size_t max_iteration_num{100}; double traffic_light_signal_timeout{1.0}; diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/turn_signal_decider.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/turn_signal_decider.hpp index fe187567cd893..29fe05775739e 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/turn_signal_decider.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/turn_signal_decider.hpp @@ -228,23 +228,23 @@ class TurnSignalDecider using tier4_autoware_utils::transformVector; const auto footprint = vehicle_info.createFootprint(); - - for (const auto & lane : lanes) { - for (size_t i = shift_line.start_idx; i < shift_line.end_idx; ++i) { - const auto transform = pose2transform(path.path.points.at(i).point.pose); - const auto shifted_vehicle_footprint = transformVector(footprint, transform); - - if (intersects(lane.leftBound2d().basicLineString(), shifted_vehicle_footprint)) { - return true; - } - - if (intersects(lane.rightBound2d().basicLineString(), shifted_vehicle_footprint)) { - return true; - } - } - } - - return false; + const auto start_itr = std::next(path.path.points.begin(), shift_line.start_idx); + const auto end_itr = std::next(path.path.points.begin(), shift_line.end_idx); + + return std::any_of(start_itr, end_itr, [&footprint, &lanes](const auto & point) { + const auto transform = pose2transform(point.point.pose); + const auto shifted_vehicle_footprint = transformVector(footprint, transform); + + auto check_for_vehicle_and_bound_intersection = + [&shifted_vehicle_footprint](const auto & lane) { + const auto & left_bound = lane.leftBound2d().basicLineString(); + const auto & right_bound = lane.rightBound2d().basicLineString(); + return intersects(left_bound, shifted_vehicle_footprint) || + intersects(right_bound, shifted_vehicle_footprint); + }; + + return std::any_of(lanes.begin(), lanes.end(), check_for_vehicle_and_bound_intersection); + }); }; inline bool isNearEndOfShift( diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp index e33c2596ab04d..a0b2d0afa0fa8 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp @@ -69,6 +69,12 @@ bool isCentroidWithinLanelet(const PredictedObject & object, const lanelet::Cons */ bool isPolygonOverlapLanelet(const PredictedObject & object, const lanelet::ConstLanelet & lanelet); +bool isPolygonOverlapLanelet( + const PredictedObject & object, const tier4_autoware_utils::Polygon2d & lanelet_polygon); + +bool isPolygonOverlapLanelet( + const PredictedObject & object, const lanelet::BasicPolygon2d & lanelet_polygon); + /** * @brief Filters objects based on various criteria. * @@ -279,6 +285,15 @@ void filterObjects(PredictedObjects & selected, PredictedObjects & removed, Func selected.objects.erase(partitioned, selected.objects.end()); } +template +void filterObjects( + std::vector & selected, std::vector & removed, Func filter) +{ + auto partitioned = std::partition(selected.begin(), selected.end(), filter); + removed.insert(removed.end(), partitioned, selected.end()); + selected.erase(partitioned, selected.end()); +} + /** * @brief Filters objects in the 'objects' container based on the provided filter function. * @@ -296,6 +311,13 @@ void filterObjects(PredictedObjects & objects, Func filter) [[maybe_unused]] PredictedObjects removed_objects{}; filterObjects(objects, removed_objects, filter); } + +template +void filterObjects(std::vector & objects, Func filter) +{ + [[maybe_unused]] std::vector removed_objects{}; + filterObjects(objects, removed_objects, filter); +} } // namespace behavior_path_planner::utils::path_safety_checker #endif // BEHAVIOR_PATH_PLANNER_COMMON__UTILS__PATH_SAFETY_CHECKER__OBJECTS_FILTERING_HPP_ diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp index b3c8034a3545c..d83c748f214b4 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp @@ -31,6 +31,7 @@ namespace behavior_path_planner::utils::path_safety_checker { +using autoware_auto_perception_msgs::msg::PredictedObject; using geometry_msgs::msg::Pose; using geometry_msgs::msg::Twist; using tier4_autoware_utils::Polygon2d; @@ -79,6 +80,17 @@ struct ExtendedPredictedObject autoware_auto_perception_msgs::msg::Shape shape; std::vector classification; std::vector predicted_paths; + + ExtendedPredictedObject() = default; + explicit ExtendedPredictedObject(const PredictedObject & object) + : uuid(object.object_id), + initial_pose(object.kinematics.initial_pose_with_covariance), + initial_twist(object.kinematics.initial_twist_with_covariance), + initial_acceleration(object.kinematics.initial_acceleration_with_covariance), + shape(object.shape), + classification(object.classification) + { + } }; using ExtendedPredictedObjects = std::vector; diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/safety_check.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/safety_check.hpp index 53c4706e49c10..c4cfed01450b7 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/safety_check.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_safety_checker/safety_check.hpp @@ -43,7 +43,8 @@ using tier4_autoware_utils::Polygon2d; using vehicle_info_util::VehicleInfo; bool isTargetObjectOncoming( - const geometry_msgs::msg::Pose & vehicle_pose, const geometry_msgs::msg::Pose & object_pose); + const geometry_msgs::msg::Pose & vehicle_pose, const geometry_msgs::msg::Pose & object_pose, + const double angle_threshold = M_PI_2); bool isTargetObjectFront( const geometry_msgs::msg::Pose & ego_pose, const Polygon2d & obj_polygon, @@ -54,11 +55,11 @@ bool isTargetObjectFront( Polygon2d createExtendedPolygon( const Pose & base_link_pose, const vehicle_info_util::VehicleInfo & vehicle_info, - const double lon_length, const double lat_margin, const double is_stopped_obj, + const double lon_length, const double lat_margin, const bool is_stopped_obj, CollisionCheckDebug & debug); Polygon2d createExtendedPolygon( const Pose & obj_pose, const Shape & shape, const double lon_length, const double lat_margin, - const double is_stopped_obj, CollisionCheckDebug & debug); + const bool is_stopped_obj, CollisionCheckDebug & debug); PredictedPath convertToPredictedPath( const std::vector & path, const double time_resolution); diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_shifter/path_shifter.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_shifter/path_shifter.hpp index 67f581123057e..880e55b64d170 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_shifter/path_shifter.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/path_shifter/path_shifter.hpp @@ -94,9 +94,9 @@ class PathShifter void setLongitudinalAcceleration(const double longitudinal_acc); /** - * @brief Add shift point. You don't have to care about the start/end_idx. + * @brief Add shift line. You don't have to care about the start/end_idx. */ - void addShiftLine(const ShiftLine & point); + void addShiftLine(const ShiftLine & line); /** * @brief Set new shift point. You don't have to care about the start/end_idx. @@ -143,7 +143,7 @@ class PathShifter //////////////////////////////////////// static double calcFeasibleVelocityFromJerk( - const double lateral, const double jerk, const double distance); + const double lateral, const double jerk, const double longitudinal_distance); static double calcLateralDistFromJerk( const double longitudinal, const double jerk, const double velocity); @@ -196,12 +196,12 @@ class PathShifter std::pair, std::vector> calcBaseLengths( const double arclength, const double shift_length, const bool offset_back) const; - std::pair, std::vector> getBaseLengthsWithoutAccelLimit( - const double arclength, const double shift_length, const bool offset_back) const; + static std::pair, std::vector> getBaseLengthsWithoutAccelLimit( + const double arclength, const double shift_length, const bool offset_back); - std::pair, std::vector> getBaseLengthsWithoutAccelLimit( + static std::pair, std::vector> getBaseLengthsWithoutAccelLimit( const double arclength, const double shift_length, const double velocity, - const double longitudinal_acc, const double total_time, const bool offset_back) const; + const double longitudinal_acc, const double total_time, const bool offset_back); /** * @brief Calculate path index for shift_lines and set is_index_aligned_ to true. @@ -235,9 +235,9 @@ class PathShifter */ bool checkShiftLinesAlignment(const ShiftLineArray & shift_lines) const; - void addLateralOffsetOnIndexPoint(ShiftedPath * path, double offset, size_t index) const; + static void addLateralOffsetOnIndexPoint(ShiftedPath * path, double offset, size_t index); - void shiftBaseLength(ShiftedPath * path, double offset) const; + static void shiftBaseLength(ShiftedPath * path, double offset); void setBaseOffset(const double val) { diff --git a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/utils.hpp b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/utils.hpp index 22db593b45586..b61ef0579cab0 100644 --- a/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/utils.hpp +++ b/planning/behavior_path_planner_common/include/behavior_path_planner_common/utils/utils.hpp @@ -262,8 +262,8 @@ std::vector getTargetLaneletPolygons( const lanelet::ConstLanelets & lanelets, const Pose & pose, const double check_length, const std::string & target_type); -PathWithLaneId getCenterLinePathFromRootLanelet( - const lanelet::ConstLanelet & root_lanelet, +PathWithLaneId getCenterLinePathFromLanelet( + const lanelet::ConstLanelet & current_route_lanelet, const std::shared_ptr & planner_data); // route handler @@ -299,6 +299,10 @@ lanelet::ConstLanelets extendPrevLane( lanelet::ConstLanelets extendLanes( const std::shared_ptr route_handler, const lanelet::ConstLanelets & lanes); +std::vector getPrecedingLanelets( + const RouteHandler & route_handler, const lanelet::ConstLanelets & target_lanes, + const Pose & current_pose, const double backward_length); + lanelet::ConstLanelets getBackwardLanelets( const RouteHandler & route_handler, const lanelet::ConstLanelets & target_lanes, const Pose & current_pose, const double backward_length); diff --git a/planning/behavior_path_planner_common/package.xml b/planning/behavior_path_planner_common/package.xml index 2dd4d12c05487..7bc40974b9a62 100644 --- a/planning/behavior_path_planner_common/package.xml +++ b/planning/behavior_path_planner_common/package.xml @@ -25,6 +25,7 @@ Fumiya Watanabe Takamasa Horibe Zulfaqar Azmi + Go Sakayori Apache License 2.0 diff --git a/planning/behavior_path_planner_common/src/turn_signal_decider.cpp b/planning/behavior_path_planner_common/src/turn_signal_decider.cpp index 7bb2bab20bdcd..320cc96577187 100644 --- a/planning/behavior_path_planner_common/src/turn_signal_decider.cpp +++ b/planning/behavior_path_planner_common/src/turn_signal_decider.cpp @@ -136,6 +136,12 @@ std::optional TurnSignalDecider::getIntersectionTurnSignalInfo( const size_t current_seg_idx, const RouteHandler & route_handler, const double nearest_dist_threshold, const double nearest_yaw_threshold) { + const auto requires_turn_signal = [&](const auto & lane_attribute) { + constexpr double stop_velocity_threshold = 0.1; + return ( + lane_attribute == "right" || lane_attribute == "left" || + (lane_attribute == "straight" && current_vel < stop_velocity_threshold)); + }; // base search distance const double base_search_distance = intersection_search_time_ * current_vel + intersection_search_distance_; @@ -164,25 +170,18 @@ std::optional TurnSignalDecider::getIntersectionTurnSignalInfo( if (processed_lanes.find(lane_id) != processed_lanes.end()) continue; auto current_lane = route_handler.getLaneletsFromId(lane_id); lanelet::ConstLanelets combined_lane_elems{}; - while (rclcpp::ok()) { + // Get the lane and its attribute + const std::string lane_attribute = + current_lane.attributeOr("turn_direction", std::string("none")); + if (!requires_turn_signal(lane_attribute)) continue; + + do { processed_lanes.insert(current_lane.id()); combined_lane_elems.push_back(current_lane); - - // Get the lane and its attribute - const std::string lane_attribute = - current_lane.attributeOr("turn_direction", std::string("none")); - - // check next lane has the same attribute lanelet::ConstLanelet next_lane{}; - if (!route_handler.getNextLaneletWithinRoute(current_lane, &next_lane)) { - break; - } - if (next_lane.attributeOr("turn_direction", std::string("none")) != lane_attribute) { - break; - } - current_lane = next_lane; - } + } while (route_handler.getNextLaneletWithinRoute(current_lane, ¤t_lane) && + current_lane.attributeOr("turn_direction", std::string("none")) == lane_attribute); if (!combined_lane_elems.empty()) { // store combined lane and its front lane @@ -254,28 +253,22 @@ std::optional TurnSignalDecider::getIntersectionTurnSignalInfo( desired_start_point_map_.erase(lane_id); } continue; - } else if (search_distance < dist_to_front_point) { + } else if (search_distance <= dist_to_front_point) { continue; } - - constexpr double stop_velocity_threshold = 0.1; - if (dist_to_front_point < search_distance) { - if ( - lane_attribute == "right" || lane_attribute == "left" || - (lane_attribute == "straight" && current_vel < stop_velocity_threshold)) { - // update map if necessary - if (desired_start_point_map_.find(lane_id) == desired_start_point_map_.end()) { - desired_start_point_map_.emplace(lane_id, current_pose); - } - - TurnSignalInfo turn_signal_info{}; - turn_signal_info.desired_start_point = desired_start_point_map_.at(lane_id); - turn_signal_info.required_start_point = lane_front_pose; - turn_signal_info.required_end_point = get_required_end_point(combined_lane.centerline3d()); - turn_signal_info.desired_end_point = lane_back_pose; - turn_signal_info.turn_signal.command = g_signal_map.at(lane_attribute); - signal_queue.push(turn_signal_info); + if (requires_turn_signal(lane_attribute)) { + // update map if necessary + if (desired_start_point_map_.find(lane_id) == desired_start_point_map_.end()) { + desired_start_point_map_.emplace(lane_id, current_pose); } + + TurnSignalInfo turn_signal_info{}; + turn_signal_info.desired_start_point = desired_start_point_map_.at(lane_id); + turn_signal_info.required_start_point = lane_front_pose; + turn_signal_info.required_end_point = get_required_end_point(combined_lane.centerline3d()); + turn_signal_info.desired_end_point = lane_back_pose; + turn_signal_info.turn_signal.command = g_signal_map.at(lane_attribute); + signal_queue.push(turn_signal_info); } } diff --git a/planning/behavior_path_planner_common/src/utils/path_safety_checker/objects_filtering.cpp b/planning/behavior_path_planner_common/src/utils/path_safety_checker/objects_filtering.cpp index ea9872f268678..cdb4b778d3ab3 100644 --- a/planning/behavior_path_planner_common/src/utils/path_safety_checker/objects_filtering.cpp +++ b/planning/behavior_path_planner_common/src/utils/path_safety_checker/objects_filtering.cpp @@ -66,8 +66,21 @@ bool isCentroidWithinLanelet(const PredictedObject & object, const lanelet::Cons bool isPolygonOverlapLanelet(const PredictedObject & object, const lanelet::ConstLanelet & lanelet) { - const auto object_polygon = tier4_autoware_utils::toPolygon2d(object); const auto lanelet_polygon = utils::toPolygon2d(lanelet); + return isPolygonOverlapLanelet(object, lanelet_polygon); +} + +bool isPolygonOverlapLanelet( + const PredictedObject & object, const tier4_autoware_utils::Polygon2d & lanelet_polygon) +{ + const auto object_polygon = tier4_autoware_utils::toPolygon2d(object); + return !boost::geometry::disjoint(lanelet_polygon, object_polygon); +} + +bool isPolygonOverlapLanelet( + const PredictedObject & object, const lanelet::BasicPolygon2d & lanelet_polygon) +{ + const auto object_polygon = tier4_autoware_utils::toPolygon2d(object); return !boost::geometry::disjoint(lanelet_polygon, object_polygon); } @@ -289,13 +302,7 @@ ExtendedPredictedObject transform( const PredictedObject & object, const double safety_check_time_horizon, const double safety_check_time_resolution) { - ExtendedPredictedObject extended_object; - extended_object.uuid = object.object_id; - extended_object.initial_pose = object.kinematics.initial_pose_with_covariance; - extended_object.initial_twist = object.kinematics.initial_twist_with_covariance; - extended_object.initial_acceleration = object.kinematics.initial_acceleration_with_covariance; - extended_object.shape = object.shape; - extended_object.classification = object.classification; + ExtendedPredictedObject extended_object(object); const auto obj_velocity = extended_object.initial_twist.twist.linear.x; @@ -330,8 +337,9 @@ TargetObjectsOnLane createTargetObjectsOnLane( lanelet::ConstLanelets all_left_lanelets; lanelet::ConstLanelets all_right_lanelets; + // TODO(sugahara): consider right side parking and define right shoulder lanelets + lanelet::ConstLanelets all_left_shoulder_lanelets; - // Define lambda functions to update left and right lanelets const auto update_left_lanelets = [&](const lanelet::ConstLanelet & target_lane) { const auto left_lanelets = route_handler->getAllLeftSharedLinestringLanelets( target_lane, include_opposite, invert_opposite); @@ -345,13 +353,21 @@ TargetObjectsOnLane createTargetObjectsOnLane( all_right_lanelets.end(), right_lanelets.begin(), right_lanelets.end()); }; - // Update left and right lanelets for each current lane + const auto update_left_shoulder_lanelet = [&](const lanelet::ConstLanelet & target_lane) { + const auto neighbor_shoulder_lane = route_handler->getLeftShoulderLanelet(target_lane); + if (neighbor_shoulder_lane) { + all_left_shoulder_lanelets.insert(all_left_shoulder_lanelets.end(), *neighbor_shoulder_lane); + } + }; + for (const auto & current_lane : current_lanes) { update_left_lanelets(current_lane); update_right_lanelets(current_lane); + update_left_shoulder_lanelet(current_lane); } TargetObjectsOnLane target_objects_on_lane{}; + const auto append_objects_on_lane = [&](auto & lane_objects, const auto & check_lanes) { std::for_each( filtered_objects.objects.begin(), filtered_objects.objects.end(), [&](const auto & object) { @@ -362,7 +378,7 @@ TargetObjectsOnLane createTargetObjectsOnLane( }); }; - // TODO(Sugahara): Consider shoulder and other lane objects + // TODO(Sugahara): Consider other lane objects if (object_lane_configuration.check_current_lane && !current_lanes.empty()) { append_objects_on_lane(target_objects_on_lane.on_current_lane, current_lanes); } @@ -372,6 +388,9 @@ TargetObjectsOnLane createTargetObjectsOnLane( if (object_lane_configuration.check_right_lane && !all_right_lanelets.empty()) { append_objects_on_lane(target_objects_on_lane.on_right_lane, all_right_lanelets); } + if (object_lane_configuration.check_shoulder_lane && !all_left_shoulder_lanelets.empty()) { + append_objects_on_lane(target_objects_on_lane.on_shoulder_lane, all_left_shoulder_lanelets); + } return target_objects_on_lane; } diff --git a/planning/behavior_path_planner_common/src/utils/path_safety_checker/safety_check.cpp b/planning/behavior_path_planner_common/src/utils/path_safety_checker/safety_check.cpp index 6390c45376b37..e1884e57f7221 100644 --- a/planning/behavior_path_planner_common/src/utils/path_safety_checker/safety_check.cpp +++ b/planning/behavior_path_planner_common/src/utils/path_safety_checker/safety_check.cpp @@ -43,9 +43,10 @@ void appendPointToPolygon(Polygon2d & polygon, const geometry_msgs::msg::Point & } bool isTargetObjectOncoming( - const geometry_msgs::msg::Pose & vehicle_pose, const geometry_msgs::msg::Pose & object_pose) + const geometry_msgs::msg::Pose & vehicle_pose, const geometry_msgs::msg::Pose & object_pose, + const double angle_threshold) { - return std::abs(calcYawDeviation(vehicle_pose, object_pose)) > M_PI_2; + return std::abs(calcYawDeviation(vehicle_pose, object_pose)) > angle_threshold; } bool isTargetObjectFront( @@ -90,7 +91,7 @@ bool isTargetObjectFront( Polygon2d createExtendedPolygon( const Pose & base_link_pose, const vehicle_info_util::VehicleInfo & vehicle_info, - const double lon_length, const double lat_margin, const double is_stopped_obj, + const double lon_length, const double lat_margin, const bool is_stopped_obj, CollisionCheckDebug & debug) { const double & base_to_front = vehicle_info.max_longitudinal_offset_m; @@ -131,7 +132,7 @@ Polygon2d createExtendedPolygon( Polygon2d createExtendedPolygon( const Pose & obj_pose, const Shape & shape, const double lon_length, const double lat_margin, - const double is_stopped_obj, CollisionCheckDebug & debug) + const bool is_stopped_obj, CollisionCheckDebug & debug) { const auto obj_polygon = tier4_autoware_utils::toPolygon2d(obj_pose, shape); if (obj_polygon.outer().empty()) { @@ -189,7 +190,7 @@ Polygon2d createExtendedPolygon( Polygon2d createExtendedPolygonAlongPath( const PathWithLaneId & planned_path, const Pose & base_link_pose, const vehicle_info_util::VehicleInfo & vehicle_info, const double lon_length, - const double lat_margin, const double is_stopped_obj, CollisionCheckDebug & debug) + const double lat_margin, const bool is_stopped_obj, CollisionCheckDebug & debug) { const double & base_to_front = vehicle_info.max_longitudinal_offset_m; const double & width = vehicle_info.vehicle_width_m; diff --git a/planning/behavior_path_planner_common/src/utils/path_shifter/path_shifter.cpp b/planning/behavior_path_planner_common/src/utils/path_shifter/path_shifter.cpp index 7a74ca598de8f..38eafb2f38d7d 100644 --- a/planning/behavior_path_planner_common/src/utils/path_shifter/path_shifter.cpp +++ b/planning/behavior_path_planner_common/src/utils/path_shifter/path_shifter.cpp @@ -116,7 +116,13 @@ bool PathShifter::generate( } for (const auto & shift_line : shift_lines_) { - int idx_gap = shift_line.end_idx - shift_line.start_idx; + if (shift_line.end_idx < shift_line.start_idx) { + RCLCPP_WARN_STREAM_THROTTLE( + logger_, clock_, 3000, "Invalid indices: end_idx is less than start_idx"); + return false; + } + + const auto idx_gap = shift_line.end_idx - shift_line.start_idx; if (idx_gap <= 1) { RCLCPP_WARN_STREAM_THROTTLE( logger_, clock_, 3000, @@ -185,7 +191,7 @@ void PathShifter::applyLinearShifter(ShiftedPath * shifted_path) const // For all path.points, for (size_t i = 0; i < shifted_path->path.points.size(); ++i) { // Set shift length. - double ith_shift_length; + double ith_shift_length = 0.0; if (i < shift_line.start_idx) { ith_shift_length = 0.0; } else if (shift_line.start_idx <= i && i <= shift_line.end_idx) { @@ -235,7 +241,8 @@ void PathShifter::applySplineShifter(ShiftedPath * shifted_path, const bool offs logger_, "base_distance = %s, base_length = %s", toStr(base_distance).c_str(), toStr(base_length).c_str()); - std::vector query_distance, query_length; + std::vector query_distance; + std::vector query_length; // For all path.points, // Note: start_idx is not included since shift = 0, @@ -257,7 +264,7 @@ void PathShifter::applySplineShifter(ShiftedPath * shifted_path, const bool offs } } - if (offset_back == true) { + if (offset_back) { // Apply shifting after shift for (size_t i = shift_line.end_idx; i < shifted_path->path.points.size(); ++i) { addLateralOffsetOnIndexPoint(shifted_path, delta_shift, i); @@ -272,7 +279,7 @@ void PathShifter::applySplineShifter(ShiftedPath * shifted_path, const bool offs } std::pair, std::vector> PathShifter::getBaseLengthsWithoutAccelLimit( - const double arclength, const double shift_length, const bool offset_back) const + const double arclength, const double shift_length, const bool offset_back) { const auto s = arclength; const auto l = shift_length; @@ -286,14 +293,13 @@ std::pair, std::vector> PathShifter::getBaseLengthsW std::pair, std::vector> PathShifter::getBaseLengthsWithoutAccelLimit( const double arclength, const double shift_length, const double velocity, - const double longitudinal_acc, const double total_time, const bool offset_back) const + const double longitudinal_acc, const double total_time, const bool offset_back) { - const auto & s = arclength; - const auto & l = shift_length; - const auto & v0 = velocity; - const auto & a = longitudinal_acc; - const auto & T = total_time; - const double t = T / 4; + const auto s = arclength; + const auto l = shift_length; + const auto v0 = velocity; + const auto a = longitudinal_acc; + const auto t = total_time / 4; const double s1 = std::min(v0 * t + 0.5 * a * t * t, s); const double v1 = v0 + a * t; @@ -322,7 +328,7 @@ std::pair, std::vector> PathShifter::calcBaseLengths return getBaseLengthsWithoutAccelLimit(arclength, shift_length, offset_back); } - const auto & S = arclength; + const auto S = arclength; const auto L = std::abs(shift_length); const auto T = a > acc_threshold ? (-v0 + std::sqrt(v0 * v0 + 2 * a * S)) / a : S / v0; const auto lateral_a_max = 8.0 * L / (T * T); @@ -512,8 +518,7 @@ void PathShifter::removeBehindShiftLineAndSetBaseOffset(const size_t nearest_idx setBaseOffset(new_base_offset); } -void PathShifter::addLateralOffsetOnIndexPoint( - ShiftedPath * path, double offset, size_t index) const +void PathShifter::addLateralOffsetOnIndexPoint(ShiftedPath * path, double offset, size_t index) { if (fabs(offset) < 1.0e-8) { return; @@ -527,10 +532,10 @@ void PathShifter::addLateralOffsetOnIndexPoint( path->shift_length.at(index) += offset; } -void PathShifter::shiftBaseLength(ShiftedPath * path, double offset) const +void PathShifter::shiftBaseLength(ShiftedPath * path, double offset) { - constexpr double BASE_OFFSET_THR = 1.0e-4; - if (std::abs(offset) > BASE_OFFSET_THR) { + constexpr double base_offset_thr = 1.0e-4; + if (std::abs(offset) > base_offset_thr) { for (size_t i = 0; i < path->path.points.size(); ++i) { addLateralOffsetOnIndexPoint(path, offset, i); } @@ -563,11 +568,11 @@ double PathShifter::calcShiftTimeFromJerk(const double lateral, const double jer } double PathShifter::calcFeasibleVelocityFromJerk( - const double lateral, const double jerk, const double longitudinal) + const double lateral, const double jerk, const double longitudinal_distance) { const double j = std::abs(jerk); const double l = std::abs(lateral); - const double d = std::abs(longitudinal); + const double d = std::abs(longitudinal_distance); if (j < 1.0e-8) { return 1.0e10; // TODO(Horibe) maybe invalid arg? } diff --git a/planning/behavior_path_planner_common/src/utils/path_utils.cpp b/planning/behavior_path_planner_common/src/utils/path_utils.cpp index 1d51426793de8..d11bc5a68e9b5 100644 --- a/planning/behavior_path_planner_common/src/utils/path_utils.cpp +++ b/planning/behavior_path_planner_common/src/utils/path_utils.cpp @@ -447,6 +447,8 @@ std::vector splineTwoPoints( std::vector base_s, std::vector base_x, const double begin_diff, const double end_diff, std::vector new_s) { + assert(base_s.size() == 2 && base_x.size() == 2); + const double h = base_s.at(1) - base_s.at(0); const double c = begin_diff; @@ -643,15 +645,12 @@ BehaviorModuleOutput createGoalAroundPath(const std::shared_ptrprev_modified_goal; const Pose goal_pose = modified_goal ? modified_goal->pose : route_handler->getGoalPose(); - const auto shoulder_lanes = route_handler->getShoulderLanelets(); lanelet::ConstLanelet goal_lane; - const bool is_failed_getting_lanelet = std::invoke([&]() { - if (isInLanelets(goal_pose, shoulder_lanes)) { - return !lanelet::utils::query::getClosestLanelet(shoulder_lanes, goal_pose, &goal_lane); - } - return !route_handler->getGoalLanelet(&goal_lane); - }); + const auto shoulder_goal_lanes = route_handler->getShoulderLaneletsAtPose(goal_pose); + if (!shoulder_goal_lanes.empty()) goal_lane = shoulder_goal_lanes.front(); + const auto is_failed_getting_lanelet = + shoulder_goal_lanes.empty() && !route_handler->getGoalLanelet(&goal_lane); if (is_failed_getting_lanelet) { return output; } diff --git a/planning/behavior_path_planner_common/src/utils/utils.cpp b/planning/behavior_path_planner_common/src/utils/utils.cpp index 6fcfad2209815..d674f7770ac67 100644 --- a/planning/behavior_path_planner_common/src/utils/utils.cpp +++ b/planning/behavior_path_planner_common/src/utils/utils.cpp @@ -496,15 +496,12 @@ bool isEgoOutOfRoute( const Pose & goal_pose = (modified_goal && modified_goal->uuid == route_handler->getRouteUuid()) ? modified_goal->pose : route_handler->getGoalPose(); - const auto shoulder_lanes = route_handler->getShoulderLanelets(); lanelet::ConstLanelet goal_lane; - const bool is_failed_getting_lanelet = std::invoke([&]() { - if (utils::isInLanelets(goal_pose, shoulder_lanes)) { - return !lanelet::utils::query::getClosestLanelet(shoulder_lanes, goal_pose, &goal_lane); - } - return !route_handler->getGoalLanelet(&goal_lane); - }); + const auto shoulder_goal_lanes = route_handler->getShoulderLaneletsAtPose(goal_pose); + if (!shoulder_goal_lanes.empty()) goal_lane = shoulder_goal_lanes.front(); + const auto is_failed_getting_lanelet = + shoulder_goal_lanes.empty() && !route_handler->getGoalLanelet(&goal_lane); if (is_failed_getting_lanelet) { RCLCPP_WARN_STREAM( rclcpp::get_logger("behavior_path_planner").get_child("util"), "cannot find goal lanelet"); @@ -527,14 +524,7 @@ bool isEgoOutOfRoute( // If ego vehicle is out of the closest lanelet, return true // Check if ego vehicle is in shoulder lane - const bool is_in_shoulder_lane = std::invoke([&]() { - lanelet::Lanelet closest_shoulder_lanelet; - if (!lanelet::utils::query::getClosestLanelet( - shoulder_lanes, self_pose, &closest_shoulder_lanelet)) { - return false; - } - return lanelet::utils::isInLanelet(self_pose, closest_shoulder_lanelet); - }); + const bool is_in_shoulder_lane = !route_handler->getShoulderLaneletsAtPose(self_pose).empty(); // Check if ego vehicle is in road lane const bool is_in_road_lane = std::invoke([&]() { lanelet::ConstLanelet closest_road_lane; @@ -1114,16 +1104,15 @@ std::shared_ptr generateCenterLinePath( return centerline_path; } -PathWithLaneId getCenterLinePathFromRootLanelet( - const lanelet::ConstLanelet & root_lanelet, - const std::shared_ptr & planner_data) +PathWithLaneId getCenterLinePathFromLanelet( + const lanelet::ConstLanelet & lanelet, const std::shared_ptr & planner_data) { const auto & route_handler = planner_data->route_handler; const auto & current_pose = planner_data->self_odometry->pose.pose; const auto & p = planner_data->parameters; const auto reference_lanes = route_handler->getLaneletSequence( - root_lanelet, current_pose, p.backward_path_length, p.forward_path_length); + lanelet, current_pose, p.backward_path_length, p.forward_path_length); return getCenterLinePath( *route_handler, reference_lanes, current_pose, p.backward_path_length, p.forward_path_length, @@ -1514,8 +1503,7 @@ lanelet::ConstLanelets getExtendedCurrentLanesFromPath( return lanes; } -// TODO(Azu): In the future, get back lanelet within `to_back_dist` [m] from queried lane -lanelet::ConstLanelets getBackwardLanelets( +std::vector getPrecedingLanelets( const RouteHandler & route_handler, const lanelet::ConstLanelets & target_lanes, const Pose & current_pose, const double backward_length) { @@ -1530,18 +1518,21 @@ lanelet::ConstLanelets getBackwardLanelets( } const auto & front_lane = target_lanes.front(); - const auto preceding_lanes = route_handler.getPrecedingLaneletSequence( + return route_handler.getPrecedingLaneletSequence( front_lane, std::abs(backward_length - arc_length.length), {front_lane}); +} - lanelet::ConstLanelets backward_lanes{}; - const auto num_of_lanes = std::invoke([&preceding_lanes]() { - size_t sum{0}; - for (const auto & lanes : preceding_lanes) { - sum += lanes.size(); - } - return sum; - }); +lanelet::ConstLanelets getBackwardLanelets( + const RouteHandler & route_handler, const lanelet::ConstLanelets & target_lanes, + const Pose & current_pose, const double backward_length) +{ + const auto preceding_lanes = + getPrecedingLanelets(route_handler, target_lanes, current_pose, backward_length); + const auto calc_sum = [](size_t sum, const auto & lanes) { return sum + lanes.size(); }; + const auto num_of_lanes = + std::accumulate(preceding_lanes.begin(), preceding_lanes.end(), 0u, calc_sum); + lanelet::ConstLanelets backward_lanes{}; backward_lanes.reserve(num_of_lanes); for (const auto & lanes : preceding_lanes) { @@ -1661,13 +1652,6 @@ bool isAllowedGoalModification(const std::shared_ptr & route_handl bool checkOriginalGoalIsInShoulder(const std::shared_ptr & route_handler) { const Pose & goal_pose = route_handler->getOriginalGoalPose(); - const auto shoulder_lanes = route_handler->getShoulderLanelets(); - - lanelet::ConstLanelet closest_shoulder_lane{}; - if (lanelet::utils::query::getClosestLanelet(shoulder_lanes, goal_pose, &closest_shoulder_lane)) { - return lanelet::utils::isInLanelet(goal_pose, closest_shoulder_lane, 0.1); - } - - return false; + return !route_handler->getShoulderLaneletsAtPose(goal_pose).empty(); } } // namespace behavior_path_planner::utils diff --git a/planning/behavior_path_sampling_planner_module/include/behavior_path_sampling_planner_module/sampling_planner_module.hpp b/planning/behavior_path_sampling_planner_module/include/behavior_path_sampling_planner_module/sampling_planner_module.hpp index f72be654d1e1e..6fac6216eb740 100644 --- a/planning/behavior_path_sampling_planner_module/include/behavior_path_sampling_planner_module/sampling_planner_module.hpp +++ b/planning/behavior_path_sampling_planner_module/include/behavior_path_sampling_planner_module/sampling_planner_module.hpp @@ -93,7 +93,7 @@ class SamplingPlannerModule : public SceneModuleInterface BehaviorModuleOutput plan() override; CandidateOutput planCandidate() const override; void updateData() override; - bool isRootLaneletToBeUpdated() const override + bool isCurrentRouteLaneletToBeReset() const override { return getCurrentStatus() == ModuleStatus::SUCCESS; } diff --git a/planning/behavior_path_sampling_planner_module/src/sampling_planner_module.cpp b/planning/behavior_path_sampling_planner_module/src/sampling_planner_module.cpp index 73a726d8cdf7c..4b0ecdcd24e14 100644 --- a/planning/behavior_path_sampling_planner_module/src/sampling_planner_module.cpp +++ b/planning/behavior_path_sampling_planner_module/src/sampling_planner_module.cpp @@ -54,19 +54,19 @@ SamplingPlannerModule::SamplingPlannerModule( sampler_common::Path & path, const sampler_common::Constraints & constraints, const MultiPoint2d & footprint) -> bool { if (!footprint.empty()) { - path.constraint_results.drivable_area = + path.constraint_results.inside_drivable_area = bg::within(footprint, constraints.drivable_polygons); } for (const auto & f : footprint) { const auto collision_index = constraints.rtree.qbegin(bgi::intersects(f)); if (collision_index != constraints.rtree.qend()) { - path.constraint_results.collision = false; + path.constraint_results.collision_free = false; break; } } - return path.constraint_results.collision && path.constraint_results.drivable_area; + return path.constraint_results.collision_free && path.constraint_results.inside_drivable_area; }); hard_constraints_.emplace_back( @@ -74,14 +74,14 @@ SamplingPlannerModule::SamplingPlannerModule( sampler_common::Path & path, const sampler_common::Constraints & constraints, [[maybe_unused]] const MultiPoint2d & footprint) -> bool { if (path.curvatures.empty()) { - path.constraint_results.curvature = false; + path.constraint_results.valid_curvature = false; return false; } const bool curvatures_satisfied = std::all_of(path.curvatures.begin(), path.curvatures.end(), [&](const auto & v) -> bool { return (v > constraints.hard.min_curvature) && (v < constraints.hard.max_curvature); }); - path.constraint_results.curvature = curvatures_satisfied; + path.constraint_results.valid_curvature = curvatures_satisfied; return curvatures_satisfied; }); @@ -267,9 +267,9 @@ bool SamplingPlannerModule::isReferencePathSafe() const []( sampler_common::Path & path, const sampler_common::Constraints & constraints, const MultiPoint2d & footprint) -> bool { - path.constraint_results.collision = + path.constraint_results.collision_free = !sampler_common::constraints::has_collision(footprint, constraints.obstacle_polygons); - return path.constraint_results.collision; + return path.constraint_results.collision_free; }); evaluateHardConstraints( reference_path, internal_params_->constraints, footprint, hard_constraints_reference_path); @@ -591,7 +591,7 @@ BehaviorModuleOutput SamplingPlannerModule::plan() sampler_common::constraints::buildFootprintPoints(path, internal_params_->constraints); std::vector hard_constraints_results = evaluateHardConstraints(path, internal_params_->constraints, footprint, hard_constraints_); - path.constraint_results.curvature = true; + path.constraint_results.valid_curvature = true; debug_data_.footprints.push_back(footprint); std::vector soft_constraints_results = evaluateSoftConstraints( path, internal_params_->constraints, soft_constraints_, soft_constraints_input); diff --git a/planning/behavior_path_side_shift_module/include/behavior_path_side_shift_module/scene.hpp b/planning/behavior_path_side_shift_module/include/behavior_path_side_shift_module/scene.hpp index 1748f57a61bec..08c2345df5814 100644 --- a/planning/behavior_path_side_shift_module/include/behavior_path_side_shift_module/scene.hpp +++ b/planning/behavior_path_side_shift_module/include/behavior_path_side_shift_module/scene.hpp @@ -92,7 +92,6 @@ class SideShiftModule : public SceneModuleInterface // member PathWithLaneId refined_path_{}; PathWithLaneId reference_path_{}; - PathWithLaneId prev_reference_{}; lanelet::ConstLanelets current_lanelets_; std::shared_ptr parameters_; diff --git a/planning/behavior_path_side_shift_module/src/scene.cpp b/planning/behavior_path_side_shift_module/src/scene.cpp index 6df8c1ec629c9..36321050da1ad 100644 --- a/planning/behavior_path_side_shift_module/src/scene.cpp +++ b/planning/behavior_path_side_shift_module/src/scene.cpp @@ -202,9 +202,6 @@ void SideShiftModule::updateData() const auto reference_pose = prev_output_.shift_length.empty() ? planner_data_->self_odometry->pose.pose : utils::getUnshiftedEgoPose(getEgoPose(), prev_output_); - if (prev_reference_.points.empty()) { - prev_reference_ = getPreviousModuleOutput().path; - } if (getPreviousModuleOutput().reference_path.points.empty()) { return; } @@ -433,13 +430,14 @@ PathWithLaneId SideShiftModule::extendBackwardLength(const PathWithLaneId & orig const auto backward_length = std::max( planner_data_->parameters.backward_path_length, longest_dist_to_shift_point + extra_margin); + const auto & prev_reference = getPreviousModuleOutput().path; const size_t orig_ego_idx = findNearestIndex(original_path.points, getEgoPose().position); - const size_t prev_ego_idx = findNearestSegmentIndex( - prev_reference_.points, getPoint(original_path.points.at(orig_ego_idx))); + const size_t prev_ego_idx = + findNearestSegmentIndex(prev_reference.points, getPoint(original_path.points.at(orig_ego_idx))); size_t clip_idx = 0; for (size_t i = 0; i < prev_ego_idx; ++i) { - if (backward_length > calcSignedArcLength(prev_reference_.points, clip_idx, prev_ego_idx)) { + if (backward_length > calcSignedArcLength(prev_reference.points, clip_idx, prev_ego_idx)) { break; } clip_idx = i; @@ -448,8 +446,8 @@ PathWithLaneId SideShiftModule::extendBackwardLength(const PathWithLaneId & orig PathWithLaneId extended_path{}; { extended_path.points.insert( - extended_path.points.end(), prev_reference_.points.begin() + clip_idx, - prev_reference_.points.begin() + prev_ego_idx); + extended_path.points.end(), prev_reference.points.begin() + clip_idx, + prev_reference.points.begin() + prev_ego_idx); } { diff --git a/planning/behavior_path_start_planner_module/include/behavior_path_start_planner_module/pull_out_planner_base.hpp b/planning/behavior_path_start_planner_module/include/behavior_path_start_planner_module/pull_out_planner_base.hpp index 3089134a16500..9a2749759d03e 100644 --- a/planning/behavior_path_start_planner_module/include/behavior_path_start_planner_module/pull_out_planner_base.hpp +++ b/planning/behavior_path_start_planner_module/include/behavior_path_start_planner_module/pull_out_planner_base.hpp @@ -79,7 +79,9 @@ class PullOutPlannerBase *dynamic_objects, parameters_.th_moving_object_velocity); auto [pull_out_lane_stop_objects, others] = utils::path_safety_checker::separateObjectsByLanelets( - stop_objects, pull_out_lanes, utils::path_safety_checker::isPolygonOverlapLanelet); + stop_objects, pull_out_lanes, [](const auto & obj, const auto & lane) { + return utils::path_safety_checker::isPolygonOverlapLanelet(obj, lane); + }); utils::path_safety_checker::filterObjectsByClass( pull_out_lane_stop_objects, parameters_.object_types_to_check_for_path_generation); diff --git a/planning/behavior_path_start_planner_module/src/start_planner_module.cpp b/planning/behavior_path_start_planner_module/src/start_planner_module.cpp index 4433020605056..bee3fb16595b7 100644 --- a/planning/behavior_path_start_planner_module/src/start_planner_module.cpp +++ b/planning/behavior_path_start_planner_module/src/start_planner_module.cpp @@ -16,6 +16,7 @@ #include "behavior_path_planner_common/utils/parking_departure/utils.hpp" #include "behavior_path_planner_common/utils/path_safety_checker/objects_filtering.hpp" +#include "behavior_path_planner_common/utils/path_safety_checker/path_safety_checker_parameters.hpp" #include "behavior_path_planner_common/utils/path_utils.hpp" #include "behavior_path_start_planner_module/debug.hpp" #include "behavior_path_start_planner_module/util.hpp" @@ -39,6 +40,7 @@ #include using behavior_path_planner::utils::parking_departure::initializeCollisionCheckDebugMap; +using behavior_path_planner::utils::path_safety_checker::ExtendedPredictedObject; using motion_utils::calcLateralOffset; using motion_utils::calcLongitudinalOffsetPose; using tier4_autoware_utils::calcOffsetPose; @@ -396,11 +398,13 @@ bool StartPlannerModule::isPreventingRearVehicleFromPassingThrough() const auto get_gap_between_ego_and_lane_border = [&]( geometry_msgs::msg::Pose & ego_overhang_point_as_pose, - const bool ego_is_merging_from_the_left) -> std::optional { + const bool ego_is_merging_from_the_left) -> std::optional> { const auto local_vehicle_footprint = vehicle_info_.createFootprint(); const auto vehicle_footprint = transformVector(local_vehicle_footprint, tier4_autoware_utils::pose2transform(current_pose)); double smallest_lateral_gap_between_ego_and_border = std::numeric_limits::max(); + double corresponding_lateral_gap_with_other_lane_bound = std::numeric_limits::max(); + for (const auto & point : vehicle_footprint) { geometry_msgs::msg::Pose point_pose; point_pose.position.x = point.x(); @@ -411,9 +415,12 @@ bool StartPlannerModule::isPreventingRearVehicleFromPassingThrough() const lanelet::utils::query::getClosestLanelet(target_lanes, point_pose, &closest_lanelet); lanelet::ConstLanelet closest_lanelet_const(closest_lanelet.constData()); - const lanelet::ConstLineString2d current_lane_bound = (ego_is_merging_from_the_left) - ? closest_lanelet_const.rightBound2d() - : closest_lanelet_const.leftBound2d(); + const auto [current_lane_bound, other_side_lane_bound] = + (ego_is_merging_from_the_left) + ? std::make_pair( + closest_lanelet_const.rightBound2d(), closest_lanelet_const.leftBound2d()) + : std::make_pair( + closest_lanelet_const.leftBound2d(), closest_lanelet_const.rightBound2d()); const double current_point_lateral_gap = calc_absolute_lateral_offset(current_lane_bound, point_pose); if (current_point_lateral_gap < smallest_lateral_gap_between_ego_and_border) { @@ -421,19 +428,35 @@ bool StartPlannerModule::isPreventingRearVehicleFromPassingThrough() const ego_overhang_point_as_pose.position.x = point.x(); ego_overhang_point_as_pose.position.y = point.y(); ego_overhang_point_as_pose.position.z = 0.0; + corresponding_lateral_gap_with_other_lane_bound = + calc_absolute_lateral_offset(other_side_lane_bound, point_pose); } } + if (smallest_lateral_gap_between_ego_and_border == std::numeric_limits::max()) { return std::nullopt; } - return smallest_lateral_gap_between_ego_and_border; + return std::make_pair( + (smallest_lateral_gap_between_ego_and_border), + (corresponding_lateral_gap_with_other_lane_bound)); }; geometry_msgs::msg::Pose ego_overhang_point_as_pose; - const auto gap_between_ego_and_lane_border = + const auto gaps_with_lane_borders_pair = get_gap_between_ego_and_lane_border(ego_overhang_point_as_pose, ego_is_merging_from_the_left); - if (!gap_between_ego_and_lane_border) return false; + if (!gaps_with_lane_borders_pair.has_value()) { + return false; + } + + const auto & gap_between_ego_and_lane_border = gaps_with_lane_borders_pair.value().first; + const auto & corresponding_lateral_gap_with_other_lane_bound = + gaps_with_lane_borders_pair.value().second; + + // middle of the lane is crossed, no need to check for collisions anymore + if (gap_between_ego_and_lane_border < corresponding_lateral_gap_with_other_lane_bound) { + return true; + } // Get the lanelets that will be queried for target objects const auto relevant_lanelets = std::invoke([&]() -> std::optional { lanelet::Lanelet closest_lanelet; @@ -483,7 +506,7 @@ bool StartPlannerModule::isPreventingRearVehicleFromPassingThrough() const if (!closest_object_width) return false; // Decide if the closest object does not fit in the gap left by the ego vehicle. return closest_object_width.value() + parameters_->extra_width_margin_for_rear_obstacle > - gap_between_ego_and_lane_border.value(); + gap_between_ego_and_lane_border; } bool StartPlannerModule::isCloseToOriginalStartPose() const @@ -1133,7 +1156,9 @@ PredictedObjects StartPlannerModule::filterStopObjectsInPullOutLanes( // filter for objects located in pull out lanes and moving at a speed below the threshold auto [stop_objects_in_pull_out_lanes, others] = utils::path_safety_checker::separateObjectsByLanelets( - stop_objects, pull_out_lanes, utils::path_safety_checker::isPolygonOverlapLanelet); + stop_objects, pull_out_lanes, [](const auto & obj, const auto & lane) { + return utils::path_safety_checker::isPolygonOverlapLanelet(obj, lane); + }); const auto path = planner_data_->route_handler->getCenterLinePath( pull_out_lanes, object_check_backward_distance, object_check_forward_distance); @@ -1324,10 +1349,18 @@ bool StartPlannerModule::isSafePath() const debug_data_.target_objects_on_lane = target_objects_on_lane; debug_data_.ego_predicted_path = ego_predicted_path; } - + std::vector merged_target_object; + merged_target_object.reserve( + target_objects_on_lane.on_current_lane.size() + target_objects_on_lane.on_shoulder_lane.size()); + merged_target_object.insert( + merged_target_object.end(), target_objects_on_lane.on_current_lane.begin(), + target_objects_on_lane.on_current_lane.end()); + merged_target_object.insert( + merged_target_object.end(), target_objects_on_lane.on_shoulder_lane.begin(), + target_objects_on_lane.on_shoulder_lane.end()); return behavior_path_planner::utils::path_safety_checker::checkSafetyWithRSS( - pull_out_path, ego_predicted_path, target_objects_on_lane.on_current_lane, - debug_data_.collision_check, planner_data_->parameters, safety_check_params_->rss_params, + pull_out_path, ego_predicted_path, merged_target_object, debug_data_.collision_check, + planner_data_->parameters, safety_check_params_->rss_params, objects_filtering_params_->use_all_predicted_path, hysteresis_factor); } diff --git a/planning/behavior_path_start_planner_module/src/util.cpp b/planning/behavior_path_start_planner_module/src/util.cpp index 82e9d1a08e816..4ed499826dbd1 100644 --- a/planning/behavior_path_start_planner_module/src/util.cpp +++ b/planning/behavior_path_start_planner_module/src/util.cpp @@ -90,11 +90,10 @@ lanelet::ConstLanelets getPullOutLanes( const auto & route_handler = planner_data->route_handler; const auto start_pose = planner_data->route_handler->getOriginalStartPose(); - lanelet::ConstLanelet current_shoulder_lane; - if (route_handler->getPullOutStartLane( - route_handler->getShoulderLanelets(), start_pose, vehicle_width, ¤t_shoulder_lane)) { + const auto current_shoulder_lane = route_handler->getPullOutStartLane(start_pose, vehicle_width); + if (current_shoulder_lane) { // pull out from shoulder lane - return route_handler->getShoulderLaneletSequence(current_shoulder_lane, start_pose); + return route_handler->getShoulderLaneletSequence(*current_shoulder_lane, start_pose); } // pull out from road lane diff --git a/planning/behavior_velocity_blind_spot_module/src/manager.cpp b/planning/behavior_velocity_blind_spot_module/src/manager.cpp index d114ab0c65da9..faa10c1fbe9b4 100644 --- a/planning/behavior_velocity_blind_spot_module/src/manager.cpp +++ b/planning/behavior_velocity_blind_spot_module/src/manager.cpp @@ -73,7 +73,8 @@ void BlindSpotModuleManager::launchNewModules( clock_)); generateUUID(module_id); updateRTCStatus( - getUUID(module_id), true, std::numeric_limits::lowest(), path.header.stamp); + getUUID(module_id), true, State::WAITING_FOR_EXECUTION, std::numeric_limits::lowest(), + path.header.stamp); } } diff --git a/planning/behavior_velocity_crosswalk_module/config/crosswalk.param.yaml b/planning/behavior_velocity_crosswalk_module/config/crosswalk.param.yaml index f8b9e5dbf1327..67b923a8d4cd8 100644 --- a/planning/behavior_velocity_crosswalk_module/config/crosswalk.param.yaml +++ b/planning/behavior_velocity_crosswalk_module/config/crosswalk.param.yaml @@ -43,6 +43,7 @@ ego_pass_later_margin_x: [0.0] # [[s]] time to vehicle margin vector for object pass first situation (the module judges that ego don't have to stop at TTV + MARGIN < TTC condition) ego_pass_later_margin_y: [13.0] # [[s]] time to collision margin vector for object pass first situation (the module judges that ego don't have to stop at TTV + MARGIN < TTC condition) ego_pass_later_additional_margin: 0.5 # [s] additional time margin for object pass first situation to suppress chattering + ego_min_assumed_speed: 2.0 # [m/s] assumed speed to calculate the time to collision point no_stop_decision: # parameters to determine if it is safe to attempt stopping before the crosswalk max_offset_to_crosswalk_for_yield: 0.0 # [m] maximum offset from ego's front to crosswalk for yield. Positive value means in front of the crosswalk. diff --git a/planning/behavior_velocity_crosswalk_module/src/manager.cpp b/planning/behavior_velocity_crosswalk_module/src/manager.cpp index aeff5e27cea7b..5110ff9993a62 100644 --- a/planning/behavior_velocity_crosswalk_module/src/manager.cpp +++ b/planning/behavior_velocity_crosswalk_module/src/manager.cpp @@ -90,6 +90,8 @@ CrosswalkModuleManager::CrosswalkModuleManager(rclcpp::Node & node) getOrDeclareParameter>(node, ns + ".pass_judge.ego_pass_later_margin_y"); cp.ego_pass_later_additional_margin = getOrDeclareParameter(node, ns + ".pass_judge.ego_pass_later_additional_margin"); + cp.ego_min_assumed_speed = + getOrDeclareParameter(node, ns + ".pass_judge.ego_min_assumed_speed"); cp.max_offset_to_crosswalk_for_yield = getOrDeclareParameter( node, ns + ".pass_judge.no_stop_decision.max_offset_to_crosswalk_for_yield"); cp.min_acc_for_no_stop_decision = @@ -188,8 +190,8 @@ void CrosswalkModuleManager::launchNewModules(const PathWithLaneId & path) clock_)); generateUUID(crosswalk_lanelet_id); updateRTCStatus( - getUUID(crosswalk_lanelet_id), true, std::numeric_limits::lowest(), - path.header.stamp); + getUUID(crosswalk_lanelet_id), true, State::WAITING_FOR_EXECUTION, + std::numeric_limits::lowest(), path.header.stamp); }; const auto crosswalk_reg_elem_map = planning_utils::getRegElemMapOnPath( diff --git a/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.cpp b/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.cpp index 7caf8651d8b33..0f9c753523f13 100644 --- a/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.cpp +++ b/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.cpp @@ -810,8 +810,6 @@ CollisionPoint CrosswalkModule::createCollisionPoint( const geometry_msgs::msg::Vector3 & obj_vel, const std::optional object_crosswalk_passage_direction) const { - constexpr double min_ego_velocity = 1.38; // [m/s] - const auto estimated_velocity = std::hypot(obj_vel.x, obj_vel.y); const auto velocity = std::max(planner_param_.min_object_velocity, estimated_velocity); @@ -824,7 +822,7 @@ CollisionPoint CrosswalkModule::createCollisionPoint( // Hence, here, we use the length that would be appropriate for the ego_pass_first judge. collision_point.time_to_collision = std::max(0.0, dist_ego2cp - planner_data_->vehicle_info_.min_longitudinal_offset_m) / - std::max(ego_vel.x, min_ego_velocity); + std::max(ego_vel.x, planner_param_.ego_min_assumed_speed); collision_point.time_to_vehicle = std::max(0.0, dist_obj2cp) / velocity; return collision_point; @@ -1075,7 +1073,7 @@ void CrosswalkModule::updateObjectState( object_info_manager_.update( obj_uuid, obj_pos, std::hypot(obj_vel.x, obj_vel.y), clock_->now(), is_ego_yielding, has_traffic_light, collision_point, object.classification.front().label, planner_param_, - crosswalk_.polygon2d().basicPolygon()); + crosswalk_.polygon2d().basicPolygon(), attention_area); const auto collision_state = object_info_manager_.getCollisionState(obj_uuid); if (collision_point) { diff --git a/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.hpp b/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.hpp index d2468e7f31aa7..e9fdc38304603 100644 --- a/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.hpp +++ b/planning/behavior_velocity_crosswalk_module/src/scene_crosswalk.hpp @@ -135,6 +135,7 @@ class CrosswalkModule : public SceneModuleInterface std::vector ego_pass_later_margin_x; std::vector ego_pass_later_margin_y; double ego_pass_later_additional_margin; + double ego_min_assumed_speed; double max_offset_to_crosswalk_for_yield; double min_acc_for_no_stop_decision; double max_jerk_for_no_stop_decision; @@ -180,7 +181,8 @@ class CrosswalkModule : public SceneModuleInterface void transitState( const rclcpp::Time & now, const geometry_msgs::msg::Point & position, const double vel, const bool is_ego_yielding, const std::optional & collision_point, - const PlannerParam & planner_param, const lanelet::BasicPolygon2d & crosswalk_polygon) + const PlannerParam & planner_param, const lanelet::BasicPolygon2d & crosswalk_polygon, + const bool is_object_on_ego_path) { const bool is_stopped = vel < planner_param.stop_object_velocity; @@ -200,7 +202,7 @@ class CrosswalkModule : public SceneModuleInterface planner_param.timeout_set_for_no_intention_to_walk, distance_to_crosswalk); const bool intent_to_cross = (now - *time_to_start_stopped).seconds() < timeout_no_intention_to_walk; - if (is_ego_yielding && !intent_to_cross) { + if (is_ego_yielding && !intent_to_cross && !is_object_on_ego_path) { collision_state = CollisionState::IGNORE; return; } @@ -253,14 +255,21 @@ class CrosswalkModule : public SceneModuleInterface const std::string & uuid, const geometry_msgs::msg::Point & position, const double vel, const rclcpp::Time & now, const bool is_ego_yielding, const bool has_traffic_light, const std::optional & collision_point, const uint8_t classification, - const PlannerParam & planner_param, const lanelet::BasicPolygon2d & crosswalk_polygon) + const PlannerParam & planner_param, const lanelet::BasicPolygon2d & crosswalk_polygon, + const Polygon2d & attention_area) { // update current uuids current_uuids_.push_back(uuid); + const bool is_object_on_ego_path = + boost::geometry::distance(tier4_autoware_utils::fromMsg(position).to_2d(), attention_area) < + 0.5; + // add new object if (objects.count(uuid) == 0) { - if (has_traffic_light && planner_param.disable_yield_for_new_stopped_object) { + if ( + has_traffic_light && planner_param.disable_yield_for_new_stopped_object && + !is_object_on_ego_path) { objects.emplace(uuid, ObjectInfo{CollisionState::IGNORE}); } else { objects.emplace(uuid, ObjectInfo{CollisionState::YIELD}); @@ -269,7 +278,8 @@ class CrosswalkModule : public SceneModuleInterface // update object state objects.at(uuid).transitState( - now, position, vel, is_ego_yielding, collision_point, planner_param, crosswalk_polygon); + now, position, vel, is_ego_yielding, collision_point, planner_param, crosswalk_polygon, + is_object_on_ego_path); objects.at(uuid).collision_point = collision_point; objects.at(uuid).position = position; objects.at(uuid).classification = classification; diff --git a/planning/behavior_velocity_detection_area_module/src/manager.cpp b/planning/behavior_velocity_detection_area_module/src/manager.cpp index 834ffc03e5dde..8e9a6b6a58a96 100644 --- a/planning/behavior_velocity_detection_area_module/src/manager.cpp +++ b/planning/behavior_velocity_detection_area_module/src/manager.cpp @@ -66,7 +66,8 @@ void DetectionAreaModuleManager::launchNewModules( logger_.get_child("detection_area_module"), clock_)); generateUUID(module_id); updateRTCStatus( - getUUID(module_id), true, std::numeric_limits::lowest(), path.header.stamp); + getUUID(module_id), true, State::WAITING_FOR_EXECUTION, + std::numeric_limits::lowest(), path.header.stamp); } } } diff --git a/planning/behavior_velocity_intersection_module/scripts/ttc.py b/planning/behavior_velocity_intersection_module/scripts/ttc.py index 6d1593d95f055..1eb6ae1ffafc1 100755 --- a/planning/behavior_velocity_intersection_module/scripts/ttc.py +++ b/planning/behavior_velocity_intersection_module/scripts/ttc.py @@ -21,6 +21,7 @@ from threading import Lock import time +from PIL import Image import imageio import matplotlib import matplotlib.pyplot as plt @@ -218,7 +219,19 @@ def plot_world(self): def cleanup(self): if self.args.save: kwargs_write = {"fps": self.args.fps, "quantizer": "nq"} - imageio.mimsave("./" + self.args.gif + ".gif", self.images, **kwargs_write) + max_size_total = 0 + max_size = None + for image in self.images: + (w, h) = image.size + if w * h > max_size_total: + max_size = image.size + max_size_total = w * h + reshaped = [] + for image in self.images: + reshaped.append(image.resize(max_size)) + + imageio.mimsave("./" + self.args.gif + ".gif", reshaped, **kwargs_write) + print("saved fig") rclpy.shutdown() def on_plot_timer(self): @@ -241,6 +254,7 @@ def on_plot_timer(self): if self.args.save: image = np.frombuffer(self.fig.canvas.tostring_rgb(), dtype="uint8") image = image.reshape(self.fig.canvas.get_width_height()[::-1] + (3,)) + image = Image.fromarray(image.astype(np.uint8)) self.images.append(image) def on_ego_ttc(self, msg): diff --git a/planning/behavior_velocity_intersection_module/src/manager.cpp b/planning/behavior_velocity_intersection_module/src/manager.cpp index 3941362d96242..424fb6841eca9 100644 --- a/planning/behavior_velocity_intersection_module/src/manager.cpp +++ b/planning/behavior_velocity_intersection_module/src/manager.cpp @@ -345,10 +345,10 @@ void IntersectionModuleManager::launchNewModules( const UUID uuid = getUUID(new_module->getModuleId()); const auto occlusion_uuid = new_module->getOcclusionUUID(); rtc_interface_.updateCooperateStatus( - uuid, true, std::numeric_limits::lowest(), std::numeric_limits::lowest(), - clock_->now()); + uuid, true, State::RUNNING, std::numeric_limits::lowest(), + std::numeric_limits::lowest(), clock_->now()); occlusion_rtc_interface_.updateCooperateStatus( - occlusion_uuid, true, std::numeric_limits::lowest(), + occlusion_uuid, true, State::RUNNING, std::numeric_limits::lowest(), std::numeric_limits::lowest(), clock_->now()); registerModule(std::move(new_module)); } @@ -404,12 +404,13 @@ void IntersectionModuleManager::sendRTC(const Time & stamp) const UUID uuid = getUUID(scene_module->getModuleId()); const bool safety = scene_module->isSafe() && (!intersection_module->isOcclusionFirstStopRequired()); - updateRTCStatus(uuid, safety, scene_module->getDistance(), stamp); + updateRTCStatus(uuid, safety, State::RUNNING, scene_module->getDistance(), stamp); const auto occlusion_uuid = intersection_module->getOcclusionUUID(); const auto occlusion_distance = intersection_module->getOcclusionDistance(); const auto occlusion_safety = intersection_module->getOcclusionSafety(); occlusion_rtc_interface_.updateCooperateStatus( - occlusion_uuid, occlusion_safety, occlusion_distance, occlusion_distance, stamp); + occlusion_uuid, occlusion_safety, State::RUNNING, occlusion_distance, occlusion_distance, + stamp); // ========================================================================================== // module debug data diff --git a/planning/behavior_velocity_intersection_module/src/scene_intersection.cpp b/planning/behavior_velocity_intersection_module/src/scene_intersection.cpp index 2103ef25c6cfc..9d0c0c8e1defb 100644 --- a/planning/behavior_velocity_intersection_module/src/scene_intersection.cpp +++ b/planning/behavior_velocity_intersection_module/src/scene_intersection.cpp @@ -239,9 +239,20 @@ intersection::DecisionResult IntersectionModule::modifyPathVelocityDetail( // passed each pass judge line for the first time, save current collision status for late // diagnosis // ========================================================================================== + tier4_debug_msgs::msg::Float64MultiArrayStamped object_ttc_time_array; updateObjectInfoManagerCollision( path_lanelets, time_distance_array, traffic_prioritized_level, safely_passed_1st_judge_line, - safely_passed_2nd_judge_line); + safely_passed_2nd_judge_line, &object_ttc_time_array); + { + const auto & debug = planner_param_.debug.ttc; + if ( + std::find(debug.begin(), debug.end(), lane_id_) != debug.end() || + std::find(debug.begin(), debug.end(), -1) != debug.end()) { + ego_ttc_pub_->publish(ego_ttc_time_array); + object_ttc_pub_->publish(object_ttc_time_array); + } + } + for (const auto & object_info : object_info_manager_.attentionObjects()) { if (!object_info->unsafe_info()) { continue; diff --git a/planning/behavior_velocity_intersection_module/src/scene_intersection.hpp b/planning/behavior_velocity_intersection_module/src/scene_intersection.hpp index 73736c804fb02..8c8874156f07b 100644 --- a/planning/behavior_velocity_intersection_module/src/scene_intersection.hpp +++ b/planning/behavior_velocity_intersection_module/src/scene_intersection.hpp @@ -754,7 +754,8 @@ class IntersectionModule : public SceneModuleInterface void updateObjectInfoManagerCollision( const intersection::PathLanelets & path_lanelets, const TimeDistanceArray & time_distance_array, const TrafficPrioritizedLevel & traffic_prioritized_level, - const bool passed_1st_judge_line_first_time, const bool passed_2nd_judge_line_first_time); + const bool passed_1st_judge_line_first_time, const bool passed_2nd_judge_line_first_time, + tier4_debug_msgs::msg::Float64MultiArrayStamped * object_ttc_time_array); void cutPredictPathWithinDuration( const builtin_interfaces::msg::Time & object_stamp, const double time_thr, diff --git a/planning/behavior_velocity_intersection_module/src/scene_intersection_collision.cpp b/planning/behavior_velocity_intersection_module/src/scene_intersection_collision.cpp index 0eff4cea63581..8388bc15492a3 100644 --- a/planning/behavior_velocity_intersection_module/src/scene_intersection_collision.cpp +++ b/planning/behavior_velocity_intersection_module/src/scene_intersection_collision.cpp @@ -144,7 +144,8 @@ void IntersectionModule::updateObjectInfoManagerCollision( const intersection::PathLanelets & path_lanelets, const IntersectionModule::TimeDistanceArray & time_distance_array, const IntersectionModule::TrafficPrioritizedLevel & traffic_prioritized_level, - const bool passed_1st_judge_line_first_time, const bool passed_2nd_judge_line_first_time) + const bool passed_1st_judge_line_first_time, const bool passed_2nd_judge_line_first_time, + tier4_debug_msgs::msg::Float64MultiArrayStamped * object_ttc_time_array) { const auto & intersection_lanelets = intersection_lanelets_.value(); @@ -183,6 +184,25 @@ void IntersectionModule::updateObjectInfoManagerCollision( planner_param_.collision_detection.not_prioritized.collision_end_margin_time); }(); + constexpr size_t object_debug_size = 57; + { + object_ttc_time_array->stamp = clock_->now(); + object_ttc_time_array->layout.dim.resize(3); + object_ttc_time_array->layout.dim.at(0).label = "objects"; + object_ttc_time_array->layout.dim.at(0).size = + 1; // incremented in the loop, first row is lane_id + object_ttc_time_array->layout.dim.at(1).label = + "[x, y, th, length, width, speed, dangerous, ref_obj_enter_time, ref_obj_exit_time, " + "start_time, start_dist, " + "end_time, end_dist, first_collision_x, first_collision_y, last_collision_x, " + "last_collision_y, " + "prd_x[0], ... pred_x[19], pred_y[0], ... pred_y[19]]"; + object_ttc_time_array->layout.dim.at(1).size = object_debug_size; + for (unsigned i = 0; i < object_debug_size; ++i) { + object_ttc_time_array->data.push_back(lane_id_); + } + } + for (auto & object_info : object_info_manager_.attentionObjects()) { const auto & predicted_object = object_info->predicted_object(); bool safe_under_traffic_control = false; @@ -226,6 +246,7 @@ void IntersectionModule::updateObjectInfoManagerCollision( // ========================================================================================== std::optional unsafe_interval{std::nullopt}; std::optional safe_interval{std::nullopt}; + std::optional> object_debug_info{std::nullopt}; for (const auto & predicted_path_ptr : sorted_predicted_paths) { auto predicted_path = *predicted_path_ptr; @@ -296,10 +317,39 @@ void IntersectionModule::updateObjectInfoManagerCollision( break; } } + auto get_object_info = [&]() { + // debug info + const auto & pose = predicted_object.kinematics.initial_pose_with_covariance.pose; + const auto & shape = predicted_object.shape; + const auto [object_start_itr, object_end_itr] = object_passage_interval.interval_position; + const auto & object_start_pos = object_passage_interval.path.at(object_start_itr).position; + const auto & object_end_pos = object_passage_interval.path.at(object_end_itr).position; + std::vector debug; + debug.reserve(object_debug_size); + + debug.insert( + debug.end(), + {pose.position.x, pose.position.y, tf2::getYaw(pose.orientation), shape.dimensions.x, + shape.dimensions.y, + predicted_object.kinematics.initial_twist_with_covariance.twist.linear.x, + 1.0 * static_cast(collision_detected), object_enter_time, object_exit_time, + ego_start_itr->first, ego_start_itr->second, ego_end_itr->first, ego_end_itr->second, + object_start_pos.x, object_start_pos.y, object_end_pos.x, object_end_pos.y}); + for (unsigned i = 0; i < 20; ++i) { + const auto & pos = object_passage_interval.path + .at(std::min(i, object_passage_interval.path.size() - 1)) + .position; + debug.push_back(pos.x); + debug.push_back(pos.y); + } + return debug; + }; + if (collision_detected) { // if judged as UNSAFE, return safe_interval = std::nullopt; unsafe_interval = object_passage_interval; + object_debug_info = get_object_info(); break; } if (!safe_interval) { @@ -308,6 +358,7 @@ void IntersectionModule::updateObjectInfoManagerCollision( // judged UNSAFE during the iteration // ========================================================================================== safe_interval = object_passage_interval; + object_debug_info = get_object_info(); } } object_info->update_safety(unsafe_interval, safe_interval, safe_under_traffic_control); @@ -337,6 +388,13 @@ void IntersectionModule::updateObjectInfoManagerCollision( .x // observed_velocity }); } + + // debug + if (object_debug_info) { + const auto & data = object_debug_info.value(); + object_ttc_time_array->layout.dim.at(0).size++; + std::copy(data.begin(), data.end(), std::back_inserter(object_ttc_time_array->data)); + } } } @@ -714,257 +772,6 @@ IntersectionModule::CollisionStatus IntersectionModule::detectCollision( return {false, intersection::CollisionInterval::ELSE, too_late_detect_objects, misjudge_objects}; } -/* -bool IntersectionModule::checkCollision( - const autoware_auto_planning_msgs::msg::PathWithLaneId & path, TargetObjects * target_objects, - const intersection::PathLanelets & path_lanelets, const size_t closest_idx, - const size_t last_intersection_stopline_candidate_idx, const double time_delay, - const TrafficPrioritizedLevel & traffic_prioritized_level) -{ - using lanelet::utils::getArcCoordinates; - using lanelet::utils::getPolygonFromArcLength; - - // check collision between target_objects predicted path and ego lane - // cut the predicted path at passing_time - tier4_debug_msgs::msg::Float64MultiArrayStamped ego_ttc_time_array; - const auto time_distance_array = calcIntersectionPassingTime( - path, closest_idx, last_intersection_stopline_candidate_idx, time_delay, &ego_ttc_time_array); - - if ( - std::find(planner_param_.debug.ttc.begin(), planner_param_.debug.ttc.end(), lane_id_) != - planner_param_.debug.ttc.end()) { - ego_ttc_time_array.stamp = path.header.stamp; - ego_ttc_pub_->publish(ego_ttc_time_array); - } - - const double passing_time = time_distance_array.back().first; - cutPredictPathWithDuration(target_objects, passing_time); - - const auto & concat_lanelets = path_lanelets.all; - const auto closest_arc_coords = getArcCoordinates( - concat_lanelets, tier4_autoware_utils::getPose(path.points.at(closest_idx).point)); - const auto & ego_lane = path_lanelets.ego_or_entry2exit; - debug_data_.ego_lane = ego_lane.polygon3d(); - const auto ego_poly = ego_lane.polygon2d().basicPolygon(); - - // change TTC margin based on ego traffic light color - const auto [collision_start_margin_time, collision_end_margin_time] = [&]() { - if (traffic_prioritized_level == TrafficPrioritizedLevel::FULLY_PRIORITIZED) { - return std::make_pair( - planner_param_.collision_detection.fully_prioritized.collision_start_margin_time, - planner_param_.collision_detection.fully_prioritized.collision_end_margin_time); - } - if (traffic_prioritized_level == TrafficPrioritizedLevel::PARTIALLY_PRIORITIZED) { - return std::make_pair( - planner_param_.collision_detection.partially_prioritized.collision_start_margin_time, - planner_param_.collision_detection.partially_prioritized.collision_end_margin_time); - } - return std::make_pair( - planner_param_.collision_detection.not_prioritized.collision_start_margin_time, - planner_param_.collision_detection.not_prioritized.collision_end_margin_time); - }(); - const auto expectedToStopBeforeStopLine = [&](const TargetObject & target_object) { - if (!target_object.dist_to_stopline) { - return false; - } - const double dist_to_stopline = target_object.dist_to_stopline.value(); - if (dist_to_stopline < 0) { - return false; - } - const double v = target_object.object.kinematics.initial_twist_with_covariance.twist.linear.x; - const double braking_distance = - v * v / - (2.0 * std::fabs(planner_param_.collision_detection.ignore_on_amber_traffic_light - .object_expected_deceleration)); - return dist_to_stopline > braking_distance; - }; - const auto isTolerableOvershoot = [&](const TargetObject & target_object) { - if ( - !target_object.attention_lanelet || !target_object.dist_to_stopline || - !target_object.stopline) { - return false; - } - const double dist_to_stopline = target_object.dist_to_stopline.value(); - const double v = target_object.object.kinematics.initial_twist_with_covariance.twist.linear.x; - const double braking_distance = - v * v / - (2.0 * std::fabs(planner_param_.collision_detection.ignore_on_amber_traffic_light - .object_expected_deceleration)); - if (dist_to_stopline > braking_distance) { - return false; - } - const auto stopline_front = target_object.stopline.value().front(); - const auto stopline_back = target_object.stopline.value().back(); - tier4_autoware_utils::LineString2d object_line; - object_line.emplace_back( - (stopline_front.x() + stopline_back.x()) / 2.0, - (stopline_front.y() + stopline_back.y()) / 2.0); - const auto stopline_mid = object_line.front(); - const auto endpoint = target_object.attention_lanelet.value().centerline().back(); - object_line.emplace_back(endpoint.x(), endpoint.y()); - std::vector intersections; - bg::intersection(object_line, ego_lane.centerline2d().basicLineString(), intersections); - if (intersections.empty()) { - return false; - } - const auto collision_point = intersections.front(); - // distance from object expected stop position to collision point - const double stopline_to_object = -1.0 * dist_to_stopline + braking_distance; - const double stopline_to_collision = - std::hypot(collision_point.x() - stopline_mid.x(), collision_point.y() - stopline_mid.y()); - const double object2collision = stopline_to_collision - stopline_to_object; - const double margin = - planner_param_.collision_detection.ignore_on_red_traffic_light.object_margin_to_path; - return (object2collision > margin) || (object2collision < 0); - }; - // check collision between predicted_path and ego_area - tier4_debug_msgs::msg::Float64MultiArrayStamped object_ttc_time_array; - object_ttc_time_array.layout.dim.resize(3); - object_ttc_time_array.layout.dim.at(0).label = "objects"; - object_ttc_time_array.layout.dim.at(0).size = 1; // incremented in the loop, first row is lane_id - object_ttc_time_array.layout.dim.at(1).label = - "[x, y, th, length, width, speed, dangerous, ref_obj_enter_time, ref_obj_exit_time, " - "start_time, start_dist, " - "end_time, end_dist, first_collision_x, first_collision_y, last_collision_x, last_collision_y, " - "prd_x[0], ... pred_x[19], pred_y[0], ... pred_y[19]]"; - object_ttc_time_array.layout.dim.at(1).size = 57; - for (unsigned i = 0; i < object_ttc_time_array.layout.dim.at(1).size; ++i) { - object_ttc_time_array.data.push_back(lane_id_); - } - bool collision_detected = false; - for (const auto & target_object : target_objects->all_attention_objects) { - const auto & object = target_object.object; - // If the vehicle is expected to stop before their stopline, ignore - const bool expected_to_stop_before_stopline = expectedToStopBeforeStopLine(target_object); - if ( - traffic_prioritized_level == TrafficPrioritizedLevel::PARTIALLY_PRIORITIZED && - expected_to_stop_before_stopline) { - debug_data_.amber_ignore_targets.objects.push_back(object); - continue; - } - const bool is_tolerable_overshoot = isTolerableOvershoot(target_object); - if ( - traffic_prioritized_level == TrafficPrioritizedLevel::FULLY_PRIORITIZED && - !expected_to_stop_before_stopline && is_tolerable_overshoot) { - debug_data_.red_overshoot_ignore_targets.objects.push_back(object); - continue; - } - for (const auto & predicted_path : object.kinematics.predicted_paths) { - if ( - predicted_path.confidence < - planner_param_.collision_detection.min_predicted_path_confidence) { - // ignore the predicted path with too low confidence - continue; - } - - // collision point - const auto first_itr = std::adjacent_find( - predicted_path.path.cbegin(), predicted_path.path.cend(), - [&ego_poly, &object](const auto & a, const auto & b) { - return bg::intersects(ego_poly, ::createOneStepPolygon(a, b, object.shape)); - }); - if (first_itr == predicted_path.path.cend()) continue; - const auto last_itr = std::adjacent_find( - predicted_path.path.crbegin(), predicted_path.path.crend(), - [&ego_poly, &object](const auto & a, const auto & b) { - return bg::intersects(ego_poly, ::createOneStepPolygon(a, b, object.shape)); - }); - if (last_itr == predicted_path.path.crend()) continue; - - // possible collision time interval - const double ref_object_enter_time = - static_cast(first_itr - predicted_path.path.begin()) * - rclcpp::Duration(predicted_path.time_step).seconds(); - auto start_time_distance_itr = time_distance_array.begin(); - if (ref_object_enter_time - collision_start_margin_time > 0) { - // start of possible ego position in the intersection - start_time_distance_itr = std::lower_bound( - time_distance_array.begin(), time_distance_array.end(), - ref_object_enter_time - collision_start_margin_time, - [](const auto & a, const double b) { return a.first < b; }); - if (start_time_distance_itr == time_distance_array.end()) { - // ego is already at the exit of intersection when npc is at collision point even if npc - // accelerates so ego's position interval is empty - continue; - } - } - const double ref_object_exit_time = - static_cast(last_itr.base() - predicted_path.path.begin()) * - rclcpp::Duration(predicted_path.time_step).seconds(); - auto end_time_distance_itr = std::lower_bound( - time_distance_array.begin(), time_distance_array.end(), - ref_object_exit_time + collision_end_margin_time, - [](const auto & a, const double b) { return a.first < b; }); - if (end_time_distance_itr == time_distance_array.end()) { - // ego is already passing the intersection, when npc is is at collision point - // so ego's position interval is up to the end of intersection lane - end_time_distance_itr = time_distance_array.end() - 1; - } - const double start_arc_length = std::max( - 0.0, closest_arc_coords.length + (*start_time_distance_itr).second - - planner_data_->vehicle_info_.rear_overhang_m); - const double end_arc_length = std::min( - closest_arc_coords.length + (*end_time_distance_itr).second + - planner_data_->vehicle_info_.max_longitudinal_offset_m, - lanelet::utils::getLaneletLength2d(concat_lanelets)); - - const auto trimmed_ego_polygon = - getPolygonFromArcLength(concat_lanelets, start_arc_length, end_arc_length); - - if (trimmed_ego_polygon.empty()) { - continue; - } - - Polygon2d polygon{}; - for (const auto & p : trimmed_ego_polygon) { - polygon.outer().emplace_back(p.x(), p.y()); - } - bg::correct(polygon); - debug_data_.candidate_collision_ego_lane_polygon = toGeomPoly(polygon); - - for (auto itr = first_itr; itr != last_itr.base(); ++itr) { - const auto footprint_polygon = tier4_autoware_utils::toPolygon2d(*itr, object.shape); - if (bg::intersects(polygon, footprint_polygon)) { - collision_detected = true; - break; - } - } - object_ttc_time_array.layout.dim.at(0).size++; - const auto & pos = object..position; - const auto & shape = object.shape; - object_ttc_time_array.data.insert( - object_ttc_time_array.data.end(), - {pos.x, pos.y, tf2::getYaw(object.kinematics.initial_pose_with_covariance.pose.orientation), - shape.dimensions.x, shape.dimensions.y, - object.kinematics.initial_twist_with_covariance.twist.linear.x, - 1.0 * static_cast(collision_detected), ref_object_enter_time, ref_object_exit_time, - start_time_distance_itr->first, start_time_distance_itr->second, - end_time_distance_itr->first, end_time_distance_itr->second, first_itr->position.x, - first_itr->position.y, last_itr->position.x, last_itr->position.y}); - for (unsigned i = 0; i < 20; i++) { - const auto & pos = - predicted_path.path.at(std::min(i, predicted_path.path.size() - 1)).position; - object_ttc_time_array.data.push_back(pos.x); - object_ttc_time_array.data.push_back(pos.y); - } - if (collision_detected) { - debug_data_.conflicting_targets.objects.push_back(object); - break; - } - } - } - - if ( - std::find(planner_param_.debug.ttc.begin(), planner_param_.debug.ttc.end(), lane_id_) != - planner_param_.debug.ttc.end()) { - object_ttc_time_array.stamp = path.header.stamp; - object_ttc_pub_->publish(object_ttc_time_array); - } - - return collision_detected; -} -*/ - std::optional IntersectionModule::checkAngleForTargetLanelets( const geometry_msgs::msg::Pose & pose, const lanelet::ConstLanelets & target_lanelets, @@ -1006,7 +813,7 @@ std::optional IntersectionModule::checkAngleForTargetLanelets( IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassingTime( const autoware_auto_planning_msgs::msg::PathWithLaneId & path, const bool is_prioritized, const intersection::IntersectionStopLines & intersection_stoplines, - tier4_debug_msgs::msg::Float64MultiArrayStamped * debug_ttc_array) const + tier4_debug_msgs::msg::Float64MultiArrayStamped * ego_ttc_array) const { const double intersection_velocity = planner_param_.collision_detection.velocity_profile.default_velocity; @@ -1053,12 +860,12 @@ IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassin second_attention_stopline_idx ? second_attention_stopline_idx.value() : std::max(occlusion_stopline_idx, first_attention_stopline_idx); - int assigned_lane_found = false; + bool assigned_lane_found = false; // crop intersection part of the path, and set the reference velocity to intersection_velocity // for ego's ttc PathWithLaneId reference_path; std::optional upstream_stopline{std::nullopt}; - for (size_t i = 0; i < path.points.size() - 1; ++i) { + for (size_t i = 0; i + 1 < path.points.size(); ++i) { auto reference_point = path.points.at(i); // assume backward velocity is current ego velocity if (i < closest_idx) { @@ -1085,12 +892,6 @@ IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassin return {{0.0, 0.0}}; // has already passed the intersection. } - std::vector> original_path_xy; - for (size_t i = 0; i < reference_path.points.size(); ++i) { - const auto & p = reference_path.points.at(i).point.pose.position; - original_path_xy.emplace_back(p.x, p.y); - } - // apply smoother to reference velocity PathWithLaneId smoothed_reference_path = reference_path; if (!smoothPath(reference_path, smoothed_reference_path, planner_data_)) { @@ -1111,7 +912,8 @@ IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassin const std::optional upstream_stopline_idx_opt = [&]() -> std::optional { if (upstream_stopline) { - const auto upstream_stopline_point = path.points.at(upstream_stopline.value()).point.pose; + const auto upstream_stopline_point = + reference_path.points.at(upstream_stopline.value()).point.pose; return motion_utils::findFirstNearestIndexWithSoftConstraints( smoothed_reference_path.points, upstream_stopline_point, planner_data_->ego_nearest_dist_threshold, planner_data_->ego_nearest_yaw_threshold); @@ -1120,7 +922,7 @@ IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassin } }(); - for (size_t i = smoothed_path_closest_idx; i < smoothed_reference_path.points.size() - 1; ++i) { + for (size_t i = smoothed_path_closest_idx; i + 1 < smoothed_reference_path.points.size(); ++i) { const auto & p1 = smoothed_reference_path.points.at(i); const auto & p2 = smoothed_reference_path.points.at(i + 1); @@ -1144,29 +946,30 @@ IntersectionModule::TimeDistanceArray IntersectionModule::calcIntersectionPassin time_distance_array.emplace_back(passing_time, dist_sum); } - debug_ttc_array->layout.dim.resize(3); - debug_ttc_array->layout.dim.at(0).label = "lane_id_@[0][0], ttc_time, ttc_dist, path_x, path_y"; - debug_ttc_array->layout.dim.at(0).size = 5; - debug_ttc_array->layout.dim.at(1).label = "values"; - debug_ttc_array->layout.dim.at(1).size = time_distance_array.size(); - debug_ttc_array->data.reserve( - time_distance_array.size() * debug_ttc_array->layout.dim.at(0).size); + ego_ttc_array->stamp = clock_->now(); + ego_ttc_array->layout.dim.resize(3); + ego_ttc_array->layout.dim.at(0).label = "lane_id_@[0][0], ttc_time, ttc_dist, path_x, path_y"; + constexpr size_t ego_debug_size = 5; + ego_ttc_array->layout.dim.at(0).size = ego_debug_size; + ego_ttc_array->layout.dim.at(1).label = "values"; + ego_ttc_array->layout.dim.at(1).size = time_distance_array.size(); + ego_ttc_array->data.reserve(time_distance_array.size() * ego_debug_size); for (unsigned i = 0; i < time_distance_array.size(); ++i) { - debug_ttc_array->data.push_back(lane_id_); + ego_ttc_array->data.push_back(lane_id_); } for (const auto & [t, d] : time_distance_array) { - debug_ttc_array->data.push_back(t); + ego_ttc_array->data.push_back(t); } for (const auto & [t, d] : time_distance_array) { - debug_ttc_array->data.push_back(d); + ego_ttc_array->data.push_back(d); } for (size_t i = smoothed_path_closest_idx; i < smoothed_reference_path.points.size(); ++i) { const auto & p = smoothed_reference_path.points.at(i).point.pose.position; - debug_ttc_array->data.push_back(p.x); + ego_ttc_array->data.push_back(p.x); } for (size_t i = smoothed_path_closest_idx; i < smoothed_reference_path.points.size(); ++i) { const auto & p = smoothed_reference_path.points.at(i).point.pose.position; - debug_ttc_array->data.push_back(p.y); + ego_ttc_array->data.push_back(p.y); } return time_distance_array; } diff --git a/planning/behavior_velocity_no_stopping_area_module/src/manager.cpp b/planning/behavior_velocity_no_stopping_area_module/src/manager.cpp index c4192750af1d5..46cc224ea0f6b 100644 --- a/planning/behavior_velocity_no_stopping_area_module/src/manager.cpp +++ b/planning/behavior_velocity_no_stopping_area_module/src/manager.cpp @@ -68,7 +68,8 @@ void NoStoppingAreaModuleManager::launchNewModules( clock_)); generateUUID(module_id); updateRTCStatus( - getUUID(module_id), true, std::numeric_limits::lowest(), path.header.stamp); + getUUID(module_id), true, State::WAITING_FOR_EXECUTION, + std::numeric_limits::lowest(), path.header.stamp); } } } diff --git a/planning/behavior_velocity_occlusion_spot_module/src/debug.cpp b/planning/behavior_velocity_occlusion_spot_module/src/debug.cpp index a6e13d0dfdcdc..1170afc490a75 100644 --- a/planning/behavior_velocity_occlusion_spot_module/src/debug.cpp +++ b/planning/behavior_velocity_occlusion_spot_module/src/debug.cpp @@ -33,7 +33,6 @@ using BasicPolygons = std::vector; using occlusion_spot_utils::PossibleCollisionInfo; using tier4_autoware_utils::appendMarkerArray; using tier4_autoware_utils::calcOffsetPose; -using tier4_autoware_utils::createDefaultMarker; using tier4_autoware_utils::createMarkerColor; using tier4_autoware_utils::createMarkerOrientation; using tier4_autoware_utils::createMarkerPosition; @@ -118,7 +117,7 @@ MarkerArray makeDebugInfoMarkers(T & debug_data) { // add slow down markers for occlusion spot MarkerArray debug_markers; - auto & possible_collisions = debug_data.possible_collisions; + const auto & possible_collisions = debug_data.possible_collisions; size_t id = 0; // draw obstacle collision for (const auto & pc : possible_collisions) { diff --git a/planning/behavior_velocity_occlusion_spot_module/src/grid_utils.cpp b/planning/behavior_velocity_occlusion_spot_module/src/grid_utils.cpp index 9f580149be7ae..c8adb324b9055 100644 --- a/planning/behavior_velocity_occlusion_spot_module/src/grid_utils.cpp +++ b/planning/behavior_velocity_occlusion_spot_module/src/grid_utils.cpp @@ -43,23 +43,6 @@ Polygon2d pointsToPoly(const Point2d p0, const Point2d p1, const double radius) return line_poly; } -std::vector> pointsToRays( - const grid_map::Position p0, const grid_map::Position p1, const double radius) -{ - using grid_map::Position; - std::vector> lines; - const double angle = atan2(p0.y() - p1.y(), p0.x() - p1.x()); - const double r = radius; - lines.emplace_back(std::make_pair(p0, p1)); - lines.emplace_back(std::make_pair( - Position(p0.x() + r * sin(angle), p0.y() - r * cos(angle)), - Position(p1.x() + r * sin(angle), p1.y() - r * cos(angle)))); - lines.emplace_back(std::make_pair( - Position(p1.x() - r * sin(angle), p1.y() + r * cos(angle)), - Position(p0.x() - r * sin(angle), p0.y() + r * cos(angle)))); - return lines; -} - void findOcclusionSpots( std::vector & occlusion_spot_positions, const grid_map::GridMap & grid, const Polygon2d & polygon, [[maybe_unused]] double min_size) @@ -86,36 +69,21 @@ bool isCollisionFree( const double radius) { const grid_map::Matrix & grid_data = grid["layer"]; - bool polys = true; try { - if (polys) { - Point2d occlusion_p = {p1.x(), p1.y()}; - Point2d collision_p = {p2.x(), p2.y()}; - Polygon2d polygon = pointsToPoly(occlusion_p, collision_p, radius); - grid_map::Polygon grid_polygon; - for (const auto & point : polygon.outer()) { - grid_polygon.addVertex({point.x(), point.y()}); - } - for (grid_map_utils::PolygonIterator iterator(grid, grid_polygon); !iterator.isPastEnd(); - ++iterator) { - const grid_map::Index & index = *iterator; - if (grid_data(index.x(), index.y()) == grid_utils::occlusion_cost_value::OCCUPIED) { - return false; - } - } - } else { - std::vector> lines = - pointsToRays(p1, p2, radius); - for (const auto & p : lines) { - for (grid_map::LineIterator iterator(grid, p.first, p.second); !iterator.isPastEnd(); - ++iterator) { - const grid_map::Index & index = *iterator; - if (grid_data(index.x(), index.y()) == grid_utils::occlusion_cost_value::OCCUPIED) { - return false; - } - } + Point2d occlusion_p = {p1.x(), p1.y()}; + Point2d collision_p = {p2.x(), p2.y()}; + Polygon2d polygon = pointsToPoly(occlusion_p, collision_p, radius); + grid_map::Polygon grid_polygon; + for (const auto & point : polygon.outer()) { + grid_polygon.addVertex({point.x(), point.y()}); + } + for (grid_map_utils::PolygonIterator iterator(grid, grid_polygon); !iterator.isPastEnd(); + ++iterator) { + const grid_map::Index & index = *iterator; + if (grid_data(index.x(), index.y()) == grid_utils::occlusion_cost_value::OCCUPIED) { + return false; } - } // polys or not + } } catch (const std::invalid_argument & e) { std::cerr << e.what() << std::endl; return false; @@ -324,7 +292,7 @@ void imageToOccupancyGrid(const cv::Mat & cv_image, nav_msgs::msg::OccupancyGrid const int idx = (height - 1 - y) + (width - 1 - x) * height; unsigned char intensity = cv_image.at(y, x); if (intensity == grid_utils::occlusion_cost_value::FREE_SPACE) { - intensity = grid_utils::occlusion_cost_value::FREE_SPACE; + // do nothing } else if (intensity == grid_utils::occlusion_cost_value::UNKNOWN_IMAGE) { intensity = grid_utils::occlusion_cost_value::UNKNOWN; } else if (intensity == grid_utils::occlusion_cost_value::OCCUPIED_IMAGE) { @@ -348,14 +316,12 @@ void toQuantizedImage( unsigned char intensity = occupancy_grid.data.at(idx); if (intensity <= param.free_space_max) { continue; - } else if (param.free_space_max < intensity && intensity < param.occupied_min) { + } else if (intensity < param.occupied_min) { intensity = grid_utils::occlusion_cost_value::UNKNOWN_IMAGE; occlusion_image->at(y, x) = intensity; - } else if (param.occupied_min <= intensity) { + } else { intensity = grid_utils::occlusion_cost_value::OCCUPIED_IMAGE; border_image->at(y, x) = intensity; - } else { - throw std::logic_error("behavior_velocity[occlusion_spot_grid]: invalid if clause"); } } } diff --git a/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.cpp b/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.cpp index f38768ce26da4..f22cedbe67c8f 100644 --- a/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.cpp +++ b/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.cpp @@ -117,6 +117,9 @@ void calcSlowDownPointsForPossibleCollision( size_t collision_index = 0; double dist_along_path_point = offset; double dist_along_next_path_point = dist_along_path_point; + if (path.points.size() == 0) { + return; + } for (size_t idx = closest_idx; idx < path.points.size() - 1; idx++) { auto p_prev = path.points.at(idx).point; auto p_next = path.points.at(idx + 1).point; @@ -242,7 +245,8 @@ void categorizeVehicles( return; } -ArcCoordinates getOcclusionPoint(const PredictedObject & obj, const ConstLineString2d & ll_string) +lanelet::ArcCoordinates getOcclusionPoint( + const PredictedObject & obj, const lanelet::ConstLineString2d & ll_string) { const auto poly = tier4_autoware_utils::toPolygon2d(obj); std::deque arcs; @@ -257,16 +261,18 @@ ArcCoordinates getOcclusionPoint(const PredictedObject & obj, const ConstLineStr * Ego===============> path **/ // sort by arc length - std::sort(arcs.begin(), arcs.end(), [](ArcCoordinates arc1, ArcCoordinates arc2) { - return arc1.length < arc2.length; - }); + std::sort( + arcs.begin(), arcs.end(), [](lanelet::ArcCoordinates arc1, lanelet::ArcCoordinates arc2) { + return arc1.length < arc2.length; + }); // remove closest 2 polygon point arcs.pop_front(); arcs.pop_front(); // sort by arc distance - std::sort(arcs.begin(), arcs.end(), [](ArcCoordinates arc1, ArcCoordinates arc2) { - return std::abs(arc1.distance) < std::abs(arc2.distance); - }); + std::sort( + arcs.begin(), arcs.end(), [](lanelet::ArcCoordinates arc1, lanelet::ArcCoordinates arc2) { + return std::abs(arc1.distance) < std::abs(arc2.distance); + }); // return closest to path point which is choosen by farthest 2 points. return arcs.at(0); } @@ -286,18 +292,19 @@ double calcSignedLateralDistanceWithOffset( } PossibleCollisionInfo calculateCollisionPathPointFromOcclusionSpot( - const ArcCoordinates & arc_coord_occlusion, - const ArcCoordinates & arc_coord_occlusion_with_offset, + const lanelet::ArcCoordinates & arc_coord_occlusion, + const lanelet::ArcCoordinates & arc_coord_occlusion_with_offset, const lanelet::ConstLanelet & path_lanelet, const PlannerParam & param) { - auto calcPosition = [](const ConstLineString2d & ll, const ArcCoordinates & arc) { - BasicPoint2d bp = fromArcCoordinates(ll, arc); - Point position; - position.x = bp[0]; - position.y = bp[1]; - position.z = 0.0; - return position; - }; + auto calcPosition = + [](const lanelet::ConstLineString2d & ll, const lanelet::ArcCoordinates & arc) { + BasicPoint2d bp = lanelet::geometry::fromArcCoordinates(ll, arc); + Point position; + position.x = bp[0]; + position.y = bp[1]; + position.z = 0.0; + return position; + }; /** * @brief calculate obstacle collision intersection from arc coordinate info. * ^ @@ -338,8 +345,8 @@ bool generatePossibleCollisionsFromObjects( lanelet::ConstLanelet path_lanelet = toPathLanelet(path); auto ll = path_lanelet.centerline2d(); for (const auto & dyn : dyn_objects) { - ArcCoordinates arc_coord_occlusion = getOcclusionPoint(dyn, ll); - ArcCoordinates arc_coord_occlusion_with_offset = { + lanelet::ArcCoordinates arc_coord_occlusion = getOcclusionPoint(dyn, ll); + lanelet::ArcCoordinates arc_coord_occlusion_with_offset = { arc_coord_occlusion.length - param.baselink_to_front, calcSignedLateralDistanceWithOffset( arc_coord_occlusion.distance, param.right_overhang, param.left_overhang, @@ -426,7 +433,8 @@ bool isBlockedByPartition(const LineString2d & direction, const BasicPolygons2d std::optional generateOneNotableCollisionFromOcclusionSpot( const grid_map::GridMap & grid, const std::vector & occlusion_spot_positions, const double offset_from_start_to_ego, const Point2d base_point, - const lanelet::ConstLanelet & path_lanelet, const PlannerParam & param, DebugData & debug_data) + const lanelet::ConstLanelet & path_lanelet, const PlannerParam & param, + const DebugData & debug_data) { const double baselink_to_front = param.baselink_to_front; const double right_overhang = param.right_overhang; @@ -451,7 +459,7 @@ std::optional generateOneNotableCollisionFromOcclusionSpo if (length_to_col < offset_from_start_to_ego) { continue; } - ArcCoordinates arc_coord_collision_point = { + lanelet::ArcCoordinates arc_coord_collision_point = { length_to_col, calcSignedLateralDistanceWithOffset( arc_coord_occlusion_point.distance, right_overhang, left_overhang, wheel_tread)}; diff --git a/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.hpp b/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.hpp index ec58e38dec45a..7f495f042d7f8 100644 --- a/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.hpp +++ b/planning/behavior_velocity_occlusion_spot_module/src/occlusion_spot_utils.hpp @@ -57,14 +57,10 @@ using autoware_auto_planning_msgs::msg::PathPointWithLaneId; using autoware_auto_planning_msgs::msg::PathWithLaneId; using geometry_msgs::msg::Point; using geometry_msgs::msg::Pose; -using lanelet::ArcCoordinates; using lanelet::BasicLineString2d; using lanelet::BasicPoint2d; using lanelet::BasicPolygon2d; -using lanelet::ConstLineString2d; using lanelet::LaneletMapPtr; -using lanelet::geometry::fromArcCoordinates; -using lanelet::geometry::toArcCoordinates; using DetectionAreaIdx = std::optional>; using BasicPolygons2d = std::vector; @@ -241,7 +237,8 @@ void calcSlowDownPointsForPossibleCollision( std::optional generateOneNotableCollisionFromOcclusionSpot( const grid_map::GridMap & grid, const std::vector & occlusion_spot_positions, const double offset_from_start_to_ego, const Point2d base_point, - const lanelet::ConstLanelet & path_lanelet, const PlannerParam & param, DebugData & debug_data); + const lanelet::ConstLanelet & path_lanelet, const PlannerParam & param, + const DebugData & debug_data); //!< @brief generate possible collisions coming from occlusion spots on the side of the path bool generatePossibleCollisionsFromGridMap( std::vector & possible_collisions, const grid_map::GridMap & grid, diff --git a/planning/behavior_velocity_out_of_lane_module/config/out_of_lane.param.yaml b/planning/behavior_velocity_out_of_lane_module/config/out_of_lane.param.yaml index 1b483b95510ed..e4d08367ee4f7 100644 --- a/planning/behavior_velocity_out_of_lane_module/config/out_of_lane.param.yaml +++ b/planning/behavior_velocity_out_of_lane_module/config/out_of_lane.param.yaml @@ -3,6 +3,7 @@ out_of_lane: # module to stop or slowdown before overlapping another lane with other objects mode: ttc # mode used to consider a conflict with an object. "threshold", "intervals", or "ttc" skip_if_already_overlapping: true # do not run this module when ego already overlaps another lane + ignore_overlaps_over_lane_changeable_lanelets: true # if true, overlaps on lane changeable lanelets are ignored threshold: time_threshold: 5.0 # [s] consider objects that will reach an overlap within this time diff --git a/planning/behavior_velocity_out_of_lane_module/src/lanelets_selection.cpp b/planning/behavior_velocity_out_of_lane_module/src/lanelets_selection.cpp index 738ea22106b29..67d8a79a63f03 100644 --- a/planning/behavior_velocity_out_of_lane_module/src/lanelets_selection.cpp +++ b/planning/behavior_velocity_out_of_lane_module/src/lanelets_selection.cpp @@ -78,6 +78,15 @@ lanelet::ConstLanelets calculate_path_lanelets( return path_lanelets; } +void add_lane_changeable_lanelets( + lanelet::ConstLanelets & lanelets_to_ignore, const lanelet::ConstLanelets & path_lanelets, + const route_handler::RouteHandler & route_handler) +{ + for (const auto & path_lanelet : path_lanelets) + for (const auto & ll : route_handler.getLaneChangeableNeighbors(path_lanelet)) + if (!contains_lanelet(lanelets_to_ignore, ll.id())) lanelets_to_ignore.push_back(ll); +} + lanelet::ConstLanelets calculate_ignored_lanelets( const EgoData & ego_data, const lanelet::ConstLanelets & path_lanelets, const route_handler::RouteHandler & route_handler, const PlannerParam & params) @@ -93,6 +102,8 @@ lanelet::ConstLanelets calculate_ignored_lanelets( const auto is_path_lanelet = contains_lanelet(path_lanelets, l.second.id()); if (!is_path_lanelet) ignored_lanelets.push_back(l.second); } + if (params.ignore_overlaps_over_lane_changeable_lanelets) + add_lane_changeable_lanelets(ignored_lanelets, path_lanelets, route_handler); return ignored_lanelets; } diff --git a/planning/behavior_velocity_out_of_lane_module/src/manager.cpp b/planning/behavior_velocity_out_of_lane_module/src/manager.cpp index 8055f5c9106ef..7d764722405af 100644 --- a/planning/behavior_velocity_out_of_lane_module/src/manager.cpp +++ b/planning/behavior_velocity_out_of_lane_module/src/manager.cpp @@ -38,6 +38,8 @@ OutOfLaneModuleManager::OutOfLaneModuleManager(rclcpp::Node & node) pp.mode = getOrDeclareParameter(node, ns + ".mode"); pp.skip_if_already_overlapping = getOrDeclareParameter(node, ns + ".skip_if_already_overlapping"); + pp.ignore_overlaps_over_lane_changeable_lanelets = + getOrDeclareParameter(node, ns + ".ignore_overlaps_over_lane_changeable_lanelets"); pp.time_threshold = getOrDeclareParameter(node, ns + ".threshold.time_threshold"); pp.intervals_ego_buffer = getOrDeclareParameter(node, ns + ".intervals.ego_time_buffer"); diff --git a/planning/behavior_velocity_out_of_lane_module/src/types.hpp b/planning/behavior_velocity_out_of_lane_module/src/types.hpp index d482870e5ce18..ff690699ee638 100644 --- a/planning/behavior_velocity_out_of_lane_module/src/types.hpp +++ b/planning/behavior_velocity_out_of_lane_module/src/types.hpp @@ -39,6 +39,8 @@ struct PlannerParam std::string mode; // mode used to consider a conflict with an object bool skip_if_already_overlapping; // if true, do not run the module when ego already overlaps // another lane + bool ignore_overlaps_over_lane_changeable_lanelets; // if true, overlaps on lane changeable + // lanelets are ignored double time_threshold; // [s](mode="threshold") objects time threshold double intervals_ego_buffer; // [s](mode="intervals") buffer to extend the ego time range diff --git a/planning/behavior_velocity_planner_common/include/behavior_velocity_planner_common/scene_module_interface.hpp b/planning/behavior_velocity_planner_common/include/behavior_velocity_planner_common/scene_module_interface.hpp index d8b042ec880e4..082a88e306169 100644 --- a/planning/behavior_velocity_planner_common/include/behavior_velocity_planner_common/scene_module_interface.hpp +++ b/planning/behavior_velocity_planner_common/include/behavior_velocity_planner_common/scene_module_interface.hpp @@ -31,6 +31,7 @@ #include #include #include +#include #include #include @@ -58,6 +59,7 @@ using tier4_debug_msgs::msg::Float64Stamped; using tier4_planning_msgs::msg::StopFactor; using tier4_planning_msgs::msg::StopReason; using tier4_rtc_msgs::msg::Module; +using tier4_rtc_msgs::msg::State; using unique_identifier_msgs::msg::UUID; struct ObjectOfInterest @@ -235,9 +237,10 @@ class SceneModuleManagerInterfaceWithRTC : public SceneModuleManagerInterface virtual void setActivation(); void updateRTCStatus( - const UUID & uuid, const bool safe, const double distance, const Time & stamp) + const UUID & uuid, const bool safe, const uint8_t state, const double distance, + const Time & stamp) { - rtc_interface_.updateCooperateStatus(uuid, safe, distance, distance, stamp); + rtc_interface_.updateCooperateStatus(uuid, safe, state, distance, distance, stamp); } void removeRTCStatus(const UUID & uuid) { rtc_interface_.removeCooperateStatus(uuid); } diff --git a/planning/behavior_velocity_planner_common/src/scene_module_interface.cpp b/planning/behavior_velocity_planner_common/src/scene_module_interface.cpp index 362493005eb17..803682489ebde 100644 --- a/planning/behavior_velocity_planner_common/src/scene_module_interface.cpp +++ b/planning/behavior_velocity_planner_common/src/scene_module_interface.cpp @@ -211,7 +211,8 @@ void SceneModuleManagerInterfaceWithRTC::sendRTC(const Time & stamp) { for (const auto & scene_module : scene_modules_) { const UUID uuid = getUUID(scene_module->getModuleId()); - updateRTCStatus(uuid, scene_module->isSafe(), scene_module->getDistance(), stamp); + const auto state = scene_module->isActivated() ? State::RUNNING : State::WAITING_FOR_EXECUTION; + updateRTCStatus(uuid, scene_module->isSafe(), state, scene_module->getDistance(), stamp); } publishRTCStatus(stamp); } diff --git a/planning/behavior_velocity_run_out_module/src/debug.cpp b/planning/behavior_velocity_run_out_module/src/debug.cpp index 23764bc73fbff..3f6935365c1a4 100644 --- a/planning/behavior_velocity_run_out_module/src/debug.cpp +++ b/planning/behavior_velocity_run_out_module/src/debug.cpp @@ -73,6 +73,8 @@ visualization_msgs::msg::MarkerArray createPolygonMarkerArray( RunOutDebug::RunOutDebug(rclcpp::Node & node) : node_(node) { + accel_reason_ = AccelReason::UNKNOWN; + pub_debug_values_ = node.create_publisher("~/debug/run_out/debug_values", 1); pub_accel_reason_ = node.create_publisher("~/debug/run_out/accel_reason", 1); diff --git a/planning/behavior_velocity_run_out_module/src/debug.hpp b/planning/behavior_velocity_run_out_module/src/debug.hpp index e9b269ee437f0..fbf682279e363 100644 --- a/planning/behavior_velocity_run_out_module/src/debug.hpp +++ b/planning/behavior_velocity_run_out_module/src/debug.hpp @@ -86,6 +86,7 @@ class RunOutDebug NO_OBSTACLE = 1, PASS = 2, LOW_JERK = 3, + UNKNOWN = 4, }; struct TextWithPosition diff --git a/planning/behavior_velocity_traffic_light_module/src/manager.cpp b/planning/behavior_velocity_traffic_light_module/src/manager.cpp index 89817f3342dbd..6e6871e20a354 100644 --- a/planning/behavior_velocity_traffic_light_module/src/manager.cpp +++ b/planning/behavior_velocity_traffic_light_module/src/manager.cpp @@ -133,7 +133,8 @@ void TrafficLightModuleManager::launchNewModules( planner_param_, logger_.get_child("traffic_light_module"), clock_)); generateUUID(module_id); updateRTCStatus( - getUUID(module_id), true, std::numeric_limits::lowest(), path.header.stamp); + getUUID(module_id), true, State::WAITING_FOR_EXECUTION, + std::numeric_limits::lowest(), path.header.stamp); } } } diff --git a/planning/freespace_planner/include/freespace_planner/freespace_planner_node.hpp b/planning/freespace_planner/include/freespace_planner/freespace_planner_node.hpp index 9c13f14d180d0..2c10b1b491ace 100644 --- a/planning/freespace_planner/include/freespace_planner/freespace_planner_node.hpp +++ b/planning/freespace_planner/include/freespace_planner/freespace_planner_node.hpp @@ -133,6 +133,8 @@ class FreespacePlannerNode : public rclcpp::Node size_t prev_target_index_; size_t target_index_; bool is_completed_ = false; + bool reset_in_progress_ = false; + bool is_new_parking_cycle_ = true; LaneletRoute::ConstSharedPtr route_; OccupancyGrid::ConstSharedPtr occupancy_grid_; diff --git a/planning/freespace_planner/src/freespace_planner/freespace_planner_node.cpp b/planning/freespace_planner/src/freespace_planner/freespace_planner_node.cpp index bd8045e653a16..1c2b4513e9c45 100644 --- a/planning/freespace_planner/src/freespace_planner/freespace_planner_node.cpp +++ b/planning/freespace_planner/src/freespace_planner/freespace_planner_node.cpp @@ -321,6 +321,8 @@ void FreespacePlannerNode::onRoute(const LaneletRoute::ConstSharedPtr msg) goal_pose_.header = msg->header; goal_pose_.pose = msg->goal_pose; + is_new_parking_cycle_ = true; + reset(); } @@ -444,23 +446,42 @@ void FreespacePlannerNode::onTimer() return; } - if (isPlanRequired()) { - // Stop before planning new trajectory - const auto stop_trajectory = partial_trajectory_.points.empty() - ? createStopTrajectory(current_pose_) - : createStopTrajectory(partial_trajectory_); - trajectory_pub_->publish(stop_trajectory); - debug_pose_array_pub_->publish(trajectory2PoseArray(stop_trajectory)); - debug_partial_pose_array_pub_->publish(trajectory2PoseArray(stop_trajectory)); + // Must stop before replanning any new trajectory + const bool is_reset_required = !reset_in_progress_ && isPlanRequired(); + if (is_reset_required) { + // Stop before planning new trajectory, except in a new parking cycle as the vehicle already + // stops. + if (!is_new_parking_cycle_) { + const auto stop_trajectory = partial_trajectory_.points.empty() + ? createStopTrajectory(current_pose_) + : createStopTrajectory(partial_trajectory_); + trajectory_pub_->publish(stop_trajectory); + debug_pose_array_pub_->publish(trajectory2PoseArray(stop_trajectory)); + debug_partial_pose_array_pub_->publish(trajectory2PoseArray(stop_trajectory)); + } reset(); - // Plan new trajectory - planTrajectory(); + reset_in_progress_ = true; + } + + if (reset_in_progress_) { + const auto is_stopped = isStopped(odom_buffer_, node_param_.th_stopped_velocity_mps); + if (is_stopped) { + // Plan new trajectory + planTrajectory(); + reset_in_progress_ = false; + } else { + // Will keep current stop trajectory + RCLCPP_WARN_THROTTLE( + get_logger(), *get_clock(), 1000, + "Waiting for the vehicle to stop before generating a new trajectory."); + } } // StopTrajectory if (trajectory_.points.size() <= 1) { + is_new_parking_cycle_ = false; return; } @@ -472,6 +493,8 @@ void FreespacePlannerNode::onTimer() trajectory_pub_->publish(partial_trajectory_); debug_pose_array_pub_->publish(trajectory2PoseArray(trajectory_)); debug_partial_pose_array_pub_->publish(trajectory2PoseArray(partial_trajectory_)); + + is_new_parking_cycle_ = false; } void FreespacePlannerNode::planTrajectory() diff --git a/planning/freespace_planning_algorithms/CMakeLists.txt b/planning/freespace_planning_algorithms/CMakeLists.txt index d5a9d32db1817..726aa47f7a5e5 100644 --- a/planning/freespace_planning_algorithms/CMakeLists.txt +++ b/planning/freespace_planning_algorithms/CMakeLists.txt @@ -2,7 +2,10 @@ cmake_minimum_required(VERSION 3.14) project(freespace_planning_algorithms) find_package(autoware_cmake REQUIRED) +find_package(python_cmake_module REQUIRED) + autoware_package() +ament_python_install_package(${PROJECT_NAME}) ament_auto_add_library(reeds_shepp SHARED src/reeds_shepp.cpp @@ -52,3 +55,22 @@ install(PROGRAMS test/debug_plot.py DESTINATION lib/${PROJECT_NAME} ) + +find_package(Python3 REQUIRED COMPONENTS Interpreter Development) +find_package(pybind11_vendor REQUIRED) +find_package(pybind11 REQUIRED) + +pybind11_add_module(${PROJECT_NAME}_pybind SHARED + scripts/bind/astar_search_pybind.cpp +) + +include_directories(${PROJECT_NAME}_pybind PRIVATE + include/ +) +target_link_libraries(${PROJECT_NAME}_pybind PRIVATE + ${PROJECT_NAME} +) + +install(TARGETS ${PROJECT_NAME}_pybind + DESTINATION "${PYTHON_INSTALL_DIR}/${PROJECT_NAME}" +) diff --git a/planning/freespace_planning_algorithms/README.md b/planning/freespace_planning_algorithms/README.md index 7069a1c0fabfc..8bd015589d58d 100644 --- a/planning/freespace_planning_algorithms/README.md +++ b/planning/freespace_planning_algorithms/README.md @@ -74,6 +74,24 @@ The black cells, green box, and red box, respectively, indicate obstacles, start configuration, and goal configuration. The sequence of the blue boxes indicate the solution path. +## Extension to Python module (only A\* supported) + +There is an implementation of the extension to the python module. +You can try A\* search via Python by setting follows: + +- parameters, +- costmap, +- start pose, +- goal pose. + +Then, you can get + +- success or failure, +- searched trajectory. + +The example code is [scripts/example/example.py](scripts/example/example.py). +Note that you need to build this package and source the setup shell script in advance. + ## License notice Files `src/reeds_shepp.cpp` and `include/astar_search/reeds_shepp.h` diff --git a/planning/freespace_planning_algorithms/freespace_planning_algorithms/__init__.py b/planning/freespace_planning_algorithms/freespace_planning_algorithms/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/planning/freespace_planning_algorithms/freespace_planning_algorithms/astar_search.py b/planning/freespace_planning_algorithms/freespace_planning_algorithms/astar_search.py new file mode 100644 index 0000000000000..c9dcc351e3ce2 --- /dev/null +++ b/planning/freespace_planning_algorithms/freespace_planning_algorithms/astar_search.py @@ -0,0 +1,64 @@ +# Copyright 2024 TIER IV, Inc. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import freespace_planning_algorithms.freespace_planning_algorithms_pybind as _fp +from geometry_msgs.msg import Point +from geometry_msgs.msg import Pose +from geometry_msgs.msg import Quaternion +from nav_msgs.msg import OccupancyGrid +from rclpy.serialization import serialize_message + +PlannerCommonParam = _fp.PlannerCommonParam +VehicleShape = _fp.VehicleShape +AstarParam = _fp.AstarParam + + +class PlannerWaypoints: + def __init__(self): + self.waypoints = [] + self.length = 0.0 + + def compute_length(self): + return self.length + + +class AstarSearch: + def __init__( + self, + planner_param: PlannerCommonParam, + vehicle_shape: VehicleShape, + astar_param: AstarParam, + ): + self.astar_search = _fp.AstarSearch(planner_param, vehicle_shape, astar_param) + + def setMap(self, costmap: OccupancyGrid): + costmap_byte = serialize_message(costmap) + self.astar_search.setMap(costmap_byte) + + def makePlan(self, start_pose: Pose, goal_pose: Pose): + start_pose_byte = serialize_message(start_pose) + goal_pose_byte = serialize_message(goal_pose) + return self.astar_search.makePlan(start_pose_byte, goal_pose_byte) + + def getWaypoints(self): + waypoints_vector = self.astar_search.getWaypoints() + waypoints = PlannerWaypoints() + + waypoints.length = waypoints_vector.length + for waypoint in waypoints_vector.waypoints: + pos = Point(x=waypoint[0], y=waypoint[1], z=waypoint[2]) + quat = Quaternion(x=waypoint[3], y=waypoint[4], z=waypoint[5], w=waypoint[6]) + waypoints.waypoints.append(Pose(position=pos, orientation=quat)) + + return waypoints diff --git a/planning/freespace_planning_algorithms/package.xml b/planning/freespace_planning_algorithms/package.xml index 2b20a935c4ae1..2fb3e066f0bdd 100644 --- a/planning/freespace_planning_algorithms/package.xml +++ b/planning/freespace_planning_algorithms/package.xml @@ -14,6 +14,7 @@ ament_cmake_auto autoware_cmake + python_cmake_module geometry_msgs nav_msgs diff --git a/planning/freespace_planning_algorithms/scripts/bind/astar_search_pybind.cpp b/planning/freespace_planning_algorithms/scripts/bind/astar_search_pybind.cpp new file mode 100644 index 0000000000000..9d10cf311fb16 --- /dev/null +++ b/planning/freespace_planning_algorithms/scripts/bind/astar_search_pybind.cpp @@ -0,0 +1,167 @@ +// Copyright 2024 TIER IV, Inc. All rights reserved. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "freespace_planning_algorithms/abstract_algorithm.hpp" +#include "freespace_planning_algorithms/astar_search.hpp" + +#include +#include + +#include +#include + +#include +#include + +struct PlannerWaypointsVector +{ + std::vector> waypoints; + double length; +}; + +class AstarSearchPython : public freespace_planning_algorithms::AstarSearch +{ + using freespace_planning_algorithms::AstarSearch::AstarSearch; + +public: + void setMapByte(const std::string & costmap_byte) + { + rclcpp::SerializedMessage serialized_msg; + static constexpr size_t message_header_length = 8u; + serialized_msg.reserve(message_header_length + costmap_byte.size()); + serialized_msg.get_rcl_serialized_message().buffer_length = costmap_byte.size(); + for (size_t i = 0; i < costmap_byte.size(); ++i) { + serialized_msg.get_rcl_serialized_message().buffer[i] = costmap_byte[i]; + } + nav_msgs::msg::OccupancyGrid costmap; + static rclcpp::Serialization serializer; + serializer.deserialize_message(&serialized_msg, &costmap); + + freespace_planning_algorithms::AstarSearch::setMap(costmap); + } + + bool makePlanByte(const std::string & start_pose_byte, const std::string & goal_pose_byte) + { + rclcpp::SerializedMessage serialized_start_msg; + static constexpr size_t message_header_length = 8u; + serialized_start_msg.reserve(message_header_length + start_pose_byte.size()); + serialized_start_msg.get_rcl_serialized_message().buffer_length = start_pose_byte.size(); + for (size_t i = 0; i < start_pose_byte.size(); ++i) { + serialized_start_msg.get_rcl_serialized_message().buffer[i] = start_pose_byte[i]; + } + geometry_msgs::msg::Pose start_pose; + static rclcpp::Serialization start_serializer; + start_serializer.deserialize_message(&serialized_start_msg, &start_pose); + + rclcpp::SerializedMessage serialized_goal_msg; + serialized_goal_msg.reserve(message_header_length + goal_pose_byte.size()); + serialized_goal_msg.get_rcl_serialized_message().buffer_length = goal_pose_byte.size(); + for (size_t i = 0; i < goal_pose_byte.size(); ++i) { + serialized_goal_msg.get_rcl_serialized_message().buffer[i] = goal_pose_byte[i]; + } + geometry_msgs::msg::Pose goal_pose; + static rclcpp::Serialization goal_serializer; + goal_serializer.deserialize_message(&serialized_goal_msg, &goal_pose); + + return freespace_planning_algorithms::AstarSearch::makePlan(start_pose, goal_pose); + } + + PlannerWaypointsVector getWaypointsAsVector() + { + freespace_planning_algorithms::PlannerWaypoints waypoints = + freespace_planning_algorithms::AstarSearch::getWaypoints(); + PlannerWaypointsVector waypoints_vector; + for (const auto & waypoint : waypoints.waypoints) { + // NOTE: it was difficult to return the deserialized pose_byte and serialize the pose_byte on + // python-side. So this function returns [*position, *quaternion] as double array + const auto & xyz = waypoint.pose.pose.position; + const auto & quat = waypoint.pose.pose.orientation; + waypoints_vector.waypoints.push_back( + std::vector({xyz.x, xyz.y, xyz.z, quat.x, quat.y, quat.z, quat.w})); + } + waypoints_vector.length = waypoints.compute_length(); + return waypoints_vector; + } +}; + +namespace py = pybind11; + +PYBIND11_MODULE(freespace_planning_algorithms_pybind, p) +{ + auto pyPlannerWaypointsVector = + py::class_(p, "PlannerWaypointsVector", py::dynamic_attr()) + .def(py::init<>()) + .def_readwrite("waypoints", &PlannerWaypointsVector::waypoints) + .def_readwrite("length", &PlannerWaypointsVector::length); + auto pyAstarParam = + py::class_(p, "AstarParam", py::dynamic_attr()) + .def(py::init<>()) + .def_readwrite( + "only_behind_solutions", &freespace_planning_algorithms::AstarParam::only_behind_solutions) + .def_readwrite("use_back", &freespace_planning_algorithms::AstarParam::use_back) + .def_readwrite( + "distance_heuristic_weight", + &freespace_planning_algorithms::AstarParam::distance_heuristic_weight); + auto pyPlannerCommonParam = + py::class_( + p, "PlannerCommonParam", py::dynamic_attr()) + .def(py::init<>()) + .def_readwrite("time_limit", &freespace_planning_algorithms::PlannerCommonParam::time_limit) + .def_readwrite( + "minimum_turning_radius", + &freespace_planning_algorithms::PlannerCommonParam::minimum_turning_radius) + .def_readwrite( + "maximum_turning_radius", + &freespace_planning_algorithms::PlannerCommonParam::maximum_turning_radius) + .def_readwrite( + "turning_radius_size", + &freespace_planning_algorithms::PlannerCommonParam::turning_radius_size) + .def_readwrite("theta_size", &freespace_planning_algorithms::PlannerCommonParam::theta_size) + .def_readwrite( + "curve_weight", &freespace_planning_algorithms::PlannerCommonParam::curve_weight) + .def_readwrite( + "reverse_weight", &freespace_planning_algorithms::PlannerCommonParam::reverse_weight) + .def_readwrite( + "lateral_goal_range", + &freespace_planning_algorithms::PlannerCommonParam::lateral_goal_range) + .def_readwrite( + "longitudinal_goal_range", + &freespace_planning_algorithms::PlannerCommonParam::longitudinal_goal_range) + .def_readwrite( + "angle_goal_range", &freespace_planning_algorithms::PlannerCommonParam::angle_goal_range) + .def_readwrite( + "obstacle_threshold", + &freespace_planning_algorithms::PlannerCommonParam::obstacle_threshold); + auto pyVehicleShape = + py::class_(p, "VehicleShape", py::dynamic_attr()) + .def(py::init<>()) + .def(py::init()) + .def_readwrite("length", &freespace_planning_algorithms::VehicleShape::length) + .def_readwrite("width", &freespace_planning_algorithms::VehicleShape::width) + .def_readwrite("base2back", &freespace_planning_algorithms::VehicleShape::base2back); + + py::class_( + p, "AbstractPlanningAlgorithm"); + py::class_< + freespace_planning_algorithms::AstarSearch, + freespace_planning_algorithms::AbstractPlanningAlgorithm>(p, "AstarSearchCpp"); + py::class_(p, "AstarSearch") + .def(py::init< + freespace_planning_algorithms::PlannerCommonParam &, + freespace_planning_algorithms::VehicleShape &, + freespace_planning_algorithms::AstarParam &>()) + .def("setMap", &AstarSearchPython::setMapByte) + .def("makePlan", &AstarSearchPython::makePlanByte) + .def("getWaypoints", &AstarSearchPython::getWaypointsAsVector); +} diff --git a/planning/freespace_planning_algorithms/scripts/example/example.py b/planning/freespace_planning_algorithms/scripts/example/example.py new file mode 100644 index 0000000000000..73f53e23bc540 --- /dev/null +++ b/planning/freespace_planning_algorithms/scripts/example/example.py @@ -0,0 +1,93 @@ +# Copyright 2024 TIER IV, Inc. All rights reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import freespace_planning_algorithms.astar_search as fp +from geometry_msgs.msg import Pose +from nav_msgs.msg import OccupancyGrid +from pyquaternion import Quaternion + +# -- Vehicle Shape -- +vehicle_shape = fp.VehicleShape() +vehicle_shape.length = 2.0 +vehicle_shape.width = 1.0 +vehicle_shape.base2back = 1.0 + + +# -- Planner Common Parameter -- +planner_param = fp.PlannerCommonParam() +# base configs +planner_param.time_limit = 30000.0 +planner_param.minimum_turning_radius = 9.0 +planner_param.maximum_turning_radius = 9.0 +planner_param.turning_radius_size = 1 +# search configs +planner_param.theta_size = 144 +planner_param.angle_goal_range = 6.0 +planner_param.curve_weight = 1.2 +planner_param.reverse_weight = 2.0 +planner_param.lateral_goal_range = 0.5 +planner_param.longitudinal_goal_range = 2.0 +# costmap configs +planner_param.obstacle_threshold = 100 + + +# -- A* search Configurations -- +astar_param = fp.AstarParam() +astar_param.only_behind_solutions = False +astar_param.use_back = True +astar_param.distance_heuristic_weight = 1.0 + +astar = fp.AstarSearch(planner_param, vehicle_shape, astar_param) + + +# -- Costmap Definition +size = 350 +resolution = 0.2 + +costmap = OccupancyGrid() +costmap.info.resolution = resolution +costmap.info.height = size +costmap.info.width = size +costmap.info.origin.position.x = -size * resolution / 2 +costmap.info.origin.position.y = -size * resolution / 2 +costmap.data = [0 for i in range(size**2)] + +astar.setMap(costmap) + + +# -- Start and Goal Pose +start_pose = Pose() +goal_pose = Pose() + +start_pose.position.x = 0.0 +start_pose.position.y = 0.0 + +goal_pose.position.x = 10.0 +goal_pose.position.y = 0.0 + +yaw = 0 +quaternion = Quaternion(axis=[0, 0, 1], angle=yaw) + +goal_pose.orientation.w = quaternion.w +goal_pose.orientation.x = quaternion.x +goal_pose.orientation.y = quaternion.y +goal_pose.orientation.z = quaternion.z + + +# -- Search -- +if astar.makePlan(start_pose, goal_pose): + print("Success to find path.") + print(" Path length:", astar.getWaypoints().length) +else: + print("Fail to find path.") diff --git a/planning/mission_planner/src/mission_planner/mission_planner.cpp b/planning/mission_planner/src/mission_planner/mission_planner.cpp index e9a0108cdaa24..af363bcf23da7 100644 --- a/planning/mission_planner/src/mission_planner/mission_planner.cpp +++ b/planning/mission_planner/src/mission_planner/mission_planner.cpp @@ -87,6 +87,17 @@ MissionPlanner::MissionPlanner(const rclcpp::NodeOptions & options) logger_configure_ = std::make_unique(this); } +void MissionPlanner::publish_pose_log(const Pose & pose, const std::string & pose_type) +{ + const auto & p = pose.position; + RCLCPP_INFO( + this->get_logger(), "%s pose - x: %f, y: %f, z: %f", pose_type.c_str(), p.x, p.y, p.z); + const auto & quaternion = pose.orientation; + RCLCPP_INFO( + this->get_logger(), "%s orientation - qx: %f, qy: %f, qz: %f, qw: %f", pose_type.c_str(), + quaternion.x, quaternion.y, quaternion.z, quaternion.w); +} + void MissionPlanner::check_initialization() { auto logger = get_logger(); @@ -239,7 +250,7 @@ void MissionPlanner::on_set_lanelet_route( if (is_reroute && !check_reroute_safety(*current_route_, route)) { cancel_route(); - change_state(is_reroute ? RouteState::SET : RouteState::UNSET); + change_state(RouteState::SET); throw service_utils::ServiceException( ResponseCode::ERROR_REROUTE_FAILED, "New route is not safe. Reroute failed."); } @@ -247,6 +258,9 @@ void MissionPlanner::on_set_lanelet_route( change_route(route); change_state(RouteState::SET); res->status.success = true; + + publish_pose_log(odometry_->pose.pose, "initial"); + publish_pose_log(req->goal_pose, "goal"); } void MissionPlanner::on_set_waypoint_route( @@ -284,7 +298,7 @@ void MissionPlanner::on_set_waypoint_route( if (is_reroute && !check_reroute_safety(*current_route_, route)) { cancel_route(); - change_state(is_reroute ? RouteState::SET : RouteState::UNSET); + change_state(RouteState::SET); throw service_utils::ServiceException( ResponseCode::ERROR_REROUTE_FAILED, "New route is not safe. Reroute failed."); } @@ -292,6 +306,9 @@ void MissionPlanner::on_set_waypoint_route( change_route(route); change_state(RouteState::SET); res->status.success = true; + + publish_pose_log(odometry_->pose.pose, "initial"); + publish_pose_log(req->goal_pose, "goal"); } void MissionPlanner::change_route() diff --git a/planning/mission_planner/src/mission_planner/mission_planner.hpp b/planning/mission_planner/src/mission_planner/mission_planner.hpp index 8016851d5a7d3..6752ceb4eaa8b 100644 --- a/planning/mission_planner/src/mission_planner/mission_planner.hpp +++ b/planning/mission_planner/src/mission_planner/mission_planner.hpp @@ -122,6 +122,8 @@ class MissionPlanner : public rclcpp::Node const Header & header, const std::vector & waypoints, const Pose & goal_pose, const UUID & uuid, const bool allow_goal_modification); + void publish_pose_log(const Pose & pose, const std::string & pose_type); + rclcpp::TimerBase::SharedPtr data_check_timer_; void check_initialization(); diff --git a/planning/obstacle_cruise_planner/config/obstacle_cruise_planner.param.yaml b/planning/obstacle_cruise_planner/config/obstacle_cruise_planner.param.yaml index 5b634823302c0..bd9c5750af78f 100644 --- a/planning/obstacle_cruise_planner/config/obstacle_cruise_planner.param.yaml +++ b/planning/obstacle_cruise_planner/config/obstacle_cruise_planner.param.yaml @@ -87,7 +87,7 @@ obstacle_traj_angle_threshold : 1.22 # [rad] = 70 [deg], yaw threshold of crossing obstacle against the nearest trajectory point for cruise or stop stop: - max_lat_margin: 0.2 # lateral margin between obstacle and trajectory band with ego's width + max_lat_margin: 0.3 # lateral margin between obstacle and trajectory band with ego's width crossing_obstacle: collision_time_margin : 4.0 # time threshold of collision between obstacle adn ego for cruise or stop [s] diff --git a/planning/obstacle_cruise_planner/src/node.cpp b/planning/obstacle_cruise_planner/src/node.cpp index a069b4b6f9395..43400acb86bd9 100644 --- a/planning/obstacle_cruise_planner/src/node.cpp +++ b/planning/obstacle_cruise_planner/src/node.cpp @@ -552,9 +552,10 @@ std::vector ObstacleCruisePlannerNode::createOneStepPolygons( const geometry_msgs::msg::Pose & current_ego_pose, const double lat_margin) const { const auto & p = behavior_determination_param_; - const bool is_enable_current_pose_consideration = p.enable_to_consider_current_pose; - const double step_length = p.decimate_trajectory_step_length; - const double time_to_convergence = p.time_to_convergence; + + const double front_length = vehicle_info.max_longitudinal_offset_m; + const double rear_length = vehicle_info.rear_overhang_m; + const double vehicle_width = vehicle_info.vehicle_width_m; const size_t nearest_idx = motion_utils::findNearestSegmentIndex(traj_points, current_ego_pose.position); @@ -563,41 +564,68 @@ std::vector ObstacleCruisePlannerNode::createOneStepPolygons( tier4_autoware_utils::inverseTransformPose(current_ego_pose, nearest_pose); const double current_ego_lat_error = current_ego_pose_error.position.y; const double current_ego_yaw_error = tf2::getYaw(current_ego_pose_error.orientation); - double time_elapsed = 0.0; - - std::vector polygons; - std::vector last_poses = {traj_points.at(0).pose}; - if (is_enable_current_pose_consideration) { - last_poses.push_back(current_ego_pose); - } + double time_elapsed{0.0}; + std::vector output_polygons; + Polygon2d tmp_polys{}; for (size_t i = 0; i < traj_points.size(); ++i) { std::vector current_poses = {traj_points.at(i).pose}; // estimate the future ego pose with assuming that the pose error against the reference path // will decrease to zero by the time_to_convergence - if (is_enable_current_pose_consideration && time_elapsed < time_to_convergence) { - const double rem_ratio = (time_to_convergence - time_elapsed) / time_to_convergence; + if (p.enable_to_consider_current_pose && time_elapsed < p.time_to_convergence) { + const double rem_ratio = (p.time_to_convergence - time_elapsed) / p.time_to_convergence; geometry_msgs::msg::Pose indexed_pose_err; indexed_pose_err.set__orientation( tier4_autoware_utils::createQuaternionFromYaw(current_ego_yaw_error * rem_ratio)); indexed_pose_err.set__position( tier4_autoware_utils::createPoint(0.0, current_ego_lat_error * rem_ratio, 0.0)); - current_poses.push_back( tier4_autoware_utils::transformPose(indexed_pose_err, traj_points.at(i).pose)); - if (traj_points.at(i).longitudinal_velocity_mps != 0.0) { - time_elapsed += step_length / std::abs(traj_points.at(i).longitudinal_velocity_mps); + time_elapsed += + p.decimate_trajectory_step_length / std::abs(traj_points.at(i).longitudinal_velocity_mps); } else { time_elapsed = std::numeric_limits::max(); } } - polygons.push_back( - polygon_utils::createOneStepPolygon(last_poses, current_poses, vehicle_info, lat_margin)); - last_poses = current_poses; + + Polygon2d idx_poly{}; + for (const auto & pose : current_poses) { + if (i == 0 && traj_points.at(i).longitudinal_velocity_mps > 1e-3) { + boost::geometry::append( + idx_poly, + tier4_autoware_utils::toFootprint(pose, front_length, rear_length, vehicle_width) + .outer()); + boost::geometry::append( + idx_poly, + tier4_autoware_utils::fromMsg(tier4_autoware_utils::calcOffsetPose( + pose, front_length, vehicle_width * 0.5 + lat_margin, 0.0) + .position) + .to_2d()); + boost::geometry::append( + idx_poly, tier4_autoware_utils::fromMsg( + tier4_autoware_utils::calcOffsetPose( + pose, front_length, -vehicle_width * 0.5 - lat_margin, 0.0) + .position) + .to_2d()); + } else { + boost::geometry::append( + idx_poly, tier4_autoware_utils::toFootprint( + pose, front_length, rear_length, vehicle_width + lat_margin * 2.0) + .outer()); + } + } + + boost::geometry::append(tmp_polys, idx_poly.outer()); + Polygon2d hull_polygon; + boost::geometry::convex_hull(tmp_polys, hull_polygon); + boost::geometry::correct(hull_polygon); + + output_polygons.push_back(hull_polygon); + tmp_polys = std::move(idx_poly); } - return polygons; + return output_polygons; } std::vector ObstacleCruisePlannerNode::convertToObstacles( diff --git a/planning/obstacle_cruise_planner/src/polygon_utils.cpp b/planning/obstacle_cruise_planner/src/polygon_utils.cpp index 6b422fbda5118..fa5a96b934f7a 100644 --- a/planning/obstacle_cruise_planner/src/polygon_utils.cpp +++ b/planning/obstacle_cruise_planner/src/polygon_utils.cpp @@ -20,18 +20,6 @@ namespace { -void appendPointToPolygon(Polygon2d & polygon, const geometry_msgs::msg::Point & geom_point) -{ - Point2d point(geom_point.x, geom_point.y); - bg::append(polygon.outer(), point); -} - -geometry_msgs::msg::Point calcOffsetPosition( - const geometry_msgs::msg::Pose & pose, const double offset_x, const double offset_y) -{ - return tier4_autoware_utils::calcOffsetPose(pose, offset_x, offset_y, 0.0).position; -} - PointWithStamp calcNearestCollisionPoint( const size_t first_within_idx, const std::vector & collision_points, const std::vector & decimated_traj_points, const bool is_driving_forward) @@ -104,38 +92,6 @@ std::optional>> getCollisionIndex( namespace polygon_utils { -Polygon2d createOneStepPolygon( - const std::vector & last_poses, - const std::vector & current_poses, - const vehicle_info_util::VehicleInfo & vehicle_info, const double lat_margin) -{ - Polygon2d polygon; - - const double base_to_front = vehicle_info.max_longitudinal_offset_m; - const double width = vehicle_info.vehicle_width_m / 2.0 + lat_margin; - const double base_to_rear = vehicle_info.rear_overhang_m; - - for (auto & pose : last_poses) { - appendPointToPolygon(polygon, calcOffsetPosition(pose, base_to_front, width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, base_to_front, -width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, -base_to_rear, -width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, -base_to_rear, width)); - } - for (auto & pose : current_poses) { - appendPointToPolygon(polygon, calcOffsetPosition(pose, base_to_front, width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, base_to_front, -width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, -base_to_rear, -width)); - appendPointToPolygon(polygon, calcOffsetPosition(pose, -base_to_rear, width)); - } - - bg::correct(polygon); - - Polygon2d hull_polygon; - bg::convex_hull(polygon, hull_polygon); - - return hull_polygon; -} - std::optional> getCollisionPoint( const std::vector & traj_points, const std::vector & traj_polygons, const Obstacle & obstacle, const bool is_driving_forward, diff --git a/planning/route_handler/include/route_handler/route_handler.hpp b/planning/route_handler/include/route_handler/route_handler.hpp index ac8e472b2f943..d13c0536cf3c1 100644 --- a/planning/route_handler/include/route_handler/route_handler.hpp +++ b/planning/route_handler/include/route_handler/route_handler.hpp @@ -27,6 +27,7 @@ #include #include #include +#include #include #include @@ -77,6 +78,7 @@ class RouteHandler lanelet::traffic_rules::TrafficRulesPtr getTrafficRulesPtr() const; std::shared_ptr getOverallGraphPtr() const; lanelet::LaneletMapPtr getLaneletMapPtr() const; + static bool isNoDrivableLane(const lanelet::ConstLanelet & llt); // for routing bool planPathLaneletsBetweenCheckpoints( @@ -324,9 +326,9 @@ class RouteHandler const double check_length) const; lanelet::routing::RelationType getRelation( const lanelet::ConstLanelet & prev_lane, const lanelet::ConstLanelet & next_lane) const; - lanelet::ConstLanelets getShoulderLanelets() const; bool isShoulderLanelet(const lanelet::ConstLanelet & lanelet) const; bool isRouteLanelet(const lanelet::ConstLanelet & lanelet) const; + bool isRoadLanelet(const lanelet::ConstLanelet & lanelet) const; lanelet::ConstLanelets getPreferredLanelets() const; // for path @@ -341,20 +343,18 @@ class RouteHandler const lanelet::ConstLanelets & lanelets, lanelet::ConstLanelet * target_lanelet) const; bool getLeftLaneChangeTargetExceptPreferredLane( const lanelet::ConstLanelets & lanelets, lanelet::ConstLanelet * target_lanelet) const; - static bool getPullOverTarget( - const lanelet::ConstLanelets & lanelets, const Pose & goal_pose, - lanelet::ConstLanelet * target_lanelet); - static bool getPullOutStartLane( - const lanelet::ConstLanelets & lanelets, const Pose & pose, const double vehicle_width, - lanelet::ConstLanelet * target_lanelet); + std::optional getPullOverTarget(const Pose & goal_pose) const; + std::optional getPullOutStartLane( + const Pose & pose, const double vehicle_width) const; double getLaneChangeableDistance(const Pose & current_pose, const Direction & direction) const; - bool getLeftShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * left_lanelet) const; - bool getRightShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * right_lanelet) const; + lanelet::ConstLanelets getRoadLaneletsAtPose(const Pose & pose) const; + std::optional getLeftShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const; + std::optional getRightShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const; + lanelet::ConstLanelets getShoulderLaneletsAtPose(const Pose & pose) const; lanelet::ConstPolygon3d getIntersectionAreaById(const lanelet::Id id) const; bool isPreferredLane(const lanelet::ConstLanelet & lanelet) const; - lanelet::ConstLanelets getClosestLanelets(const geometry_msgs::msg::Pose & target_pose) const; private: // MUST @@ -362,12 +362,10 @@ class RouteHandler lanelet::traffic_rules::TrafficRulesPtr traffic_rules_ptr_; std::shared_ptr overall_graphs_ptr_; lanelet::LaneletMapPtr lanelet_map_ptr_; - lanelet::ConstLanelets road_lanelets_; lanelet::ConstLanelets route_lanelets_; lanelet::ConstLanelets preferred_lanelets_; lanelet::ConstLanelets start_lanelets_; lanelet::ConstLanelets goal_lanelets_; - lanelet::ConstLanelets shoulder_lanelets_; std::shared_ptr route_ptr_{nullptr}; rclcpp::Logger logger_{rclcpp::get_logger("route_handler")}; @@ -409,19 +407,18 @@ class RouteHandler const lanelet::ConstLanelet & lanelet, const double min_length = std::numeric_limits::max(), const bool only_route_lanes = true) const; - bool getFollowingShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * following_lanelet) const; + std::optional getFollowingShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const; lanelet::ConstLanelets getShoulderLaneletSequenceAfter( const lanelet::ConstLanelet & lanelet, const double min_length = std::numeric_limits::max()) const; - bool getPreviousShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * prev_lanelet) const; + std::optional getPreviousShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const; lanelet::ConstLanelets getShoulderLaneletSequenceUpTo( const lanelet::ConstLanelet & lanelet, const double min_length = std::numeric_limits::max()) const; lanelet::ConstLanelets getPreviousLaneletSequence( const lanelet::ConstLanelets & lanelet_sequence) const; - lanelet::ConstLanelets getClosestLaneletSequence(const Pose & pose) const; lanelet::ConstLanelets getLaneChangeTargetLanes(const Pose & pose) const; lanelet::ConstLanelets getLaneSequenceUpTo(const lanelet::ConstLanelet & lanelet) const; lanelet::ConstLanelets getLaneSequenceAfter(const lanelet::ConstLanelet & lanelet) const; @@ -441,17 +438,41 @@ class RouteHandler */ bool hasNoDrivableLaneInPath(const lanelet::routing::LaneletPath & path) const; /** - * @brief Searches for a path between start and goal lanelets that does not include any - * no_drivable_lane. If there is more than one path fount, the function returns the shortest path - * that does not include any no_drivable_lane. + * @brief Searches for the shortest path between start and goal lanelets that does not include any + * no_drivable_lane. * @param start_lanelet start lanelet * @param goal_lanelet goal lanelet - * @param drivable_lane_path output path that does not include no_drivable_lane. - * @return true if a path without any no_drivable_lane found, false if this path is not found. + * @return the lanelet path (if found) */ - bool findDrivableLanePath( - const lanelet::ConstLanelet & start_lanelet, const lanelet::ConstLanelet & goal_lanelet, - lanelet::routing::LaneletPath & drivable_lane_path) const; + std::optional findDrivableLanePath( + const lanelet::ConstLanelet & start_lanelet, const lanelet::ConstLanelet & goal_lanelet) const; }; + +/// @brief custom routing cost with infinity cost for no drivable lanes +class RoutingCostDrivable : public lanelet::routing::RoutingCostDistance +{ +public: + RoutingCostDrivable() : lanelet::routing::RoutingCostDistance(10.0) {} + inline double getCostSucceeding( + const lanelet::traffic_rules::TrafficRules & trafficRules, + const lanelet::ConstLaneletOrArea & from, const lanelet::ConstLaneletOrArea & to) const + { + if ( + (from.isLanelet() && RouteHandler::isNoDrivableLane(*from.lanelet())) || + (to.isLanelet() && RouteHandler::isNoDrivableLane(*to.lanelet()))) + return std::numeric_limits::infinity(); + return lanelet::routing::RoutingCostDistance::getCostSucceeding(trafficRules, from, to); + } + inline double getCostLaneChange( + const lanelet::traffic_rules::TrafficRules & trafficRules, const lanelet::ConstLanelets & from, + const lanelet::ConstLanelets & to) const noexcept + { + if ( + std::any_of(from.begin(), from.end(), RouteHandler::isNoDrivableLane) || + std::any_of(to.begin(), to.end(), RouteHandler::isNoDrivableLane)) + return std::numeric_limits::infinity(); + return lanelet::routing::RoutingCostDistance::getCostLaneChange(trafficRules, from, to); + } +}; // class RoutingCostDrivable } // namespace route_handler #endif // ROUTE_HANDLER__ROUTE_HANDLER_HPP_ diff --git a/planning/route_handler/package.xml b/planning/route_handler/package.xml index 60adfb1531104..22db01d833023 100644 --- a/planning/route_handler/package.xml +++ b/planning/route_handler/package.xml @@ -9,6 +9,8 @@ Kosuke Takeuchi Takayuki Murooka Mamoru Sobue + Go Sakayori + Apache License 2.0 Fumiya Watanabe diff --git a/planning/route_handler/src/route_handler.cpp b/planning/route_handler/src/route_handler.cpp index 76763821998bd..589a98d7d5ab4 100644 --- a/planning/route_handler/src/route_handler.cpp +++ b/planning/route_handler/src/route_handler.cpp @@ -157,8 +157,6 @@ void RouteHandler::setMap(const HADMapBin & map_msg) overall_graphs_ptr_ = std::make_shared(overall_graphs); lanelet::ConstLanelets all_lanelets = lanelet::utils::query::laneletLayer(lanelet_map_ptr_); - road_lanelets_ = lanelet::utils::query::roadLanelets(all_lanelets); - shoulder_lanelets_ = lanelet::utils::query::shoulderLanelets(all_lanelets); is_map_msg_ready_ = true; is_handler_ready_ = false; @@ -646,7 +644,7 @@ lanelet::ConstLanelets RouteHandler::getLaneletSequence( const lanelet::ConstLanelets lanelet_sequence_forward = std::invoke([&]() { if (only_route_lanes) { return getLaneletSequenceAfter(lanelet, forward_distance, only_route_lanes); - } else if (lanelet::utils::contains(shoulder_lanelets_, lanelet)) { + } else if (isShoulderLanelet(lanelet)) { return getShoulderLaneletSequenceAfter(lanelet, forward_distance); } return lanelet::ConstLanelets{}; @@ -656,7 +654,7 @@ lanelet::ConstLanelets RouteHandler::getLaneletSequence( if (arc_coordinate.length < backward_distance) { if (only_route_lanes) { return getLaneletSequenceUpTo(lanelet, backward_distance, only_route_lanes); - } else if (lanelet::utils::contains(shoulder_lanelets_, lanelet)) { + } else if (isShoulderLanelet(lanelet)) { return getShoulderLaneletSequenceUpTo(lanelet, backward_distance); } } @@ -712,110 +710,136 @@ lanelet::ConstLanelets RouteHandler::getLaneletSequence( return lanelet_sequence; } -bool RouteHandler::getFollowingShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * following_lanelet) const +lanelet::ConstLanelets RouteHandler::getRoadLaneletsAtPose(const Pose & pose) const { - for (const auto & shoulder_lanelet : shoulder_lanelets_) { - if (lanelet::geometry::follows(lanelet, shoulder_lanelet)) { - *following_lanelet = shoulder_lanelet; - return true; - } + lanelet::ConstLanelets road_lanelets_at_pose; + const lanelet::BasicPoint2d p{pose.position.x, pose.position.y}; + const auto lanelets_at_pose = lanelet_map_ptr_->laneletLayer.search(lanelet::BoundingBox2d(p)); + for (const auto & lanelet_at_pose : lanelets_at_pose) { + // confirm that the pose is inside the lanelet since "search" does an approximation with boxes + const auto is_pose_inside_lanelet = lanelet::geometry::inside(lanelet_at_pose, p); + if (is_pose_inside_lanelet && isRoadLanelet(lanelet_at_pose)) + road_lanelets_at_pose.push_back(lanelet_at_pose); } - return false; + return road_lanelets_at_pose; } -bool RouteHandler::getLeftShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * left_lanelet) const +std::optional RouteHandler::getFollowingShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const { - for (const auto & shoulder_lanelet : shoulder_lanelets_) { - if (lanelet::geometry::leftOf(shoulder_lanelet, lanelet)) { - *left_lanelet = shoulder_lanelet; - return true; - } + bool found = false; + const auto & search_point = lanelet.centerline().back().basicPoint2d(); + const auto next_lanelet = lanelet_map_ptr_->laneletLayer.nearestUntil( + search_point, [&](const auto & bbox, const auto & ll) { + if (isShoulderLanelet(ll) && lanelet::geometry::follows(lanelet, ll)) found = true; + // stop search once next shoulder lanelet is found, or the bbox does not touch the search + // point + return found || lanelet::geometry::distance2d(bbox, search_point) > 1e-3; + }); + if (found && next_lanelet.has_value()) return *next_lanelet; + return std::nullopt; +} + +std::optional RouteHandler::getLeftShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const +{ + for (const auto & other_lanelet : + lanelet_map_ptr_->laneletLayer.findUsages(lanelet.leftBound())) { + if (other_lanelet.rightBound() == lanelet.leftBound() && isShoulderLanelet(other_lanelet)) + return other_lanelet; } - return false; + return std::nullopt; } -bool RouteHandler::getRightShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * right_lanelet) const +std::optional RouteHandler::getRightShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const { - for (const auto & shoulder_lanelet : shoulder_lanelets_) { - if (lanelet::geometry::rightOf(shoulder_lanelet, lanelet)) { - *right_lanelet = shoulder_lanelet; - return true; - } + for (const auto & other_lanelet : + lanelet_map_ptr_->laneletLayer.findUsages(lanelet.rightBound())) { + if (other_lanelet.leftBound() == lanelet.rightBound() && isShoulderLanelet(other_lanelet)) + return other_lanelet; } - return false; + return std::nullopt; +} + +lanelet::ConstLanelets RouteHandler::getShoulderLaneletsAtPose(const Pose & pose) const +{ + lanelet::ConstLanelets lanelets_at_pose; + const lanelet::BasicPoint2d p{pose.position.x, pose.position.y}; + const auto candidates_at_pose = lanelet_map_ptr_->laneletLayer.search(lanelet::BoundingBox2d(p)); + for (const auto & candidate : candidates_at_pose) { + // confirm that the pose is inside the lanelet since "search" does an approximation with boxes + const auto is_pose_inside_lanelet = lanelet::geometry::inside(candidate, p); + if (is_pose_inside_lanelet && isShoulderLanelet(candidate)) + lanelets_at_pose.push_back(candidate); + } + return lanelets_at_pose; } lanelet::ConstLanelets RouteHandler::getShoulderLaneletSequenceAfter( const lanelet::ConstLanelet & lanelet, const double min_length) const { lanelet::ConstLanelets lanelet_sequence_forward; - if (!exists(shoulder_lanelets_, lanelet)) { - return lanelet_sequence_forward; - } + if (!isShoulderLanelet(lanelet)) return lanelet_sequence_forward; double length = 0; lanelet::ConstLanelet current_lanelet = lanelet; std::set searched_ids{}; while (rclcpp::ok() && length < min_length) { - lanelet::ConstLanelet next_lanelet; - if (!getFollowingShoulderLanelet(current_lanelet, &next_lanelet)) { - break; - } - lanelet_sequence_forward.push_back(next_lanelet); - if (searched_ids.find(next_lanelet.id()) != searched_ids.end()) { + const auto next_lanelet = getFollowingShoulderLanelet(current_lanelet); + if (!next_lanelet) break; + lanelet_sequence_forward.push_back(*next_lanelet); + if (searched_ids.find(next_lanelet->id()) != searched_ids.end()) { // loop shoulder detected break; } - searched_ids.insert(next_lanelet.id()); - current_lanelet = next_lanelet; + searched_ids.insert(next_lanelet->id()); + current_lanelet = *next_lanelet; length += - static_cast(boost::geometry::length(next_lanelet.centerline().basicLineString())); + static_cast(boost::geometry::length(next_lanelet->centerline().basicLineString())); } return lanelet_sequence_forward; } -bool RouteHandler::getPreviousShoulderLanelet( - const lanelet::ConstLanelet & lanelet, lanelet::ConstLanelet * prev_lanelet) const +std::optional RouteHandler::getPreviousShoulderLanelet( + const lanelet::ConstLanelet & lanelet) const { - for (const auto & shoulder_lanelet : shoulder_lanelets_) { - if (lanelet::geometry::follows(shoulder_lanelet, lanelet)) { - *prev_lanelet = shoulder_lanelet; - return true; - } - } - return false; + bool found = false; + const auto & search_point = lanelet.centerline().front().basicPoint2d(); + const auto previous_lanelet = lanelet_map_ptr_->laneletLayer.nearestUntil( + search_point, [&](const auto & bbox, const auto & ll) { + if (isShoulderLanelet(ll) && lanelet::geometry::follows(ll, lanelet)) found = true; + // stop search once prev shoulder lanelet is found, or the bbox does not touch the search + // point + return found || lanelet::geometry::distance2d(bbox, search_point) > 1e-3; + }); + if (found && previous_lanelet.has_value()) return *previous_lanelet; + return std::nullopt; } lanelet::ConstLanelets RouteHandler::getShoulderLaneletSequenceUpTo( const lanelet::ConstLanelet & lanelet, const double min_length) const { lanelet::ConstLanelets lanelet_sequence_backward; - if (!exists(shoulder_lanelets_, lanelet)) { - return lanelet_sequence_backward; - } + if (!isShoulderLanelet(lanelet)) return lanelet_sequence_backward; double length = 0; lanelet::ConstLanelet current_lanelet = lanelet; std::set searched_ids{}; while (rclcpp::ok() && length < min_length) { - lanelet::ConstLanelet prev_lanelet; - if (!getPreviousShoulderLanelet(current_lanelet, &prev_lanelet)) { - break; - } + const auto prev_lanelet = getPreviousShoulderLanelet(current_lanelet); + if (!prev_lanelet) break; - lanelet_sequence_backward.insert(lanelet_sequence_backward.begin(), prev_lanelet); - if (searched_ids.find(prev_lanelet.id()) != searched_ids.end()) { + lanelet_sequence_backward.insert(lanelet_sequence_backward.begin(), *prev_lanelet); + if (searched_ids.find(prev_lanelet->id()) != searched_ids.end()) { // loop shoulder detected break; } - searched_ids.insert(prev_lanelet.id()); - current_lanelet = prev_lanelet; + searched_ids.insert(prev_lanelet->id()); + current_lanelet = *prev_lanelet; length += - static_cast(boost::geometry::length(prev_lanelet.centerline().basicLineString())); + static_cast(boost::geometry::length(prev_lanelet->centerline().basicLineString())); } return lanelet_sequence_backward; @@ -826,7 +850,7 @@ lanelet::ConstLanelets RouteHandler::getShoulderLaneletSequence( const double forward_distance) const { lanelet::ConstLanelets lanelet_sequence; - if (!exists(shoulder_lanelets_, lanelet)) { + if (!isShoulderLanelet(lanelet)) { return lanelet_sequence; } @@ -1009,20 +1033,16 @@ std::optional RouteHandler::getRightLanelet( { // right road lanelet of shoulder lanelet if (isShoulderLanelet(lanelet)) { - for (const auto & road_lanelet : road_lanelets_) { - if (lanelet::geometry::rightOf(road_lanelet, lanelet)) { - return road_lanelet; - } - } + const auto right_lanelets = lanelet_map_ptr_->laneletLayer.findUsages(lanelet.rightBound()); + for (const auto & right_lanelet : right_lanelets) + if (isRoadLanelet(right_lanelet)) return right_lanelet; return std::nullopt; } // right shoulder lanelet if (get_shoulder_lane) { - lanelet::ConstLanelet right_shoulder_lanelet; - if (getRightShoulderLanelet(lanelet, &right_shoulder_lanelet)) { - return right_shoulder_lanelet; - } + const auto right_shoulder_lanelet = getRightShoulderLanelet(lanelet); + if (right_shoulder_lanelet) return *right_shoulder_lanelet; } // routable lane @@ -1090,20 +1110,16 @@ std::optional RouteHandler::getLeftLanelet( { // left road lanelet of shoulder lanelet if (isShoulderLanelet(lanelet)) { - for (const auto & road_lanelet : road_lanelets_) { - if (lanelet::geometry::leftOf(road_lanelet, lanelet)) { - return road_lanelet; - } - } + const auto left_lanelets = lanelet_map_ptr_->laneletLayer.findUsages(lanelet.leftBound()); + for (const auto & left_lanelet : left_lanelets) + if (isRoadLanelet(left_lanelet)) return left_lanelet; return std::nullopt; } // left shoulder lanelet if (get_shoulder_lane) { - lanelet::ConstLanelet left_shoulder_lanelet; - if (getLeftShoulderLanelet(lanelet, &left_shoulder_lanelet)) { - return left_shoulder_lanelet; - } + const auto left_shoulder_lanelet = getLeftShoulderLanelet(lanelet); + if (left_shoulder_lanelet) return *left_shoulder_lanelet; } // routable lane @@ -1510,39 +1526,33 @@ bool RouteHandler::getLeftLaneChangeTargetExceptPreferredLane( return false; } -bool RouteHandler::getPullOverTarget( - const lanelet::ConstLanelets & lanelets, const Pose & goal_pose, - lanelet::ConstLanelet * target_lanelet) +std::optional RouteHandler::getPullOverTarget(const Pose & goal_pose) const { - for (const auto & shoulder_lanelet : lanelets) { - if (lanelet::utils::isInLanelet(goal_pose, shoulder_lanelet, 0.1)) { - *target_lanelet = shoulder_lanelet; - return true; - } + const lanelet::BasicPoint2d p(goal_pose.position.x, goal_pose.position.y); + constexpr auto search_distance = 0.1; + const lanelet::BasicPoint2d offset(search_distance, search_distance); + const auto lanelets_in_range = + lanelet_map_ptr_->laneletLayer.search(lanelet::BoundingBox2d(p - offset, p + offset)); + for (const auto & lanelet : lanelets_in_range) { + const auto is_in_lanelet = lanelet::utils::isInLanelet(goal_pose, lanelet, search_distance); + if (is_in_lanelet && isShoulderLanelet(lanelet)) return lanelet; } - return false; + return std::nullopt; } -bool RouteHandler::getPullOutStartLane( - const lanelet::ConstLanelets & lanelets, const Pose & pose, const double vehicle_width, - lanelet::ConstLanelet * target_lanelet) +std::optional RouteHandler::getPullOutStartLane( + const Pose & pose, const double vehicle_width) const { - for (const auto & shoulder_lanelet : lanelets) { - if (lanelet::utils::isInLanelet(pose, shoulder_lanelet, vehicle_width / 2.0)) { - *target_lanelet = shoulder_lanelet; - return true; - } + const lanelet::BasicPoint2d p(pose.position.x, pose.position.y); + const auto search_distance = vehicle_width / 2.0; + const lanelet::BasicPoint2d offset(search_distance, search_distance); + const auto lanelets_in_range = + lanelet_map_ptr_->laneletLayer.search(lanelet::BoundingBox2d(p - offset, p + offset)); + for (const auto & lanelet : lanelets_in_range) { + const auto is_in_lanelet = lanelet::utils::isInLanelet(pose, lanelet, search_distance); + if (is_in_lanelet && isShoulderLanelet(lanelet)) return lanelet; } - return false; -} - -lanelet::ConstLanelets RouteHandler::getClosestLaneletSequence(const Pose & pose) const -{ - lanelet::ConstLanelet lanelet; - if (!getClosestLaneletWithinRoute(pose, &lanelet)) { - return lanelet::ConstLanelets{}; - } - return getLaneletSequence(lanelet); + return std::nullopt; } int RouteHandler::getNumLaneToPreferredLane( @@ -1933,14 +1943,10 @@ lanelet::routing::RelationType RouteHandler::getRelation( return lanelet::routing::RelationType::None; } -lanelet::ConstLanelets RouteHandler::getShoulderLanelets() const -{ - return shoulder_lanelets_; -} - bool RouteHandler::isShoulderLanelet(const lanelet::ConstLanelet & lanelet) const { - return lanelet::utils::contains(shoulder_lanelets_, lanelet); + return lanelet.hasAttribute(lanelet::AttributeName::Subtype) && + lanelet.attribute(lanelet::AttributeName::Subtype) == "road_shoulder"; } bool RouteHandler::isRouteLanelet(const lanelet::ConstLanelet & lanelet) const @@ -1948,6 +1954,12 @@ bool RouteHandler::isRouteLanelet(const lanelet::ConstLanelet & lanelet) const return lanelet::utils::contains(route_lanelets_, lanelet); } +bool RouteHandler::isRoadLanelet(const lanelet::ConstLanelet & lanelet) const +{ + return lanelet.hasAttribute(lanelet::AttributeName::Subtype) && + lanelet.attribute(lanelet::AttributeName::Subtype) == lanelet::AttributeValueString::Road; +} + lanelet::ConstLanelets RouteHandler::getPreviousLaneletSequence( const lanelet::ConstLanelets & lanelet_sequence) const { @@ -2120,28 +2132,47 @@ bool RouteHandler::planPathLaneletsBetweenCheckpoints( lanelet::ConstLanelets * path_lanelets, const bool consider_no_drivable_lanes) const { // Find lanelets for start point. First, find all lanelets containing the start point to calculate - // all possible route later. It fails when the point is not located on any road_lanelet (e.g. the + // all possible route later. It fails when the point is not located on any road lanelet (e.g. the // start point is located out of any lanelets or road_shoulder lanelet which is not contained in - // road_lanelet). In that case, find the closest lanelet instead. + // road lanelet). In that case, find the closest lanelet instead (within some maximum range). + constexpr auto max_search_range = 20.0; + auto start_lanelets = getRoadLaneletsAtPose(start_checkpoint); lanelet::ConstLanelet start_lanelet; - lanelet::ConstLanelets start_lanelets; - if (!lanelet::utils::query::getCurrentLanelets( - road_lanelets_, start_checkpoint, &start_lanelets)) { - if (!lanelet::utils::query::getClosestLanelet( - road_lanelets_, start_checkpoint, &start_lanelet)) { - RCLCPP_WARN_STREAM( - logger_, "Failed to find current lanelet." - << std::endl - << " - start checkpoint: " << toString(start_checkpoint) << std::endl - << " - goal checkpoint: " << toString(goal_checkpoint) << std::endl); - return false; - } - start_lanelets = {start_lanelet}; + if (start_lanelets.empty()) { + const lanelet::BasicPoint2d p(start_checkpoint.position.x, start_checkpoint.position.y); + const lanelet::BoundingBox2d bbox( + lanelet::BasicPoint2d(p.x() - max_search_range, p.y() - max_search_range), + lanelet::BasicPoint2d(p.x() + max_search_range, p.y() + max_search_range)); + // std::as_const(*ptr) to use the const version of the search function + auto candidates = std::as_const(*lanelet_map_ptr_).laneletLayer.search(bbox); + candidates.erase( + std::remove_if( + candidates.begin(), candidates.end(), [&](const auto & l) { return !isRoadLanelet(l); }), + candidates.end()); + if (lanelet::utils::query::getClosestLanelet(candidates, start_checkpoint, &start_lanelet)) + start_lanelets = {start_lanelet}; + } + if (start_lanelets.empty()) { + RCLCPP_WARN_STREAM( + logger_, "Failed to find current lanelet." + << std::endl + << " - start checkpoint: " << toString(start_checkpoint) << std::endl + << " - goal checkpoint: " << toString(goal_checkpoint) << std::endl); + return false; } // Find lanelets for goal point. lanelet::ConstLanelet goal_lanelet; - if (!lanelet::utils::query::getClosestLanelet(road_lanelets_, goal_checkpoint, &goal_lanelet)) { + const lanelet::BasicPoint2d p(goal_checkpoint.position.x, goal_checkpoint.position.y); + const lanelet::BoundingBox2d bbox( + lanelet::BasicPoint2d(p.x() - max_search_range, p.y() - max_search_range), + lanelet::BasicPoint2d(p.x() + max_search_range, p.y() + max_search_range)); + auto candidates = std::as_const(*lanelet_map_ptr_).laneletLayer.search(bbox); + candidates.erase( + std::remove_if( + candidates.begin(), candidates.end(), [&](const auto & l) { return !isRoadLanelet(l); }), + candidates.end()); + if (!lanelet::utils::query::getClosestLanelet(candidates, goal_checkpoint, &goal_lanelet)) { RCLCPP_WARN_STREAM( logger_, "Failed to find closest lanelet." << std::endl @@ -2189,14 +2220,11 @@ bool RouteHandler::planPathLaneletsBetweenCheckpoints( if (is_route_found) { lanelet::routing::LaneletPath path; path = [&]() -> lanelet::routing::LaneletPath { - if (!consider_no_drivable_lanes) return shortest_path; - lanelet::routing::LaneletPath drivable_lane_path; - bool drivable_lane_path_found = false; - if (hasNoDrivableLaneInPath(shortest_path)) { - drivable_lane_path_found = - findDrivableLanePath(start_lanelet, goal_lanelet, drivable_lane_path); + if (consider_no_drivable_lanes && hasNoDrivableLaneInPath(shortest_path)) { + const auto drivable_lane_path = findDrivableLanePath(start_lanelet, goal_lanelet); + if (drivable_lane_path) return *drivable_lane_path; } - return (drivable_lane_path_found) ? drivable_lane_path : shortest_path; + return shortest_path; }(); path_lanelets->reserve(path.size()); @@ -2248,49 +2276,28 @@ lanelet::ConstLanelets RouteHandler::getMainLanelets( return main_lanelets; } -bool RouteHandler::hasNoDrivableLaneInPath(const lanelet::routing::LaneletPath & path) const +bool RouteHandler::isNoDrivableLane(const lanelet::ConstLanelet & llt) { - for (const auto & llt : path) { - const std::string no_drivable_lane_attribute = llt.attributeOr("no_drivable_lane", "no"); - if (no_drivable_lane_attribute == "yes") { - return true; - } - } - - return false; + const std::string no_drivable_lane_attribute = llt.attributeOr("no_drivable_lane", "no"); + return no_drivable_lane_attribute == "yes"; } -bool RouteHandler::findDrivableLanePath( - const lanelet::ConstLanelet & start_lanelet, const lanelet::ConstLanelet & goal_lanelet, - lanelet::routing::LaneletPath & drivable_lane_path) const +bool RouteHandler::hasNoDrivableLaneInPath(const lanelet::routing::LaneletPath & path) const { - double drivable_lane_path_length2d = std::numeric_limits::max(); - bool drivable_lane_path_found = false; - - for (const auto & llt : road_lanelets_) { - lanelet::ConstLanelets via_lanelet; - via_lanelet.push_back(llt); - const lanelet::Optional optional_route = - routing_graph_ptr_->getRouteVia(start_lanelet, via_lanelet, goal_lanelet, 0); - - if ((optional_route) && (!hasNoDrivableLaneInPath(optional_route->shortestPath()))) { - if (optional_route->length2d() < drivable_lane_path_length2d) { - drivable_lane_path_length2d = optional_route->length2d(); - drivable_lane_path = optional_route->shortestPath(); - drivable_lane_path_found = true; - } - } - via_lanelet.clear(); - } - - return drivable_lane_path_found; + for (const auto & llt : path) + if (isNoDrivableLane(llt)) return true; + return false; } -lanelet::ConstLanelets RouteHandler::getClosestLanelets( - const geometry_msgs::msg::Pose & target_pose) const +std::optional RouteHandler::findDrivableLanePath( + const lanelet::ConstLanelet & start_lanelet, const lanelet::ConstLanelet & goal_lanelet) const { - lanelet::ConstLanelets target_lanelets; - lanelet::utils::query::getCurrentLanelets(road_lanelets_, target_pose, &target_lanelets); - return target_lanelets; + // we create a new routing graph with infinite cost on no drivable lanes + const auto drivable_routing_graph_ptr = lanelet::routing::RoutingGraph::build( + *lanelet_map_ptr_, *traffic_rules_ptr_, + lanelet::routing::RoutingCostPtrs{std::make_shared()}); + const auto route = drivable_routing_graph_ptr->getRoute(start_lanelet, goal_lanelet, 0); + if (route) return route->shortestPath(); + return {}; } } // namespace route_handler diff --git a/planning/rtc_interface/include/rtc_interface/rtc_interface.hpp b/planning/rtc_interface/include/rtc_interface/rtc_interface.hpp index aed7d42cda5e6..8d6e8c8fc1c7c 100644 --- a/planning/rtc_interface/include/rtc_interface/rtc_interface.hpp +++ b/planning/rtc_interface/include/rtc_interface/rtc_interface.hpp @@ -24,6 +24,7 @@ #include "tier4_rtc_msgs/msg/cooperate_status.hpp" #include "tier4_rtc_msgs/msg/cooperate_status_array.hpp" #include "tier4_rtc_msgs/msg/module.hpp" +#include "tier4_rtc_msgs/msg/state.hpp" #include "tier4_rtc_msgs/srv/auto_mode.hpp" #include "tier4_rtc_msgs/srv/cooperate_commands.hpp" #include @@ -41,6 +42,7 @@ using tier4_rtc_msgs::msg::CooperateResponse; using tier4_rtc_msgs::msg::CooperateStatus; using tier4_rtc_msgs::msg::CooperateStatusArray; using tier4_rtc_msgs::msg::Module; +using tier4_rtc_msgs::msg::State; using tier4_rtc_msgs::srv::AutoMode; using tier4_rtc_msgs::srv::CooperateCommands; using unique_identifier_msgs::msg::UUID; @@ -51,8 +53,8 @@ class RTCInterface RTCInterface(rclcpp::Node * node, const std::string & name, const bool enable_rtc = true); void publishCooperateStatus(const rclcpp::Time & stamp); void updateCooperateStatus( - const UUID & uuid, const bool safe, const double start_distance, const double finish_distance, - const rclcpp::Time & stamp); + const UUID & uuid, const bool safe, const uint8_t state, const double start_distance, + const double finish_distance, const rclcpp::Time & stamp); void removeCooperateStatus(const UUID & uuid); void clearCooperateStatus(); bool isActivated(const UUID & uuid) const; diff --git a/planning/rtc_interface/src/rtc_interface.cpp b/planning/rtc_interface/src/rtc_interface.cpp index a7661f4c419a5..c7afea57afce3 100644 --- a/planning/rtc_interface/src/rtc_interface.cpp +++ b/planning/rtc_interface/src/rtc_interface.cpp @@ -201,8 +201,8 @@ void RTCInterface::onTimer() } void RTCInterface::updateCooperateStatus( - const UUID & uuid, const bool safe, const double start_distance, const double finish_distance, - const rclcpp::Time & stamp) + const UUID & uuid, const bool safe, const uint8_t state, const double start_distance, + const double finish_distance, const rclcpp::Time & stamp) { std::lock_guard lock(mutex_); // Find registered status which has same uuid @@ -218,6 +218,7 @@ void RTCInterface::updateCooperateStatus( status.module = module_; status.safe = safe; status.command_status.type = Command::DEACTIVATE; + status.state.type = State::WAITING_FOR_EXECUTION; status.start_distance = start_distance; status.finish_distance = finish_distance; status.auto_mode = is_auto_mode_enabled_; @@ -228,6 +229,7 @@ void RTCInterface::updateCooperateStatus( // If the registered status is found, update status itr->stamp = stamp; itr->safe = safe; + itr->state.type = state; itr->start_distance = start_distance; itr->finish_distance = finish_distance; } diff --git a/planning/sampling_based_planner/path_sampler/include/path_sampler/node.hpp b/planning/sampling_based_planner/path_sampler/include/path_sampler/node.hpp index 50464f12114b0..ab9bc71bc79e4 100644 --- a/planning/sampling_based_planner/path_sampler/include/path_sampler/node.hpp +++ b/planning/sampling_based_planner/path_sampler/include/path_sampler/node.hpp @@ -95,7 +95,10 @@ class PathSampler : public rclcpp::Node void copyVelocity( const std::vector & from_traj, std::vector & to_traj, const geometry_msgs::msg::Pose & ego_pose); - std::vector generatePath(const PlannerData & planner_data); + sampler_common::Path generatePath(const PlannerData & planner_data); + std::vector generateCandidatesFromPreviousPath( + const PlannerData & planner_data, const sampler_common::transform::Spline2D & path_spline); + std::vector generateTrajectoryPoints(const PlannerData & planner_data); void publishVirtualWall(const geometry_msgs::msg::Pose & stop_pose) const; void publishDebugMarker(const std::vector & traj_points) const; }; diff --git a/planning/sampling_based_planner/path_sampler/include/path_sampler/parameters.hpp b/planning/sampling_based_planner/path_sampler/include/path_sampler/parameters.hpp index 1c5c51e33b431..03887d8357e0d 100644 --- a/planning/sampling_based_planner/path_sampler/include/path_sampler/parameters.hpp +++ b/planning/sampling_based_planner/path_sampler/include/path_sampler/parameters.hpp @@ -46,6 +46,12 @@ struct Parameters bool force_zero_heading{}; bool smooth_reference{}; } preprocessing{}; + + struct + { + double max_lat_dev{}; + double direct_reuse_dist{}; + } path_reuse{}; }; #endif // PATH_SAMPLER__PARAMETERS_HPP_ diff --git a/planning/sampling_based_planner/path_sampler/src/node.cpp b/planning/sampling_based_planner/path_sampler/src/node.cpp index 748486edf9ff6..97bafb68c47a8 100644 --- a/planning/sampling_based_planner/path_sampler/src/node.cpp +++ b/planning/sampling_based_planner/path_sampler/src/node.cpp @@ -84,12 +84,20 @@ PathSampler::PathSampler(const rclcpp::NodeOptions & node_options) declare_parameter("constraints.hard.max_curvature"); params_.constraints.hard.min_curvature = declare_parameter("constraints.hard.min_curvature"); + params_.constraints.hard.min_dist_from_obstacles = + declare_parameter("constraints.hard.min_distance_from_obstacles"); + params_.constraints.hard.limit_footprint_inside_drivable_area = + declare_parameter("constraints.hard.limit_footprint_inside_drivable_area"); params_.constraints.soft.lateral_deviation_weight = declare_parameter("constraints.soft.lateral_deviation_weight"); params_.constraints.soft.length_weight = declare_parameter("constraints.soft.length_weight"); params_.constraints.soft.curvature_weight = declare_parameter("constraints.soft.curvature_weight"); + params_.path_reuse.max_lat_dev = + declare_parameter("path_reuse.maximum_lateral_deviation"); + params_.path_reuse.direct_reuse_dist = + declare_parameter("path_reuse.direct_reuse_distance"); params_.sampling.enable_frenet = declare_parameter("sampling.enable_frenet"); params_.sampling.enable_bezier = declare_parameter("sampling.enable_bezier"); params_.sampling.resolution = declare_parameter("sampling.resolution"); @@ -144,6 +152,12 @@ rcl_interfaces::msg::SetParametersResult PathSampler::onParam( updateParam(parameters, "constraints.hard.max_curvature", params_.constraints.hard.max_curvature); updateParam(parameters, "constraints.hard.min_curvature", params_.constraints.hard.min_curvature); + updateParam( + parameters, "constraints.hard.min_distance_from_obstacles", + params_.constraints.hard.min_dist_from_obstacles); + updateParam( + parameters, "constraints.hard.limit_footprint_inside_drivable_area", + params_.constraints.hard.limit_footprint_inside_drivable_area); updateParam( parameters, "constraints.soft.lateral_deviation_weight", params_.constraints.soft.lateral_deviation_weight); @@ -243,9 +257,8 @@ void PathSampler::onPath(const Path::SharedPtr path_ptr) const auto generated_traj_points = generateTrajectory(planner_data); // 3. extend trajectory to connect the optimized trajectory and the following path smoothly if (!generated_traj_points.empty()) { - auto full_traj_points = extendTrajectory(planner_data.traj_points, generated_traj_points); const auto output_traj_msg = - motion_utils::convertToTrajectory(full_traj_points, path_ptr->header); + motion_utils::convertToTrajectory(generated_traj_points, path_ptr->header); traj_pub_->publish(output_traj_msg); } else { auto stopping_traj = trajectory_utils::convertToTrajectoryPoints(planner_data.traj_points); @@ -367,7 +380,7 @@ std::vector PathSampler::generateTrajectory(const PlannerData & const auto & input_traj_points = planner_data.traj_points; - auto generated_traj_points = generatePath(planner_data); + auto generated_traj_points = generateTrajectoryPoints(planner_data); copyVelocity(input_traj_points, generated_traj_points, planner_data.ego_pose); copyZ(input_traj_points, generated_traj_points); @@ -377,65 +390,89 @@ std::vector PathSampler::generateTrajectory(const PlannerData & return generated_traj_points; } -std::vector PathSampler::generatePath(const PlannerData & planner_data) +std::vector PathSampler::generateCandidatesFromPreviousPath( + const PlannerData & planner_data, const sampler_common::transform::Spline2D & path_spline) { - std::vector trajectory; - time_keeper_ptr_->tic(__func__); - const auto & p = planner_data; - - const auto path_spline = preparePathSpline(p.traj_points, params_.preprocessing.smooth_reference); + std::vector candidates; + if (!prev_path_ || prev_path_->points.size() < 2) return candidates; + // Update previous path sampler_common::State current_state; current_state.pose = {planner_data.ego_pose.position.x, planner_data.ego_pose.position.y}; current_state.heading = tf2::getYaw(planner_data.ego_pose.orientation); + const auto closest_iter = std::min_element( + prev_path_->points.begin(), prev_path_->points.end() - 1, + [&](const auto & p1, const auto & p2) { + return boost::geometry::distance(p1, current_state.pose) <= + boost::geometry::distance(p2, current_state.pose); + }); + if (closest_iter != prev_path_->points.end()) { + const auto current_idx = std::distance(prev_path_->points.begin(), closest_iter); + const auto length_offset = prev_path_->lengths[current_idx]; + for (auto & l : prev_path_->lengths) l -= length_offset; + constexpr auto behind_dist = -5.0; // [m] TODO(Maxime): param + auto behind_idx = current_idx; + while (behind_idx > 0 && prev_path_->lengths[behind_idx] > behind_dist) --behind_idx; + *prev_path_ = *prev_path_->subset(behind_idx, prev_path_->points.size()); + + // Use previous path for replanning + const auto prev_path_length = prev_path_->lengths.back(); + const auto reuse_step = prev_path_length / params_.sampling.previous_path_reuse_points_nb; + for (double reuse_length = reuse_step; reuse_length <= prev_path_length; + reuse_length += reuse_step) { + sampler_common::State reuse_state; + size_t reuse_idx = 0; + for (reuse_idx = 0; reuse_idx + 1 < prev_path_->lengths.size() && + prev_path_->lengths[reuse_idx] < reuse_length; + ++reuse_idx) + ; + if (reuse_idx == 0UL) continue; + const auto reused_path = *prev_path_->subset(0UL, reuse_idx); + reuse_state.curvature = reused_path.curvatures.back(); + reuse_state.pose = reused_path.points.back(); + reuse_state.heading = reused_path.yaws.back(); + reuse_state.frenet = path_spline.frenet(reuse_state.pose); + auto paths = generateCandidatePaths(reuse_state, path_spline, reuse_length, params_); + for (auto & p : paths) candidates.push_back(reused_path.extend(p)); + } + } + return candidates; +} - const auto planning_state = getPlanningState(current_state, path_spline); - prepareConstraints(params_.constraints, *in_objects_ptr_, p.left_bound, p.right_bound); - - auto candidate_paths = generateCandidatePaths(planning_state, path_spline, 0.0, params_); - if (prev_path_ && prev_path_->lengths.size() > 1) { - // Update previous path - constexpr auto max_deviation = 2.0; // [m] TODO(Maxime): param - const auto closest_iter = std::min_element( - prev_path_->points.begin(), prev_path_->points.end() - 1, - [&](const auto & p1, const auto & p2) { - return boost::geometry::distance(p1, current_state.pose) <= - boost::geometry::distance(p2, current_state.pose); - }); - if ( - closest_iter != prev_path_->points.end() && - boost::geometry::distance(*closest_iter, current_state.pose) <= max_deviation) { - const auto current_idx = std::distance(prev_path_->points.begin(), closest_iter); - const auto length_offset = prev_path_->lengths[current_idx]; - for (auto & l : prev_path_->lengths) l -= length_offset; - constexpr auto behind_dist = -5.0; // [m] TODO(Maxime): param - auto behind_idx = current_idx; - while (behind_idx > 0 && prev_path_->lengths[behind_idx] > behind_dist) --behind_idx; - *prev_path_ = *prev_path_->subset(behind_idx, prev_path_->points.size()); - - // Use previous path for replanning - const auto prev_path_length = prev_path_->lengths.back(); - const auto reuse_step = prev_path_length / params_.sampling.previous_path_reuse_points_nb; - for (double reuse_length = reuse_step; reuse_length <= prev_path_length; - reuse_length += reuse_step) { - sampler_common::State reuse_state; - size_t reuse_idx = 0; - for (reuse_idx = 0; reuse_idx + 1 < prev_path_->lengths.size() && - prev_path_->lengths[reuse_idx] < reuse_length; - ++reuse_idx) - ; - if (reuse_idx == 0UL) continue; - const auto reused_path = *prev_path_->subset(0UL, reuse_idx); - reuse_state.curvature = reused_path.curvatures.back(); - reuse_state.pose = reused_path.points.back(); - reuse_state.heading = reused_path.yaws.back(); - reuse_state.frenet = path_spline.frenet(reuse_state.pose); - auto paths = generateCandidatePaths(reuse_state, path_spline, reuse_length, params_); - for (auto & p : paths) candidate_paths.push_back(reused_path.extend(p)); - } +sampler_common::Path PathSampler::generatePath(const PlannerData & planner_data) +{ + time_keeper_ptr_->tic(__func__); + sampler_common::Path generated_path{}; + + if (prev_path_ && prev_path_->points.size() > 1) { + sampler_common::constraints::checkHardConstraints(*prev_path_, params_.constraints); + if (prev_path_->constraint_results.isValid()) { + const auto prev_path_spline = + preparePathSpline(trajectory_utils::convertToTrajectoryPoints(*prev_path_), false); + const auto frenet_p = prev_path_spline.frenet( + {planner_data.ego_pose.position.x, planner_data.ego_pose.position.y}); + if (std::abs(frenet_p.d) > params_.path_reuse.max_lat_dev || frenet_p.s < 0.0) + resetPreviousData(); + else if (frenet_p.s <= params_.path_reuse.direct_reuse_dist) + return *prev_path_; } else { resetPreviousData(); } } + const auto path_spline = + preparePathSpline(planner_data.traj_points, params_.preprocessing.smooth_reference); + sampler_common::State current_state; + current_state.pose = {planner_data.ego_pose.position.x, planner_data.ego_pose.position.y}; + current_state.heading = tf2::getYaw(planner_data.ego_pose.orientation); + + const auto planning_state = getPlanningState(current_state, path_spline); + prepareConstraints( + params_.constraints, *in_objects_ptr_, planner_data.left_bound, planner_data.right_bound); + + auto candidate_paths = generateCandidatePaths(planning_state, path_spline, 0.0, params_); + const auto candidates_from_prev_path = + generateCandidatesFromPreviousPath(planner_data, path_spline); + candidate_paths.insert( + candidate_paths.end(), candidates_from_prev_path.begin(), candidates_from_prev_path.end()); debug_data_.footprints.clear(); for (auto & path : candidate_paths) { const auto footprint = @@ -457,9 +494,7 @@ std::vector PathSampler::generatePath(const PlannerData & plann }; const auto selected_path_idx = best_path_idx(candidate_paths); if (selected_path_idx) { - const auto & selected_path = candidate_paths[*selected_path_idx]; - trajectory = trajectory_utils::convertToTrajectoryPoints(selected_path); - prev_path_ = selected_path; + generated_path = candidate_paths[*selected_path_idx]; } else { RCLCPP_WARN( get_logger(), "No valid path found (out of %lu) outputting %s\n", candidate_paths.size(), @@ -468,18 +503,28 @@ std::vector PathSampler::generatePath(const PlannerData & plann int da = 0; int k = 0; for (const auto & p : candidate_paths) { - coll += static_cast(!p.constraint_results.collision); - da += static_cast(!p.constraint_results.drivable_area); - k += static_cast(!p.constraint_results.curvature); + coll += static_cast(!p.constraint_results.collision_free); + da += static_cast(!p.constraint_results.inside_drivable_area); + k += static_cast(!p.constraint_results.valid_curvature); } RCLCPP_WARN(get_logger(), "\tInvalid coll/da/k = %d/%d/%d\n", coll, da, k); - if (prev_path_) trajectory = trajectory_utils::convertToTrajectoryPoints(*prev_path_); + if (prev_path_) generated_path = *prev_path_; } time_keeper_ptr_->toc(__func__, " "); debug_data_.previous_sampled_candidates_nb = debug_data_.sampled_candidates.size(); debug_data_.sampled_candidates = candidate_paths; debug_data_.obstacles = params_.constraints.obstacle_polygons; - return trajectory; + + prev_path_ = generated_path; + return generated_path; +} + +std::vector PathSampler::generateTrajectoryPoints(const PlannerData & planner_data) +{ + std::vector trajectory; + time_keeper_ptr_->tic(__func__); + const auto path = generatePath(planner_data); + return trajectory_utils::convertToTrajectoryPoints(path); } void PathSampler::publishVirtualWall(const geometry_msgs::msg::Pose & stop_pose) const diff --git a/planning/sampling_based_planner/sampler_common/include/sampler_common/constraints/hard_constraint.hpp b/planning/sampling_based_planner/sampler_common/include/sampler_common/constraints/hard_constraint.hpp index 652167ad94e75..a314e83b065d7 100644 --- a/planning/sampling_based_planner/sampler_common/include/sampler_common/constraints/hard_constraint.hpp +++ b/planning/sampling_based_planner/sampler_common/include/sampler_common/constraints/hard_constraint.hpp @@ -22,7 +22,9 @@ namespace sampler_common::constraints { /// @brief Check if the path satisfies the hard constraints MultiPoint2d checkHardConstraints(Path & path, const Constraints & constraints); -bool has_collision(const MultiPoint2d & footprint, const MultiPolygon2d & obstacles); +bool has_collision( + const MultiPoint2d & footprint, const MultiPolygon2d & obstacles, + const double min_distance = 0.0); bool satisfyMinMax(const std::vector & values, const double min, const double max); } // namespace sampler_common::constraints diff --git a/planning/sampling_based_planner/sampler_common/include/sampler_common/structures.hpp b/planning/sampling_based_planner/sampler_common/include/sampler_common/structures.hpp index 05c7fe47d79ef..cef791a01df44 100644 --- a/planning/sampling_based_planner/sampler_common/include/sampler_common/structures.hpp +++ b/planning/sampling_based_planner/sampler_common/include/sampler_common/structures.hpp @@ -50,13 +50,16 @@ typedef boost::geometry::index::rtree #include #include @@ -30,11 +31,12 @@ bool satisfyMinMax(const std::vector & values, const double min, const d return true; } -bool has_collision(const MultiPoint2d & footprint, const MultiPolygon2d & obstacles) +bool has_collision( + const MultiPoint2d & footprint, const MultiPolygon2d & obstacles, const double min_distance) { + if (footprint.empty()) return false; for (const auto & o : obstacles) - for (const auto & p : footprint) - if (boost::geometry::within(p, o)) return true; + if (boost::geometry::distance(o, footprint) <= min_distance) return true; return false; } @@ -42,14 +44,15 @@ MultiPoint2d checkHardConstraints(Path & path, const Constraints & constraints) { const auto footprint = buildFootprintPoints(path, constraints); if (!footprint.empty()) { - if (!boost::geometry::within(footprint, constraints.drivable_polygons)) { - path.constraint_results.drivable_area = false; - } + if (constraints.hard.limit_footprint_inside_drivable_area) + path.constraint_results.inside_drivable_area = + boost::geometry::within(footprint, constraints.drivable_polygons); + path.constraint_results.collision_free = !has_collision( + footprint, constraints.obstacle_polygons, constraints.hard.min_dist_from_obstacles); } - path.constraint_results.collision = !has_collision(footprint, constraints.obstacle_polygons); if (!satisfyMinMax( path.curvatures, constraints.hard.min_curvature, constraints.hard.max_curvature)) { - path.constraint_results.curvature = false; + path.constraint_results.valid_curvature = false; } return footprint; } diff --git a/planning/static_centerline_generator/src/static_centerline_generator_node.cpp b/planning/static_centerline_generator/src/static_centerline_generator_node.cpp index 750b2e68b16b0..ec24f47dacc27 100644 --- a/planning/static_centerline_generator/src/static_centerline_generator_node.cpp +++ b/planning/static_centerline_generator/src/static_centerline_generator_node.cpp @@ -304,8 +304,9 @@ CenterlineWithRoute StaticCenterlineGeneratorNode::generate_centerline_with_rout } else if (centerline_source_ == CenterlineSource::BagEgoTrajectoryBase) { const auto bag_centerline = generate_centerline_with_bag(*this); const auto start_lanelets = - route_handler_ptr_->getClosestLanelets(bag_centerline.front().pose); - const auto end_lanelets = route_handler_ptr_->getClosestLanelets(bag_centerline.back().pose); + route_handler_ptr_->getRoadLaneletsAtPose(bag_centerline.front().pose); + const auto end_lanelets = + route_handler_ptr_->getRoadLaneletsAtPose(bag_centerline.back().pose); if (start_lanelets.empty() || end_lanelets.empty()) { RCLCPP_ERROR(get_logger(), "Nearest lanelets to the bag's centerline are not found."); return CenterlineWithRoute{}; diff --git a/sensing/image_diagnostics/package.xml b/sensing/image_diagnostics/package.xml index ea57285e81aba..ceb1283b115a5 100644 --- a/sensing/image_diagnostics/package.xml +++ b/sensing/image_diagnostics/package.xml @@ -5,6 +5,7 @@ 0.1.0 The image_diagnostics_package Dai Nguyen + Yoshi Ri Apache License 2.0 Dai Nguyen diff --git a/sensing/image_transport_decompressor/package.xml b/sensing/image_transport_decompressor/package.xml index 264a8f249da3f..ed7ae7ae060b5 100644 --- a/sensing/image_transport_decompressor/package.xml +++ b/sensing/image_transport_decompressor/package.xml @@ -5,6 +5,7 @@ 0.0.0 The image_transport_decompressor package Yukihiro Saito + Kenzo Lobos-Tsunekawa Apache License 2.0 diff --git a/sensing/livox/livox_tag_filter/CMakeLists.txt b/sensing/livox/livox_tag_filter/CMakeLists.txt index 90b5eeed713c0..36c500aefa74d 100644 --- a/sensing/livox/livox_tag_filter/CMakeLists.txt +++ b/sensing/livox/livox_tag_filter/CMakeLists.txt @@ -21,4 +21,5 @@ rclcpp_components_register_node(livox_tag_filter ament_auto_package(INSTALL_TO_SHARE launch + config ) diff --git a/sensing/livox/livox_tag_filter/config/livox_tag_filter.param.yaml b/sensing/livox/livox_tag_filter/config/livox_tag_filter.param.yaml new file mode 100644 index 0000000000000..7b7e8cb5bd61a --- /dev/null +++ b/sensing/livox/livox_tag_filter/config/livox_tag_filter.param.yaml @@ -0,0 +1,19 @@ +/**: + ros__parameters: + ignore_tags: [] + # bit 0~1: Point property based on spatial position + # 00: Normal + # 01: High confidence level of the noise + # 10: Moderate confidence level of the noise + # 11: Low confidence level of the noise + # bit 2~3: Point property based on intensity + # 00: Normal + # 01: High confidence level of the noise + # 10: Moderate confidence level of the noise + # 11: Reserved + # bit 4~5: Return number + # 00: return 0 + # 01: return 1 + # 10: return 2 + # 11: return 3 + # bit 6~7: Reserved diff --git a/sensing/livox/livox_tag_filter/launch/livox_tag_filter.launch.xml b/sensing/livox/livox_tag_filter/launch/livox_tag_filter.launch.xml index 1da6c3074e7e7..331db891358f7 100644 --- a/sensing/livox/livox_tag_filter/launch/livox_tag_filter.launch.xml +++ b/sensing/livox/livox_tag_filter/launch/livox_tag_filter.launch.xml @@ -1,30 +1,11 @@ - - - + - + diff --git a/sensing/livox/livox_tag_filter/package.xml b/sensing/livox/livox_tag_filter/package.xml index 4fe994766027b..2b3d429480ef7 100644 --- a/sensing/livox/livox_tag_filter/package.xml +++ b/sensing/livox/livox_tag_filter/package.xml @@ -5,6 +5,7 @@ 0.1.0 The livox_tag_filter package Ryohsuke Mitsudome + Kenzo Lobos-Tsunekawa Apache License 2.0 ament_cmake_auto diff --git a/sensing/livox/livox_tag_filter/schema/livox_tag_filter.schema.json b/sensing/livox/livox_tag_filter/schema/livox_tag_filter.schema.json new file mode 100644 index 0000000000000..74d9881192258 --- /dev/null +++ b/sensing/livox/livox_tag_filter/schema/livox_tag_filter.schema.json @@ -0,0 +1,33 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "title": "Livox Tag Filter Parameters", + "type": "object", + "definitions": { + "livox_tag_filter": { + "type": "object", + "properties": { + "ignore_tags": { + "type": "array", + "description": "ignored tags (int array) (See the table in the readme file)", + "default": "[]" + } + }, + "required": ["ignore_tags"], + "additionalProperties": false + } + }, + "properties": { + "/**": { + "type": "object", + "properties": { + "ros__parameters": { + "$ref": "#/definitions/livox_tag_filter" + } + }, + "required": ["ros__parameters"], + "additionalProperties": false + } + }, + "required": ["/**"], + "additionalProperties": false +} diff --git a/sensing/livox/livox_tag_filter/src/livox_tag_filter_node/livox_tag_filter_node.cpp b/sensing/livox/livox_tag_filter/src/livox_tag_filter_node/livox_tag_filter_node.cpp index 2fd55ce8df6a0..f3216fdcd9b6a 100644 --- a/sensing/livox/livox_tag_filter/src/livox_tag_filter_node/livox_tag_filter_node.cpp +++ b/sensing/livox/livox_tag_filter/src/livox_tag_filter_node/livox_tag_filter_node.cpp @@ -40,7 +40,7 @@ LivoxTagFilterNode::LivoxTagFilterNode(const rclcpp::NodeOptions & node_options) : Node("livox_tag_filter", node_options) { // Parameter - ignore_tags_ = this->declare_parameter("ignore_tags", std::vector{}); + ignore_tags_ = this->declare_parameter>("ignore_tags"); // Subscriber using std::placeholders::_1; diff --git a/sensing/pointcloud_preprocessor/CMakeLists.txt b/sensing/pointcloud_preprocessor/CMakeLists.txt index 219f43e48730a..0cbb04345477e 100644 --- a/sensing/pointcloud_preprocessor/CMakeLists.txt +++ b/sensing/pointcloud_preprocessor/CMakeLists.txt @@ -65,6 +65,7 @@ ament_auto_add_library(pointcloud_preprocessor_filter SHARED src/downsample_filter/voxel_grid_downsample_filter_nodelet.cpp src/downsample_filter/random_downsample_filter_nodelet.cpp src/downsample_filter/approximate_downsample_filter_nodelet.cpp + src/downsample_filter/pickup_based_voxel_grid_downsample_filter.cpp src/outlier_filter/ring_outlier_filter_nodelet.cpp src/outlier_filter/voxel_grid_outlier_filter_nodelet.cpp src/outlier_filter/radius_search_2d_outlier_filter_nodelet.cpp @@ -114,6 +115,11 @@ rclcpp_components_register_node(pointcloud_preprocessor_filter PLUGIN "pointcloud_preprocessor::VoxelGridDownsampleFilterComponent" EXECUTABLE voxel_grid_downsample_filter_node) +# -- Pickup Based Voxel Grid Downsample Filter -- +rclcpp_components_register_node(pointcloud_preprocessor_filter + PLUGIN "pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent" + EXECUTABLE pickup_based_voxel_grid_downsample_filter_node) + # -- Random Downsample Filter -- rclcpp_components_register_node(pointcloud_preprocessor_filter PLUGIN "pointcloud_preprocessor::RandomDownsampleFilterComponent" @@ -214,7 +220,6 @@ ament_auto_package(INSTALL_TO_SHARE config ) - if(BUILD_TESTING) add_ros_test( test/test_distortion_corrector.py diff --git a/sensing/pointcloud_preprocessor/docs/downsample-filter.md b/sensing/pointcloud_preprocessor/docs/downsample-filter.md index 181cebb496cbf..25faf62b765bc 100644 --- a/sensing/pointcloud_preprocessor/docs/downsample-filter.md +++ b/sensing/pointcloud_preprocessor/docs/downsample-filter.md @@ -18,6 +18,10 @@ The `downsample_filter` is a node that reduces the number of points. `pcl::VoxelGrid` is used, which points in each voxel are approximated with their centroid. +### Pickup Based Voxel Grid Downsample Filter + +This algorithm samples a single actual point existing within the voxel, not the centroid. The computation cost is low compared to Centroid Based Voxel Grid Filter. + ## Inputs / Outputs These implementations inherit `pointcloud_preprocessor::Filter` class, please refer [README](../README.md). @@ -52,8 +56,20 @@ These implementations inherit `pointcloud_preprocessor::Filter` class, please re | `voxel_size_y` | double | 0.3 | voxel size y [m] | | `voxel_size_z` | double | 0.1 | voxel size z [m] | +### Pickup Based Voxel Grid Downsample Filter + +| Name | Type | Default Value | Description | +| -------------- | ------ | ------------- | ---------------- | +| `voxel_size_x` | double | 1.0 | voxel size x [m] | +| `voxel_size_y` | double | 1.0 | voxel size y [m] | +| `voxel_size_z` | double | 1.0 | voxel size z [m] | + ## Assumptions / Known limits + + +This implementation uses the `robin_hood.h` hashing library by martinus, available under the MIT License at [martinus/robin-hood-hashing](https://github.com/martinus/robin-hood-hashing) on GitHub. Special thanks to martinus for this contribution. + ## (Optional) Error detection and handling ## (Optional) Performance characterization diff --git a/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/faster_voxel_grid_downsample_filter.hpp b/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/faster_voxel_grid_downsample_filter.hpp index d92b511d40c69..d80e62d08330d 100644 --- a/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/faster_voxel_grid_downsample_filter.hpp +++ b/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/faster_voxel_grid_downsample_filter.hpp @@ -45,16 +45,22 @@ class FasterVoxelGridDownsampleFilter float x; float y; float z; + float intensity; uint32_t point_count_; - Centroid() : x(0), y(0), z(0) {} - Centroid(float _x, float _y, float _z) : x(_x), y(_y), z(_z) { this->point_count_ = 1; } + Centroid() : x(0), y(0), z(0), intensity(-1.0) {} + Centroid(float _x, float _y, float _z, float _intensity) + : x(_x), y(_y), z(_z), intensity(_intensity) + { + this->point_count_ = 1; + } - void add_point(float _x, float _y, float _z) + void add_point(float _x, float _y, float _z, float _intensity) { this->x += _x; this->y += _y; this->z += _z; + this->intensity += _intensity; this->point_count_++; } @@ -62,20 +68,20 @@ class FasterVoxelGridDownsampleFilter { Eigen::Vector4f centroid( (this->x / this->point_count_), (this->y / this->point_count_), - (this->z / this->point_count_), 1.0f); + (this->z / this->point_count_), (this->intensity / this->point_count_)); return centroid; } }; Eigen::Vector3f inverse_voxel_size_; - std::vector xyz_fields_; int x_offset_; int y_offset_; int z_offset_; + int intensity_index_; int intensity_offset_; bool offset_initialized_; - Eigen::Vector3f get_point_from_global_offset( + Eigen::Vector4f get_point_from_global_offset( const PointCloud2ConstPtr & input, size_t global_offset); bool get_min_max_voxel( diff --git a/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/pickup_based_voxel_grid_downsample_filter.hpp b/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/pickup_based_voxel_grid_downsample_filter.hpp new file mode 100644 index 0000000000000..a923473ecbe36 --- /dev/null +++ b/sensing/pointcloud_preprocessor/include/pointcloud_preprocessor/downsample_filter/pickup_based_voxel_grid_downsample_filter.hpp @@ -0,0 +1,64 @@ +// Copyright 2023 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef POINTCLOUD_PREPROCESSOR__DOWNSAMPLE_FILTER__PICKUP_BASED_VOXEL_GRID_DOWNSAMPLE_FILTER_HPP_ +#define POINTCLOUD_PREPROCESSOR__DOWNSAMPLE_FILTER__PICKUP_BASED_VOXEL_GRID_DOWNSAMPLE_FILTER_HPP_ + +#include "pointcloud_preprocessor/filter.hpp" + +#include + +#include +#include + +#include +#include +#include + +namespace pointcloud_preprocessor +{ +/** + * @class PickupBasedVoxelGridDownsampleFilterComponent + * @brief A filter component for downsampling point clouds using a voxel grid approach. + * + * This component reduces the number of points in a point cloud by grouping them into voxels + * and picking a representative point for each voxel. It's useful for reducing computational + * load when processing large point clouds. + */ +class PickupBasedVoxelGridDownsampleFilterComponent : public pointcloud_preprocessor::Filter +{ +protected: + void filter( + const PointCloud2ConstPtr & input, const IndicesPtr & indices, PointCloud2 & output) override; + +private: + float voxel_size_x_; ///< The size of the voxel in the x dimension. + float voxel_size_y_; ///< The size of the voxel in the y dimension. + float voxel_size_z_; ///< The size of the voxel in the z dimension. + + /** \brief Parameter service callback result : needed to be hold */ + OnSetParametersCallbackHandle::SharedPtr set_param_res_; + + /** \brief Parameter service callback */ + rcl_interfaces::msg::SetParametersResult paramCallback(const std::vector & p); + +public: + PCL_MAKE_ALIGNED_OPERATOR_NEW + explicit PickupBasedVoxelGridDownsampleFilterComponent(const rclcpp::NodeOptions & options); +}; +} // namespace pointcloud_preprocessor + +// clang-format off +#endif // POINTCLOUD_PREPROCESSOR__DOWNSAMPLE_FILTER__PICKUP_BASED_VOXEL_GRID_DOWNSAMPLE_FILTER_HPP_ // NOLINT +// clang-format on diff --git a/sensing/pointcloud_preprocessor/package.xml b/sensing/pointcloud_preprocessor/package.xml index 73f40cc4b44b0..9a1eae786c379 100644 --- a/sensing/pointcloud_preprocessor/package.xml +++ b/sensing/pointcloud_preprocessor/package.xml @@ -9,6 +9,9 @@ Shunsuke Miura Kyoichi Sugahara Dai Nguyen + Kenzo Lobos-Tsunekawa + Yihsiang Fang + Yoshi Ri Apache License 2.0 diff --git a/sensing/pointcloud_preprocessor/src/distortion_corrector/distortion_corrector.cpp b/sensing/pointcloud_preprocessor/src/distortion_corrector/distortion_corrector.cpp index d1d91ed7ec439..b90a64dc47c91 100644 --- a/sensing/pointcloud_preprocessor/src/distortion_corrector/distortion_corrector.cpp +++ b/sensing/pointcloud_preprocessor/src/distortion_corrector/distortion_corrector.cpp @@ -242,6 +242,16 @@ bool DistortionCorrectorComponent::undistortPointCloud( // For performance, avoid transform computation if unnecessary bool need_transform = points.header.frame_id != base_link_frame_; + // For performance, do not instantiate `rclcpp::Time` inside of the for-loop + double imu_stamp{0.0}; + if (use_imu_ && !angular_velocity_queue_.empty()) { + imu_stamp = rclcpp::Time(imu_it->header.stamp).seconds(); + } + + // If there is a point that cannot be associated, record it to issue a warning + bool twist_time_stamp_is_too_late = false; + bool imu_time_stamp_is_too_late = false; + for (; it_x != it_x.end(); ++it_x, ++it_y, ++it_z, ++it_time_stamp) { while (twist_it != std::end(twist_queue_) - 1 && *it_time_stamp > twist_stamp) { ++twist_it; @@ -252,32 +262,19 @@ bool DistortionCorrectorComponent::undistortPointCloud( float w{static_cast(twist_it->twist.angular.z)}; if (std::abs(*it_time_stamp - twist_stamp) > 0.1) { - RCLCPP_WARN_STREAM_THROTTLE( - get_logger(), *get_clock(), 10000 /* ms */, - "twist time_stamp is too late. Could not interpolate."); + twist_time_stamp_is_too_late = true; v = 0.0f; w = 0.0f; } if (use_imu_ && !angular_velocity_queue_.empty()) { - // For performance, do not instantiate `rclcpp::Time` inside of the for-loop - double imu_stamp = rclcpp::Time(imu_it->header.stamp).seconds(); - - for (; - (imu_it != std::end(angular_velocity_queue_) - 1 && - *it_time_stamp > rclcpp::Time(imu_it->header.stamp).seconds()); - ++imu_it) { - } - while (imu_it != std::end(angular_velocity_queue_) - 1 && *it_time_stamp > imu_stamp) { ++imu_it; imu_stamp = rclcpp::Time(imu_it->header.stamp).seconds(); } if (std::abs(*it_time_stamp - imu_stamp) > 0.1) { - RCLCPP_WARN_STREAM_THROTTLE( - get_logger(), *get_clock(), 10000 /* ms */, - "imu time_stamp is too late. Could not interpolate."); + imu_time_stamp_is_too_late = true; } else { w = static_cast(imu_it->vector.z); } @@ -314,6 +311,19 @@ bool DistortionCorrectorComponent::undistortPointCloud( prev_time_stamp_sec = *it_time_stamp; } + + if (twist_time_stamp_is_too_late) { + RCLCPP_WARN_STREAM_THROTTLE( + get_logger(), *get_clock(), 10000 /* ms */, + "twist time_stamp is too late. Could not interpolate."); + } + + if (imu_time_stamp_is_too_late) { + RCLCPP_WARN_STREAM_THROTTLE( + get_logger(), *get_clock(), 10000 /* ms */, + "imu time_stamp is too late. Could not interpolate."); + } + return true; } diff --git a/sensing/pointcloud_preprocessor/src/downsample_filter/faster_voxel_grid_downsample_filter.cpp b/sensing/pointcloud_preprocessor/src/downsample_filter/faster_voxel_grid_downsample_filter.cpp index 5829277335433..9c07a4ec47cba 100644 --- a/sensing/pointcloud_preprocessor/src/downsample_filter/faster_voxel_grid_downsample_filter.cpp +++ b/sensing/pointcloud_preprocessor/src/downsample_filter/faster_voxel_grid_downsample_filter.cpp @@ -19,8 +19,6 @@ namespace pointcloud_preprocessor FasterVoxelGridDownsampleFilter::FasterVoxelGridDownsampleFilter() { - pcl::for_each_type::type>( - pcl::detail::FieldAdder(xyz_fields_)); offset_initialized_ = false; } @@ -36,9 +34,9 @@ void FasterVoxelGridDownsampleFilter::set_field_offsets(const PointCloud2ConstPt x_offset_ = input->fields[pcl::getFieldIndex(*input, "x")].offset; y_offset_ = input->fields[pcl::getFieldIndex(*input, "y")].offset; z_offset_ = input->fields[pcl::getFieldIndex(*input, "z")].offset; - int intensity_index = pcl::getFieldIndex(*input, "intensity"); - if (intensity_index != -1) { - intensity_offset_ = input->fields[intensity_index].offset; + intensity_index_ = pcl::getFieldIndex(*input, "intensity"); + if (intensity_index_ != -1) { + intensity_offset_ = input->fields[intensity_index_].offset; } else { intensity_offset_ = z_offset_ + sizeof(float); } @@ -72,7 +70,7 @@ void FasterVoxelGridDownsampleFilter::filter( output.row_step = voxel_centroid_map.size() * input->point_step; output.data.resize(output.row_step); output.width = voxel_centroid_map.size(); - pcl_conversions::fromPCL(xyz_fields_, output.fields); + output.fields = input->fields; output.is_dense = true; // we filter out invalid points output.height = input->height; output.is_bigendian = input->is_bigendian; @@ -83,13 +81,19 @@ void FasterVoxelGridDownsampleFilter::filter( copy_centroids_to_output(voxel_centroid_map, output, transform_info); } -Eigen::Vector3f FasterVoxelGridDownsampleFilter::get_point_from_global_offset( +Eigen::Vector4f FasterVoxelGridDownsampleFilter::get_point_from_global_offset( const PointCloud2ConstPtr & input, size_t global_offset) { - Eigen::Vector3f point( + float intensity = 0.0; + if (intensity_index_ == -1) { + intensity = -1.0; + } else { + intensity = *reinterpret_cast(&input->data[global_offset + intensity_offset_]); + } + Eigen::Vector4f point( *reinterpret_cast(&input->data[global_offset + x_offset_]), *reinterpret_cast(&input->data[global_offset + y_offset_]), - *reinterpret_cast(&input->data[global_offset + z_offset_])); + *reinterpret_cast(&input->data[global_offset + z_offset_]), intensity); return point; } @@ -102,10 +106,10 @@ bool FasterVoxelGridDownsampleFilter::get_min_max_voxel( max_point.setConstant(-FLT_MAX); for (size_t global_offset = 0; global_offset + input->point_step <= input->data.size(); global_offset += input->point_step) { - Eigen::Vector3f point = get_point_from_global_offset(input, global_offset); + Eigen::Vector4f point = get_point_from_global_offset(input, global_offset); if (std::isfinite(point[0]) && std::isfinite(point[1]), std::isfinite(point[2])) { - min_point = min_point.cwiseMin(point); - max_point = max_point.cwiseMax(point); + min_point = min_point.cwiseMin(point.head<3>()); + max_point = max_point.cwiseMax(point.head<3>()); } } @@ -142,7 +146,7 @@ FasterVoxelGridDownsampleFilter::calc_centroids_each_voxel( for (size_t global_offset = 0; global_offset + input->point_step <= input->data.size(); global_offset += input->point_step) { - Eigen::Vector3f point = get_point_from_global_offset(input, global_offset); + Eigen::Vector4f point = get_point_from_global_offset(input, global_offset); if (std::isfinite(point[0]) && std::isfinite(point[1]), std::isfinite(point[2])) { // Calculate the voxel index to which the point belongs int ijk0 = static_cast(std::floor(point[0] * inverse_voxel_size_[0]) - min_voxel[0]); @@ -152,9 +156,9 @@ FasterVoxelGridDownsampleFilter::calc_centroids_each_voxel( // Add the point to the corresponding centroid if (voxel_centroid_map.find(voxel_id) == voxel_centroid_map.end()) { - voxel_centroid_map[voxel_id] = Centroid(point[0], point[1], point[2]); + voxel_centroid_map[voxel_id] = Centroid(point[0], point[1], point[2], point[3]); } else { - voxel_centroid_map[voxel_id].add_point(point[0], point[1], point[2]); + voxel_centroid_map[voxel_id].add_point(point[0], point[1], point[2], point[3]); } } } diff --git a/sensing/pointcloud_preprocessor/src/downsample_filter/pickup_based_voxel_grid_downsample_filter.cpp b/sensing/pointcloud_preprocessor/src/downsample_filter/pickup_based_voxel_grid_downsample_filter.cpp new file mode 100644 index 0000000000000..6393a935562ac --- /dev/null +++ b/sensing/pointcloud_preprocessor/src/downsample_filter/pickup_based_voxel_grid_downsample_filter.cpp @@ -0,0 +1,193 @@ +// Copyright 2024 TIER IV, Inc. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "pointcloud_preprocessor/downsample_filter/pickup_based_voxel_grid_downsample_filter.hpp" + +#include "robin_hood.h" + +namespace +{ +/** + * @brief Hash function for voxel keys. + * Utilizes prime numbers to calculate a unique hash for each voxel key. + */ +struct VoxelKeyHash +{ + std::size_t operator()(const std::array & k) const + { + // Primes based on the following paper: 'Investigating the Use of Primes in Hashing for + // Volumetric Data'. + return (k[0] * 73856093 ^ k[1] * 19349663 ^ k[2] * 83492791); + // In general, the performance of the search may be improved by restricting the hashkey to the + // following However, the risk of key collisions also increases, so the value must be + // appropriate. Enable the following code depending on the situation. return ((1 << 16) - 1) & + // (k[0] * 73856093 ^ k[1] * 19349663 ^ k[2] * 83492791); + } +}; + +/** + * @brief Equality function for voxel keys. + * Checks if two voxel keys are equal. + */ +struct VoxelKeyEqual +{ + bool operator()(const std::array & a, const std::array & b) const + { + return a == b; + } +}; +} // namespace + +namespace pointcloud_preprocessor +{ +PickupBasedVoxelGridDownsampleFilterComponent::PickupBasedVoxelGridDownsampleFilterComponent( + const rclcpp::NodeOptions & options) +: Filter("PickupBasedVoxelGridDownsampleFilterComponent", options) +{ + // initialize debug tool + { + using tier4_autoware_utils::DebugPublisher; + using tier4_autoware_utils::StopWatch; + stop_watch_ptr_ = std::make_unique>(); + debug_publisher_ = std::make_unique(this, this->get_name()); + stop_watch_ptr_->tic("cyclic_time"); + stop_watch_ptr_->tic("processing_time"); + } + + // Initialization of voxel sizes from parameters + voxel_size_x_ = static_cast(declare_parameter("voxel_size_x", 1.0)); + voxel_size_y_ = static_cast(declare_parameter("voxel_size_y", 1.0)); + voxel_size_z_ = static_cast(declare_parameter("voxel_size_z", 1.0)); + + using std::placeholders::_1; + set_param_res_ = this->add_on_set_parameters_callback( + std::bind(&PickupBasedVoxelGridDownsampleFilterComponent::paramCallback, this, _1)); +} + +void PickupBasedVoxelGridDownsampleFilterComponent::filter( + const PointCloud2ConstPtr & input, [[maybe_unused]] const IndicesPtr & indices, + PointCloud2 & output) +{ + std::scoped_lock lock(mutex_); + + stop_watch_ptr_->toc("processing_time", true); + + using VoxelKey = std::array; + // std::unordered_map voxel_map; + robin_hood::unordered_map voxel_map; + + voxel_map.reserve(input->data.size() / input->point_step); + + constexpr float large_num_offset = 100000.0; + const float inverse_voxel_size_x = 1.0 / voxel_size_x_; + const float inverse_voxel_size_y = 1.0 / voxel_size_y_; + const float inverse_voxel_size_z = 1.0 / voxel_size_z_; + + const int x_offset = input->fields[pcl::getFieldIndex(*input, "x")].offset; + const int y_offset = input->fields[pcl::getFieldIndex(*input, "y")].offset; + const int z_offset = input->fields[pcl::getFieldIndex(*input, "z")].offset; + + // Process each point in the point cloud + for (size_t global_offset = 0; global_offset + input->point_step <= input->data.size(); + global_offset += input->point_step) { + const float & x = *reinterpret_cast(&input->data[global_offset + x_offset]); + const float & y = *reinterpret_cast(&input->data[global_offset + y_offset]); + const float & z = *reinterpret_cast(&input->data[global_offset + z_offset]); + + // The reason for adding a large value is that when converting from float to int, values around + // -1 to 1 are all rounded down to 0. Therefore, to prevent the numbers from becoming negative, + // a large value is added. It has been tuned to reduce computational costs, and deliberately + // avoids using round or floor functions. + VoxelKey key = { + static_cast((x + large_num_offset) * inverse_voxel_size_x), + static_cast((y + large_num_offset) * inverse_voxel_size_y), + static_cast((z + large_num_offset) * inverse_voxel_size_z)}; + + voxel_map.emplace(key, global_offset); + } + + // Populate the output point cloud + size_t output_global_offset = 0; + output.data.resize(voxel_map.size() * input->point_step); + for (const auto & kv : voxel_map) { + std::memcpy( + &output.data[output_global_offset + x_offset], &input->data[kv.second + x_offset], + sizeof(float)); + std::memcpy( + &output.data[output_global_offset + y_offset], &input->data[kv.second + y_offset], + sizeof(float)); + std::memcpy( + &output.data[output_global_offset + z_offset], &input->data[kv.second + z_offset], + sizeof(float)); + output_global_offset += input->point_step; + } + + // Set the output point cloud metadata + output.header.frame_id = input->header.frame_id; + output.height = 1; + output.fields = input->fields; + output.is_bigendian = input->is_bigendian; + output.point_step = input->point_step; + output.is_dense = input->is_dense; + output.width = static_cast(output.data.size() / output.height / output.point_step); + output.row_step = static_cast(output.data.size() / output.height); + + // add processing time for debug + if (debug_publisher_) { + const double cyclic_time_ms = stop_watch_ptr_->toc("cyclic_time", true); + const double processing_time_ms = stop_watch_ptr_->toc("processing_time", true); + debug_publisher_->publish( + "debug/cyclic_time_ms", cyclic_time_ms); + debug_publisher_->publish( + "debug/processing_time_ms", processing_time_ms); + + auto pipeline_latency_ms = + std::chrono::duration( + std::chrono::nanoseconds((this->get_clock()->now() - input->header.stamp).nanoseconds())) + .count(); + + debug_publisher_->publish( + "debug/pipeline_latency_ms", pipeline_latency_ms); + } +} + +rcl_interfaces::msg::SetParametersResult +PickupBasedVoxelGridDownsampleFilterComponent::paramCallback( + const std::vector & p) +{ + std::scoped_lock lock(mutex_); + + // Handling dynamic updates for the voxel sizes + if (get_param(p, "voxel_size_x", voxel_size_x_)) { + RCLCPP_DEBUG(get_logger(), "Setting new distance threshold to: %f.", voxel_size_x_); + } + if (get_param(p, "voxel_size_y", voxel_size_y_)) { + RCLCPP_DEBUG(get_logger(), "Setting new distance threshold to: %f.", voxel_size_y_); + } + if (get_param(p, "voxel_size_z", voxel_size_z_)) { + RCLCPP_DEBUG(get_logger(), "Setting new distance threshold to: %f.", voxel_size_z_); + } + + rcl_interfaces::msg::SetParametersResult result; + result.successful = true; + result.reason = "success"; + + return result; +} + +} // namespace pointcloud_preprocessor + +#include +RCLCPP_COMPONENTS_REGISTER_NODE( + pointcloud_preprocessor::PickupBasedVoxelGridDownsampleFilterComponent) diff --git a/sensing/pointcloud_preprocessor/src/downsample_filter/robin_hood.h b/sensing/pointcloud_preprocessor/src/downsample_filter/robin_hood.h new file mode 100644 index 0000000000000..02fa183e5d017 --- /dev/null +++ b/sensing/pointcloud_preprocessor/src/downsample_filter/robin_hood.h @@ -0,0 +1,2748 @@ +// Copyright (c) 2018-2021 Martin Ankerl +// ______ _____ ______ _________ +// ______________ ___ /_ ___(_)_______ ___ /_ ______ ______ ______ / +// __ ___/_ __ \__ __ \__ / __ __ \ __ __ \_ __ \_ __ \_ __ / +// _ / / /_/ /_ /_/ /_ / _ / / / _ / / // /_/ // /_/ // /_/ / +// /_/ \____/ /_.___/ /_/ /_/ /_/ ________/_/ /_/ \____/ \____/ \__,_/ +// _/_____/ +// +// Fast & memory efficient hashtable based on robin hood hashing for C++11/14/17/20 +// https://github.com/martinus/robin-hood-hashing +// +// Licensed under the MIT License . +// SPDX-License-Identifier: MIT +// Copyright (c) 2018-2021 Martin Ankerl +// +// Permission is hereby granted, free of charge, to any person obtaining a copy +// of this software and associated documentation files (the "Software"), to deal +// in the Software without restriction, including without limitation the rights +// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +// copies of the Software, and to permit persons to whom the Software is +// furnished to do so, subject to the following conditions: +// +// The above copyright notice and this permission notice shall be included in all +// copies or substantial portions of the Software. +// +// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +// SOFTWARE. + +// clang-format off +// (because it messes up the whole file and this is a external file) + +// cspell: ignore _CPPUNWIND +// cspell: ignore BITSCANFORWARD +// cspell: ignore clzl +// cspell: ignore ctzll +// cspell: ignore clzll +// cspell: ignore WCHART +// cspell: ignore Inds +// cspell: ignore inlinings +// cspell: ignore murmurhash +// cspell: ignore Wuseless +// cspell: ignore martinus +// cspell: ignore keyval +// cspell: ignore initlist +// cspell: ignore ilist +// cspell: ignore nonheap + +#ifndef DOWNSAMPLE_FILTER__ROBIN_HOOD_H_ +#define DOWNSAMPLE_FILTER__ROBIN_HOOD_H_ + +// see https://semver.org/ +#define ROBIN_HOOD_VERSION_MAJOR 3 // for incompatible API changes +#define ROBIN_HOOD_VERSION_MINOR 11 // for adding functionality in a backwards-compatible manner +#define ROBIN_HOOD_VERSION_PATCH 5 // for backwards-compatible bug fixes + +#include +#include +#include +#include +#include +#include // only to support hash of smart pointers +#include +#include +#include +#include +#if __cplusplus >= 201703L +#include +#endif + +// #define ROBIN_HOOD_LOG_ENABLED +#ifdef ROBIN_HOOD_LOG_ENABLED +#include +#define ROBIN_HOOD_LOG(...) \ + std::cout << __FUNCTION__ << "@" << __LINE__ << ": " << __VA_ARGS__ << std::endl; +#else +#define ROBIN_HOOD_LOG(x) +#endif + +// #define ROBIN_HOOD_TRACE_ENABLED +#ifdef ROBIN_HOOD_TRACE_ENABLED +#include +#define ROBIN_HOOD_TRACE(...) \ + std::cout << __FUNCTION__ << "@" << __LINE__ << ": " << __VA_ARGS__ << std::endl; +#else +#define ROBIN_HOOD_TRACE(x) +#endif + +// #define ROBIN_HOOD_COUNT_ENABLED +#ifdef ROBIN_HOOD_COUNT_ENABLED +#include +#define ROBIN_HOOD_COUNT(x) ++counts().x; +namespace robin_hood +{ +struct Counts +{ + uint64_t shiftUp{}; + uint64_t shiftDown{}; +}; +inline std::ostream & operator<<(std::ostream & os, Counts const & c) +{ + return os << c.shiftUp << " shiftUp" << std::endl << c.shiftDown << " shiftDown" << std::endl; +} + +static Counts & counts() +{ + static Counts counts{}; + return counts; +} +} // namespace robin_hood +#else +#define ROBIN_HOOD_COUNT(x) +#endif + +// all non-argument macros should use this facility. See +// https://www.fluentcpp.com/2019/05/28/better-macros-better-flags/ +#define ROBIN_HOOD(x) ROBIN_HOOD_PRIVATE_DEFINITION_##x() + +// mark unused members with this macro +#define ROBIN_HOOD_UNUSED(identifier) + +// bitness +#if SIZE_MAX == UINT32_MAX +#define ROBIN_HOOD_PRIVATE_DEFINITION_BITNESS() 32 +#elif SIZE_MAX == UINT64_MAX +#define ROBIN_HOOD_PRIVATE_DEFINITION_BITNESS() 64 +#else +#error Unsupported bitness +#endif + +// endianess +#ifdef _MSC_VER +#define ROBIN_HOOD_PRIVATE_DEFINITION_LITTLE_ENDIAN() 1 +#define ROBIN_HOOD_PRIVATE_DEFINITION_BIG_ENDIAN() 0 +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_LITTLE_ENDIAN() (__BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__) +#define ROBIN_HOOD_PRIVATE_DEFINITION_BIG_ENDIAN() (__BYTE_ORDER__ == __ORDER_BIG_ENDIAN__) +#endif + +// inline +#ifdef _MSC_VER +#define ROBIN_HOOD_PRIVATE_DEFINITION_NOINLINE() __declspec(noinline) +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_NOINLINE() __attribute__((noinline)) +#endif + +// exceptions +#if !defined(__cpp_exceptions) && !defined(__EXCEPTIONS) && !defined(_CPPUNWIND) +#define ROBIN_HOOD_PRIVATE_DEFINITION_HAS_EXCEPTIONS() 0 +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_HAS_EXCEPTIONS() 1 +#endif + +// count leading/trailing bits +#if !defined(ROBIN_HOOD_DISABLE_INTRINSICS) +#ifdef _MSC_VER +#if ROBIN_HOOD(BITNESS) == 32 +#define ROBIN_HOOD_PRIVATE_DEFINITION_BITSCANFORWARD() _BitScanForward +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_BITSCANFORWARD() _BitScanForward64 +#endif +#include +#pragma intrinsic(ROBIN_HOOD(BITSCANFORWARD)) +#define ROBIN_HOOD_COUNT_TRAILING_ZEROES(x) \ + [](size_t mask) noexcept -> int { \ + unsigned long index; \ // NOLINT + return ROBIN_HOOD(BITSCANFORWARD)(&index, mask) ? static_cast(index) \ + : ROBIN_HOOD(BITNESS); \ + }(x) +#else +#if ROBIN_HOOD(BITNESS) == 32 +#define ROBIN_HOOD_PRIVATE_DEFINITION_CTZ() __builtin_ctzl +#define ROBIN_HOOD_PRIVATE_DEFINITION_CLZ() __builtin_clzl +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_CTZ() __builtin_ctzll +#define ROBIN_HOOD_PRIVATE_DEFINITION_CLZ() __builtin_clzll +#endif +#define ROBIN_HOOD_COUNT_LEADING_ZEROES(x) ((x) ? ROBIN_HOOD(CLZ)(x) : ROBIN_HOOD(BITNESS)) +#define ROBIN_HOOD_COUNT_TRAILING_ZEROES(x) ((x) ? ROBIN_HOOD(CTZ)(x) : ROBIN_HOOD(BITNESS)) +#endif +#endif + +// fallthrough +#ifndef __has_cpp_attribute // For backwards compatibility +#define __has_cpp_attribute(x) 0 +#endif +#if __has_cpp_attribute(clang::fallthrough) +#define ROBIN_HOOD_PRIVATE_DEFINITION_FALLTHROUGH() [[clang::fallthrough]] +#elif __has_cpp_attribute(gnu::fallthrough) +#define ROBIN_HOOD_PRIVATE_DEFINITION_FALLTHROUGH() [[gnu::fallthrough]] +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_FALLTHROUGH() +#endif + +// likely/unlikely +#ifdef _MSC_VER +#define ROBIN_HOOD_LIKELY(condition) condition +#define ROBIN_HOOD_UNLIKELY(condition) condition +#else +#define ROBIN_HOOD_LIKELY(condition) __builtin_expect(condition, 1) +#define ROBIN_HOOD_UNLIKELY(condition) __builtin_expect(condition, 0) +#endif + +// detect if native wchar_t type is available in MSVC +#ifdef _MSC_VER +#ifdef _NATIVE_WCHAR_T_DEFINED +#define ROBIN_HOOD_PRIVATE_DEFINITION_HAS_NATIVE_WCHART() 1 +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_HAS_NATIVE_WCHART() 0 +#endif +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_HAS_NATIVE_WCHART() 1 +#endif + +// detect if MSVC supports the pair(std::piecewise_construct_t,...) constructor being constexpr +#ifdef _MSC_VER +#if _MSC_VER <= 1900 +#define ROBIN_HOOD_PRIVATE_DEFINITION_BROKEN_CONSTEXPR() 1 +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_BROKEN_CONSTEXPR() 0 +#endif +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_BROKEN_CONSTEXPR() 0 +#endif + +// workaround missing "is_trivially_copyable" in g++ < 5.0 +// See https://stackoverflow.com/a/31798726/48181 +#if defined(__GNUC__) && __GNUC__ < 5 +#define ROBIN_HOOD_IS_TRIVIALLY_COPYABLE(...) __has_trivial_copy(__VA_ARGS__) +#else +#define ROBIN_HOOD_IS_TRIVIALLY_COPYABLE(...) std::is_trivially_copyable<__VA_ARGS__>::value +#endif + +// helpers for C++ versions, see https://gcc.gnu.org/onlinedocs/cpp/Standard-Predefined-Macros.html +#define ROBIN_HOOD_PRIVATE_DEFINITION_CXX() __cplusplus +#define ROBIN_HOOD_PRIVATE_DEFINITION_CXX98() 199711L +#define ROBIN_HOOD_PRIVATE_DEFINITION_CXX11() 201103L +#define ROBIN_HOOD_PRIVATE_DEFINITION_CXX14() 201402L +#define ROBIN_HOOD_PRIVATE_DEFINITION_CXX17() 201703L + +#if ROBIN_HOOD(CXX) >= ROBIN_HOOD(CXX17) +#define ROBIN_HOOD_PRIVATE_DEFINITION_NODISCARD() [[nodiscard]] +#else +#define ROBIN_HOOD_PRIVATE_DEFINITION_NODISCARD() +#endif + +namespace robin_hood +{ + +#if ROBIN_HOOD(CXX) >= ROBIN_HOOD(CXX14) +#define ROBIN_HOOD_STD std +#else + +// c++11 compatibility layer +namespace ROBIN_HOOD_STD +{ +template +struct alignment_of +: std::integral_constant::type)> +{ +}; + +template +class integer_sequence +{ +public: + using value_type = T; + static_assert(std::is_integral::value, "not integral type"); + static constexpr std::size_t size() noexcept { return sizeof...(Ints); } +}; +template +using index_sequence = integer_sequence; + +namespace detail_ +{ +template +struct IntSeqImpl +{ + using TValue = T; + static_assert(std::is_integral::value, "not integral type"); + static_assert(Begin >= 0 && Begin < End, "unexpected argument (Begin<0 || Begin<=End)"); + + template + struct IntSeqCombiner; + + template + struct IntSeqCombiner, integer_sequence> + { + using TResult = integer_sequence; + }; + + using TResult = typename IntSeqCombiner< + typename IntSeqImpl::TResult, + typename IntSeqImpl< + TValue, Begin + (End - Begin) / 2, End, (End - Begin + 1) / 2 == 1>::TResult>::TResult; +}; + +template +struct IntSeqImpl +{ + using TValue = T; + static_assert(std::is_integral::value, "not integral type"); + static_assert(Begin >= 0, "unexpected argument (Begin<0)"); + using TResult = integer_sequence; +}; + +template +struct IntSeqImpl +{ + using TValue = T; + static_assert(std::is_integral::value, "not integral type"); + static_assert(Begin >= 0, "unexpected argument (Begin<0)"); + using TResult = integer_sequence; +}; +} // namespace detail_ + +template +using make_integer_sequence = typename detail_::IntSeqImpl::TResult; + +template +using make_index_sequence = make_integer_sequence; + +template +using index_sequence_for = make_index_sequence; + +} // namespace ROBIN_HOOD_STD + +#endif + +namespace detail +{ + +// make sure we static_cast to the correct type for hash_int +#if ROBIN_HOOD(BITNESS) == 64 +using SizeT = uint64_t; +#else +using SizeT = uint32_t; +#endif + +template +T rotr(T x, unsigned k) +{ + return (x >> k) | (x << (8U * sizeof(T) - k)); +} + +// This cast gets rid of warnings like "cast from 'uint8_t*' {aka 'unsigned char*'} to +// 'uint64_t*' {aka 'long unsigned int*'} increases required alignment of target type". Use with +// care! +template +inline T reinterpret_cast_no_cast_align_warning(void * ptr) noexcept +{ + return reinterpret_cast(ptr); +} + +template +inline T reinterpret_cast_no_cast_align_warning(void const * ptr) noexcept +{ + return reinterpret_cast(ptr); +} + +// make sure this is not inlined as it is slow and dramatically enlarges code, thus making other +// inlinings more difficult. Throws are also generally the slow path. +template +[[noreturn]] ROBIN_HOOD(NOINLINE) +#if ROBIN_HOOD(HAS_EXCEPTIONS) + void doThrow(Args &&... args) +{ + // NOLINTNEXTLINE (cppcoreguidelines-pro-bounds-array-to-pointer-decay) + throw E(std::forward(args)...); +} +#else + void doThrow(Args &&... ROBIN_HOOD_UNUSED(args) /*unused*/) +{ + abort(); +} +#endif + +template +T * assertNotNull(T * t, Args &&... args) +{ + if (ROBIN_HOOD_UNLIKELY(nullptr == t)) { + doThrow(std::forward(args)...); + } + return t; +} + +template +inline T unaligned_load(void const * ptr) noexcept +{ + // using memcpy so we don't get into unaligned load problems. + // compiler should optimize this very well anyways. + T t; + std::memcpy(&t, ptr, sizeof(T)); + return t; +} + +// Allocates bulks of memory for objects of type T. This deallocates the memory in the destructor, +// and keeps a linked list of the allocated memory around. Overhead per allocation is the size of a +// pointer. +template +class BulkPoolAllocator +{ +public: + BulkPoolAllocator() noexcept = default; + + // does not copy anything, just creates a new allocator. + BulkPoolAllocator(const BulkPoolAllocator & ROBIN_HOOD_UNUSED(o) /*unused*/) noexcept + : mHead(nullptr), mListForFree(nullptr) + { + } + + BulkPoolAllocator(BulkPoolAllocator && o) noexcept : mHead(o.mHead), mListForFree(o.mListForFree) + { + o.mListForFree = nullptr; + o.mHead = nullptr; + } + + BulkPoolAllocator & operator=(BulkPoolAllocator && o) noexcept + { + reset(); + mHead = o.mHead; + mListForFree = o.mListForFree; + o.mListForFree = nullptr; + o.mHead = nullptr; + return *this; + } + + BulkPoolAllocator & + // NOLINTNEXTLINE (bugprone-unhandled-self-assignment,cert-oop54-cpp) + operator=(const BulkPoolAllocator & ROBIN_HOOD_UNUSED(o) /*unused*/) noexcept + { + // does not do anything + return *this; + } + + ~BulkPoolAllocator() noexcept { reset(); } + + // Deallocates all allocated memory. + void reset() noexcept + { + while (mListForFree) { + T * tmp = *mListForFree; + ROBIN_HOOD_LOG("std::free") + std::free(mListForFree); + mListForFree = reinterpret_cast_no_cast_align_warning(tmp); + } + mHead = nullptr; + } + + // allocates, but does NOT initialize. Use in-place new constructor, e.g. + // T* obj = pool.allocate(); + // ::new (static_cast(obj)) T(); + T * allocate() + { + T * tmp = mHead; + if (!tmp) { + tmp = performAllocation(); + } + + mHead = *reinterpret_cast_no_cast_align_warning(tmp); + return tmp; + } + + // does not actually deallocate but puts it in store. + // make sure you have already called the destructor! e.g. with + // obj->~T(); + // pool.deallocate(obj); + void deallocate(T * obj) noexcept + { + *reinterpret_cast_no_cast_align_warning(obj) = mHead; + mHead = obj; + } + + // Adds an already allocated block of memory to the allocator. This allocator is from now on + // responsible for freeing the data (with free()). If the provided data is not large enough to + // make use of, it is immediately freed. Otherwise it is reused and freed in the destructor. + void addOrFree(void * ptr, const size_t numBytes) noexcept + { + // calculate number of available elements in ptr + if (numBytes < ALIGNMENT + ALIGNED_SIZE) { + // not enough data for at least one element. Free and return. + ROBIN_HOOD_LOG("std::free") + std::free(ptr); + } else { + ROBIN_HOOD_LOG("add to buffer") + add(ptr, numBytes); + } + } + + void swap(BulkPoolAllocator & other) noexcept + { + using std::swap; + swap(mHead, other.mHead); + swap(mListForFree, other.mListForFree); + } + +private: + // iterates the list of allocated memory to calculate how many to alloc next. + // Recalculating this each time saves us a size_t member. + // This ignores the fact that memory blocks might have been added manually with addOrFree. In + // practice, this should not matter much. + ROBIN_HOOD(NODISCARD) size_t calcNumElementsToAlloc() const noexcept + { + auto tmp = mListForFree; + size_t numAllocs = MinNumAllocs; + + while (numAllocs * 2 <= MaxNumAllocs && tmp) { + auto x = reinterpret_cast(tmp); + tmp = *x; + numAllocs *= 2; + } + + return numAllocs; + } + + // WARNING: Underflow if numBytes < ALIGNMENT! This is guarded in addOrFree(). + void add(void * ptr, const size_t numBytes) noexcept + { + const size_t numElements = (numBytes - ALIGNMENT) / ALIGNED_SIZE; + + auto data = reinterpret_cast(ptr); + + // link free list + auto x = reinterpret_cast(data); + *x = mListForFree; + mListForFree = data; + + // create linked list for newly allocated data + auto * const headT = + reinterpret_cast_no_cast_align_warning(reinterpret_cast(ptr) + ALIGNMENT); + + auto * const head = reinterpret_cast(headT); + + // Visual Studio compiler automatically unrolls this loop, which is pretty cool + for (size_t i = 0; i < numElements; ++i) { + *reinterpret_cast_no_cast_align_warning(head + i * ALIGNED_SIZE) = + head + (i + 1) * ALIGNED_SIZE; + } + + // last one points to 0 + *reinterpret_cast_no_cast_align_warning(head + (numElements - 1) * ALIGNED_SIZE) = mHead; + mHead = headT; + } + + // Called when no memory is available (mHead == 0). + // Don't inline this slow path. + ROBIN_HOOD(NOINLINE) T * performAllocation() + { + size_t const numElementsToAlloc = calcNumElementsToAlloc(); + + // alloc new memory: [prev |T, T, ... T] + size_t const bytes = ALIGNMENT + ALIGNED_SIZE * numElementsToAlloc; + ROBIN_HOOD_LOG( + "std::malloc " << bytes << " = " << ALIGNMENT << " + " << ALIGNED_SIZE << " * " + << numElementsToAlloc) + add(assertNotNull(std::malloc(bytes)), bytes); + return mHead; + } + + // enforce byte alignment of the T's +#if ROBIN_HOOD(CXX) >= ROBIN_HOOD(CXX14) + static constexpr size_t ALIGNMENT = + (std::max)(std::alignment_of::value, std::alignment_of::value); +#else + static const size_t ALIGNMENT = + (ROBIN_HOOD_STD::alignment_of::value > ROBIN_HOOD_STD::alignment_of::value) + ? ROBIN_HOOD_STD::alignment_of::value + : +ROBIN_HOOD_STD::alignment_of::value; // the + is for walk around +#endif + + static constexpr size_t ALIGNED_SIZE = ((sizeof(T) - 1) / ALIGNMENT + 1) * ALIGNMENT; + + static_assert(MinNumAllocs >= 1, "MinNumAllocs"); + static_assert(MaxNumAllocs >= MinNumAllocs, "MaxNumAllocs"); + static_assert(ALIGNED_SIZE >= sizeof(T *), "ALIGNED_SIZE"); + static_assert(0 == (ALIGNED_SIZE % sizeof(T *)), "ALIGNED_SIZE mod"); + static_assert(ALIGNMENT >= sizeof(T *), "ALIGNMENT"); + + T * mHead{nullptr}; + T ** mListForFree{nullptr}; +}; + +template +struct NodeAllocator; + +// dummy allocator that does nothing +template +struct NodeAllocator +{ + // we are not using the data, so just free it. + void addOrFree(void * ptr, size_t ROBIN_HOOD_UNUSED(numBytes) /*unused*/) noexcept + { + ROBIN_HOOD_LOG("std::free") + std::free(ptr); + } +}; + +template +struct NodeAllocator : public BulkPoolAllocator +{ +}; + +// c++14 doesn't have is_nothrow_swappable, and clang++ 6.0.1 doesn't like it either, so I'm making +// my own here. +namespace swappable +{ +#if ROBIN_HOOD(CXX) < ROBIN_HOOD(CXX17) +using std::swap; +template +struct nothrow +{ + static const bool value = noexcept(swap(std::declval(), std::declval())); +}; +#else +template +struct nothrow +{ + static const bool value = std::is_nothrow_swappable::value; +}; +#endif +} // namespace swappable + +} // namespace detail + +struct is_transparent_tag +{ +}; + +// A custom pair implementation is used in the map because std::pair is not is_trivially_copyable, +// which means it would not be allowed to be used in std::memcpy. This struct is copyable, which is +// also tested. +template +struct pair +{ + using first_type = T1; + using second_type = T2; + + template < + typename U1 = T1, typename U2 = T2, + typename = typename std::enable_if< + std::is_default_constructible::value && std::is_default_constructible::value>::type> + constexpr pair() noexcept(noexcept(U1()) && noexcept(U2())) : first(), second() + { + } + + // pair constructors are explicit so we don't accidentally call this ctor when we don't have to. + explicit constexpr pair(std::pair const & o) noexcept( + noexcept(T1(std::declval())) && noexcept(T2(std::declval()))) + : first(o.first), second(o.second) + { + } + + // pair constructors are explicit so we don't accidentally call this ctor when we don't have to. + explicit constexpr pair(std::pair && o) noexcept(noexcept( + T1(std::move(std::declval()))) && noexcept(T2(std::move(std::declval())))) + : first(std::move(o.first)), second(std::move(o.second)) + { + } + + constexpr pair(T1 && a, T2 && b) noexcept(noexcept( + T1(std::move(std::declval()))) && noexcept(T2(std::move(std::declval())))) + : first(std::move(a)), second(std::move(b)) + { + } + + template + constexpr pair(U1 && a, U2 && b) noexcept(noexcept(T1(std::forward( + std::declval()))) && noexcept(T2(std::forward(std::declval())))) + : first(std::forward(a)), second(std::forward(b)) + { + } + + template + // MSVC 2015 produces error "C2476: ‘constexpr’ constructor does not initialize all members" + // if this constructor is constexpr +#if !ROBIN_HOOD(BROKEN_CONSTEXPR) + constexpr +#endif + pair(std::piecewise_construct_t /*unused*/, std::tuple a, std::tuple b) noexcept( + noexcept(pair( + std::declval &>(), std::declval &>(), + ROBIN_HOOD_STD::index_sequence_for(), ROBIN_HOOD_STD::index_sequence_for()))) + : pair( + a, b, ROBIN_HOOD_STD::index_sequence_for(), + ROBIN_HOOD_STD::index_sequence_for()) + { + } + + // constructor called from the std::piecewise_construct_t ctor + template + pair( + std::tuple & a, std::tuple & b, ROBIN_HOOD_STD::index_sequence /*unused*/, + ROBIN_HOOD_STD::index_sequence< + I2...> /*unused*/) noexcept(noexcept(T1(std:: + forward(std::get( + std::declval &>()))...)) && noexcept(T2(std:: + forward(std::get(std::declval &>()))...))) // NOLINT + : first(std::forward(std::get(a))...), second(std::forward(std::get(b))...) + { + // make visual studio compiler happy about warning about unused a & b. + // Visual studio's pair implementation disables warning 4100. + (void)a; + (void)b; + } + + void swap(pair & o) noexcept( + (detail::swappable::nothrow::value) && (detail::swappable::nothrow::value)) + { + using std::swap; + swap(first, o.first); + swap(second, o.second); + } + + T1 first; // NOLINT (misc-non-private-member-variables-in-classes) + T2 second; // NOLINT (misc-non-private-member-variables-in-classes) +}; + +template +inline void swap(pair & a, pair & b) noexcept( + noexcept(std::declval &>().swap(std::declval &>()))) +{ + a.swap(b); +} + +template +inline constexpr bool operator==(pair const & x, pair const & y) +{ + return (x.first == y.first) && (x.second == y.second); +} +template +inline constexpr bool operator!=(pair const & x, pair const & y) +{ + return !(x == y); +} +template +inline constexpr bool operator<(pair const & x, pair const & y) noexcept(noexcept( + std::declval() < + std::declval()) && noexcept(std::declval() < std::declval())) +{ + return x.first < y.first || (!(y.first < x.first) && x.second < y.second); +} +template +inline constexpr bool operator>(pair const & x, pair const & y) +{ + return y < x; +} +template +inline constexpr bool operator<=(pair const & x, pair const & y) +{ + return !(x > y); +} +template +inline constexpr bool operator>=(pair const & x, pair const & y) +{ + return !(x < y); +} + +inline size_t hash_bytes(void const * ptr, size_t len) noexcept +{ + static constexpr uint64_t m = UINT64_C(0xc6a4a7935bd1e995); + static constexpr uint64_t seed = UINT64_C(0xe17a1465); + static constexpr unsigned int r = 47; + + auto const * const data64 = static_cast(ptr); + uint64_t h = seed ^ (len * m); + + size_t const n_blocks = len / 8; + for (size_t i = 0; i < n_blocks; ++i) { + auto k = detail::unaligned_load(data64 + i); + + k *= m; + k ^= k >> r; + k *= m; + + h ^= k; + h *= m; + } + + auto const * const data8 = reinterpret_cast(data64 + n_blocks); + switch (len & 7U) { + case 7: + h ^= static_cast(data8[6]) << 48U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 6: + h ^= static_cast(data8[5]) << 40U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 5: + h ^= static_cast(data8[4]) << 32U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 4: + h ^= static_cast(data8[3]) << 24U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 3: + h ^= static_cast(data8[2]) << 16U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 2: + h ^= static_cast(data8[1]) << 8U; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + case 1: + h ^= static_cast(data8[0]); + h *= m; + ROBIN_HOOD(FALLTHROUGH); // FALLTHROUGH + default: + break; + } + + h ^= h >> r; + + // not doing the final step here, because this will be done by keyToIdx anyways + // h *= m; + // h ^= h >> r; + return static_cast(h); +} + +inline size_t hash_int(uint64_t x) noexcept +{ + // tried lots of different hashes, let's stick with murmurhash3. It's simple, fast, well tested, + // and doesn't need any special 128bit operations. + x ^= x >> 33U; + x *= UINT64_C(0xff51afd7ed558ccd); + x ^= x >> 33U; + + // not doing the final step here, because this will be done by keyToIdx anyways + // x *= UINT64_C(0xc4ceb9fe1a85ec53); + // x ^= x >> 33U; + return static_cast(x); +} + +// A thin wrapper around std::hash, performing an additional simple mixing step of the result. +template +struct hash : public std::hash +{ + size_t operator()(T const & obj) const + noexcept(noexcept(std::declval>().operator()(std::declval()))) + { + // call base hash + auto result = std::hash::operator()(obj); + // return mixed of that, to be save against identity has + return hash_int(static_cast(result)); + } +}; + +template +struct hash> +{ + size_t operator()(std::basic_string const & str) const noexcept + { + return hash_bytes(str.data(), sizeof(CharT) * str.size()); + } +}; + +#if ROBIN_HOOD(CXX) >= ROBIN_HOOD(CXX17) +template +struct hash> +{ + size_t operator()(std::basic_string_view const & sv) const noexcept + { + return hash_bytes(sv.data(), sizeof(CharT) * sv.size()); + } +}; +#endif + +template +struct hash +{ + size_t operator()(T * ptr) const noexcept + { + return hash_int(reinterpret_cast(ptr)); + } +}; + +template +struct hash> +{ + size_t operator()(std::unique_ptr const & ptr) const noexcept + { + return hash_int(reinterpret_cast(ptr.get())); + } +}; + +template +struct hash> +{ + size_t operator()(std::shared_ptr const & ptr) const noexcept + { + return hash_int(reinterpret_cast(ptr.get())); + } +}; + +template +struct hash::value>::type> +{ + size_t operator()(Enum e) const noexcept + { + using Underlying = typename std::underlying_type::type; + return hash{}(static_cast(e)); + } +}; + +#define ROBIN_HOOD_HASH_INT(T) \ + template <> \ + struct hash \ + { \ + size_t operator()(T const & obj) const noexcept \ + { \ + return hash_int(static_cast(obj)); \ + } \ + } + +#if defined(__GNUC__) && !defined(__clang__) +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wuseless-cast" +#endif +// see https://en.cppreference.com/w/cpp/utility/hash +ROBIN_HOOD_HASH_INT(bool); +ROBIN_HOOD_HASH_INT(char); +ROBIN_HOOD_HASH_INT(signed char); +ROBIN_HOOD_HASH_INT(unsigned char); +ROBIN_HOOD_HASH_INT(char16_t); +ROBIN_HOOD_HASH_INT(char32_t); +#if ROBIN_HOOD(HAS_NATIVE_WCHART) +ROBIN_HOOD_HASH_INT(wchar_t); +#endif +ROBIN_HOOD_HASH_INT(short); // NOLINT +ROBIN_HOOD_HASH_INT(unsigned short); // NOLINT +ROBIN_HOOD_HASH_INT(int); +ROBIN_HOOD_HASH_INT(unsigned int); +ROBIN_HOOD_HASH_INT(long); // NOLINT +ROBIN_HOOD_HASH_INT(long long); // NOLINT +ROBIN_HOOD_HASH_INT(unsigned long); // NOLINT +ROBIN_HOOD_HASH_INT(unsigned long long); // NOLINT +#if defined(__GNUC__) && !defined(__clang__) +#pragma GCC diagnostic pop +#endif +namespace detail +{ + +template +struct void_type +{ + using type = void; +}; + +template +struct has_is_transparent : public std::false_type +{ +}; + +template +struct has_is_transparent::type> +: public std::true_type +{ +}; + +// using wrapper classes for hash and key_equal prevents the diamond problem when the same type +// is used. see https://stackoverflow.com/a/28771920/48181 +template +struct WrapHash : public T +{ + WrapHash() = default; + explicit WrapHash(T const & o) noexcept(noexcept(T(std::declval()))) : T(o) {} +}; + +template +struct WrapKeyEqual : public T +{ + WrapKeyEqual() = default; + explicit WrapKeyEqual(T const & o) noexcept(noexcept(T(std::declval()))) : T(o) {} +}; + +// A highly optimized hashmap implementation, using the Robin Hood algorithm. +// +// In most cases, this map should be usable as a drop-in replacement for std::unordered_map, but +// be about 2x faster in most cases and require much less allocations. +// +// This implementation uses the following memory layout: +// +// [Node, Node, ... Node | info, info, ... infoSentinel ] +// +// * Node: either a DataNode that directly has the std::pair as member, +// or a DataNode with a pointer to std::pair. Which DataNode representation to use +// depends on how fast the swap() operation is. Heuristically, this is automatically choosen +// based on sizeof(). there are always 2^n Nodes. +// +// * info: Each Node in the map has a corresponding info byte, so there are 2^n info bytes. +// Each byte is initialized to 0, meaning the corresponding Node is empty. Set to 1 means the +// corresponding node contains data. Set to 2 means the corresponding Node is filled, but it +// actually belongs to the previous position and was pushed out because that place is already +// taken. +// +// * infoSentinel: Sentinel byte set to 1, so that iterator's ++ can stop at end() without the +// need for a idx variable. +// +// According to STL, order of templates has effect on throughput. That's why I've moved the +// boolean to the front. +// https://www.reddit.com/r/cpp/comments/ahp6iu/compile_time_binary_size_reductions_and_cs_future/eeguck4/ +template < + bool IsFlat, size_t MaxLoadFactor100, typename Key, typename T, typename Hash, typename KeyEqual> +class Table +: public WrapHash, + public WrapKeyEqual, + detail::NodeAllocator< + typename std::conditional< + std::is_void::value, Key, + robin_hood::pair::type, T>>::type, + 4, 16384, IsFlat> +{ +public: + static constexpr bool is_flat = IsFlat; + static constexpr bool is_map = !std::is_void::value; + static constexpr bool is_set = !is_map; + static constexpr bool is_transparent = + has_is_transparent::value && has_is_transparent::value; + + using key_type = Key; + using mapped_type = T; + using value_type = typename std::conditional< + is_set, Key, + robin_hood::pair::type, T>>::type; + using size_type = size_t; + using hasher = Hash; + using key_equal = KeyEqual; + using Self = Table; + +private: + static_assert( + MaxLoadFactor100 > 10 && MaxLoadFactor100 < 100, "MaxLoadFactor100 needs to be >10 && < 100"); + + using WHash = WrapHash; + using WKeyEqual = WrapKeyEqual; + + // configuration defaults + + // make sure we have 8 elements, needed to quickly rehash mInfo + static constexpr size_t InitialNumElements = sizeof(uint64_t); + static constexpr uint32_t InitialInfoNumBits = 5; + static constexpr uint8_t InitialInfoInc = 1U << InitialInfoNumBits; + static constexpr size_t InfoMask = InitialInfoInc - 1U; + static constexpr uint8_t InitialInfoHashShift = 0; + using DataPool = detail::NodeAllocator; + + // type needs to be wider than uint8_t. + using InfoType = uint32_t; + + // DataNode //////////////////////////////////////////////////////// + + // Primary template for the data node. We have special implementations for small and big + // objects. For large objects it is assumed that swap() is fairly slow, so we allocate these + // on the heap so swap merely swaps a pointer. + template + class DataNode + { + }; + + // Small: just allocate on the stack. + template + class DataNode final + { + public: + template + explicit DataNode(M & ROBIN_HOOD_UNUSED(map) /*unused*/, Args &&... args) noexcept( + noexcept(value_type(std::forward(args)...))) + : mData(std::forward(args)...) + { + } + + DataNode(M & ROBIN_HOOD_UNUSED(map) /*unused*/, DataNode && n) noexcept( + std::is_nothrow_move_constructible::value) + : mData(std::move(n.mData)) + { + } + + // doesn't do anything + void destroy(M & ROBIN_HOOD_UNUSED(map) /*unused*/) noexcept {} + void destroyDoNotDeallocate() noexcept {} + + value_type const * operator->() const noexcept { return &mData; } + value_type * operator->() noexcept { return &mData; } + + const value_type & operator*() const noexcept { return mData; } + + value_type & operator*() noexcept { return mData; } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() noexcept + { + return mData.first; + } + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() noexcept + { + return mData; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() const noexcept + { + return mData.first; + } + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() const noexcept + { + return mData; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getSecond() noexcept + { + return mData.second; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getSecond() const noexcept + { + return mData.second; + } + + void swap(DataNode & o) noexcept( + noexcept(std::declval().swap(std::declval()))) + { + mData.swap(o.mData); + } + + private: + value_type mData; + }; + + // big object: allocate on heap. + template + class DataNode + { + public: + template + explicit DataNode(M & map, Args &&... args) : mData(map.allocate()) + { + ::new (static_cast(mData)) value_type(std::forward(args)...); + } + + DataNode(M & ROBIN_HOOD_UNUSED(map) /*unused*/, DataNode && n) noexcept + : mData(std::move(n.mData)) + { + } + + void destroy(M & map) noexcept + { + // don't deallocate, just put it into list of data pool. + mData->~value_type(); + map.deallocate(mData); + } + + void destroyDoNotDeallocate() noexcept { mData->~value_type(); } + + value_type const * operator->() const noexcept { return mData; } + + value_type * operator->() noexcept { return mData; } + + const value_type & operator*() const { return *mData; } + + value_type & operator*() { return *mData; } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() noexcept + { + return mData->first; + } + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() noexcept + { + return *mData; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() const noexcept + { + return mData->first; + } + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getFirst() const noexcept + { + return *mData; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getSecond() noexcept + { + return mData->second; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::type getSecond() const noexcept + { + return mData->second; + } + + void swap(DataNode & o) noexcept + { + using std::swap; + swap(mData, o.mData); + } + + private: + value_type * mData; + }; + + using Node = DataNode; + + // helpers for insertKeyPrepareEmptySpot: extract first entry (only const required) + ROBIN_HOOD(NODISCARD) key_type const & getFirstConst(Node const & n) const noexcept + { + return n.getFirst(); + } + + // in case we have void mapped_type, we are not using a pair, thus we just route k through. + // No need to disable this because it's just not used if not applicable. + ROBIN_HOOD(NODISCARD) key_type const & getFirstConst(key_type const & k) const noexcept + { + return k; + } + + // in case we have non-void mapped_type, we have a standard robin_hood::pair + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::value, key_type const &>::type + getFirstConst(value_type const & vt) const noexcept + { + return vt.first; + } + + // Cloner ////////////////////////////////////////////////////////// + + template + struct Cloner; + + // fast path: Just copy data, without allocating anything. + template + struct Cloner + { + void operator()(M const & source, M & target) const + { + auto const * const src = reinterpret_cast(source.mKeyVals); + auto * tgt = reinterpret_cast(target.mKeyVals); + auto const numElementsWithBuffer = target.calcNumElementsWithBuffer(target.mMask + 1); + std::copy(src, src + target.calcNumBytesTotal(numElementsWithBuffer), tgt); + } + }; + + template + struct Cloner + { + void operator()(M const & s, M & t) const + { + auto const numElementsWithBuffer = t.calcNumElementsWithBuffer(t.mMask + 1); + std::copy(s.mInfo, s.mInfo + t.calcNumBytesInfo(numElementsWithBuffer), t.mInfo); + + for (size_t i = 0; i < numElementsWithBuffer; ++i) { + if (t.mInfo[i]) { + ::new (static_cast(t.mKeyVals + i)) Node(t, *s.mKeyVals[i]); + } + } + } + }; + + // Destroyer /////////////////////////////////////////////////////// + + template + struct Destroyer + { + }; + + template + struct Destroyer + { + void nodes(M & m) const noexcept { m.mNumElements = 0; } + + void nodesDoNotDeallocate(M & m) const noexcept { m.mNumElements = 0; } + }; + + template + struct Destroyer + { + void nodes(M & m) const noexcept + { + m.mNumElements = 0; + // clear also resets mInfo to 0, that's sometimes not necessary. + auto const numElementsWithBuffer = m.calcNumElementsWithBuffer(m.mMask + 1); + + for (size_t idx = 0; idx < numElementsWithBuffer; ++idx) { + if (0 != m.mInfo[idx]) { + Node & n = m.mKeyVals[idx]; + n.destroy(m); + n.~Node(); + } + } + } + + void nodesDoNotDeallocate(M & m) const noexcept + { + m.mNumElements = 0; + // clear also resets mInfo to 0, that's sometimes not necessary. + auto const numElementsWithBuffer = m.calcNumElementsWithBuffer(m.mMask + 1); + for (size_t idx = 0; idx < numElementsWithBuffer; ++idx) { + if (0 != m.mInfo[idx]) { + Node & n = m.mKeyVals[idx]; + n.destroyDoNotDeallocate(); + n.~Node(); + } + } + } + }; + + // Iter //////////////////////////////////////////////////////////// + + struct fast_forward_tag + { + }; + + // generic iterator for both const_iterator and iterator. + template + // NOLINTNEXTLINE (hicpp-special-member-functions,cppcoreguidelines-special-member-functions) + class Iter + { + private: + using NodePtr = typename std::conditional::type; + + public: + using difference_type = std::ptrdiff_t; + using value_type = typename Self::value_type; + using reference = typename std::conditional::type; + using pointer = typename std::conditional::type; + using iterator_category = std::forward_iterator_tag; + + // default constructed iterator can be compared to itself, but WON'T return true when + // compared to end(). + Iter() = default; + + // Rule of zero: nothing specified. The conversion constructor is only enabled for + // iterator to const_iterator, so it doesn't accidentally work as a copy ctor. + + // Conversion constructor from iterator to const_iterator. + template ::type> + // NOLINTNEXTLINE (hicpp-explicit-conversions) + Iter(Iter const & other) noexcept : mKeyVals(other.mKeyVals), mInfo(other.mInfo) + { + } + + Iter(NodePtr valPtr, uint8_t const * infoPtr) noexcept : mKeyVals(valPtr), mInfo(infoPtr) {} + + Iter( + NodePtr valPtr, uint8_t const * infoPtr, + fast_forward_tag ROBIN_HOOD_UNUSED(tag) /*unused*/) noexcept + : mKeyVals(valPtr), mInfo(infoPtr) + { + fastForward(); + } + + template ::type> + Iter & operator=(Iter const & other) noexcept + { + mKeyVals = other.mKeyVals; + mInfo = other.mInfo; + return *this; + } + + // prefix increment. Undefined behavior if we are at end()! + Iter & operator++() noexcept + { + mInfo++; + mKeyVals++; + fastForward(); + return *this; + } + + Iter operator++(int) noexcept + { + Iter tmp = *this; + ++(*this); + return tmp; + } + + reference operator*() const { return **mKeyVals; } + + pointer operator->() const { return &**mKeyVals; } + + template + bool operator==(Iter const & o) const noexcept + { + return mKeyVals == o.mKeyVals; + } + + template + bool operator!=(Iter const & o) const noexcept + { + return mKeyVals != o.mKeyVals; + } + + private: + // fast forward to the next non-free info byte + // I've tried a few variants that don't depend on intrinsics, but unfortunately they are + // quite a bit slower than this one. So I've reverted that change again. See map_benchmark. + void fastForward() noexcept + { + size_t n = 0; + while (0U == (n = detail::unaligned_load(mInfo))) { + mInfo += sizeof(size_t); + mKeyVals += sizeof(size_t); + } +#if defined(ROBIN_HOOD_DISABLE_INTRINSICS) + // we know for certain that within the next 8 bytes we'll find a non-zero one. + if (ROBIN_HOOD_UNLIKELY(0U == detail::unaligned_load(mInfo))) { + mInfo += 4; + mKeyVals += 4; + } + if (ROBIN_HOOD_UNLIKELY(0U == detail::unaligned_load(mInfo))) { + mInfo += 2; + mKeyVals += 2; + } + if (ROBIN_HOOD_UNLIKELY(0U == *mInfo)) { + mInfo += 1; + mKeyVals += 1; + } +#else +#if ROBIN_HOOD(LITTLE_ENDIAN) + auto inc = ROBIN_HOOD_COUNT_TRAILING_ZEROES(n) / 8; +#else + auto inc = ROBIN_HOOD_COUNT_LEADING_ZEROES(n) / 8; +#endif + mInfo += inc; + mKeyVals += inc; +#endif + } + + friend class Table; + NodePtr mKeyVals{nullptr}; + uint8_t const * mInfo{nullptr}; + }; + + //////////////////////////////////////////////////////////////////// + + // highly performance relevant code. + // Lower bits are used for indexing into the array (2^n size) + // The upper 1-5 bits need to be a reasonable good hash, to save comparisons. + template + void keyToIdx(HashKey && key, size_t * idx, InfoType * info) const + { + // In addition to whatever hash is used, add another mul & shift so we get better hashing. + // This serves as a bad hash prevention, if the given data is + // badly mixed. + auto h = static_cast(WHash::operator()(key)); + + h *= mHashMultiplier; + h ^= h >> 33U; + + // the lower InitialInfoNumBits are reserved for info. + *info = mInfoInc + static_cast((h & InfoMask) >> mInfoHashShift); + *idx = (static_cast(h) >> InitialInfoNumBits) & mMask; + } + + // forwards the index by one, wrapping around at the end + void next(InfoType * info, size_t * idx) const noexcept + { + *idx = *idx + 1; + *info += mInfoInc; + } + + void nextWhileLess(InfoType * info, size_t * idx) const noexcept + { + // unrolling this by hand did not bring any speedups. + while (*info < mInfo[*idx]) { + next(info, idx); + } + } + + // Shift everything up by one element. Tries to move stuff around. + void shiftUp(size_t startIdx, size_t const insertion_idx) noexcept( + std::is_nothrow_move_assignable::value) + { + auto idx = startIdx; + ::new (static_cast(mKeyVals + idx)) Node(std::move(mKeyVals[idx - 1])); + while (--idx != insertion_idx) { + mKeyVals[idx] = std::move(mKeyVals[idx - 1]); + } + + idx = startIdx; + while (idx != insertion_idx) { + ROBIN_HOOD_COUNT(shiftUp) + mInfo[idx] = static_cast(mInfo[idx - 1] + mInfoInc); + if (ROBIN_HOOD_UNLIKELY(mInfo[idx] + mInfoInc > 0xFF)) { + mMaxNumElementsAllowed = 0; + } + --idx; + } + } + + void shiftDown(size_t idx) noexcept(std::is_nothrow_move_assignable::value) + { + // until we find one that is either empty or has zero offset. + // TODO(martinus) we don't need to move everything, just the last one for the same + // bucket. + mKeyVals[idx].destroy(*this); + + // until we find one that is either empty or has zero offset. + while (mInfo[idx + 1] >= 2 * mInfoInc) { + ROBIN_HOOD_COUNT(shiftDown) + mInfo[idx] = static_cast(mInfo[idx + 1] - mInfoInc); + mKeyVals[idx] = std::move(mKeyVals[idx + 1]); + ++idx; + } + + mInfo[idx] = 0; + // don't destroy, we've moved it + // mKeyVals[idx].destroy(*this); + mKeyVals[idx].~Node(); + } + + // copy of find(), except that it returns iterator instead of const_iterator. + template + ROBIN_HOOD(NODISCARD) + size_t findIdx(Other const & key) const + { + size_t idx{}; + InfoType info{}; + keyToIdx(key, &idx, &info); + + do { + // unrolling this twice gives a bit of a speedup. More unrolling did not help. + if ( + info == mInfo[idx] && + ROBIN_HOOD_LIKELY(WKeyEqual::operator()(key, mKeyVals[idx].getFirst()))) { + return idx; + } + next(&info, &idx); + if ( + info == mInfo[idx] && + ROBIN_HOOD_LIKELY(WKeyEqual::operator()(key, mKeyVals[idx].getFirst()))) { + return idx; + } + next(&info, &idx); + } while (info <= mInfo[idx]); + + // nothing found! + return mMask == 0 ? 0 + : static_cast(std::distance( + mKeyVals, reinterpret_cast_no_cast_align_warning(mInfo))); + } + + void cloneData(const Table & o) + { + Cloner()(o, *this); + } + + // inserts a keyval that is guaranteed to be new, e.g. when the hashmap is resized. + // @return True on success, false if something went wrong + void insert_move(Node && keyval) + { + // we don't retry, fail if overflowing + // don't need to check max num elements + if (0 == mMaxNumElementsAllowed && !try_increase_info()) { + throwOverflowError(); + } + + size_t idx{}; + InfoType info{}; + keyToIdx(keyval.getFirst(), &idx, &info); + + // skip forward. Use <= because we are certain that the element is not there. + while (info <= mInfo[idx]) { + idx = idx + 1; + info += mInfoInc; + } + + // key not found, so we are now exactly where we want to insert it. + auto const insertion_idx = idx; + auto const insertion_info = static_cast(info); + if (ROBIN_HOOD_UNLIKELY(insertion_info + mInfoInc > 0xFF)) { + mMaxNumElementsAllowed = 0; + } + + // find an empty spot + while (0 != mInfo[idx]) { + next(&info, &idx); + } + + auto & l = mKeyVals[insertion_idx]; + if (idx == insertion_idx) { + ::new (static_cast(&l)) Node(std::move(keyval)); + } else { + shiftUp(idx, insertion_idx); + l = std::move(keyval); + } + + // put at empty spot + mInfo[insertion_idx] = insertion_info; + + ++mNumElements; + } + +public: + using iterator = Iter; + using const_iterator = Iter; + + Table() noexcept(noexcept(Hash()) && noexcept(KeyEqual())) : WHash(), WKeyEqual() + { + ROBIN_HOOD_TRACE(this) + } + + // Creates an empty hash map. Nothing is allocated yet, this happens at the first insert. + // This tremendously speeds up ctor & dtor of a map that never receives an element. The + // penalty is payed at the first insert, and not before. Lookup of this empty map works + // because everybody points to DummyInfoByte::b. parameter bucket_count is dictated by the + // standard, but we can ignore it. + explicit Table( + size_t ROBIN_HOOD_UNUSED(bucket_count) /*unused*/, const Hash & h = Hash{}, + const KeyEqual & equal = KeyEqual{}) noexcept(noexcept(Hash(h)) && noexcept(KeyEqual(equal))) + : WHash(h), WKeyEqual(equal) + { + ROBIN_HOOD_TRACE(this) + } + + template + Table( + Iter first, Iter last, size_t ROBIN_HOOD_UNUSED(bucket_count) /*unused*/ = 0, + const Hash & h = Hash{}, const KeyEqual & equal = KeyEqual{}) + : WHash(h), WKeyEqual(equal) + { + ROBIN_HOOD_TRACE(this) + insert(first, last); + } + + Table( + std::initializer_list initlist, + size_t ROBIN_HOOD_UNUSED(bucket_count) /*unused*/ = 0, const Hash & h = Hash{}, + const KeyEqual & equal = KeyEqual{}) + : WHash(h), WKeyEqual(equal) + { + ROBIN_HOOD_TRACE(this) + insert(initlist.begin(), initlist.end()); + } + + Table(Table && o) noexcept + : WHash(std::move(static_cast(o))), + WKeyEqual(std::move(static_cast(o))), + DataPool(std::move(static_cast(o))) + { + ROBIN_HOOD_TRACE(this) + if (o.mMask) { + mHashMultiplier = std::move(o.mHashMultiplier); + mKeyVals = std::move(o.mKeyVals); + mInfo = std::move(o.mInfo); + mNumElements = std::move(o.mNumElements); + mMask = std::move(o.mMask); + mMaxNumElementsAllowed = std::move(o.mMaxNumElementsAllowed); + mInfoInc = std::move(o.mInfoInc); + mInfoHashShift = std::move(o.mInfoHashShift); + // set other's mask to 0 so its destructor won't do anything + o.init(); + } + } + + Table & operator=(Table && o) noexcept + { + ROBIN_HOOD_TRACE(this) + if (&o != this) { + if (o.mMask) { + // only move stuff if the other map actually has some data + destroy(); + mHashMultiplier = std::move(o.mHashMultiplier); + mKeyVals = std::move(o.mKeyVals); + mInfo = std::move(o.mInfo); + mNumElements = std::move(o.mNumElements); + mMask = std::move(o.mMask); + mMaxNumElementsAllowed = std::move(o.mMaxNumElementsAllowed); + mInfoInc = std::move(o.mInfoInc); + mInfoHashShift = std::move(o.mInfoHashShift); + WHash::operator=(std::move(static_cast(o))); + WKeyEqual::operator=(std::move(static_cast(o))); + DataPool::operator=(std::move(static_cast(o))); + + o.init(); + + } else { + // nothing in the other map => just clear us. + clear(); + } + } + return *this; + } + + Table(const Table & o) + : WHash(static_cast(o)), + WKeyEqual(static_cast(o)), + DataPool(static_cast(o)) + { + ROBIN_HOOD_TRACE(this) + if (!o.empty()) { + // not empty: create an exact copy. it is also possible to just iterate through all + // elements and insert them, but copying is probably faster. + + auto const numElementsWithBuffer = calcNumElementsWithBuffer(o.mMask + 1); + auto const numBytesTotal = calcNumBytesTotal(numElementsWithBuffer); + + ROBIN_HOOD_LOG( + "std::malloc " << numBytesTotal << " = calcNumBytesTotal(" << numElementsWithBuffer << ")") + mHashMultiplier = o.mHashMultiplier; + mKeyVals = + static_cast(detail::assertNotNull(std::malloc(numBytesTotal))); + // no need for calloc because cloneData does memcpy + mInfo = reinterpret_cast(mKeyVals + numElementsWithBuffer); + mNumElements = o.mNumElements; + mMask = o.mMask; + mMaxNumElementsAllowed = o.mMaxNumElementsAllowed; + mInfoInc = o.mInfoInc; + mInfoHashShift = o.mInfoHashShift; + cloneData(o); + } + } + + // Creates a copy of the given map. Copy constructor of each entry is used. + // Not sure why clang-tidy thinks this doesn't handle self assignment, it does + // NOLINTNEXTLINE (bugprone-unhandled-self-assignment,cert-oop54-cpp) + Table & operator=(Table const & o) + { + ROBIN_HOOD_TRACE(this) + if (&o == this) { + // prevent assigning of itself + return *this; + } + + // we keep using the old allocator and not assign the new one, because we want to keep + // the memory available. when it is the same size. + if (o.empty()) { + if (0 == mMask) { + // nothing to do, we are empty too + return *this; + } + + // not empty: destroy what we have there + // clear also resets mInfo to 0, that's sometimes not necessary. + destroy(); + init(); + WHash::operator=(static_cast(o)); + WKeyEqual::operator=(static_cast(o)); + DataPool::operator=(static_cast(o)); + + return *this; + } + + // clean up old stuff + Destroyer::value>{}.nodes(*this); + + if (mMask != o.mMask) { + // no luck: we don't have the same array size allocated, so we need to realloc. + if (0 != mMask) { + // only deallocate if we actually have data! + ROBIN_HOOD_LOG("std::free") + std::free(mKeyVals); + } + + auto const numElementsWithBuffer = calcNumElementsWithBuffer(o.mMask + 1); + auto const numBytesTotal = calcNumBytesTotal(numElementsWithBuffer); + ROBIN_HOOD_LOG( + "std::malloc " << numBytesTotal << " = calcNumBytesTotal(" << numElementsWithBuffer << ")") + mKeyVals = + static_cast(detail::assertNotNull(std::malloc(numBytesTotal))); + + // no need for calloc here because cloneData performs a memcpy. + mInfo = reinterpret_cast(mKeyVals + numElementsWithBuffer); + // sentinel is set in cloneData + } + WHash::operator=(static_cast(o)); + WKeyEqual::operator=(static_cast(o)); + DataPool::operator=(static_cast(o)); + mHashMultiplier = o.mHashMultiplier; + mNumElements = o.mNumElements; + mMask = o.mMask; + mMaxNumElementsAllowed = o.mMaxNumElementsAllowed; + mInfoInc = o.mInfoInc; + mInfoHashShift = o.mInfoHashShift; + cloneData(o); + + return *this; + } + + // Swaps everything between the two maps. + void swap(Table & o) + { + ROBIN_HOOD_TRACE(this) + using std::swap; + swap(o, *this); + } + + // Clears all data, without resizing. + void clear() + { + ROBIN_HOOD_TRACE(this) + if (empty()) { + // don't do anything! also important because we don't want to write to + // DummyInfoByte::b, even though we would just write 0 to it. + return; + } + + Destroyer::value>{}.nodes(*this); + + auto const numElementsWithBuffer = calcNumElementsWithBuffer(mMask + 1); + // clear everything, then set the sentinel again + uint8_t const z = 0; + std::fill(mInfo, mInfo + calcNumBytesInfo(numElementsWithBuffer), z); + mInfo[numElementsWithBuffer] = 1; + + mInfoInc = InitialInfoInc; + mInfoHashShift = InitialInfoHashShift; + } + + // Destroys the map and all it's contents. + ~Table() + { + ROBIN_HOOD_TRACE(this) + destroy(); + } + + // Checks if both tables contain the same entries. Order is irrelevant. + bool operator==(const Table & other) const + { + ROBIN_HOOD_TRACE(this) + if (other.size() != size()) { + return false; + } + for (auto const & otherEntry : other) { + if (!has(otherEntry)) { + return false; + } + } + + return true; + } + + bool operator!=(const Table & other) const + { + ROBIN_HOOD_TRACE(this) + return !operator==(other); + } + + template + typename std::enable_if::value, Q &>::type operator[](const key_type & key) + { + ROBIN_HOOD_TRACE(this) + auto idxAndState = insertKeyPrepareEmptySpot(key); + switch (idxAndState.second) { + case InsertionState::key_found: + break; + + case InsertionState::new_node: + ::new (static_cast(&mKeyVals[idxAndState.first])) Node( + *this, std::piecewise_construct, std::forward_as_tuple(key), std::forward_as_tuple()); + break; + + case InsertionState::overwrite_node: + mKeyVals[idxAndState.first] = Node( + *this, std::piecewise_construct, std::forward_as_tuple(key), std::forward_as_tuple()); + break; + + case InsertionState::overflow_error: + throwOverflowError(); + } + + return mKeyVals[idxAndState.first].getSecond(); + } + + template + typename std::enable_if::value, Q &>::type operator[](key_type && key) + { + ROBIN_HOOD_TRACE(this) + auto idxAndState = insertKeyPrepareEmptySpot(key); + switch (idxAndState.second) { + case InsertionState::key_found: + break; + + case InsertionState::new_node: + ::new (static_cast(&mKeyVals[idxAndState.first])) Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::move(key)), + std::forward_as_tuple()); + break; + + case InsertionState::overwrite_node: + mKeyVals[idxAndState.first] = Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::move(key)), + std::forward_as_tuple()); + break; + + case InsertionState::overflow_error: + throwOverflowError(); + } + + return mKeyVals[idxAndState.first].getSecond(); + } + + template + void insert(Iter first, Iter last) + { + for (; first != last; ++first) { + // value_type ctor needed because this might be called with std::pair's + insert(value_type(*first)); + } + } + + void insert(std::initializer_list ilist) + { + for (auto && vt : ilist) { + insert(std::move(vt)); + } + } + + template + std::pair emplace(Args &&... args) + { + ROBIN_HOOD_TRACE(this) + Node n{*this, std::forward(args)...}; + auto idxAndState = insertKeyPrepareEmptySpot(getFirstConst(n)); + switch (idxAndState.second) { + case InsertionState::key_found: + n.destroy(*this); + break; + + case InsertionState::new_node: + ::new (static_cast(&mKeyVals[idxAndState.first])) Node(*this, std::move(n)); + break; + + case InsertionState::overwrite_node: + mKeyVals[idxAndState.first] = std::move(n); + break; + + case InsertionState::overflow_error: + n.destroy(*this); + throwOverflowError(); + break; + } + + return std::make_pair( + iterator(mKeyVals + idxAndState.first, mInfo + idxAndState.first), + InsertionState::key_found != idxAndState.second); + } + + template + iterator emplace_hint(const_iterator position, Args &&... args) + { + (void)position; + return emplace(std::forward(args)...).first; + } + + template + std::pair try_emplace(const key_type & key, Args &&... args) + { + return try_emplace_impl(key, std::forward(args)...); + } + + template + std::pair try_emplace(key_type && key, Args &&... args) + { + return try_emplace_impl(std::move(key), std::forward(args)...); + } + + template + iterator try_emplace(const_iterator hint, const key_type & key, Args &&... args) + { + (void)hint; + return try_emplace_impl(key, std::forward(args)...).first; + } + + template + iterator try_emplace(const_iterator hint, key_type && key, Args &&... args) + { + (void)hint; + return try_emplace_impl(std::move(key), std::forward(args)...).first; + } + + template + std::pair insert_or_assign(const key_type & key, Mapped && obj) + { + return insertOrAssignImpl(key, std::forward(obj)); + } + + template + std::pair insert_or_assign(key_type && key, Mapped && obj) + { + return insertOrAssignImpl(std::move(key), std::forward(obj)); + } + + template + iterator insert_or_assign(const_iterator hint, const key_type & key, Mapped && obj) + { + (void)hint; + return insertOrAssignImpl(key, std::forward(obj)).first; + } + + template + iterator insert_or_assign(const_iterator hint, key_type && key, Mapped && obj) + { + (void)hint; + return insertOrAssignImpl(std::move(key), std::forward(obj)).first; + } + + std::pair insert(const value_type & keyval) + { + ROBIN_HOOD_TRACE(this) + return emplace(keyval); + } + + iterator insert(const_iterator hint, const value_type & keyval) + { + (void)hint; + return emplace(keyval).first; + } + + std::pair insert(value_type && keyval) { return emplace(std::move(keyval)); } + + iterator insert(const_iterator hint, value_type && keyval) + { + (void)hint; + return emplace(std::move(keyval)).first; + } + + // Returns 1 if key is found, 0 otherwise. + size_t count(const key_type & key) const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + auto kv = mKeyVals + findIdx(key); + if (kv != reinterpret_cast_no_cast_align_warning(mInfo)) { + return 1; + } + return 0; + } + + template + // NOLINTNEXTLINE (modernize-use-nodiscard) + typename std::enable_if::type count(const OtherKey & key) const + { + ROBIN_HOOD_TRACE(this) + auto kv = mKeyVals + findIdx(key); + if (kv != reinterpret_cast_no_cast_align_warning(mInfo)) { + return 1; + } + return 0; + } + + bool contains(const key_type & key) const + { // NOLINT (modernize-use-nodiscard) + return 1U == count(key); + } + + template + // NOLINTNEXTLINE (modernize-use-nodiscard) + typename std::enable_if::type contains(const OtherKey & key) const + { + return 1U == count(key); + } + + // Returns a reference to the value found for key. + // Throws std::out_of_range if element cannot be found + template + // NOLINTNEXTLINE (modernize-use-nodiscard) + typename std::enable_if::value, Q &>::type at(key_type const & key) + { + ROBIN_HOOD_TRACE(this) + auto kv = mKeyVals + findIdx(key); + if (kv == reinterpret_cast_no_cast_align_warning(mInfo)) { + doThrow("key not found"); + } + return kv->getSecond(); + } + + // Returns a reference to the value found for key. + // Throws std::out_of_range if element cannot be found + template + // NOLINTNEXTLINE (modernize-use-nodiscard) + typename std::enable_if::value, Q const &>::type at(key_type const & key) const + { + ROBIN_HOOD_TRACE(this) + auto kv = mKeyVals + findIdx(key); + if (kv == reinterpret_cast_no_cast_align_warning(mInfo)) { + doThrow("key not found"); + } + return kv->getSecond(); + } + + const_iterator find(const key_type & key) const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return const_iterator{mKeyVals + idx, mInfo + idx}; + } + + template + const_iterator find(const OtherKey & key, is_transparent_tag /*unused*/) const + { + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return const_iterator{mKeyVals + idx, mInfo + idx}; + } + + template + typename std::enable_if< + Self_::is_transparent, // NOLINT (modernize-use-nodiscard) + const_iterator>::type // NOLINT (modernize-use-nodiscard) + find(const OtherKey & key) const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return const_iterator{mKeyVals + idx, mInfo + idx}; + } + + iterator find(const key_type & key) + { + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return iterator{mKeyVals + idx, mInfo + idx}; + } + + template + iterator find(const OtherKey & key, is_transparent_tag /*unused*/) + { + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return iterator{mKeyVals + idx, mInfo + idx}; + } + + template + typename std::enable_if::type find(const OtherKey & key) + { + ROBIN_HOOD_TRACE(this) + const size_t idx = findIdx(key); + return iterator{mKeyVals + idx, mInfo + idx}; + } + + iterator begin() + { + ROBIN_HOOD_TRACE(this) + if (empty()) { + return end(); + } + return iterator(mKeyVals, mInfo, fast_forward_tag{}); + } + const_iterator begin() const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return cbegin(); + } + const_iterator cbegin() const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + if (empty()) { + return cend(); + } + return const_iterator(mKeyVals, mInfo, fast_forward_tag{}); + } + + iterator end() + { + ROBIN_HOOD_TRACE(this) + // no need to supply valid info pointer: end() must not be dereferenced, and only node + // pointer is compared. + return iterator{reinterpret_cast_no_cast_align_warning(mInfo), nullptr}; + } + const_iterator end() const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return cend(); + } + const_iterator cend() const + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return const_iterator{reinterpret_cast_no_cast_align_warning(mInfo), nullptr}; + } + + iterator erase(const_iterator pos) + { + ROBIN_HOOD_TRACE(this) + // its safe to perform const cast here + // NOLINTNEXTLINE (cppcoreguidelines-pro-type-const-cast) + return erase(iterator{const_cast(pos.mKeyVals), const_cast(pos.mInfo)}); + } + + // Erases element at pos, returns iterator to the next element. + iterator erase(iterator pos) + { + ROBIN_HOOD_TRACE(this) + // we assume that pos always points to a valid entry, and not end(). + auto const idx = static_cast(pos.mKeyVals - mKeyVals); + + shiftDown(idx); + --mNumElements; + + if (*pos.mInfo) { + // we've backward shifted, return this again + return pos; + } + + // no backward shift, return next element + return ++pos; + } + + size_t erase(const key_type & key) + { + ROBIN_HOOD_TRACE(this) + size_t idx{}; + InfoType info{}; + keyToIdx(key, &idx, &info); + + // check while info matches with the source idx + do { + if (info == mInfo[idx] && WKeyEqual::operator()(key, mKeyVals[idx].getFirst())) { + shiftDown(idx); + --mNumElements; + return 1; + } + next(&info, &idx); + } while (info <= mInfo[idx]); + + // nothing found to delete + return 0; + } + + // reserves space for the specified number of elements. Makes sure the old data fits. + // exactly the same as reserve(c). + void rehash(size_t c) + { + // forces a reserve + reserve(c, true); + } + + // reserves space for the specified number of elements. Makes sure the old data fits. + // Exactly the same as rehash(c). Use rehash(0) to shrink to fit. + void reserve(size_t c) + { + // reserve, but don't force rehash + reserve(c, false); + } + + // If possible reallocates the map to a smaller one. This frees the underlying table. + // Does not do anything if load_factor is too large for decreasing the table's size. + void compact() + { + ROBIN_HOOD_TRACE(this) + auto newSize = InitialNumElements; + while (calcMaxNumElementsAllowed(newSize) < mNumElements && newSize != 0) { + newSize *= 2; + } + if (ROBIN_HOOD_UNLIKELY(newSize == 0)) { + throwOverflowError(); + } + + ROBIN_HOOD_LOG("newSize > mMask + 1: " << newSize << " > " << mMask << " + 1") + + // only actually do anything when the new size is bigger than the old one. This prevents to + // continuously allocate for each reserve() call. + if (newSize < mMask + 1) { + rehashPowerOfTwo(newSize, true); + } + } + + size_type size() const noexcept + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return mNumElements; + } + + size_type max_size() const noexcept + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return static_cast(-1); + } + + ROBIN_HOOD(NODISCARD) bool empty() const noexcept + { + ROBIN_HOOD_TRACE(this) + return 0 == mNumElements; + } + + float max_load_factor() const noexcept + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return MaxLoadFactor100 / 100.0F; + } + + // Average number of elements per bucket. Since we allow only 1 per bucket + float load_factor() const noexcept + { // NOLINT (modernize-use-nodiscard) + ROBIN_HOOD_TRACE(this) + return static_cast(size()) / static_cast(mMask + 1); + } + + ROBIN_HOOD(NODISCARD) size_t mask() const noexcept + { + ROBIN_HOOD_TRACE(this) + return mMask; + } + + ROBIN_HOOD(NODISCARD) size_t calcMaxNumElementsAllowed(size_t maxElements) const noexcept + { + if (ROBIN_HOOD_LIKELY(maxElements <= (std::numeric_limits::max)() / 100)) { + return maxElements * MaxLoadFactor100 / 100; + } + + // we might be a bit imprecise, but since maxElements is quite large that doesn't matter + return (maxElements / 100) * MaxLoadFactor100; + } + + ROBIN_HOOD(NODISCARD) size_t calcNumBytesInfo(size_t numElements) const noexcept + { + // we add a uint64_t, which houses the sentinel (first byte) and padding so we can load + // 64bit types. + return numElements + sizeof(uint64_t); + } + + ROBIN_HOOD(NODISCARD) + size_t calcNumElementsWithBuffer(size_t numElements) const noexcept + { + auto maxNumElementsAllowed = calcMaxNumElementsAllowed(numElements); + return numElements + (std::min)(maxNumElementsAllowed, (static_cast(0xFF))); + } + + // calculation only allowed for 2^n values + ROBIN_HOOD(NODISCARD) size_t calcNumBytesTotal(size_t numElements) const + { +#if ROBIN_HOOD(BITNESS) == 64 + return numElements * sizeof(Node) + calcNumBytesInfo(numElements); +#else + // make sure we're doing 64bit operations, so we are at least safe against 32bit overflows. + auto const ne = static_cast(numElements); + auto const s = static_cast(sizeof(Node)); + auto const infos = static_cast(calcNumBytesInfo(numElements)); + + auto const total64 = ne * s + infos; + auto const total = static_cast(total64); + + if (ROBIN_HOOD_UNLIKELY(static_cast(total) != total64)) { + throwOverflowError(); + } + return total; +#endif + } + +private: + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::value, bool>::type has(const value_type & e) const + { + ROBIN_HOOD_TRACE(this) + auto it = find(e.first); + return it != end() && it->second == e.second; + } + + template + ROBIN_HOOD(NODISCARD) + typename std::enable_if::value, bool>::type has(const value_type & e) const + { + ROBIN_HOOD_TRACE(this) + return find(e) != end(); + } + + void reserve(size_t c, bool forceRehash) + { + ROBIN_HOOD_TRACE(this) + auto const minElementsAllowed = (std::max)(c, mNumElements); + auto newSize = InitialNumElements; + while (calcMaxNumElementsAllowed(newSize) < minElementsAllowed && newSize != 0) { + newSize *= 2; + } + if (ROBIN_HOOD_UNLIKELY(newSize == 0)) { + throwOverflowError(); + } + + ROBIN_HOOD_LOG("newSize > mMask + 1: " << newSize << " > " << mMask << " + 1") + + // only actually do anything when the new size is bigger than the old one. This prevents to + // continuously allocate for each reserve() call. + if (forceRehash || newSize > mMask + 1) { + rehashPowerOfTwo(newSize, false); + } + } + + // reserves space for at least the specified number of elements. + // only works if numBuckets if power of two + // True on success, false otherwise + void rehashPowerOfTwo(size_t numBuckets, bool forceFree) + { + ROBIN_HOOD_TRACE(this) + + Node * const oldKeyVals = mKeyVals; + uint8_t const * const oldInfo = mInfo; + + const size_t oldMaxElementsWithBuffer = calcNumElementsWithBuffer(mMask + 1); + + // resize operation: move stuff + initData(numBuckets); + if (oldMaxElementsWithBuffer > 1) { + for (size_t i = 0; i < oldMaxElementsWithBuffer; ++i) { + if (oldInfo[i] != 0) { + // might throw an exception, which is really bad since we are in the middle of + // moving stuff. + insert_move(std::move(oldKeyVals[i])); + // destroy the node but DON'T destroy the data. + oldKeyVals[i].~Node(); + } + } + + // this check is not necessary as it's guarded by the previous if, but it helps + // silence g++'s overeager "attempt to free a non-heap object 'map' + // [-Werror=free-nonheap-object]" warning. + if (oldKeyVals != reinterpret_cast_no_cast_align_warning(&mMask)) { + // don't destroy old data: put it into the pool instead + if (forceFree) { + std::free(oldKeyVals); + } else { + DataPool::addOrFree(oldKeyVals, calcNumBytesTotal(oldMaxElementsWithBuffer)); + } + } + } + } + + ROBIN_HOOD(NOINLINE) void throwOverflowError() const + { +#if ROBIN_HOOD(HAS_EXCEPTIONS) + throw std::overflow_error("robin_hood::map overflow"); +#else + abort(); +#endif + } + + template + std::pair try_emplace_impl(OtherKey && key, Args &&... args) + { + ROBIN_HOOD_TRACE(this) + auto idxAndState = insertKeyPrepareEmptySpot(key); + switch (idxAndState.second) { + case InsertionState::key_found: + break; + + case InsertionState::new_node: + ::new (static_cast(&mKeyVals[idxAndState.first])) Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::forward(key)), + std::forward_as_tuple(std::forward(args)...)); + break; + + case InsertionState::overwrite_node: + mKeyVals[idxAndState.first] = Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::forward(key)), + std::forward_as_tuple(std::forward(args)...)); + break; + + case InsertionState::overflow_error: + throwOverflowError(); + break; + } + + return std::make_pair( + iterator(mKeyVals + idxAndState.first, mInfo + idxAndState.first), + InsertionState::key_found != idxAndState.second); + } + + template + std::pair insertOrAssignImpl(OtherKey && key, Mapped && obj) + { + ROBIN_HOOD_TRACE(this) + auto idxAndState = insertKeyPrepareEmptySpot(key); + switch (idxAndState.second) { + case InsertionState::key_found: + mKeyVals[idxAndState.first].getSecond() = std::forward(obj); + break; + + case InsertionState::new_node: + ::new (static_cast(&mKeyVals[idxAndState.first])) Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::forward(key)), + std::forward_as_tuple(std::forward(obj))); + break; + + case InsertionState::overwrite_node: + mKeyVals[idxAndState.first] = Node( + *this, std::piecewise_construct, std::forward_as_tuple(std::forward(key)), + std::forward_as_tuple(std::forward(obj))); + break; + + case InsertionState::overflow_error: + throwOverflowError(); + break; + } + + return std::make_pair( + iterator(mKeyVals + idxAndState.first, mInfo + idxAndState.first), + InsertionState::key_found != idxAndState.second); + } + + void initData(size_t max_elements) + { + mNumElements = 0; + mMask = max_elements - 1; + mMaxNumElementsAllowed = calcMaxNumElementsAllowed(max_elements); + + auto const numElementsWithBuffer = calcNumElementsWithBuffer(max_elements); + + // malloc & zero mInfo. Faster than calloc everything. + auto const numBytesTotal = calcNumBytesTotal(numElementsWithBuffer); + ROBIN_HOOD_LOG( + "std::calloc " << numBytesTotal << " = calcNumBytesTotal(" << numElementsWithBuffer << ")") + mKeyVals = + reinterpret_cast(detail::assertNotNull(std::malloc(numBytesTotal))); + mInfo = reinterpret_cast(mKeyVals + numElementsWithBuffer); + std::memset(mInfo, 0, numBytesTotal - numElementsWithBuffer * sizeof(Node)); + + // set sentinel + mInfo[numElementsWithBuffer] = 1; + + mInfoInc = InitialInfoInc; + mInfoHashShift = InitialInfoHashShift; + } + + enum class InsertionState { overflow_error, key_found, new_node, overwrite_node }; + + // Finds key, and if not already present prepares a spot where to pot the key & value. + // This potentially shifts nodes out of the way, updates mInfo and number of inserted + // elements, so the only operation left to do is create/assign a new node at that spot. + template + std::pair insertKeyPrepareEmptySpot(OtherKey && key) + { + for (int i = 0; i < 256; ++i) { + size_t idx{}; + InfoType info{}; + keyToIdx(key, &idx, &info); + nextWhileLess(&info, &idx); + + // while we potentially have a match + while (info == mInfo[idx]) { + if (WKeyEqual::operator()(key, mKeyVals[idx].getFirst())) { + // key already exists, do NOT insert. + // see http://en.cppreference.com/w/cpp/container/unordered_map/insert + return std::make_pair(idx, InsertionState::key_found); + } + next(&info, &idx); + } + + // unlikely that this evaluates to true + if (ROBIN_HOOD_UNLIKELY(mNumElements >= mMaxNumElementsAllowed)) { + if (!increase_size()) { + return std::make_pair(size_t(0), InsertionState::overflow_error); + } + continue; + } + + // key not found, so we are now exactly where we want to insert it. + auto const insertion_idx = idx; + auto const insertion_info = info; + if (ROBIN_HOOD_UNLIKELY(insertion_info + mInfoInc > 0xFF)) { + mMaxNumElementsAllowed = 0; + } + + // find an empty spot + while (0 != mInfo[idx]) { + next(&info, &idx); + } + + if (idx != insertion_idx) { + shiftUp(idx, insertion_idx); + } + // put at empty spot + mInfo[insertion_idx] = static_cast(insertion_info); + ++mNumElements; + return std::make_pair( + insertion_idx, + idx == insertion_idx ? InsertionState::new_node : InsertionState::overwrite_node); + } + + // enough attempts failed, so finally give up. + return std::make_pair(size_t(0), InsertionState::overflow_error); + } + + bool try_increase_info() + { + ROBIN_HOOD_LOG( + "mInfoInc=" << mInfoInc << ", numElements=" << mNumElements + << ", maxNumElementsAllowed=" << calcMaxNumElementsAllowed(mMask + 1)) + if (mInfoInc <= 2) { + // need to be > 2 so that shift works (otherwise undefined behavior!) + return false; + } + // we got space left, try to make info smaller + mInfoInc = static_cast(mInfoInc >> 1U); + + // remove one bit of the hash, leaving more space for the distance info. + // This is extremely fast because we can operate on 8 bytes at once. + ++mInfoHashShift; + auto const numElementsWithBuffer = calcNumElementsWithBuffer(mMask + 1); + + for (size_t i = 0; i < numElementsWithBuffer; i += 8) { + auto val = unaligned_load(mInfo + i); + val = (val >> 1U) & UINT64_C(0x7f7f7f7f7f7f7f7f); + std::memcpy(mInfo + i, &val, sizeof(val)); + } + // update sentinel, which might have been cleared out! + mInfo[numElementsWithBuffer] = 1; + + mMaxNumElementsAllowed = calcMaxNumElementsAllowed(mMask + 1); + return true; + } + + // True if resize was possible, false otherwise + bool increase_size() + { + // nothing allocated yet? just allocate InitialNumElements + if (0 == mMask) { + initData(InitialNumElements); + return true; + } + + auto const maxNumElementsAllowed = calcMaxNumElementsAllowed(mMask + 1); + if (mNumElements < maxNumElementsAllowed && try_increase_info()) { + return true; + } + + ROBIN_HOOD_LOG( + "mNumElements=" << mNumElements << ", maxNumElementsAllowed=" << maxNumElementsAllowed + << ", load=" + << (static_cast(mNumElements) * 100.0 / + (static_cast(mMask) + 1))) + + if (mNumElements * 2 < calcMaxNumElementsAllowed(mMask + 1)) { + // we have to resize, even though there would still be plenty of space left! + // Try to rehash instead. Delete freed memory so we don't steadily increase mem in case + // we have to rehash a few times + nextHashMultiplier(); + rehashPowerOfTwo(mMask + 1, true); + } else { + // we've reached the capacity of the map, so the hash seems to work nice. Keep using it. + rehashPowerOfTwo((mMask + 1) * 2, false); + } + return true; + } + + void nextHashMultiplier() + { + // adding an *even* number, so that the multiplier will always stay odd. This is necessary + // so that the hash stays a mixing function (and thus doesn't have any information loss). + mHashMultiplier += UINT64_C(0xc4ceb9fe1a85ec54); + } + + void destroy() + { + if (0 == mMask) { + // don't deallocate! + return; + } + + Destroyer::value>{}.nodesDoNotDeallocate( + *this); + + // This protection against not deleting mMask shouldn't be needed as it's sufficiently + // protected with the 0==mMask check, but I have this anyways because g++ 7 otherwise + // reports a compile error: attempt to free a non-heap object 'fm' + // [-Werror=free-nonheap-object] + if (mKeyVals != reinterpret_cast_no_cast_align_warning(&mMask)) { + ROBIN_HOOD_LOG("std::free") + std::free(mKeyVals); + } + } + + void init() noexcept + { + mKeyVals = reinterpret_cast_no_cast_align_warning(&mMask); + mInfo = reinterpret_cast(&mMask); + mNumElements = 0; + mMask = 0; + mMaxNumElementsAllowed = 0; + mInfoInc = InitialInfoInc; + mInfoHashShift = InitialInfoHashShift; + } + + // members are sorted so no padding occurs + uint64_t mHashMultiplier = UINT64_C(0xc4ceb9fe1a85ec53); // 8 byte 8 + Node * mKeyVals = reinterpret_cast_no_cast_align_warning(&mMask); // 8 byte 16 + uint8_t * mInfo = reinterpret_cast(&mMask); // 8 byte 24 + size_t mNumElements = 0; // 8 byte 32 + size_t mMask = 0; // 8 byte 40 + size_t mMaxNumElementsAllowed = 0; // 8 byte 48 + InfoType mInfoInc = InitialInfoInc; // 4 byte 52 + InfoType mInfoHashShift = InitialInfoHashShift; // 4 byte 56 + // 16 byte 56 if NodeAllocator +}; + +} // namespace detail + +// map + +template < + typename Key, typename T, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_flat_map = detail::Table; + +template < + typename Key, typename T, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_node_map = detail::Table; + +template < + typename Key, typename T, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_map = detail::Table< + sizeof(robin_hood::pair) <= sizeof(size_t) * 6 && + std::is_nothrow_move_constructible>::value && + std::is_nothrow_move_assignable>::value, + MaxLoadFactor100, Key, T, Hash, KeyEqual>; + +// set + +template < + typename Key, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_flat_set = detail::Table; + +template < + typename Key, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_node_set = detail::Table; + +template < + typename Key, typename Hash = hash, typename KeyEqual = std::equal_to, + size_t MaxLoadFactor100 = 80> +using unordered_set = detail::Table< + sizeof(Key) <= sizeof(size_t) * 6 && std::is_nothrow_move_constructible::value && + std::is_nothrow_move_assignable::value, + MaxLoadFactor100, Key, void, Hash, KeyEqual>; + +} // namespace robin_hood + +#endif // DOWNSAMPLE_FILTER__ROBIN_HOOD_H_ diff --git a/sensing/radar_tracks_noise_filter/src/radar_tracks_noise_filter_node/radar_tracks_noise_filter_node.cpp b/sensing/radar_tracks_noise_filter/src/radar_tracks_noise_filter_node/radar_tracks_noise_filter_node.cpp index 5bd143a42eced..82a0a21ff6fdc 100644 --- a/sensing/radar_tracks_noise_filter/src/radar_tracks_noise_filter_node/radar_tracks_noise_filter_node.cpp +++ b/sensing/radar_tracks_noise_filter/src/radar_tracks_noise_filter_node/radar_tracks_noise_filter_node.cpp @@ -56,7 +56,7 @@ RadarTrackCrossingNoiseFilterNode::RadarTrackCrossingNoiseFilterNode( // Subscriber sub_tracks_ = create_subscription( - "~/input/tracks", rclcpp::QoS{1}, + "~/input/tracks", rclcpp::QoS{1}.best_effort(), std::bind(&RadarTrackCrossingNoiseFilterNode::onTracks, this, std::placeholders::_1)); // Publisher diff --git a/simulator/fault_injection/config/fault_injection.param.yaml b/simulator/fault_injection/config/fault_injection.param.yaml index e9e90a336348e..bb871163ffd4f 100644 --- a/simulator/fault_injection/config/fault_injection.param.yaml +++ b/simulator/fault_injection/config/fault_injection.param.yaml @@ -3,7 +3,7 @@ event_diag_list: vehicle_is_out_of_lane: ": lane_departure" trajectory_deviation_is_high: ": trajectory_deviation" - localization_matching_score_is_low: ": ndt_scan_matcher" + localization_matching_score_is_low: ": scan_matching_status" localization_accuracy_is_low: ": localization_error_ellipse" map_version_is_different: ": map_version" trajectory_is_invalid: ": trajectory_point_validation" diff --git a/simulator/learning_based_vehicle_model/CMakeLists.txt b/simulator/learning_based_vehicle_model/CMakeLists.txt new file mode 100644 index 0000000000000..58a3ad57e6f9e --- /dev/null +++ b/simulator/learning_based_vehicle_model/CMakeLists.txt @@ -0,0 +1,23 @@ +cmake_minimum_required(VERSION 3.14.4) +project(learning_based_vehicle_model) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +find_package(Python3 COMPONENTS Interpreter Development) +find_package(pybind11 CONFIG) + +ament_auto_add_library(${PROJECT_NAME} SHARED + DIRECTORY src +) +target_link_libraries(${PROJECT_NAME} pybind11::embed ${Python3_LIBRARIES}) +target_include_directories(${PROJECT_NAME} PRIVATE ${Python3_INCLUDE_DIRS}) + +target_compile_options(${PROJECT_NAME} PRIVATE -fvisibility=hidden) + +install( + DIRECTORY include/ + DESTINATION include/${PROJECT_NAME} +) + +ament_auto_package() diff --git a/simulator/learning_based_vehicle_model/README.md b/simulator/learning_based_vehicle_model/README.md new file mode 100644 index 0000000000000..b6df96b2d576c --- /dev/null +++ b/simulator/learning_based_vehicle_model/README.md @@ -0,0 +1,208 @@ +# Learned Model + +This is the design document for the Python learned model used in the `simple_planning_simulator` package. + +## Purpose / Use cases + + + + +This library creates an interface between models in Python and PSIM (C++). It is used to quickly deploy learned Python models in PSIM without a need for complex C++ implementation. + +## Design + + + + +The idea behind this package is that the model we want to use for simulation consists of multiple sub-models (e.g., steering model, drive model, vehicle kinematics, etc.). These sub-models are implemented in Python and can be trainable. Each sub-model has string names for all of its inputs/outputs, which are used to create model interconnections automatically (see image below). This allows us to easily switch sub-models for better customization of the simulator. + +![py_model_interface](./image/python_model_interface.png "PyModel interface") + +## Assumptions / Known limits + + + +To use this package `python3` and `pybind11` need to be installed. The only assumption on Python sub-models is their interface. + +```python +class PythonSubmodelInterface: + + def forward(self, action, state): # Required + """ + Calculate forward pass through the model and returns next_state. + """ + return list() + + def get_state_names(self): # Required + """ + Return list of string names of the model states (outputs). + """ + return list() + + def get_action_names(self): # Required + """ + Return list of string names of the model actions (inputs). + """ + return list() + + def reset(self): # Required + """ + Reset model. This function is called after load_params(). + """ + pass + + def load_params(self, path): # Required + """ + Load parameters of the model. + Inputs: + - path: Path to a parameter file to load by the model. + """ + pass + + def dtSet(self, dt): # Required + """ + Set dt of the model. + Inputs: + - dt: time step + """ + pass +``` + +## API + + + + +To successfully create a vehicle model an InterconnectedModel class needs to be set up correctly. + +### InterconnectedModel class + +#### `Constructor` + +The constructor takes no arguments. + +#### `void addSubmodel(std::tuple model_descriptor)` + +Add a new sub-model to the model. + +Inputs: + +- model_descriptor: Describes what model should be used. The model descriptor contains three strings: + - The first string is a path to a python module where the model is implemented. + - The second string is a path to the file where model parameters are stored. + - The third string is the name of the class that implements the model. + +Outputs: + +- None + +#### `void generateConnections(std::vector in_names, std::vector out_names)` + +Generate connections between sub-models and inputs/outputs of the model. + +Inputs: + +- in_names: String names for all of the model inputs in order. +- out_names: String names for all of the model outputs in order. + +Outputs: + +- None + +#### `void initState(std::vector new_state)` + +Set the initial state of the model. + +Inputs: + +- new_state: New state of the model. + +Outputs: + +- None + +#### `std::vector updatePyModel(std::vector psim_input)` + +Calculate the next state of the model by calculating the next state of all of the sub-models. + +Inputs: + +- psim_input: Input to the model. + +Outputs: + +- next_state: Next state of the model. + +#### `dtSet(double dt)` + +Set the time step of the model. + +Inputs: + +- dt: time step + +Outputs: + +- None + +### Example + +Firstly we need to set up the model. + +```C++ +InterconnectedModel vehicle; + +// Example of model descriptors +std::tuple model_descriptor_1 = { + (char*)"path_to_python_module_with_model_class_1", + (char*)nullptr, // If no param file is needed you can pass 'nullptr' + (char*)"ModelClass1" + }; + +std::tuple model_descriptor_2 = { + (char*)"path_to_python_module_with_model_class_2", + (char*)"/path_to/param_file", + (char*)"ModelClass2" // Name of the python class. Needs to use the interface from 'Assumptions' + }; + +// Create sub-models based on descriptors +vehicle.addSubmodel(model_descriptor_1); +vehicle.addSubmodel(model_descriptor_2); + +// Define STATE and INPUT names of the system +std::vector state_names = {(char*)"STATE_NAME_1", (char*)"STATE_NAME_2"}; +std::vector input_names = {(char*)"INPUT_NAME_1", (char*)"INPUT_NAME_2"}; + +// Automatically connect sub-systems with model input +vehicle.generateConnections(input_names, state_names); + +// Set the time step of the model +vehicle.dtSet(dt); +``` + +After the model is correctly set up, we can use it the following way. + +```C++ +// Example of an model input +std::vector vehicle_input = {0.0, 1.0}; // INPUT_NAME_1, INPUT_NAME_2 + +// Example of an model state +std::vector current_state = {0.2, 0.5}; // STATE_NAME_1, STATE_NAME_2 + +// Set model state +vehicle.initState(current_state); + +// Calculate the next state of the model +std::vector next_state = vehicle.updatePyModel(vehicle_input); +``` + +## References / External links + + + +## Related issues + + diff --git a/simulator/learning_based_vehicle_model/image/python_model_interface.png b/simulator/learning_based_vehicle_model/image/python_model_interface.png new file mode 100644 index 0000000000000..d81caf7a94000 Binary files /dev/null and b/simulator/learning_based_vehicle_model/image/python_model_interface.png differ diff --git a/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/interconnected_model.hpp b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/interconnected_model.hpp new file mode 100644 index 0000000000000..56a196c257189 --- /dev/null +++ b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/interconnected_model.hpp @@ -0,0 +1,130 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef LEARNING_BASED_VEHICLE_MODEL__INTERCONNECTED_MODEL_HPP_ +#define LEARNING_BASED_VEHICLE_MODEL__INTERCONNECTED_MODEL_HPP_ + +#include "learning_based_vehicle_model/model_connections_helpers.hpp" +#include "learning_based_vehicle_model/simple_pymodel.hpp" +#include "learning_based_vehicle_model/submodel_interface.hpp" + +#include +#include +#include + +#include +#include +#include +#include +#include + +namespace py = pybind11; + +class __attribute__((visibility("default"))) InterconnectedModel +{ + // Vector of unique names of inputs and outputs of sub-models + std::vector signals_vec_names; + std::vector model_signals_vec; + int num_signals; + + std::vector> submodels; + + // index in "map_in_to_sig_vec" is index in "py_inputs" and value in "map_in_to_sig_vec" is index + // in "all_variables_names" + std::vector map_in_to_sig_vec; + + // index in "map_sig_vec_to_out" is index in "py_model_outputs" and value in "map_sig_vec_to_out" + // is index in "all_variables_names" + std::vector map_sig_vec_to_out; + +public: + py::scoped_interpreter guard{}; // start the interpreter and keep it alive + + /** + * @brief constructor + */ + InterconnectedModel() + { + // Initialize python library + // cspell:ignore libpython + // Manually load libpython3.10.so as we need it for python.h. + dlopen("libpython3.10.so", RTLD_GLOBAL | RTLD_NOW); + /* + More about the line above here: + https://stackoverflow.com/questions/60719987/embedding-python-which-uses-numpy-in-c-doesnt-work-in-library-dynamically-loa + https://mail.python.org/pipermail/new-bugs-announce/2008-November/003322.html + https://stackoverflow.com/questions/67891197/ctypes-cpython-39-x86-64-linux-gnu-so-undefined-symbol-pyfloat-type-in-embedd + https://man7.org/linux/man-pages/man3/dlopen.3.html + */ + } + +private: + /** + * @brief create a mapping between vector of signal input names from PSIM to vector of signals + * @param [in] in_names vector of signal input names from PSIM + */ + void mapInputs(std::vector in_names); + + /** + * @brief create a mapping between vector of signal output names from PSIM to vector of signals + * @param [in] out_names vector of signal output names from PSIM + */ + void mapOutputs(std::vector out_names); + + /** + * @brief add unique names to the vector of signal names + * @param [in] names vector of signal names + */ + void addNamesToSigVec(const std::vector & names); + + /** + * @brief create of signal names from all sub-models and PSIM signal names + */ + void getSignalNames(std::vector in_names, std::vector out_names); + +public: + /** + * @brief automatically create connections between PSIM and all of the sub-models + * @param [in] in_names string names of inputs available from PSIM + * @param [in] out_names string names of outputs required by PSIM + */ + void generateConnections(std::vector in_names, std::vector out_names); + + /** + * @brief add a sub-model consisting of base + error model + * @param [in] submodel_desc descriptor of the sub-model + */ + void addSubmodel(std::tuple submodel_desc); + + /** + * @brief set a new model state if it was changed using PSIM interface (mainly position and + * orientation) + * @param [in] new_state new state set by PSIM + */ + void initState(std::vector new_state); + + /** + * @brief set time step for all the models + * @param [in] dt time step + */ + void dtSet(double dt); + + /** + * @brief compute next step of the PSIM model using python sub-models + * @param [in] psim_input vector of input values provided by PSIM + */ + std::vector updatePyModel(std::vector psim_input); +}; + +#endif // LEARNING_BASED_VEHICLE_MODEL__INTERCONNECTED_MODEL_HPP_ diff --git a/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/model_connections_helpers.hpp b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/model_connections_helpers.hpp new file mode 100644 index 0000000000000..3f21595662fc5 --- /dev/null +++ b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/model_connections_helpers.hpp @@ -0,0 +1,27 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef LEARNING_BASED_VEHICLE_MODEL__MODEL_CONNECTIONS_HELPERS_HPP_ +#define LEARNING_BASED_VEHICLE_MODEL__MODEL_CONNECTIONS_HELPERS_HPP_ + +#include +#include + +std::vector fillVectorUsingMap( + std::vector vector1, std::vector vector2, std::vector map, bool inverse); + +std::vector createConnectionsMap( + std::vector connection_names_1, std::vector connection_names_2); + +#endif // LEARNING_BASED_VEHICLE_MODEL__MODEL_CONNECTIONS_HELPERS_HPP_ diff --git a/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/simple_pymodel.hpp b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/simple_pymodel.hpp new file mode 100644 index 0000000000000..fd9cf5cf44de9 --- /dev/null +++ b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/simple_pymodel.hpp @@ -0,0 +1,102 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +// cspell:ignore pymodel +#ifndef LEARNING_BASED_VEHICLE_MODEL__SIMPLE_PYMODEL_HPP_ +#define LEARNING_BASED_VEHICLE_MODEL__SIMPLE_PYMODEL_HPP_ + +#include "learning_based_vehicle_model/model_connections_helpers.hpp" +#include "learning_based_vehicle_model/submodel_interface.hpp" + +#include +#include + +#include +#include + +namespace py = pybind11; + +/** + * @class SimplePyModel + * @brief This class is an interface between C++ and python models. + */ +class SimplePyModel : public SubModelInterface +{ +private: + std::string py_model_import_name; + + int num_inputs_py; + int num_outputs_py; + + py::object py_model_class; + + std::vector + map_sig_vec_to_py_model_inputs; // index in "map_sig_vec_to_py_model_inputs" is index in + // "py_inputs" and value in "map_sig_vec_to_py_model_inputs" is + // index in "signals_vec_names" + std::vector map_py_model_outputs_to_sig_vec; // index in "map_py_model_outputs_to_sig_vec" + // is index in "py_model_outputs" and value in + // "map_py_model_outputs_to_sig_vec" is index + // in "signals_vec_names" + + std::vector py_model_input_names; + std::vector py_model_state_names; + +public: + /** + * @brief constructor + * @param [in] py_model_import_name_ path to python model + * @param [in] param_file_path path to saved parameter file of the python sub-model + * @param [in] py_class_name name of the python class + */ + SimplePyModel( + std::string py_model_import_name_, std::string param_file_path, std::string py_class_name); + + /** + * @brief calculate the next state of a python model + * @param [in] model_signals_vec all available inputs from PSIM + */ + std::vector getNextState( + std::vector model_signals_vec, std::vector model_signals_vec_next) override; + + /** + * @brief set time step of the model + * @param [in] dt time step + */ + void dtSet(double dt) override; + + /** + * @brief get names of inputs of python model + */ + std::vector getInputNames() override; + + /** + * @brief get names of states of python model + */ + std::vector getStateNames() override; + + /** + * @brief create a map from model signal vector to python model inputs + * @param [in] signal_vec_names names of signals in model signal vector + */ + void mapInputs(std::vector signals_vec_names) override; + + /** + * @brief create a map from python outputs to model signal vector + * @param [in] signal_vec_names names of signals in model signal vector + */ + void mapOutputs(std::vector signals_vec_names) override; +}; + +#endif // LEARNING_BASED_VEHICLE_MODEL__SIMPLE_PYMODEL_HPP_ diff --git a/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/submodel_interface.hpp b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/submodel_interface.hpp new file mode 100644 index 0000000000000..d4662036709d5 --- /dev/null +++ b/simulator/learning_based_vehicle_model/include/learning_based_vehicle_model/submodel_interface.hpp @@ -0,0 +1,60 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef LEARNING_BASED_VEHICLE_MODEL__SUBMODEL_INTERFACE_HPP_ +#define LEARNING_BASED_VEHICLE_MODEL__SUBMODEL_INTERFACE_HPP_ + +#include + +class SubModelInterface +{ +public: + /** + * @brief set time step of the model + * @param [in] dt time step + */ + virtual void dtSet(double dt) = 0; + + /** + * @brief get names of inputs of python model + */ + virtual std::vector getInputNames() = 0; + + /** + * @brief get names of states of python model + */ + virtual std::vector getStateNames() = 0; + + /** + * @brief create a map from model signal vector to python model inputs + * @param [in] signal_vec_names names of signals in model signal vector + */ + virtual void mapInputs(std::vector signals_vec_names) = 0; + + /** + * @brief create a map from python outputs to model signal vector + * @param [in] signal_vec_names names of signals in model signal vector + */ + virtual void mapOutputs(std::vector signals_vec_names) = 0; + + /** + * @brief calculate the next state of this submodule + * @param [in] model_signals_vec values of signals in model signal vector + * @param [in] model_signals_vec_next values of signals in model signal vector to update + */ + virtual std::vector getNextState( + std::vector model_signals_vec, std::vector model_signals_vec_next) = 0; +}; + +#endif // LEARNING_BASED_VEHICLE_MODEL__SUBMODEL_INTERFACE_HPP_ diff --git a/simulator/learning_based_vehicle_model/package.xml b/simulator/learning_based_vehicle_model/package.xml new file mode 100644 index 0000000000000..18db5236c272e --- /dev/null +++ b/simulator/learning_based_vehicle_model/package.xml @@ -0,0 +1,26 @@ + + + + learning_based_vehicle_model + 1.0.0 + learning_based_vehicle_model for simple_planning_simulator + Maxime Clement + Tomas Nagy + Apache License 2.0 + + ament_cmake_auto + autoware_cmake + + autoware_cmake + + pybind11_vendor + python3-dev + + ament_cmake_ros + ament_lint_auto + autoware_lint_common + + + ament_cmake + + diff --git a/simulator/learning_based_vehicle_model/src/interconnected_model.cpp b/simulator/learning_based_vehicle_model/src/interconnected_model.cpp new file mode 100644 index 0000000000000..4dd3b321312d0 --- /dev/null +++ b/simulator/learning_based_vehicle_model/src/interconnected_model.cpp @@ -0,0 +1,138 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "learning_based_vehicle_model/interconnected_model.hpp" + +void InterconnectedModel::mapInputs(std::vector in_names) +{ + // index in "map_in_to_sig_vec" is index in "in_names" and value in "map_in_to_sig_vec" is index + // in "signals_vec_names" + map_in_to_sig_vec = createConnectionsMap(signals_vec_names, in_names); +} + +void InterconnectedModel::mapOutputs(std::vector out_names) +{ + // index in "map_sig_vec_to_out" is index in "out_names" and value in "map_sig_vec_to_out" is + // index in "signals_vec_names" + map_sig_vec_to_out = createConnectionsMap(signals_vec_names, out_names); +} + +void InterconnectedModel::addNamesToSigVec(const std::vector & names) +{ + // Check if the name is already in the vector. If not add it. + for (char * name : names) { + if ( + std::find(signals_vec_names.begin(), signals_vec_names.end(), name) == + signals_vec_names.end()) { + signals_vec_names.push_back(name); + } + } +} + +void InterconnectedModel::getSignalNames( + std::vector in_names, std::vector out_names) +{ + addNamesToSigVec(in_names); + addNamesToSigVec(out_names); + for (auto & submodel : submodels) { + addNamesToSigVec(submodel->getInputNames()); + addNamesToSigVec(submodel->getStateNames()); + } +} + +void InterconnectedModel::generateConnections( + std::vector in_names, std::vector out_names) +{ + // Create vector of signal names + getSignalNames(in_names, out_names); + num_signals = signals_vec_names.size(); + // Init vector of signal values + for (int i = 0; i < num_signals; i++) model_signals_vec.push_back(0); + + // For every sub-model create mapping from vector of signals to inputs and outputs + for (auto & submodel : submodels) { + submodel->mapInputs(signals_vec_names); + submodel->mapOutputs(signals_vec_names); + } + + // Create mapping from vector of signals to inputs and outputs of PSIM + mapInputs(in_names); + mapOutputs(out_names); +} + +void InterconnectedModel::addSubmodel( + std::tuple submodel_desc) +{ + const auto [lib_path, param_path, class_name] = submodel_desc; + auto new_model = new SimplePyModel(lib_path, param_path, class_name); + submodels.push_back(std::unique_ptr(new_model)); +} + +void InterconnectedModel::initState(std::vector new_state) +{ + bool state_changed_externally = false; + + // Check if some state was changed externally + for (size_t PSIM_STATE_IDX = 0; PSIM_STATE_IDX < new_state.size(); PSIM_STATE_IDX++) { + if ( + abs(model_signals_vec[map_sig_vec_to_out[PSIM_STATE_IDX]] - new_state[PSIM_STATE_IDX]) > + 1e-6) { + state_changed_externally = true; + break; + } + } + + if (state_changed_externally) { + // Reinitialize model + // Currently initializing model to zero -> TODO find a way how to initialize them to some + // other default values + std::fill(model_signals_vec.begin(), model_signals_vec.end(), 0.0); + + for (size_t PSIM_STATE_IDX = 0; PSIM_STATE_IDX < new_state.size(); PSIM_STATE_IDX++) { + model_signals_vec[map_sig_vec_to_out[PSIM_STATE_IDX]] = new_state[PSIM_STATE_IDX]; + } + } +} + +void InterconnectedModel::dtSet(double dt) +{ + for (auto & submodel : submodels) { + submodel->dtSet(dt); + } +} + +std::vector InterconnectedModel::updatePyModel(std::vector psim_input) +{ + // map input to vector of all variables + for (size_t PSIM_INPUT_IDX = 0; PSIM_INPUT_IDX < psim_input.size(); PSIM_INPUT_IDX++) { + model_signals_vec[map_in_to_sig_vec[PSIM_INPUT_IDX]] = psim_input[PSIM_INPUT_IDX]; + } + + // Compute forward pass through all models (order should not matter) + std::vector model_signals_vec_next = model_signals_vec; + for (auto & submodel : submodels) { + model_signals_vec_next = submodel->getNextState(model_signals_vec, model_signals_vec_next); + } + + // Map vector of all variables to + std::vector psim_next_state; + for (size_t PSIM_STATE_IDX = 0; PSIM_STATE_IDX < map_sig_vec_to_out.size(); PSIM_STATE_IDX++) { + psim_next_state.push_back(model_signals_vec_next[map_sig_vec_to_out[PSIM_STATE_IDX]]); + } + + // Update vector of all variables + model_signals_vec = model_signals_vec_next; + + return psim_next_state; +} diff --git a/simulator/learning_based_vehicle_model/src/model_connections_helpers.cpp b/simulator/learning_based_vehicle_model/src/model_connections_helpers.cpp new file mode 100644 index 0000000000000..09f7359af45bf --- /dev/null +++ b/simulator/learning_based_vehicle_model/src/model_connections_helpers.cpp @@ -0,0 +1,47 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "learning_based_vehicle_model/model_connections_helpers.hpp" + +std::vector fillVectorUsingMap( + std::vector vector1, std::vector vector2, std::vector map, bool inverse) +{ + // index in "map" is index in "vector1" and value in "map" is index in "vector2" + // inverse = 0 from 1 -> 2; inverse = 1 from 2 -> 1 + for (std::size_t idx = 0; idx < map.size(); idx++) { + if (map[idx] == -1) continue; + inverse ? vector1[idx] = vector2[map[idx]] : vector2[map[idx]] = vector1[idx]; + } + return inverse ? vector1 : vector2; +} + +std::vector createConnectionsMap( + std::vector connection_names_1, std::vector connection_names_2) +{ + std::vector connection_map; + // index in "connection_map" is index in "connection_names_2" and value in "connection_map" is + // index in "connection_names_1" + for (auto name_2 : connection_names_2) { + int mapped_idx = -1; // -1 means that we cannot create a connection between some signals + for (std::size_t NAME_1_IDX = 0; NAME_1_IDX < connection_names_1.size(); NAME_1_IDX++) { + if (strcmp(name_2, connection_names_1[NAME_1_IDX]) == 0) { // 0 means strings are the same + // and we can create connection + mapped_idx = NAME_1_IDX; + break; + } + } + connection_map.push_back(mapped_idx); + } + return connection_map; +} diff --git a/simulator/learning_based_vehicle_model/src/simple_pymodel.cpp b/simulator/learning_based_vehicle_model/src/simple_pymodel.cpp new file mode 100644 index 0000000000000..9c3cb9aa06150 --- /dev/null +++ b/simulator/learning_based_vehicle_model/src/simple_pymodel.cpp @@ -0,0 +1,111 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "learning_based_vehicle_model/simple_pymodel.hpp" + +#include +#include + +#include + +namespace py = pybind11; + +SimplePyModel::SimplePyModel( + std::string py_model_import_name_, std::string param_file_path, std::string py_class_name) +{ + // Import model class + py_model_import_name = py_model_import_name_; + if (!py_model_import_name.empty()) { + // Import python module + py::module_ imported_module = py::module_::import(py_model_import_name.c_str()); + // Initialize model class from imported module + py_model_class = imported_module.attr(py_class_name.c_str())(); + } else { + return; + } + + // Load model parameters and reset the model + if (!param_file_path.empty()) { + py::object load_params_succ = py_model_class.attr("load_params")(param_file_path.c_str()); + py_model_class.attr("reset")(); + } + + // Get string names of states of python model, convert them to C++ string and store them in + // py_model_state_names + py::list py_model_state_names_ = py_model_class.attr("get_state_names")(); + num_outputs_py = py_model_state_names_.size(); + for (int STATE_IDX = 0; STATE_IDX < num_outputs_py; STATE_IDX++) { + py_model_state_names.push_back(PyBytes_AS_STRING( + PyUnicode_AsEncodedString(py_model_state_names_[STATE_IDX].ptr(), "UTF-8", "strict"))); + } + + // Get string names of actions (inputs) of python model, convert them to C++ string and store + // them in py_model_input_names + py::list py_model_input_names_ = py_model_class.attr("get_action_names")(); + num_inputs_py = py_model_input_names_.size(); + for (int INPUT_IDX = 0; INPUT_IDX < num_inputs_py; INPUT_IDX++) { + py_model_input_names.push_back(PyBytes_AS_STRING( + PyUnicode_AsEncodedString(py_model_input_names_[INPUT_IDX].ptr(), "UTF-8", "strict"))); + } +} + +std::vector SimplePyModel::getNextState( + std::vector model_signals_vec, std::vector model_signals_vec_next) +{ + // get inputs and states of the python model from the vector of signals + std::vector py_inputs(num_inputs_py); + std::vector py_state(num_outputs_py); + py_inputs = + fillVectorUsingMap(py_inputs, model_signals_vec, map_sig_vec_to_py_model_inputs, true); + py_state = fillVectorUsingMap(py_state, model_signals_vec, map_py_model_outputs_to_sig_vec, true); + + // forward pass through the base model + py::tuple res = py_model_class.attr("forward")(py_inputs, py_state); + std::vector py_state_next = res.cast>(); + + // map outputs from python model to required outputs + std::vector next_state = fillVectorUsingMap( + py_state_next, model_signals_vec_next, map_py_model_outputs_to_sig_vec, false); + + return next_state; +} + +void SimplePyModel::dtSet(double dt) +{ + py_model_class.attr("dtSet")(dt); +} + +std::vector SimplePyModel::getInputNames() +{ + return py_model_input_names; +} + +std::vector SimplePyModel::getStateNames() +{ + return py_model_state_names; +} + +void SimplePyModel::mapInputs(std::vector signals_vec_names) +{ + // index in "map_sig_vec_to_py_model_inputs" is index in "py_inputs" and value in + // "map_sig_vec_to_py_model_inputs" is index in "signals_vec_names" + map_sig_vec_to_py_model_inputs = createConnectionsMap(signals_vec_names, py_model_input_names); +} + +void SimplePyModel::mapOutputs(std::vector signals_vec_names) +{ + // index in "map_py_model_outputs_to_sig_vec" is index in "py_model_outputs" and value in + // "map_py_model_outputs_to_sig_vec" is index in "signals_vec_names" + map_py_model_outputs_to_sig_vec = createConnectionsMap(signals_vec_names, py_model_state_names); +} diff --git a/system/diagnostic_graph_aggregator/src/common/graph/debug.hpp b/simulator/learning_based_vehicle_model/src/submodel_interface.cpp similarity index 59% rename from system/diagnostic_graph_aggregator/src/common/graph/debug.hpp rename to simulator/learning_based_vehicle_model/src/submodel_interface.cpp index 69a0eeb2c8023..906aff4b01ae0 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/debug.hpp +++ b/simulator/learning_based_vehicle_model/src/submodel_interface.cpp @@ -1,4 +1,4 @@ -// Copyright 2023 The Autoware Contributors +// Copyright 2024 The Autoware Foundation. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. @@ -12,18 +12,4 @@ // See the License for the specific language governing permissions and // limitations under the License. -#ifndef COMMON__GRAPH__DEBUG_HPP_ -#define COMMON__GRAPH__DEBUG_HPP_ - -#include -#include - -namespace diagnostic_graph_aggregator -{ - -constexpr size_t diag_debug_size = 4; -using DiagDebugData = std::array; - -} // namespace diagnostic_graph_aggregator - -#endif // COMMON__GRAPH__DEBUG_HPP_ +#include "learning_based_vehicle_model/submodel_interface.hpp" diff --git a/simulator/simple_planning_simulator/CMakeLists.txt b/simulator/simple_planning_simulator/CMakeLists.txt index 87d0f7e5fef0b..331d5e819df77 100644 --- a/simulator/simple_planning_simulator/CMakeLists.txt +++ b/simulator/simple_planning_simulator/CMakeLists.txt @@ -2,6 +2,8 @@ cmake_minimum_required(VERSION 3.14) project(simple_planning_simulator) find_package(autoware_cmake REQUIRED) +find_package(Python3 COMPONENTS Interpreter Development) +find_package(learning_based_vehicle_model REQUIRED) autoware_package() # Component @@ -14,15 +16,13 @@ ament_auto_add_library(${PROJECT_NAME} SHARED src/simple_planning_simulator/vehicle_model/sim_model_ideal_steer_acc.cpp src/simple_planning_simulator/vehicle_model/sim_model_ideal_steer_acc_geared.cpp src/simple_planning_simulator/vehicle_model/sim_model_delay_steer_vel.cpp + src/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.cpp src/simple_planning_simulator/vehicle_model/sim_model_delay_steer_acc.cpp src/simple_planning_simulator/vehicle_model/sim_model_delay_steer_acc_geared.cpp src/simple_planning_simulator/vehicle_model/sim_model_delay_steer_map_acc_geared.cpp src/simple_planning_simulator/utils/csv_loader.cpp ) -target_include_directories(${PROJECT_NAME} SYSTEM PUBLIC ${tf2_INCLUDE_DIRS}) - -target_compile_options(${PROJECT_NAME} PRIVATE -Wno-old-style-cast) # RCLCPP_ERROR_THROTTLE() has built-in old-style casts. - +target_include_directories(${PROJECT_NAME} PUBLIC ${Python3_INCLUDE_DIRS} ${learning_based_vehicle_model_INCLUDE_DIRS}) # Node executable rclcpp_components_register_node(${PROJECT_NAME} PLUGIN "simulation::simple_planning_simulator::SimplePlanningSimulator" diff --git a/simulator/simple_planning_simulator/README.md b/simulator/simple_planning_simulator/README.md index d2ed19708c5c5..1f8762b722a29 100644 --- a/simulator/simple_planning_simulator/README.md +++ b/simulator/simple_planning_simulator/README.md @@ -63,28 +63,34 @@ The purpose of this simulator is for the integration test of planning and contro - `DELAY_STEER_ACC` - `DELAY_STEER_ACC_GEARED` - `DELAY_STEER_MAP_ACC_GEARED`: applies 1D dynamics and time delay to the steering and acceleration commands. The simulated acceleration is determined by a value converted through the provided acceleration map. This model is valuable for an accurate simulation with acceleration deviations in a real vehicle. +- `LEARNED_STEER_VEL`: launches learned python models. More about this [here](../learning_based_vehicle_model). The `IDEAL` model moves ideally as commanded, while the `DELAY` model moves based on a 1st-order with time delay model. The `STEER` means the model receives the steer command. The `VEL` means the model receives the target velocity command, while the `ACC` model receives the target acceleration command. The `GEARED` suffix means that the motion will consider the gear command: the vehicle moves only one direction following the gear. The table below shows which models correspond to what parameters. The model names are written in abbreviated form (e.g. IDEAL_STEER_VEL = I_ST_V). -| Name | Type | Description | I_ST_V | I_ST_A | I_ST_A_G | D_ST_V | D_ST_A | D_ST_A_G | D_ST_M_ACC_G | Default value | unit | -| :------------------------- | :----- | :---------------------------------------------------------------------------------------------------------- | :----- | :----- | :------- | :----- | :----- | :------- | :----------- | :------------ | :------ | -| acc_time_delay | double | dead time for the acceleration input | x | x | x | x | o | o | o | 0.1 | [s] | -| steer_time_delay | double | dead time for the steering input | x | x | x | o | o | o | o | 0.24 | [s] | -| vel_time_delay | double | dead time for the velocity input | x | x | x | o | x | x | x | 0.25 | [s] | -| acc_time_constant | double | time constant of the 1st-order acceleration dynamics | x | x | x | x | o | o | o | 0.1 | [s] | -| steer_time_constant | double | time constant of the 1st-order steering dynamics | x | x | x | o | o | o | o | 0.27 | [s] | -| steer_dead_band | double | dead band for steering angle | x | x | x | o | o | o | x | 0.0 | [rad] | -| vel_time_constant | double | time constant of the 1st-order velocity dynamics | x | x | x | o | x | x | x | 0.5 | [s] | -| vel_lim | double | limit of velocity | x | x | x | o | o | o | o | 50.0 | [m/s] | -| vel_rate_lim | double | limit of acceleration | x | x | x | o | o | o | o | 7.0 | [m/ss] | -| steer_lim | double | limit of steering angle | x | x | x | o | o | o | o | 1.0 | [rad] | -| steer_rate_lim | double | limit of steering angle change rate | x | x | x | o | o | o | o | 5.0 | [rad/s] | -| steer_bias | double | bias for steering angle | x | x | x | o | o | o | o | 0.0 | [rad] | -| debug_acc_scaling_factor | double | scaling factor for accel command | x | x | x | x | o | o | x | 1.0 | [-] | -| debug_steer_scaling_factor | double | scaling factor for steer command | x | x | x | x | o | o | x | 1.0 | [-] | -| acceleration_map_path | string | path to csv file for acceleration map which converts velocity and ideal acceleration to actual acceleration | x | x | x | x | x | x | o | - | [-] | +| Name | Type | Description | I_ST_V | I_ST_A | I_ST_A_G | D_ST_V | D_ST_A | D_ST_A_G | D_ST_M_ACC_G | L_S_V | Default value | unit | +| :------------------------- | :----- | :---------------------------------------------------------------------------------------------------------- | :----- | :----- | :------- | :----- | :----- | :------- | :----------- | :---- | :------------ | :------ | +| acc_time_delay | double | dead time for the acceleration input | x | x | x | x | o | o | o | x | 0.1 | [s] | +| steer_time_delay | double | dead time for the steering input | x | x | x | o | o | o | o | x | 0.24 | [s] | +| vel_time_delay | double | dead time for the velocity input | x | x | x | o | x | x | x | x | 0.25 | [s] | +| acc_time_constant | double | time constant of the 1st-order acceleration dynamics | x | x | x | x | o | o | o | x | 0.1 | [s] | +| steer_time_constant | double | time constant of the 1st-order steering dynamics | x | x | x | o | o | o | o | x | 0.27 | [s] | +| steer_dead_band | double | dead band for steering angle | x | x | x | o | o | o | x | x | 0.0 | [rad] | +| vel_time_constant | double | time constant of the 1st-order velocity dynamics | x | x | x | o | x | x | x | x | 0.5 | [s] | +| vel_lim | double | limit of velocity | x | x | x | o | o | o | o | x | 50.0 | [m/s] | +| vel_rate_lim | double | limit of acceleration | x | x | x | o | o | o | o | x | 7.0 | [m/ss] | +| steer_lim | double | limit of steering angle | x | x | x | o | o | o | o | x | 1.0 | [rad] | +| steer_rate_lim | double | limit of steering angle change rate | x | x | x | o | o | o | o | x | 5.0 | [rad/s] | +| steer_bias | double | bias for steering angle | x | x | x | o | o | o | o | x | 0.0 | [rad] | +| debug_acc_scaling_factor | double | scaling factor for accel command | x | x | x | x | o | o | x | x | 1.0 | [-] | +| debug_steer_scaling_factor | double | scaling factor for steer command | x | x | x | x | o | o | x | x | 1.0 | [-] | +| acceleration_map_path | string | path to csv file for acceleration map which converts velocity and ideal acceleration to actual acceleration | x | x | x | x | x | x | o | x | - | [-] | +| model_module_paths | string | path to a python module where the model is implemented | x | x | x | x | x | x | x | o | - | [-] | +| model_param_paths | string | path to the file where model parameters are stored (can be empty string if no parameter file is required) | x | x | x | x | x | x | x | o | - | [-] | +| model_class_names | string | name of the class that implements the model | x | x | x | x | x | x | x | o | - | [-] | + +_Note:_ Parameters `model_module_paths`, `model_param_paths`, and `model_class_names` need to have the same length. The `acceleration_map` is used only for `DELAY_STEER_MAP_ACC_GEARED` and it shows the acceleration command on the vertical axis and the current velocity on the horizontal axis, with each cell representing the converted acceleration command that is actually used in the simulator's motion calculation. Values in between are linearly interpolated. @@ -119,6 +125,25 @@ default, 0.00, 1.39, 2.78, 4.17, 5.56, 6.94, 8.33, 9.72, 11.11, 12.50, 1 _Note_: The steering/velocity/acceleration dynamics is modeled by a first order system with a deadtime in a _delay_ model. The definition of the _time constant_ is the time it takes for the step response to rise up to 63% of its final value. The _deadtime_ is a delay in the response to a control input. +### Example of LEARNED_STEER_VEL model + +We created a few basic models to showcase how `LEARNED_STEER_VEL` works. + +1. Install [a library](https://github.com/atomyks/control_analysis_pipeline/tree/v0.1_autoware) that contains basic Python models. (branch: `v0.1_autoware`) + +2. In a file `src/vehicle/sample_vehicle_launch/sample_vehicle_description/config/simulator_model.param.yaml` set `vehicle_model_type` to `LEARNED_STEER_VEL`. In the same file set the following parameters. These models are for testing and do not require any parameter file. + +```yaml +model_module_paths: + [ + "control_analysis_pipeline.autoware_models.vehicle.kinematic", + "control_analysis_pipeline.autoware_models.steering.steer_example", + "control_analysis_pipeline.autoware_models.drive.drive_example", + ] +model_param_paths: ["", "", ""] +model_class_names: ["KinematicModel", "SteerExample", "DriveExample"] +``` + ### Default TF configuration Since the vehicle outputs `odom`->`base_link` tf, this simulator outputs the tf with the same frame_id configuration. diff --git a/simulator/simple_planning_simulator/include/simple_planning_simulator/simple_planning_simulator_core.hpp b/simulator/simple_planning_simulator/include/simple_planning_simulator/simple_planning_simulator_core.hpp index 58914d19552df..e81d4fef00abb 100644 --- a/simulator/simple_planning_simulator/include/simple_planning_simulator/simple_planning_simulator_core.hpp +++ b/simulator/simple_planning_simulator/include/simple_planning_simulator/simple_planning_simulator_core.hpp @@ -210,7 +210,8 @@ class PLANNING_SIMULATOR_PUBLIC SimplePlanningSimulator : public rclcpp::Node DELAY_STEER_ACC_GEARED = 3, IDEAL_STEER_VEL = 4, DELAY_STEER_VEL = 5, - DELAY_STEER_MAP_ACC_GEARED = 6 + DELAY_STEER_MAP_ACC_GEARED = 6, + LEARNED_STEER_VEL = 7 } vehicle_model_type_; //!< @brief vehicle model type to decide the model dynamics std::shared_ptr vehicle_model_ptr_; //!< @brief vehicle model pointer diff --git a/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model.hpp b/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model.hpp index 9fa4516c1a522..ced7349f28914 100644 --- a/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model.hpp +++ b/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model.hpp @@ -23,5 +23,6 @@ #include "simple_planning_simulator/vehicle_model/sim_model_ideal_steer_acc_geared.hpp" #include "simple_planning_simulator/vehicle_model/sim_model_ideal_steer_vel.hpp" #include "simple_planning_simulator/vehicle_model/sim_model_interface.hpp" +#include "simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.hpp" #endif // SIMPLE_PLANNING_SIMULATOR__VEHICLE_MODEL__SIM_MODEL_HPP_ diff --git a/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.hpp b/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.hpp new file mode 100644 index 0000000000000..c6301db42620e --- /dev/null +++ b/simulator/simple_planning_simulator/include/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.hpp @@ -0,0 +1,144 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef SIMPLE_PLANNING_SIMULATOR__VEHICLE_MODEL__SIM_MODEL_LEARNED_STEER_VEL_HPP_ +#define SIMPLE_PLANNING_SIMULATOR__VEHICLE_MODEL__SIM_MODEL_LEARNED_STEER_VEL_HPP_ + +#include "learning_based_vehicle_model/interconnected_model.hpp" +#include "simple_planning_simulator/vehicle_model/sim_model_interface.hpp" + +#include +#include + +#include +#include +#include +#include +#include + +/** + * @class SimModelLearnedSteerVel + * @brief calculate delay steering dynamics + */ +class SimModelLearnedSteerVel : public SimModelInterface /*delay steer velocity*/ +{ +public: + /** + * @brief constructor + * @param [in] dt delta time information to set input buffer for delay + */ + SimModelLearnedSteerVel( + double dt, std::vector model_python_paths, + std::vector model_param_paths, std::vector model_class_names); + + /** + * @brief destructor + */ + ~SimModelLearnedSteerVel() = default; + +private: + /* + Specify string names for states and inputs. So we can automatically map states and + inputs of this model to states and inputs of the python model. + */ + + std::vector state_names = {const_cast("POS_X"), const_cast("POS_Y"), + const_cast("YAW"), const_cast("YAW_RATE"), + const_cast("VX"), const_cast("VY"), + const_cast("STEER")}; + + std::vector input_names = {const_cast("VX_DES"), const_cast("STEER_DES")}; + + enum IDX { + X = 0, + Y, + YAW, + YAW_RATE, + VX, + VY, + STEER, + }; + enum IDX_U { + VX_DES = 0, + STEER_DES, + }; + + InterconnectedModel vehicle; + + double prev_vx_ = 0.0; + double current_ax_ = 0.0; + + std::deque vx_input_queue_; //!< @brief buffer for velocity command + std::deque steer_input_queue_; //!< @brief buffer for angular velocity command + + /** + * @brief get vehicle position x + */ + double getX() override; + + /** + * @brief get vehicle position y + */ + double getY() override; + + /** + * @brief get vehicle angle yaw + */ + double getYaw() override; + + /** + * @brief get vehicle longitudinal velocity + */ + double getVx() override; + + /** + * @brief get vehicle lateral velocity + */ + double getVy() override; + + /** + * @brief get vehicle longitudinal acceleration + */ + double getAx() override; + + /** + * @brief get vehicle angular-velocity wz + */ + double getWz() override; + + /** + * @brief get vehicle steering angle + */ + double getSteer() override; + + /** + * @brief update vehicle states + * @param [in] dt delta time [s] + */ + void update(const double & dt) override; + + /** + * @brief not used for this model. calculate derivative of states with delay steering model + * @param [in] state current model state + * @param [in] input input vector to model + */ + Eigen::VectorXd calcModel( + [[maybe_unused]] const Eigen::VectorXd & state, + [[maybe_unused]] const Eigen::VectorXd & input) override + { + return Eigen::VectorXd::Zero(dim_x_); + } +}; + +#endif // SIMPLE_PLANNING_SIMULATOR__VEHICLE_MODEL__SIM_MODEL_LEARNED_STEER_VEL_HPP_ diff --git a/simulator/simple_planning_simulator/package.xml b/simulator/simple_planning_simulator/package.xml index a2038486029dc..14509f83ae2fe 100644 --- a/simulator/simple_planning_simulator/package.xml +++ b/simulator/simple_planning_simulator/package.xml @@ -21,6 +21,7 @@ geometry_msgs lanelet2_core lanelet2_extension + learning_based_vehicle_model motion_utils nav_msgs rclcpp diff --git a/simulator/simple_planning_simulator/src/simple_planning_simulator/simple_planning_simulator_core.cpp b/simulator/simple_planning_simulator/src/simple_planning_simulator/simple_planning_simulator_core.cpp index e99f6d5f2cf00..524597e927f61 100644 --- a/simulator/simple_planning_simulator/src/simple_planning_simulator/simple_planning_simulator_core.cpp +++ b/simulator/simple_planning_simulator/src/simple_planning_simulator/simple_planning_simulator_core.cpp @@ -238,6 +238,13 @@ void SimplePlanningSimulator::initialize_vehicle_model() const auto vehicle_info = vehicle_info_util::VehicleInfoUtil(*this).getVehicleInfo(); const double wheelbase = vehicle_info.wheel_base_m; + std::vector model_module_paths = declare_parameter>( + "model_module_paths", std::vector({""})); + std::vector model_param_paths = declare_parameter>( + "model_param_paths", std::vector({""})); + std::vector model_class_names = declare_parameter>( + "model_class_names", std::vector({""})); + if (vehicle_model_type_str == "IDEAL_STEER_VEL") { vehicle_model_type_ = VehicleModelType::IDEAL_STEER_VEL; vehicle_model_ptr_ = std::make_shared(wheelbase); @@ -281,6 +288,12 @@ void SimplePlanningSimulator::initialize_vehicle_model() vel_lim, steer_lim, vel_rate_lim, steer_rate_lim, wheelbase, timer_sampling_time_ms_ / 1000.0, acc_time_delay, acc_time_constant, steer_time_delay, steer_time_constant, steer_bias, acceleration_map_path); + } else if (vehicle_model_type_str == "LEARNED_STEER_VEL") { + vehicle_model_type_ = VehicleModelType::LEARNED_STEER_VEL; + + vehicle_model_ptr_ = std::make_shared( + timer_sampling_time_ms_ / 1000.0, model_module_paths, model_param_paths, model_class_names); + } else { throw std::invalid_argument("Invalid vehicle_model_type: " + vehicle_model_type_str); } @@ -478,7 +491,8 @@ void SimplePlanningSimulator::set_input( if ( vehicle_model_type_ == VehicleModelType::IDEAL_STEER_VEL || - vehicle_model_type_ == VehicleModelType::DELAY_STEER_VEL) { + vehicle_model_type_ == VehicleModelType::DELAY_STEER_VEL || + vehicle_model_type_ == VehicleModelType::LEARNED_STEER_VEL) { input << vel, steer; } else if ( // NOLINT vehicle_model_type_ == VehicleModelType::IDEAL_STEER_ACC || @@ -566,7 +580,9 @@ void SimplePlanningSimulator::set_initial_state(const Pose & pose, const Twist & const double x = pose.position.x; const double y = pose.position.y; const double yaw = tf2::getYaw(pose.orientation); + const double yaw_rate = 0.0; const double vx = twist.linear.x; + const double vy = 0.0; const double steer = 0.0; const double accx = 0.0; @@ -581,6 +597,8 @@ void SimplePlanningSimulator::set_initial_state(const Pose & pose, const Twist & } else if ( // NOLINT vehicle_model_type_ == VehicleModelType::DELAY_STEER_VEL) { state << x, y, yaw, vx, steer; + } else if (vehicle_model_type_ == VehicleModelType::LEARNED_STEER_VEL) { + state << x, y, yaw, yaw_rate, vx, vy, steer; } else if ( // NOLINT vehicle_model_type_ == VehicleModelType::DELAY_STEER_ACC || vehicle_model_type_ == VehicleModelType::DELAY_STEER_ACC_GEARED || diff --git a/simulator/simple_planning_simulator/src/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.cpp b/simulator/simple_planning_simulator/src/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.cpp new file mode 100644 index 0000000000000..fba34e04ade7c --- /dev/null +++ b/simulator/simple_planning_simulator/src/simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.cpp @@ -0,0 +1,88 @@ +// Copyright 2024 The Autoware Foundation. +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "simple_planning_simulator/vehicle_model/sim_model_learned_steer_vel.hpp" + +#include "learning_based_vehicle_model/interconnected_model.hpp" + +#include + +SimModelLearnedSteerVel::SimModelLearnedSteerVel( + double dt, std::vector model_python_paths, + std::vector model_param_paths, std::vector model_class_names) +: SimModelInterface(7 /* dim x */, 2 /* dim u */) +{ + for (size_t i = 0; i < model_python_paths.size(); i++) { + std::tuple descriptor = { + model_python_paths[i], model_param_paths[i], model_class_names[i]}; + vehicle.addSubmodel(descriptor); + } + + vehicle.generateConnections(input_names, state_names); + + vehicle.dtSet(dt); +} + +double SimModelLearnedSteerVel::getX() +{ + return state_(IDX::X); +} +double SimModelLearnedSteerVel::getY() +{ + return state_(IDX::Y); +} +double SimModelLearnedSteerVel::getYaw() +{ + return state_(IDX::YAW); +} +double SimModelLearnedSteerVel::getVx() +{ + return state_(IDX::VX); +} +double SimModelLearnedSteerVel::getVy() +{ + return state_(IDX::VY); +} +double SimModelLearnedSteerVel::getAx() +{ + return current_ax_; +} +double SimModelLearnedSteerVel::getWz() +{ + return state_(IDX::YAW_RATE); +} +double SimModelLearnedSteerVel::getSteer() +{ + return state_(IDX::STEER); +} +void SimModelLearnedSteerVel::update(const double & dt) +{ + // Eigen::VectorXd to std::vector for model input + std::vector vehicle_input_(input_.data(), input_.data() + input_.size()); + + // Eigen::VectorXd to std::vector for model state + std::vector new_state(state_.data(), state_.data() + state_.size()); + // set model state + vehicle.initState(new_state); + + // model forward + std::vector vehicle_state_ = vehicle.updatePyModel(vehicle_input_); + + // std::vector to Eigen::VectorXd + for (size_t i = 0; i < vehicle_state_.size(); i++) state_[i] = vehicle_state_[i]; + + // Calculate + current_ax_ = (input_(IDX_U::VX_DES) - prev_vx_) / dt; + prev_vx_ = input_(IDX_U::VX_DES); +} diff --git a/system/component_state_monitor/config/topics.yaml b/system/component_state_monitor/config/topics.yaml index f056892849fbc..098aa0e56b1ae 100644 --- a/system/component_state_monitor/config/topics.yaml +++ b/system/component_state_monitor/config/topics.yaml @@ -50,19 +50,6 @@ error_rate: 1.0 timeout: 1.0 -- module: localization - mode: [online, logging_simulation] - type: autonomous - args: - node_name_suffix: pose_estimator_pose - topic: /localization/pose_estimator/pose_with_covariance - topic_type: geometry_msgs/msg/PoseWithCovarianceStamped - best_effort: false - transient_local: false - warn_rate: 2.0 - error_rate: 1.0 - timeout: 1.0 - - module: perception mode: [online, logging_simulation] type: launch diff --git a/system/diagnostic_graph_aggregator/CMakeLists.txt b/system/diagnostic_graph_aggregator/CMakeLists.txt index 574978ec5adce..905cc07d81da1 100644 --- a/system/diagnostic_graph_aggregator/CMakeLists.txt +++ b/system/diagnostic_graph_aggregator/CMakeLists.txt @@ -5,32 +5,27 @@ find_package(autoware_cmake REQUIRED) autoware_package() ament_auto_add_library(${PROJECT_NAME} SHARED + src/common/graph/error.cpp + src/common/graph/data.cpp src/common/graph/config.cpp - src/common/graph/debug.cpp + src/common/graph/loader.cpp src/common/graph/graph.cpp src/common/graph/units.cpp ) ament_auto_add_executable(aggregator src/node/aggregator.cpp - src/node/plugin/modes.cpp + src/node/availability.cpp ) target_include_directories(aggregator PRIVATE src/common) -ament_auto_add_executable(converter - src/node/converter.cpp -) -target_include_directories(converter PRIVATE src/common) - ament_auto_add_executable(tree src/tool/tree.cpp - src/tool/utils/loader.cpp ) target_include_directories(tree PRIVATE src/common) ament_auto_add_executable(plantuml src/tool/plantuml.cpp - src/tool/utils/loader.cpp ) target_include_directories(plantuml PRIVATE src/common) @@ -45,10 +40,4 @@ if(BUILD_TESTING) target_include_directories(gtest_${PROJECT_NAME} PRIVATE src/common) endif() -install(PROGRAMS - script/dump.py - RENAME dump - DESTINATION lib/${PROJECT_NAME} -) - ament_auto_package(INSTALL_TO_SHARE config example launch) diff --git a/system/diagnostic_graph_aggregator/README.md b/system/diagnostic_graph_aggregator/README.md index cc49ed88ba98f..c0cd78e0610c2 100644 --- a/system/diagnostic_graph_aggregator/README.md +++ b/system/diagnostic_graph_aggregator/README.md @@ -3,20 +3,25 @@ ## Overview The diagnostic graph aggregator node subscribes to diagnostic array and publishes aggregated diagnostic graph. -As shown in the diagram below, this node introduces extra diagnostic status for intermediate functional unit. -Diagnostic status dependencies will be directed acyclic graph (DAG). +As shown in the diagram below, this node introduces extra diagnostic status for intermediate functional units. ![overview](./doc/overview.drawio.svg) -## Diagnostics graph message +## Diagnostic graph structures -The diagnostics graph that this node outputs is a combination of diagnostic status and connections between them. -This graph consists of an array of diagnostic nodes, and each node has a status and links. -This link contains an index indicating the position of the node in the graph. -Therefore, the graph can be reconstructed from the array of nodes using links. -The following is an example of a message representing the graph in the overview section. +The diagnostic graph is actually a set of fault tree analysis (FTA) for each operation mode of Autoware. +Since the status of the same node may be referenced by multiple nodes, the overall structure is a directed acyclic graph (DAG). +Each node in the diagnostic graph represents the diagnostic status of a specific functional unit, including the input diagnostics. +So we define this as "unit", and call the unit corresponding to the input diagnosis "diag unit" and the others "node unit". -![message](./doc/message.drawio.svg) +Every unit has an error level that is the same as DiagnosticStatus, a unit type, and optionally a unit path. +In addition, every diag unit has a message, a hardware_id, and values that are the same as DiagnosticStatus. +The unit type represents how the unit status is calculated, such as AND or OR. +The unit path is any unique string that represents the functionality of the unit. + +NOTE: This feature is currently under development. +The diagnostic graph also supports "link" because there are cases where connections between units have additional status. +For example, it is natural that many functional units will have an error status until initialization is complete. ## Operation mode availability @@ -34,11 +39,13 @@ This feature breaks the generality of the graph and may be changed to a plugin o ## Interfaces -| Interface Type | Interface Name | Data Type | Description | -| -------------- | ------------------------------------- | ------------------------------------------------- | ------------------ | -| subscription | `/diagnostics` | `diagnostic_msgs/msg/DiagnosticArray` | Diagnostics input. | -| publisher | `/diagnostics_graph` | `tier4_system_msgs/msg/DiagnosticGraph` | Diagnostics graph. | -| publisher | `/system/operation_mode/availability` | `tier4_system_msgs/msg/OperationModeAvailability` | mode availability. | +| Interface Type | Interface Name | Data Type | Description | +| -------------- | ------------------------------------- | ------------------------------------------------- | ---------------------------------- | +| subscription | `/diagnostics` | `diagnostic_msgs/msg/DiagnosticArray` | Diagnostics input. | +| publisher | `/diagnostics_graph/unknowns` | `diagnostic_msgs/msg/DiagnosticArray` | Diagnostics not included in graph. | +| publisher | `/diagnostics_graph/struct` | `tier4_system_msgs/msg/DiagGraphStruct` | Diagnostic graph (static part). | +| publisher | `/diagnostics_graph/status` | `tier4_system_msgs/msg/DiagGraphStatus` | Diagnostic graph (dynamic part). | +| publisher | `/system/operation_mode/availability` | `tier4_system_msgs/msg/OperationModeAvailability` | Operation mode availability. | ## Parameters @@ -49,7 +56,6 @@ This feature breaks the generality of the graph and may be changed to a plugin o | `input_qos_depth` | `uint` | QoS depth of input array topic. | | `graph_qos_depth` | `uint` | QoS depth of output graph topic. | | `use_operation_mode_availability` | `bool` | Use operation mode availability publisher. | -| `use_debug_mode` | `bool` | Use debug output to stdout. | ## Examples @@ -73,13 +79,12 @@ ros2 launch diagnostic_graph_aggregator example-edit.launch.xml ## Debug tools -- [dump](./doc/tool/dump.md) -- [converter](./doc/tool/converter.md) - [tree](./doc/tool/tree.md) +- [diagnostic_graph_utils](../diagnostic_graph_utils/README.md) ## Graph file format - [graph](./doc/format/graph.md) - [path](./doc/format/path.md) -- [node](./doc/format/node.md) +- [unit](./doc/format/unit.md) - [edit](./doc/format/edit.md) diff --git a/system/diagnostic_graph_aggregator/config/default.param.yaml b/system/diagnostic_graph_aggregator/config/default.param.yaml index 2660396bd86df..4fb2303bbd898 100644 --- a/system/diagnostic_graph_aggregator/config/default.param.yaml +++ b/system/diagnostic_graph_aggregator/config/default.param.yaml @@ -1,7 +1,6 @@ /**: ros__parameters: use_operation_mode_availability: true - use_debug_mode: false rate: 10.0 input_qos_depth: 1000 graph_qos_depth: 1 diff --git a/system/diagnostic_graph_aggregator/doc/format/edit/remove.md b/system/diagnostic_graph_aggregator/doc/format/edit/remove.md index 6cd4b25e98828..9a9847e5c6dd3 100644 --- a/system/diagnostic_graph_aggregator/doc/format/edit/remove.md +++ b/system/diagnostic_graph_aggregator/doc/format/edit/remove.md @@ -1,10 +1,10 @@ # Remove -The `remove` object is a edit that removes other nodes. +The `remove` object is a edit that removes other units. ## Format | Name | Type | Required | Description | | ------ | -------- | -------- | ---------------------------------------- | | `type` | `string` | yes | Specify `remove` when using this object. | -| `path` | `string` | yes | The path of the node to remove. | +| `path` | `string` | yes | The path of the unit to remove. | diff --git a/system/diagnostic_graph_aggregator/doc/format/graph.md b/system/diagnostic_graph_aggregator/doc/format/graph.md index 9dace8a2f0e6d..efe85c6e6aaff 100644 --- a/system/diagnostic_graph_aggregator/doc/format/graph.md +++ b/system/diagnostic_graph_aggregator/doc/format/graph.md @@ -7,5 +7,5 @@ The graph object is the top level structure that makes up the configuration file | Name | Type | Required | Description | | ------- | -------------------------------------- | -------- | ------------------------------------------------- | | `files` | list\[[path](./path.md)\] | no | List of path objects for importing subgraphs. | -| `nodes` | list\[[node](./node.md)\] | no | List of node objects that make up the graph. | +| `units` | list\[[unit](./unit.md)\] | no | List of unit objects that make up the graph. | | `edits` | list\[[edit](./edit.md)\] | no | List of edit objects to partially edit the graph. | diff --git a/system/diagnostic_graph_aggregator/doc/format/node/remap.md b/system/diagnostic_graph_aggregator/doc/format/node/remap.md deleted file mode 100644 index abf0d11fae12d..0000000000000 --- a/system/diagnostic_graph_aggregator/doc/format/node/remap.md +++ /dev/null @@ -1,21 +0,0 @@ -# Constant - -!!! warning - - This object is under development. It may be removed in the future. - -The remapping object is a node that converts error levels. - -## Format - -| Name | Type | Required | Description | -| ------ | -------------------------------------- | -------- | ---------------------------------------------------- | -| `type` | `string` | yes | Specify remapping type when using this object. | -| `list` | list\[[node](../node.md)] | yes | List of input node objects. The list size must be 1. | - -## Remapping types - -The supported remapping types are as follows. - -- `warn-to-ok` -- `warn-to-error` diff --git a/system/diagnostic_graph_aggregator/doc/format/node.md b/system/diagnostic_graph_aggregator/doc/format/unit.md similarity index 59% rename from system/diagnostic_graph_aggregator/doc/format/node.md rename to system/diagnostic_graph_aggregator/doc/format/unit.md index 0f4b52b9b8a72..6df4671259f9d 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit.md @@ -1,24 +1,24 @@ -# Node +# Unit -The `node` is a base object that makes up the diagnostic graph. -Any derived object can be used where a node object is required. +The `unit` is a base object that makes up the diagnostic graph. +Any derived object can be used where a unit object is required. ## Format | Name | Type | Required | Description | | ------ | -------- | -------- | ------------------------------------------------- | | `type` | `string` | yes | The string indicating the type of derived object. | -| `path` | `string` | no | Any string to reference from other nodes. | +| `path` | `string` | no | Any string to reference from other units. | ## Derived objects -- [diag](./node/diag.md) -- [and](./node/and.md) -- [or](./node/or.md) -- [remapping](./node/remap.md) +- [diag](./unit/diag.md) +- [and](./unit/and.md) +- [or](./unit/or.md) +- [remapping](./unit/remap.md) - warn-to-ok - warn-to-error -- [constant](./node/const.md) +- [constant](./unit/const.md) - ok - warn - error diff --git a/system/diagnostic_graph_aggregator/doc/format/node/and.md b/system/diagnostic_graph_aggregator/doc/format/unit/and.md similarity index 71% rename from system/diagnostic_graph_aggregator/doc/format/node/and.md rename to system/diagnostic_graph_aggregator/doc/format/unit/and.md index 562018bf0995b..ea14d5101a53c 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node/and.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit/and.md @@ -1,6 +1,6 @@ # And -The `and` object is a node that is evaluated as the maximum error level of the input nodes. +The `and` object is a unit that is evaluated as the maximum error level of the input units. Note that error level `stale` is treated as `error`. ## Format @@ -8,7 +8,7 @@ Note that error level `stale` is treated as `error`. | Name | Type | Required | Description | | ------ | -------------------------------------- | -------- | ------------------------------------------------------------ | | `type` | string | yes | Specify `and` or `short-circuit-and` when using this object. | -| `list` | list\[[node](../node.md)] | yes | List of input node objects. | +| `list` | list\[[unit](../unit.md)] | yes | List of input unit objects. | ## Short-circuit evaluation diff --git a/system/diagnostic_graph_aggregator/doc/format/node/const.md b/system/diagnostic_graph_aggregator/doc/format/unit/const.md similarity index 86% rename from system/diagnostic_graph_aggregator/doc/format/node/const.md rename to system/diagnostic_graph_aggregator/doc/format/unit/const.md index 13495be6cdbda..dac095814a616 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node/const.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit/const.md @@ -1,6 +1,6 @@ # Constant -The constant object is a node with a fixed error level. +The constant object is a unit with a fixed error level. ## Format diff --git a/system/diagnostic_graph_aggregator/doc/format/node/diag.md b/system/diagnostic_graph_aggregator/doc/format/unit/diag.md similarity index 84% rename from system/diagnostic_graph_aggregator/doc/format/node/diag.md rename to system/diagnostic_graph_aggregator/doc/format/unit/diag.md index beba8ed0df5b4..377284322d9a9 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node/diag.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit/diag.md @@ -1,6 +1,6 @@ # Diag -The `diag` object is a node that refers to a specific status within the source diagnostics. +The `diag` object is a unit that refers to a specific status within the source diagnostics. ## Format diff --git a/system/diagnostic_graph_aggregator/doc/format/node/link.md b/system/diagnostic_graph_aggregator/doc/format/unit/link.md similarity index 67% rename from system/diagnostic_graph_aggregator/doc/format/node/link.md rename to system/diagnostic_graph_aggregator/doc/format/unit/link.md index c23aa92575e54..3649bc49df112 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node/link.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit/link.md @@ -1,10 +1,10 @@ # Link -The `link` object is a node that refers to other nodes. +The `link` object is a unit that refers to another unit. ## Format | Name | Type | Required | Description | | ------ | -------- | -------- | -------------------------------------- | | `type` | `string` | yes | Specify `link` when using this object. | -| `link` | `string` | yes | The path of the node to reference. | +| `link` | `string` | yes | The path of the unit to reference. | diff --git a/system/diagnostic_graph_aggregator/doc/format/node/or.md b/system/diagnostic_graph_aggregator/doc/format/unit/or.md similarity index 66% rename from system/diagnostic_graph_aggregator/doc/format/node/or.md rename to system/diagnostic_graph_aggregator/doc/format/unit/or.md index 74e94ffd628e3..66d0d5fa75125 100644 --- a/system/diagnostic_graph_aggregator/doc/format/node/or.md +++ b/system/diagnostic_graph_aggregator/doc/format/unit/or.md @@ -1,6 +1,6 @@ # Or -The `or` object is a node that is evaluated as the minimum error level of the input nodes. +The `or` object is a unit that is evaluated as the minimum error level of the input units. Note that error level `stale` is treated as `error`. ## Format @@ -8,4 +8,4 @@ Note that error level `stale` is treated as `error`. | Name | Type | Required | Description | | ------ | -------------------------------------- | -------- | ------------------------------------ | | `type` | string | yes | Specify `or` when using this object. | -| `list` | list\[[node](../node.md)] | yes | List of input node objects. | +| `list` | list\[[unit](../unit.md)] | yes | List of input unit objects. | diff --git a/system/diagnostic_graph_aggregator/doc/format/unit/remap.md b/system/diagnostic_graph_aggregator/doc/format/unit/remap.md new file mode 100644 index 0000000000000..35bbf9cb5b408 --- /dev/null +++ b/system/diagnostic_graph_aggregator/doc/format/unit/remap.md @@ -0,0 +1,21 @@ +# Constant + +!!! warning + + This object is under development. It may be removed in the future. + +The remapping object is a unit that converts error levels. + +## Format + +| Name | Type | Required | Description | +| ------ | ------------------------------- | -------- | ---------------------------------------------- | +| `type` | `string` | yes | Specify remapping type when using this object. | +| `item` | [unit](../unit.md) | yes | Input unit object. | + +## Remapping types + +The supported remapping types are as follows. + +- `warn-to-ok` +- `warn-to-error` diff --git a/system/diagnostic_graph_aggregator/doc/message.drawio.svg b/system/diagnostic_graph_aggregator/doc/message.drawio.svg deleted file mode 100644 index aef836dccf235..0000000000000 --- a/system/diagnostic_graph_aggregator/doc/message.drawio.svg +++ /dev/null @@ -1,677 +0,0 @@ - - - - - - - -
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- - - - - - - - - - Text is not SVG - cannot display - - - diff --git a/system/diagnostic_graph_aggregator/doc/tool/converter.md b/system/diagnostic_graph_aggregator/doc/tool/converter.md deleted file mode 100644 index 2351bc1e01054..0000000000000 --- a/system/diagnostic_graph_aggregator/doc/tool/converter.md +++ /dev/null @@ -1,29 +0,0 @@ -# Converter tool - -This tool converts `/diagnostics_graph` to `/diagnostics_agg` so it can be read by tools such as `rqt_runtime_monitor` and `rqt_robot_monitor`. - -## Usage - -```bash -ros2 launch diagnostic_graph_aggregator converter.launch.xml complement:=false -``` - -The `complement` argument specifies whether to add an intermediate path that does not exist. -This means that if the graph contains paths `/A/B` and `/A/B/C/D/E`, the intermediate paths `/A`, `/A/B/C` and `/A/B/C/D` will be added. -This is useful for tree view in `rqt_robot_monitor`. The completed node has an error level of `STALE`. - -## Examples - -```bash -ros2 launch diagnostic_graph_aggregator example-main.launch.xml complement:=false -ros2 run rqt_runtime_monitor rqt_runtime_monitor --ros-args -r diagnostics:=diagnostics_agg -``` - -![rqt_runtime_monitor](./images/rqt_runtime_monitor.png) - -```bash -ros2 launch diagnostic_graph_aggregator example-main.launch.xml complement:=true -ros2 run rqt_robot_monitor rqt_robot_monitor -``` - -![rqt_robot_monitor](./images/rqt_robot_monitor.png) diff --git a/system/diagnostic_graph_aggregator/doc/tool/dump.md b/system/diagnostic_graph_aggregator/doc/tool/dump.md deleted file mode 100644 index 33f05ff866603..0000000000000 --- a/system/diagnostic_graph_aggregator/doc/tool/dump.md +++ /dev/null @@ -1,36 +0,0 @@ -# Dump tool - -This tool displays `/diagnostics_graph` in table format. - -## Usage - -```bash -ros2 run diagnostic_graph_aggregator dump -``` - -## Examples - -```bash -ros2 launch diagnostic_graph_aggregator example-main.launch.xml -ros2 run diagnostic_graph_aggregator dump -``` - -```txt -| ----- | ----- | -------------------------------- | ----- | -| index | level | name | links | -| ----- | ----- | -------------------------------- | ----- | -| 0 | OK | /sensing/radars/front | | -| 1 | OK | /sensing/lidars/front | | -| 2 | ERROR | /sensing/lidars/top | | -| 3 | OK | /functions/obstacle_detection | 1 0 | -| 4 | ERROR | /functions/pose_estimation | 2 | -| 5 | OK | /external/remote_command | | -| 6 | OK | /external/joystick_command | | -| 7 | ERROR | /autoware/modes/pull_over | 4 3 | -| 8 | OK | /autoware/modes/comfortable_stop | 3 | -| 9 | OK | /autoware/modes/emergency_stop | | -| 10 | OK | /autoware/modes/remote | 5 | -| 11 | OK | /autoware/modes/local | 6 | -| 12 | ERROR | /autoware/modes/autonomous | 4 3 | -| 13 | OK | /autoware/modes/stop | | -``` diff --git a/system/diagnostic_graph_aggregator/doc/tool/images/rqt_robot_monitor.png b/system/diagnostic_graph_aggregator/doc/tool/images/rqt_robot_monitor.png deleted file mode 100644 index e4aa169f02add..0000000000000 Binary files a/system/diagnostic_graph_aggregator/doc/tool/images/rqt_robot_monitor.png and /dev/null differ diff --git a/system/diagnostic_graph_aggregator/doc/tool/tree.md b/system/diagnostic_graph_aggregator/doc/tool/tree.md index 79fa61f527038..12b664ecc48d6 100644 --- a/system/diagnostic_graph_aggregator/doc/tool/tree.md +++ b/system/diagnostic_graph_aggregator/doc/tool/tree.md @@ -11,30 +11,30 @@ ros2 run diagnostic_graph_aggregator tree ## Examples ```bash -ros2 run diagnostic_graph_aggregator tree system/diagnostic_graph_aggregator/example/graph/main.yaml +ros2 run diagnostic_graph_aggregator tree '$(find-pkg-share diagnostic_graph_aggregator)/example/graph/main.yaml' ``` ```txt -===== root nodes ================================= +===== Top-level trees ============================ +- /autoware/modes/autonomous (and) + - /functions/pose_estimation (and) + - /functions/obstacle_detection (or) - /autoware/modes/local (and) - /external/joystick_command (diag) +- /autoware/modes/remote (and) + - /external/remote_command (diag) - /autoware/modes/comfortable_stop (and) - /functions/obstacle_detection (or) - /autoware/modes/pull_over (and) - /functions/pose_estimation (and) - /functions/obstacle_detection (or) -- /autoware/modes/autonomous (and) - - /functions/pose_estimation (and) - - /functions/obstacle_detection (or) -- /autoware/modes/remote (and) - - /external/remote_command (diag) -===== intermediate nodes ========================= +===== Subtrees =================================== +- /functions/pose_estimation (and) + - /sensing/lidars/top (diag) - /functions/obstacle_detection (or) - /sensing/lidars/front (diag) - /sensing/radars/front (diag) -- /functions/pose_estimation (and) - - /sensing/lidars/top (diag) -===== isolated nodes ============================= -- /autoware/modes/stop (const) -- /autoware/modes/emergency_stop (const) +===== Isolated units ============================= +- /autoware/modes/stop (ok) +- /autoware/modes/emergency_stop (ok) ``` diff --git a/system/diagnostic_graph_aggregator/example/dummy-diags.py b/system/diagnostic_graph_aggregator/example/dummy-diags.py index 08f81bcd738ed..210462271a1ea 100755 --- a/system/diagnostic_graph_aggregator/example/dummy-diags.py +++ b/system/diagnostic_graph_aggregator/example/dummy-diags.py @@ -53,9 +53,9 @@ def create_status(name: str): if __name__ == "__main__": diags = [ - "lidar_driver/top: status", - "lidar_driver/front: status", - "radar_driver/front: status", + "lidar_driver_top: status", + "lidar_driver_front: status", + "radar_driver_front: status", "external_command_checker: joystick_command", "external_command_checker: remote_command", ] diff --git a/system/diagnostic_graph_aggregator/example/example-edit.launch.xml b/system/diagnostic_graph_aggregator/example/example-edit.launch.xml index c168b76f19c21..d56f76b1726cf 100644 --- a/system/diagnostic_graph_aggregator/example/example-edit.launch.xml +++ b/system/diagnostic_graph_aggregator/example/example-edit.launch.xml @@ -1,10 +1,6 @@ - - + - - - diff --git a/system/diagnostic_graph_aggregator/example/example-main.launch.xml b/system/diagnostic_graph_aggregator/example/example-main.launch.xml index cdc1bc8afca53..b7019640e993c 100644 --- a/system/diagnostic_graph_aggregator/example/example-main.launch.xml +++ b/system/diagnostic_graph_aggregator/example/example-main.launch.xml @@ -1,10 +1,6 @@ - - - - diff --git a/system/diagnostic_graph_aggregator/example/graph/main.yaml b/system/diagnostic_graph_aggregator/example/graph/main.yaml index 2bea907d9c119..b48c1ebe801ea 100644 --- a/system/diagnostic_graph_aggregator/example/graph/main.yaml +++ b/system/diagnostic_graph_aggregator/example/graph/main.yaml @@ -2,7 +2,7 @@ files: - { path: $(dirname)/module1.yaml } - { path: $(dirname)/module2.yaml } -nodes: +units: - path: /autoware/modes/stop type: ok diff --git a/system/diagnostic_graph_aggregator/example/graph/module1.yaml b/system/diagnostic_graph_aggregator/example/graph/module1.yaml index 07d4951b89446..1e1ae9b994587 100644 --- a/system/diagnostic_graph_aggregator/example/graph/module1.yaml +++ b/system/diagnostic_graph_aggregator/example/graph/module1.yaml @@ -1,4 +1,4 @@ -nodes: +units: - path: /functions/pose_estimation type: and list: @@ -12,12 +12,15 @@ nodes: - path: /sensing/lidars/top type: diag - diag: "lidar_driver/top: status" + node: lidar_driver_top + name: status - path: /sensing/lidars/front type: diag - diag: "lidar_driver/front: status" + node: lidar_driver_front + name: status - path: /sensing/radars/front type: diag - diag: "radar_driver/front: status" + node: radar_driver_front + name: status diff --git a/system/diagnostic_graph_aggregator/example/graph/module2.yaml b/system/diagnostic_graph_aggregator/example/graph/module2.yaml index a03701b661ba9..47e100087c650 100644 --- a/system/diagnostic_graph_aggregator/example/graph/module2.yaml +++ b/system/diagnostic_graph_aggregator/example/graph/module2.yaml @@ -1,8 +1,10 @@ -nodes: +units: - path: /external/joystick_command type: diag - diag: "external_command_checker: joystick_command" + node: external_command_checker + name: joystick_command - path: /external/remote_command type: diag - diag: "external_command_checker: remote_command" + node: external_command_checker + name: remote_command diff --git a/system/diagnostic_graph_aggregator/launch/converter.launch.xml b/system/diagnostic_graph_aggregator/launch/converter.launch.xml deleted file mode 100644 index 9111338bf622a..0000000000000 --- a/system/diagnostic_graph_aggregator/launch/converter.launch.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - diff --git a/system/diagnostic_graph_aggregator/src/common/graph/config.cpp b/system/diagnostic_graph_aggregator/src/common/graph/config.cpp index 39044d1c82bf9..c9d281a5c886e 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/config.cpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/config.cpp @@ -14,341 +14,297 @@ #include "config.hpp" -#include "error.hpp" +#include "names.hpp" +#include "types.hpp" #include +#include #include -#include +#include #include -#include #include #include #include -#include - -// DEBUG -#include namespace diagnostic_graph_aggregator { -template -void extend(std::vector & u, const std::vector & v) +std::string resolve_substitution(const std::string & substitution, const TreeData & data) { - u.insert(u.end(), v.begin(), v.end()); -} + std::stringstream ss(substitution); + std::string word; + std::vector words; + while (getline(ss, word, ' ')) { + words.push_back(word); + } -template -auto enumerate(const std::vector & v) -{ - std::vector> result; - for (size_t i = 0; i < v.size(); ++i) { - result.push_back(std::make_pair(i, v[i])); + if (words.size() == 2 && words[0] == "find-pkg-share") { + return ament_index_cpp::get_package_share_directory(words[1]); } - return result; + if (words.size() == 1 && words[0] == "dirname") { + return std::filesystem::path(data.path().file()).parent_path(); + } + throw UnknownSubstitution(data.path(), substitution); } -ConfigData::ConfigData(const std::string & path) +std::string resolve_file_path(const std::string & path, const TreeData & data) { - file = path; + static const std::regex pattern(R"(\$\(([^()]*)\))"); + std::smatch m; + std::string result = path; + while (std::regex_search(result, m, pattern)) { + const std::string prefix = m.prefix(); + const std::string suffix = m.suffix(); + result = prefix + resolve_substitution(m.str(1), data) + suffix; + } + return result; } -ConfigData ConfigData::load(YAML::Node yaml) +FileLoader::FileLoader(const PathConfig * path) { - if (!yaml.IsMap()) { - throw error("object is not a dict type", *this); - } - for (const auto & kv : yaml) { - object[kv.first.as()] = kv.second; + if (!std::filesystem::exists(path->resolved)) { + throw FileNotFound(path->data.path(), path->resolved); } - return *this; + + TreeData tree = TreeData::Load(path->resolved); + const auto paths = tree.optional("files").children("files"); + const auto edits = tree.optional("edits").children("edits"); + const auto units = tree.optional("units").children("units"); + for (const auto & data : paths) create_path_config(data); + for (const auto & data : edits) create_edit_config(data); + for (const auto & data : units) create_unit_config(data); } -ConfigData ConfigData::type(const std::string & name) const +PathConfig * FileLoader::create_path_config(const TreeData & data) { - ConfigData data(file); - data.mark = mark.empty() ? name : mark + "-" + name; - return data; + const auto path = paths_.emplace_back(std::make_unique(data)).get(); + path->original = path->data.required("path").text(); + path->resolved = resolve_file_path(path->original, data); + return path; } -ConfigData ConfigData::node(const size_t index) const +EditConfig * FileLoader::create_edit_config(const TreeData & data) { - return type(std::to_string(index)); + const auto edit = edits_.emplace_back(std::make_unique(data)).get(); + edit->type = edit->data.required("type").text(); + return edit; } -std::optional ConfigData::take_yaml(const std::string & name) +UnitConfig * FileLoader::create_unit_config(const TreeData & data) { - if (!object.count(name)) { - return std::nullopt; - } + const auto unit = units_.emplace_back(std::make_unique(data)).get(); + unit->type = unit->data.required("type").text(); + unit->path = unit->data.optional("path").text(); - const auto yaml = object.at(name); - object.erase(name); - return yaml; + const auto item = unit->data.optional("item").child("c"); + if (item.is_valid()) { + unit->item = create_link_config(item, unit); + } + const auto list = unit->data.optional("list").children(); + for (const auto & data : list) { + unit->list.push_back(create_link_config(data, unit)); + } + return unit; } -std::string ConfigData::take_text(const std::string & name) +LinkConfig * FileLoader::create_link_config(const TreeData & data, UnitConfig * unit) { - if (!object.count(name)) { - throw error("required field is not found", name, *this); - } - - const auto yaml = object.at(name); - object.erase(name); - return yaml.as(); + const auto link = links_.emplace_back(std::make_unique()).get(); + link->parent = unit; + link->child = create_unit_config(data); + return link; } -std::string ConfigData::take_text(const std::string & name, const std::string & fail) +void FileLoader::release(FileConfig & config) { - if (!object.count(name)) { - return fail; - } - - const auto yaml = object.at(name); - object.erase(name); - return yaml.as(); + for (auto & path : paths_) config.paths.push_back(std::move(path)); + for (auto & edit : edits_) config.edits.push_back(std::move(edit)); + for (auto & unit : units_) config.units.push_back(std::move(unit)); + for (auto & link : links_) config.links.push_back(std::move(link)); } -std::vector ConfigData::take_list(const std::string & name) +TreeLoader TreeLoader::Load(const std::string & path) { - if (!object.count(name)) { - return std::vector(); - } - - const auto yaml = object.at(name); - object.erase(name); + PathConfig root(TreeData::None()); + root.original = path; + root.resolved = resolve_file_path(path, root.data); + return TreeLoader(&root); +} - if (!yaml.IsSequence()) { - throw error("field is not a list type", name, *this); +TreeLoader::TreeLoader(const PathConfig * root) +{ + std::queue paths; + paths.push(root); + + // TODO(Takagi, Isamu): check include loop. + while (!paths.empty()) { + files_.emplace_back(paths.front()); + paths.pop(); + for (const auto & path : files_.back().paths()) { + paths.push(path.get()); + } } - return std::vector(yaml.begin(), yaml.end()); } -void resolve_link_nodes(RootConfig & root) +auto create_path_mapping(const std::vector> & units) { - std::unordered_map paths; - for (const auto & node : root.nodes) { - if (node->path.empty()) { + std::unordered_map path_to_unit; + for (const auto & unit : units) { + if (unit->path.empty()) { continue; } - if (paths.count(node->path)) { - throw error("object path is not unique", node->path); + if (path_to_unit.count(unit->path)) { + throw PathConflict(unit->path); } - paths[node->path] = node; + path_to_unit[unit->path] = unit.get(); } + return path_to_unit; +} - std::vector nodes; - std::vector links; - for (const auto & node : root.nodes) { - if (node->type == "link") { - links.push_back(node); +void apply_links(FileConfig & config) +{ + // Separate units into link types and others. + std::vector> link_units; + std::vector> node_units; + for (auto & unit : config.units) { + if (unit->type == unit_name::link) { + link_units.push_back(std::move(unit)); } else { - nodes.push_back(node); + node_units.push_back(std::move(unit)); } } - std::unordered_map targets; - for (const auto & node : nodes) { - targets[node] = node; - } - for (const auto & node : links) { - const auto path = node->data.take_text("link"); - if (!paths.count(path)) { - throw error("link path is not found", path, node->data); - } - const auto link = paths.at(path); - if (link->type == "link") { - throw error("link target is link type", path, node->data); + // Create a mapping from path to unit. + const auto path_to_unit = create_path_mapping(node_units); + + // Create a mapping from unit to unit. + std::unordered_map unit_to_unit; + for (const auto & unit : link_units) { + const auto path = unit->data.required("link").text(); + if (path_to_unit.count(path) == 0) { + throw PathNotFound(unit->data.path(), path); } - targets[node] = link; + unit_to_unit[unit.get()] = path_to_unit.at(path); } - for (const auto & node : nodes) { - for (auto & child : node->children) { - child = targets.at(child); + + // Update links. + for (const auto & link : config.links) { + if (unit_to_unit.count(link->child) != 0) { + link->child = unit_to_unit.at(link->child); } } - root.nodes = nodes; + + // Remove link type units from the graph. + config.units = std::move(node_units); } -void resolve_remove_edits(RootConfig & root) +void apply_edits(FileConfig & config) { - std::unordered_map paths; - for (const auto & node : root.nodes) { - paths[node->path] = node; - } - - std::unordered_set removes; - for (const auto & edit : root.edits) { - if (edit->type == "remove") { - if (!paths.count(edit->path)) { - throw error("remove path is not found", edit->path, edit->data); + // Create a mapping from path to unit. + const auto path_to_unit = create_path_mapping(config.units); + + // List units to remove and links from/to them. + std::unordered_set remove_units; + std::unordered_set remove_links; + for (const auto & edit : config.edits) { + if (edit->type == edit_name::remove) { + const auto path = edit->data.required("path").text(); + if (path_to_unit.count(path) == 0) { + throw PathNotFound(edit->data.path(), path); } - removes.insert(paths.at(edit->path)); + remove_units.insert(path_to_unit.at(path)); } } - - const auto filter = [removes](const std::vector & nodes) { - std::vector result; - for (const auto & node : nodes) { - if (!removes.count(node)) { - result.push_back(node); - } + for (const auto & link : config.links) { + if (remove_units.count(link->parent) || remove_units.count(link->child)) { + remove_links.insert(link.get()); } - return result; - }; - for (const auto & node : root.nodes) { - node->children = filter(node->children); - } - root.nodes = filter(root.nodes); -} - -std::string complement_node_type(ConfigData & data) -{ - if (data.object.count("diag")) { - return "diag"; } - return data.take_text("type"); -} -std::string resolve_substitution(const std::string & substitution, const ConfigData & data) -{ - std::stringstream ss(substitution); - std::string word; - std::vector words; - while (getline(ss, word, ' ')) { - words.push_back(word); + // Filter references to the removed links. + for (const auto & unit : config.units) { + if (remove_links.count(unit->item) != 0) { + unit->item = nullptr; + } + std::vector filtered_list; + for (const auto & link : unit->list) { + if (remove_links.count(link) == 0) { + filtered_list.push_back(link); + } + } + unit->list = filtered_list; } - if (words.size() == 2 && words[0] == "find-pkg-share") { - return ament_index_cpp::get_package_share_directory(words[1]); - } - if (words.size() == 1 && words[0] == "dirname") { - return std::filesystem::path(data.file).parent_path(); + // Remove units and links. + std::vector> filtered_units; + std::vector> filtered_links; + for (auto & unit : config.units) { + if (remove_units.count(unit.get()) == 0) { + filtered_units.push_back(std::move(unit)); + } } - throw error("unknown substitution", substitution, data); -} - -std::string resolve_file_path(const std::string & path, const ConfigData & data) -{ - static const std::regex pattern(R"(\$\(([^()]*)\))"); - std::smatch m; - std::string result = path; - while (std::regex_search(result, m, pattern)) { - const std::string prefix = m.prefix(); - const std::string suffix = m.suffix(); - result = prefix + resolve_substitution(m.str(1), data) + suffix; + for (auto & link : config.links) { + if (remove_links.count(link.get()) == 0) { + filtered_links.push_back(std::move(link)); + } } - return result; + config.units = std::move(filtered_units); + config.links = std::move(filtered_links); } -PathConfig::SharedPtr parse_path_config(const ConfigData & data) +void topological_sort(FileConfig & config) { - const auto path = std::make_shared(data); - path->original = path->data.take_text("path"); - path->resolved = resolve_file_path(path->original, path->data); - return path; -} - -UnitConfig::SharedPtr parse_node_config(const ConfigData & data) -{ - const auto node = std::make_shared(data); - node->path = node->data.take_text("path", ""); - node->type = node->data.take_text("type", ""); - - if (node->type.empty()) { - node->type = complement_node_type(node->data); + std::unordered_map degrees; + std::deque units; + std::deque result; + std::deque buffer; + + // Create a list of raw pointer units. + for (const auto & unit : config.units) units.push_back(unit.get()); + + // Count degrees of each unit. + for (const auto & unit : units) { + if (const auto & link = unit->item) ++degrees[link->child]; + for (const auto & link : unit->list) ++degrees[link->child]; } - for (const auto & [index, yaml] : enumerate(node->data.take_list("list"))) { - const auto child = data.node(index).load(yaml); - node->children.push_back(parse_node_config(child)); + // Find initial units that are zero degrees. + for (const auto & unit : units) { + if (degrees[unit] == 0) buffer.push_back(unit); } - return node; -} - -EditConfig::SharedPtr parse_edit_config(const ConfigData & data) -{ - const auto edit = std::make_shared(data); - edit->path = edit->data.take_text("path", ""); - edit->type = edit->data.take_text("type", ""); - return edit; -} -FileConfig::SharedPtr parse_file_config(const ConfigData & data) -{ - const auto file = std::make_shared(data); - const auto path_data = data.type("file"); - const auto node_data = data.type("node"); - const auto edit_data = data.type("edit"); - const auto paths = file->data.take_list("files"); - const auto nodes = file->data.take_list("nodes"); - const auto edits = file->data.take_list("edits"); - - for (const auto & [index, yaml] : enumerate(paths)) { - const auto path = path_data.node(index).load(yaml); - file->paths.push_back(parse_path_config(path)); - } - for (const auto & [index, yaml] : enumerate(nodes)) { - const auto node = node_data.node(index).load(yaml); - file->nodes.push_back(parse_node_config(node)); - } - for (const auto & [index, yaml] : enumerate(edits)) { - const auto edit = edit_data.node(index).load(yaml); - file->edits.push_back(parse_edit_config(edit)); + // Sort by topological order. + while (!buffer.empty()) { + const auto unit = buffer.front(); + buffer.pop_front(); + if (const auto & link = unit->item) { + if (--degrees[link->child] == 0) { + buffer.push_back(link->child); + } + } + for (const auto & link : unit->list) { + if (--degrees[link->child] == 0) { + buffer.push_back(link->child); + } + } + result.push_back(unit); } - return file; -} -FileConfig::SharedPtr load_file_config(PathConfig & config) -{ - const auto path = std::filesystem::path(config.resolved); - if (!std::filesystem::exists(path)) { - throw error("file is not found", path, config.data); + // Detect circulation because the result does not include the units on the loop. + if (result.size() != units.size()) { + throw GraphStructure("detect graph circulation"); } - const auto file = ConfigData(path).load(YAML::LoadFile(path)); - return parse_file_config(file); } -RootConfig load_root_config(const PathConfig::SharedPtr root) +FileConfig TreeLoader::construct() { - std::vector paths; - paths.push_back(root); - - std::vector files; - for (size_t i = 0; i < paths.size(); ++i) { - const auto path = paths[i]; - const auto file = load_file_config(*path); - files.push_back(file); - extend(paths, file->paths); - } - - std::vector nodes; - std::vector edits; - for (const auto & file : files) { - extend(nodes, file->nodes); - extend(edits, file->edits); - } - for (size_t i = 0; i < nodes.size(); ++i) { - const auto node = nodes[i]; - extend(nodes, node->children); - } - - RootConfig config; - config.files = files; - config.nodes = nodes; - config.edits = edits; - resolve_link_nodes(config); - resolve_remove_edits(config); + FileConfig config; + for (auto & file : files_) file.release(config); + apply_links(config); + apply_edits(config); + topological_sort(config); // Check graph structure. return config; } -RootConfig load_root_config(const std::string & path) -{ - const auto root = std::make_shared(ConfigData("root-file")); - root->original = path; - root->resolved = path; - return load_root_config(root); -} - } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/config.hpp b/system/diagnostic_graph_aggregator/src/common/graph/config.hpp index 40f16235ed5d6..a22daf907a27e 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/config.hpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/config.hpp @@ -15,114 +15,87 @@ #ifndef COMMON__GRAPH__CONFIG_HPP_ #define COMMON__GRAPH__CONFIG_HPP_ -#include +#include "data.hpp" +#include "types.hpp" #include -#include #include -#include #include namespace diagnostic_graph_aggregator { -struct ConfigData +struct PathConfig { - explicit ConfigData(const std::string & file); - ConfigData load(YAML::Node yaml); - ConfigData type(const std::string & name) const; - ConfigData node(const size_t index) const; - - template - T take(const std::string & name, const T & fail) - { - const auto yaml = take_yaml(name); - return yaml ? yaml.value().as() : fail; - } - - std::optional take_yaml(const std::string & name); - std::string take_text(const std::string & name); - std::string take_text(const std::string & name, const std::string & fail); - std::vector take_list(const std::string & name); - - std::string file; - std::string mark; - std::unordered_map object; -}; - -struct BaseConfig -{ - explicit BaseConfig(const ConfigData & data) : data(data) {} - ConfigData data; -}; - -struct PathConfig : public BaseConfig -{ - using SharedPtr = std::shared_ptr; - using BaseConfig::BaseConfig; + explicit PathConfig(const TreeData & data) : data(data) {} + TreeData data; std::string original; std::string resolved; }; -struct UnitConfig : public BaseConfig +struct EditConfig { - using SharedPtr = std::shared_ptr; - using BaseConfig::BaseConfig; + explicit EditConfig(const TreeData & data) : data(data) {} + TreeData data; std::string type; - std::string path; - std::vector children; }; -struct EditConfig : public BaseConfig +struct LinkConfig { - using SharedPtr = std::shared_ptr; - using BaseConfig::BaseConfig; - std::string type; - std::string path; + UnitConfig * parent = nullptr; + UnitConfig * child = nullptr; }; -struct FileConfig : public BaseConfig +struct UnitConfig { - using SharedPtr = std::shared_ptr; - using BaseConfig::BaseConfig; - std::vector paths; - std::vector nodes; - std::vector edits; + explicit UnitConfig(const TreeData & data) : data(data) {} + TreeData data; + std::string type; + std::string path; + LinkConfig * item = nullptr; + std::vector list; + size_t index; }; -struct RootConfig +struct FileConfig { - std::vector files; - std::vector nodes; - std::vector edits; + // Note: keep order correspondence between links and unit children for viewer. + std::vector> paths; + std::vector> edits; + std::vector> units; + std::vector> links; }; -template -T error(const std::string & text, const ConfigData & data) -{ - const auto hint = data.mark.empty() ? data.file : data.mark + ":" + data.file; - return T(text + " (" + hint + ")"); -} - -template -T error(const std::string & text) +class FileLoader { - return T(text); -} - -template -T error(const std::string & text, const std::string & value, const ConfigData & data) -{ - return error(text + ": " + value, data); -} +public: + explicit FileLoader(const PathConfig * path); + const auto & paths() const { return paths_; } + void release(FileConfig & config); + +private: + PathConfig * create_path_config(const TreeData & data); + EditConfig * create_edit_config(const TreeData & data); + UnitConfig * create_unit_config(const TreeData & data); + LinkConfig * create_link_config(const TreeData & data, UnitConfig * unit); + + // Note: keep order correspondence between links and unit children for viewer. + std::vector> paths_; + std::vector> edits_; + std::vector> units_; + std::vector> links_; +}; -template -T error(const std::string & text, const std::string & value) +class TreeLoader { - return error(text + ": " + value); -} +public: + static TreeLoader Load(const std::string & path); + explicit TreeLoader(const PathConfig * root); + FileConfig construct(); -RootConfig load_root_config(const std::string & path); +private: + std::vector files_; +}; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/data.cpp b/system/diagnostic_graph_aggregator/src/common/graph/data.cpp new file mode 100644 index 0000000000000..ff186098c32e3 --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/data.cpp @@ -0,0 +1,97 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "data.hpp" + +namespace diagnostic_graph_aggregator +{ + +TreeData TreeData::Load(const std::string & path) +{ + return TreeData(YAML::LoadFile(path), TreePath(path)); +} + +TreeData TreeData::None() +{ + return TreeData(YAML::Node(), TreePath("")); +} + +TreeData::TreeData(const YAML::Node & yaml, const TreePath & path) : path_(path) +{ + yaml_ = yaml; +} + +TreeData::Item TreeData::required(const std::string & name) +{ + // TODO(Takagi, Isamu): check map type. + const auto path = path_.field(name); + if (!yaml_[name]) { + throw FieldNotFound(path); + } + const auto data = yaml_[name]; + yaml_.remove(name); + return TreeData(data, path); +} + +TreeData::Item TreeData::optional(const std::string & name) +{ + // TODO(Takagi, Isamu): check map type. + const auto path = path_.field(name); + if (!yaml_[name]) { + return TreeData(YAML::Node(YAML::NodeType::Undefined), path); + } + const auto data = yaml_[name]; + yaml_.remove(name); + return TreeData(data, path); +} + +bool TreeData::is_valid() const +{ + return yaml_.Type() != YAML::NodeType::Undefined; +} + +TreeData::Item TreeData::child(const std::string & path) +{ + return TreeData(yaml_, path_.child(path)); +} + +TreeData::List TreeData::children(const std::string & path) +{ + if (yaml_.Type() == YAML::NodeType::Undefined) { + return {}; + } + if (yaml_.Type() != YAML::NodeType::Sequence) { + throw InvalidType(path_); + } + + TreeData::List result; + for (size_t i = 0; i < yaml_.size(); ++i) { + result.emplace_back(yaml_[i], path_.child(path, i)); + } + return result; +} + +std::string TreeData::text(const std::string & fail) +{ + // TODO(Takagi, Isamu): check conversion failure + return yaml_.as(fail); +} + +double TreeData::real(double fail) +{ + // TODO(Takagi, Isamu): check conversion failure + return yaml_.as(fail); +} + +} // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/data.hpp b/system/diagnostic_graph_aggregator/src/common/graph/data.hpp new file mode 100644 index 0000000000000..437e3793df398 --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/data.hpp @@ -0,0 +1,56 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef COMMON__GRAPH__DATA_HPP_ +#define COMMON__GRAPH__DATA_HPP_ + +#include "error.hpp" + +#include + +#include +#include +#include + +namespace diagnostic_graph_aggregator +{ + +class TreeData +{ +public: + using Item = TreeData; + using List = std::vector; + + static TreeData Load(const std::string & path); + static TreeData None(); + TreeData(const YAML::Node & yaml, const TreePath & path); + + const auto & path() const { return path_; } + Item required(const std::string & name); + Item optional(const std::string & name); + bool is_valid() const; + + Item child(const std::string & path); + List children(const std::string & path = ""); + std::string text(const std::string & fail = ""); + double real(double fail); + +private: + YAML::Node yaml_; + TreePath path_; +}; + +} // namespace diagnostic_graph_aggregator + +#endif // COMMON__GRAPH__DATA_HPP_ diff --git a/system/diagnostic_graph_aggregator/src/common/graph/debug.cpp b/system/diagnostic_graph_aggregator/src/common/graph/debug.cpp deleted file mode 100644 index 8f2b741edd805..0000000000000 --- a/system/diagnostic_graph_aggregator/src/common/graph/debug.cpp +++ /dev/null @@ -1,75 +0,0 @@ -// Copyright 2023 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "debug.hpp" - -#include "graph.hpp" -#include "types.hpp" -#include "units.hpp" - -#include -#include -#include -#include - -namespace diagnostic_graph_aggregator -{ - -std::string get_level_text(DiagnosticLevel level) -{ - switch (level) { - case DiagnosticStatus::OK: - return "OK"; - case DiagnosticStatus::WARN: - return "WARN"; - case DiagnosticStatus::ERROR: - return "ERROR"; - case DiagnosticStatus::STALE: - return "STALE"; - } - return "UNKNOWN"; -} - -void Graph::debug() -{ - std::vector lines; - for (const auto & node : nodes_) { - const auto level_name = get_level_text(node->level()); - const auto index_name = std::to_string(node->index()); - lines.push_back({index_name, level_name, node->path(), node->type()}); - } - for (const auto & [name, level] : unknowns_) { - const auto level_name = get_level_text(level); - lines.push_back({"*", level_name, name, "unknown"}); - } - - std::array widths = {}; - for (const auto & line : lines) { - for (size_t i = 0; i < diag_debug_size; ++i) { - widths[i] = std::max(widths[i], line[i].length()); - } - } - - const size_t total_width = std::accumulate(widths.begin(), widths.end(), 0); - std::cout << std::string(total_width + 3 * diag_debug_size + 1, '=') << std::endl; - - for (const auto & line : lines) { - for (size_t i = 0; i < diag_debug_size; ++i) { - std::cout << "| " << std::left << std::setw(widths[i]) << line[i] << " "; - } - std::cout << "|" << std::endl; - } -} - -} // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/error.cpp b/system/diagnostic_graph_aggregator/src/common/graph/error.cpp new file mode 100644 index 0000000000000..e78a444c5ab7f --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/error.cpp @@ -0,0 +1,58 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "error.hpp" + +namespace diagnostic_graph_aggregator +{ + +TreePath::TreePath(const std::string & file) +{ + file_ = file; +} + +TreePath TreePath::field(const std::string & name) +{ + TreePath result(file_); + result.node_ = node_; + result.name_ = name; + return result; +} + +TreePath TreePath::child(const std::string & path) +{ + const auto sep = node_.empty() ? "" : "-"; + TreePath result(file_); + result.node_ = node_ + sep + path; + return result; +} + +TreePath TreePath::child(const std::string & path, const size_t index) +{ + const auto sep = path.empty() ? "" : "-"; + return child(path + sep + std::to_string(index)); +} + +TreePath TreePath::child(const size_t index) +{ + return child(std::to_string(index)); +} + +std::string TreePath::text() const +{ + const auto sep = node_.empty() ? "" : ":"; + return " (" + file_ + sep + node_ + ")"; +} + +} // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/error.hpp b/system/diagnostic_graph_aggregator/src/common/graph/error.hpp index dadfab450c783..d923e12caf783 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/error.hpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/error.hpp @@ -16,51 +16,113 @@ #define COMMON__GRAPH__ERROR_HPP_ #include +#include namespace diagnostic_graph_aggregator { +struct TreePath +{ + explicit TreePath(const std::string & file); + TreePath field(const std::string & name); + TreePath child(const std::string & path); + TreePath child(const std::string & path, const size_t index); + TreePath child(const size_t index); + std::string text() const; + std::string file() const { return file_; } + std::string node() const { return node_; } + std::string name() const { return name_; } + +private: + std::string file_; + std::string node_; + std::string name_; +}; + struct Exception : public std::runtime_error { using runtime_error::runtime_error; }; -class FileNotFound : public Exception +struct FileNotFound : public Exception { - using Exception::Exception; + explicit FileNotFound(const TreePath & path, const std::string & file) + : Exception(format(path, file)) + { + } + static std::string format(const TreePath & path, const std::string & file) + { + return "file is not found: " + file + path.text(); + } }; -class UnknownType : public Exception +struct FieldNotFound : public Exception { - using Exception::Exception; + explicit FieldNotFound(const TreePath & path) : Exception(format(path)) {} + static std::string format(const TreePath & path) + { + return "required field is not found: " + path.name() + path.text(); + } }; -class InvalidType : public Exception +struct InvalidType : public Exception { - using Exception::Exception; + explicit InvalidType(const TreePath & path) : Exception(format(path)) {} + static std::string format(const TreePath & path) + { + return "field is not a list type: " + path.name() + path.text(); + } }; -class InvalidValue : public Exception +struct ModeNotFound : public Exception { - using Exception::Exception; + explicit ModeNotFound(const std::string & path) : Exception(format(path)) {} + static std::string format(const std::string & path) { return "mode path is not found: " + path; } }; -class FieldNotFound : public Exception +struct PathConflict : public Exception { - using Exception::Exception; + explicit PathConflict(const std::string & path) : Exception(format(path)) {} + static std::string format(const std::string & path) { return "node path is not unique: " + path; } }; -class PathConflict : public Exception +struct PathNotFound : public Exception { - using Exception::Exception; + explicit PathNotFound(const TreePath & path, const std::string & link) + : Exception(format(path, link)) + { + } + static std::string format(const TreePath & path, const std::string & link) + { + return "path is not found: " + link + path.text(); + } }; -class PathNotFound : public Exception +struct UnknownSubstitution : public Exception { - using Exception::Exception; + explicit UnknownSubstitution(const TreePath & path, const std::string & substitution) + : Exception(format(path, substitution)) + { + } + static std::string format(const TreePath & path, const std::string & substitution) + { + return "unknown substitution: " + substitution + path.text(); + } +}; + +struct UnknownUnitType : public Exception +{ + explicit UnknownUnitType(const TreePath & path, const std::string & type) + : Exception(format(path, type)) + { + } + static std::string format(const TreePath & path, const std::string & type) + { + return "unknown unit type: " + type + path.text(); + } }; -class GraphStructure : public Exception +struct GraphStructure : public Exception { using Exception::Exception; }; diff --git a/system/diagnostic_graph_aggregator/src/common/graph/graph.cpp b/system/diagnostic_graph_aggregator/src/common/graph/graph.cpp index 5d7c11879a9cc..0a7d78a5ce982 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/graph.cpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/graph.cpp @@ -16,211 +16,64 @@ #include "config.hpp" #include "error.hpp" +#include "loader.hpp" #include "units.hpp" -#include -#include -#include #include -#include -#include - -// DEBUG -#include namespace diagnostic_graph_aggregator { -BaseUnit::UniquePtrList topological_sort(BaseUnit::UniquePtrList && input) -{ - std::unordered_map degrees; - std::deque nodes; - std::deque result; - std::deque buffer; - - // Create a list of raw pointer nodes. - for (const auto & node : input) { - nodes.push_back(node.get()); - } - - // Count degrees of each node. - for (const auto & node : nodes) { - for (const auto & child : node->children()) { - ++degrees[child]; - } - } - - // Find initial nodes that are zero degrees. - for (const auto & node : nodes) { - if (degrees[node] == 0) { - buffer.push_back(node); - } - } - - // Sort by topological order. - while (!buffer.empty()) { - const auto node = buffer.front(); - buffer.pop_front(); - for (const auto & child : node->children()) { - if (--degrees[child] == 0) { - buffer.push_back(child); - } - } - result.push_back(node); - } - - // Detect circulation because the result does not include the nodes on the loop. - if (result.size() != nodes.size()) { - throw error("detect graph circulation"); - } - - // Reverse the result to process from leaf node. - result = std::deque(result.rbegin(), result.rend()); - - // Replace node vector. - std::unordered_map indices; - for (size_t i = 0; i < result.size(); ++i) { - indices[result[i]] = i; - } - std::vector> sorted(input.size()); - for (auto & node : input) { - sorted[indices[node.get()]] = std::move(node); - } - return sorted; -} - -BaseUnit::UniquePtr make_node(const UnitConfig::SharedPtr & config) -{ - if (config->type == "diag") { - return std::make_unique(config->path); - } - if (config->type == "and") { - return std::make_unique(config->path, false); - } - if (config->type == "short-circuit-and") { - return std::make_unique(config->path, true); - } - if (config->type == "or") { - return std::make_unique(config->path); - } - if (config->type == "warn-to-ok") { - return std::make_unique(config->path, DiagnosticStatus::OK); - } - if (config->type == "warn-to-error") { - return std::make_unique(config->path, DiagnosticStatus::ERROR); - } - if (config->type == "ok") { - return std::make_unique(config->path, DiagnosticStatus::OK); - } - if (config->type == "warn") { - return std::make_unique(config->path, DiagnosticStatus::WARN); - } - if (config->type == "error") { - return std::make_unique(config->path, DiagnosticStatus::ERROR); - } - if (config->type == "stale") { - return std::make_unique(config->path, DiagnosticStatus::STALE); - } - throw error("unknown node type", config->type, config->data); -} - -Graph::Graph() +void Graph::create(const std::string & file, const std::string & id) { - // for unique_ptr + GraphLoader graph(file); + nodes_ = graph.release_nodes(); + diags_ = graph.release_diags(); + links_ = graph.release_links(); + for (const auto & diag : diags_) names_[diag->name()] = diag.get(); + for (const auto & node : nodes_) units_.push_back(node.get()); + for (const auto & diag : diags_) units_.push_back(diag.get()); + + id_ = id; } -Graph::~Graph() +void Graph::update(const rclcpp::Time & stamp) { - // for unique_ptr + for (const auto & diag : diags_) diag->on_time(stamp); } -void Graph::init(const std::string & file) +bool Graph::update(const rclcpp::Time & stamp, const DiagnosticStatus & status) { - BaseUnit::UniquePtrList nodes; - BaseUnit::NodeDict dict; - - for (const auto & config : load_root_config(file).nodes) { - const auto node = nodes.emplace_back(make_node(config)).get(); - dict.configs[config] = node; - dict.paths[config->path] = node; - } - dict.paths.erase(""); - - for (const auto & [config, node] : dict.configs) { - node->init(config, dict); - } - - // Sort units in topological order for update dependencies. - nodes = topological_sort(std::move(nodes)); - - // List diag nodes that have diag name. - for (const auto & node : nodes) { - const auto diag = dynamic_cast(node.get()); - if (diag) { - diags_[diag->name()] = diag; - } - } - - // List unit nodes that have path name. - for (const auto & node : nodes) { - if (!node->path().empty()) { - units_.push_back(node.get()); - } - } - - // Set unit index. - for (size_t index = 0; index < units_.size(); ++index) { - units_[index]->set_index(index); - } - - nodes_ = std::move(nodes); + const auto iter = names_.find(status.name); + if (iter == names_.end()) return false; + iter->second->on_diag(stamp, status); + return true; } -void Graph::callback(const rclcpp::Time & stamp, const DiagnosticArray & array) +DiagGraphStruct Graph::create_struct(const rclcpp::Time & stamp) const { - for (const auto & status : array.status) { - const auto iter = diags_.find(status.name); - if (iter != diags_.end()) { - iter->second->callback(stamp, status); - } else { - unknowns_[status.name] = status.level; - } - } + DiagGraphStruct msg; + msg.stamp = stamp; + msg.id = id_; + for (const auto & node : nodes_) msg.nodes.push_back(node->create_struct()); + for (const auto & diag : diags_) msg.diags.push_back(diag->create_struct()); + for (const auto & link : links_) msg.links.push_back(link->create_struct()); + return msg; } -DiagnosticGraph Graph::report(const rclcpp::Time & stamp) +DiagGraphStatus Graph::create_status(const rclcpp::Time & stamp) const { - for (const auto & node : nodes_) { - node->update(stamp); - } - - DiagnosticGraph message; - message.stamp = stamp; - message.nodes.reserve(units_.size()); - for (const auto & node : units_) { - const auto report = node->report(); - DiagnosticNode temp; - temp.status.name = node->path(); - temp.status.level = report.level; - for (const auto & [ref, used] : report.links) { - DiagnosticLink link; - link.index = ref->index(); - link.used = used; - temp.links.push_back(link); - } - message.nodes.push_back(temp); - } - return message; + DiagGraphStatus msg; + msg.stamp = stamp; + msg.id = id_; + for (const auto & node : nodes_) msg.nodes.push_back(node->create_status()); + for (const auto & diag : diags_) msg.diags.push_back(diag->create_status()); + for (const auto & link : links_) msg.links.push_back(link->create_status()); + return msg; } -std::vector Graph::nodes() const -{ - std::vector result; - result.reserve(nodes_.size()); - for (const auto & node : nodes_) { - result.push_back(node.get()); - } - return result; -} +// For unique_ptr members. +Graph::Graph() = default; +Graph::~Graph() = default; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/graph.hpp b/system/diagnostic_graph_aggregator/src/common/graph/graph.hpp index 8c29a303814b8..ed7bac0e96ce3 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/graph.hpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/graph.hpp @@ -22,29 +22,34 @@ #include #include #include -#include #include namespace diagnostic_graph_aggregator { -class Graph final +class Graph { public: - Graph(); - ~Graph(); - - void init(const std::string & file); - void callback(const rclcpp::Time & stamp, const DiagnosticArray & array); - void debug(); - DiagnosticGraph report(const rclcpp::Time & stamp); - std::vector nodes() const; + void create(const std::string & file, const std::string & id = ""); + void update(const rclcpp::Time & stamp); + bool update(const rclcpp::Time & stamp, const DiagnosticStatus & status); + const auto & nodes() const { return nodes_; } + const auto & diags() const { return diags_; } + const auto & units() const { return units_; } + DiagGraphStruct create_struct(const rclcpp::Time & stamp) const; + DiagGraphStatus create_status(const rclcpp::Time & stamp) const; + + Graph(); // For unique_ptr members. + ~Graph(); // For unique_ptr members. private: - std::vector> nodes_; + // Note: keep order correspondence between links and unit children for viewer. + std::vector> nodes_; + std::vector> diags_; + std::vector> links_; std::vector units_; - std::unordered_map diags_; - std::unordered_map unknowns_; + std::unordered_map names_; + std::string id_; }; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/loader.cpp b/system/diagnostic_graph_aggregator/src/common/graph/loader.cpp new file mode 100644 index 0000000000000..74636adab7415 --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/loader.cpp @@ -0,0 +1,189 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "loader.hpp" + +#include "config.hpp" +#include "error.hpp" +#include "names.hpp" +#include "types.hpp" +#include "units.hpp" + +#include + +namespace diagnostic_graph_aggregator +{ + +struct UnitLoader::GraphLinks +{ + std::unordered_map config_links; + std::unordered_map> parent_links; +}; + +size_t UnitLoader::index() const +{ + return config_->index; +} + +const std::string & UnitLoader::path() const +{ + return config_->path; +} + +const std::string & UnitLoader::type() const +{ + return config_->type; +} + +TreeData & UnitLoader::data() const +{ + return config_->data; +} + +UnitLink * UnitLoader::child() const +{ + return links_.config_links.at(config_->item); +} + +std::vector UnitLoader::children() const +{ + std::vector result; + for (const auto & config : config_->list) { + result.push_back(links_.config_links.at(config)); + } + return result; +} + +std::vector UnitLoader::parents() const +{ + return links_.parent_links.at(config_); +} + +GraphLoader::GraphLoader(const std::string & file) +{ + TreeLoader tree = TreeLoader::Load(file); + FileConfig root = tree.construct(); + + // Init array index to be able get it from unit itself. + std::vector diags; + std::vector nodes; + for (const auto & config : root.units) { + (config->type == unit_name::diag ? diags : nodes).push_back(config.get()); + } + for (size_t i = 0; i < diags.size(); ++i) diags[i]->index = i; + for (size_t i = 0; i < nodes.size(); ++i) nodes[i]->index = i; + + // Create link objects. + UnitLoader::GraphLinks graph_links; + for (const auto & config : root.units) { + graph_links.parent_links[config.get()] = {}; + } + for (const auto & config : root.links) { + const auto link = links_.emplace_back(create_link()).get(); + graph_links.config_links[config.get()] = link; + graph_links.parent_links[config->child].push_back(link); + } + + // Create node objects. + std::unordered_map config_units; + for (const auto & config : diags) { + const auto unit = UnitLoader(config, graph_links); + const auto diag = diags_.emplace_back(create_diag(unit)).get(); + config_units[config] = diag; + } + for (const auto & config : nodes) { + const auto unit = UnitLoader(config, graph_links); + const auto node = nodes_.emplace_back(create_node(unit)).get(); + config_units[config] = node; + } + + // Connect links and nodes; + for (const auto & [config, link] : graph_links.config_links) { + const auto parent = config_units.at(config->parent); + const auto child = config_units.at(config->child); + link->initialize_object(parent, child); + } + + // Init struct. + for (auto & node : nodes_) node->initialize_struct(); + for (auto & diag : diags_) diag->initialize_struct(); + for (auto & link : links_) link->initialize_struct(); + + // Init status that needs struct. + for (auto & node : nodes_) node->initialize_status(); + for (auto & diag : diags_) diag->initialize_status(); + for (auto & link : links_) link->initialize_status(); +} + +std::vector> GraphLoader::release_links() +{ + return std::move(links_); +} + +std::vector> GraphLoader::release_nodes() +{ + return std::move(nodes_); +} + +std::vector> GraphLoader::release_diags() +{ + return std::move(diags_); +} + +std::unique_ptr GraphLoader::create_link() +{ + return std::make_unique(); +} + +std::unique_ptr GraphLoader::create_diag(const UnitLoader & unit) +{ + if (unit.type() == unit_name::diag) { + return std::make_unique(unit); + } + throw UnknownUnitType(unit.data().path(), unit.type()); +} + +std::unique_ptr GraphLoader::create_node(const UnitLoader & unit) +{ + if (unit.type() == unit_name::max) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::short_circuit_max) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::min) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::warn_to_ok) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::warn_to_error) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::ok) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::warn) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::error) { + return std::make_unique(unit); + } + if (unit.type() == unit_name::stale) { + return std::make_unique(unit); + } + throw UnknownUnitType(unit.data().path(), unit.type()); +} + +} // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/loader.hpp b/system/diagnostic_graph_aggregator/src/common/graph/loader.hpp new file mode 100644 index 0000000000000..226b3ab279b22 --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/loader.hpp @@ -0,0 +1,67 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef COMMON__GRAPH__LOADER_HPP_ +#define COMMON__GRAPH__LOADER_HPP_ + +#include "types.hpp" + +#include +#include +#include +#include + +namespace diagnostic_graph_aggregator +{ + +class UnitLoader +{ +public: + struct GraphLinks; + UnitLoader(UnitConfig * config, GraphLinks & links) : config_(config), links_(links) {} + const std::string & path() const; + const std::string & type() const; + size_t index() const; + TreeData & data() const; + UnitLink * child() const; + std::vector children() const; + std::vector parents() const; + +private: + UnitConfig * config_; + GraphLinks & links_; +}; + +class GraphLoader +{ +public: + explicit GraphLoader(const std::string & file); + std::vector> release_nodes(); + std::vector> release_diags(); + std::vector> release_links(); + +private: + std::unique_ptr create_link(); + std::unique_ptr create_diag(const UnitLoader & unit); + std::unique_ptr create_node(const UnitLoader & unit); + + // Note: keep order correspondence between links and unit children for viewer. + std::vector> nodes_; + std::vector> diags_; + std::vector> links_; +}; + +} // namespace diagnostic_graph_aggregator + +#endif // COMMON__GRAPH__LOADER_HPP_ diff --git a/system/diagnostic_graph_aggregator/src/common/graph/names.hpp b/system/diagnostic_graph_aggregator/src/common/graph/names.hpp new file mode 100644 index 0000000000000..aa5a9c46e7b37 --- /dev/null +++ b/system/diagnostic_graph_aggregator/src/common/graph/names.hpp @@ -0,0 +1,42 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef COMMON__GRAPH__NAMES_HPP_ +#define COMMON__GRAPH__NAMES_HPP_ + +namespace diagnostic_graph_aggregator::unit_name +{ + +constexpr char const * link = "link"; +constexpr char const * diag = "diag"; +constexpr char const * min = "or"; +constexpr char const * max = "and"; +constexpr char const * short_circuit_max = "short-circuit-and"; +constexpr char const * warn_to_ok = "warn-to-ok"; +constexpr char const * warn_to_error = "warn-to-error"; +constexpr char const * ok = "ok"; +constexpr char const * warn = "warn"; +constexpr char const * error = "error"; +constexpr char const * stale = "stale"; + +} // namespace diagnostic_graph_aggregator::unit_name + +namespace diagnostic_graph_aggregator::edit_name +{ + +constexpr char const * remove = "remove"; + +} // namespace diagnostic_graph_aggregator::edit_name + +#endif // COMMON__GRAPH__NAMES_HPP_ diff --git a/system/diagnostic_graph_aggregator/src/common/graph/types.hpp b/system/diagnostic_graph_aggregator/src/common/graph/types.hpp index 693094914db1d..6eae26a1f98c7 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/types.hpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/types.hpp @@ -17,22 +17,47 @@ #include #include +#include +#include +#include +#include +#include +#include +#include +#include #include #include #include +#include + namespace diagnostic_graph_aggregator { using diagnostic_msgs::msg::DiagnosticArray; using diagnostic_msgs::msg::DiagnosticStatus; -using tier4_system_msgs::msg::DiagnosticGraph; -using tier4_system_msgs::msg::DiagnosticLink; -using tier4_system_msgs::msg::DiagnosticNode; +using tier4_system_msgs::msg::DiagGraphStatus; +using tier4_system_msgs::msg::DiagGraphStruct; +using tier4_system_msgs::msg::DiagLeafStatus; +using tier4_system_msgs::msg::DiagLeafStruct; +using tier4_system_msgs::msg::DiagLinkStatus; +using tier4_system_msgs::msg::DiagLinkStruct; +using tier4_system_msgs::msg::DiagNodeStatus; +using tier4_system_msgs::msg::DiagNodeStruct; using DiagnosticLevel = DiagnosticStatus::_level_type; +struct PathConfig; +struct EditConfig; +struct UnitConfig; +struct LinkConfig; + +class TreeData; +class UnitLink; class BaseUnit; +class NodeUnit; class DiagUnit; +class Graph; +class UnitLoader; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/units.cpp b/system/diagnostic_graph_aggregator/src/common/graph/units.cpp index 6048cae85e633..da801ae078e6c 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/units.cpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/units.cpp @@ -14,168 +14,216 @@ #include "units.hpp" +#include "config.hpp" #include "error.hpp" +#include "loader.hpp" #include -#include -#include -#include namespace diagnostic_graph_aggregator { -using LinkList = std::vector>; +void UnitLink::initialize_object(BaseUnit * parent, BaseUnit * child) +{ + parent_ = parent; + child_ = child; +} -void merge(LinkList & a, const LinkList & b, bool uses) +void UnitLink::initialize_struct() { - for (const auto & [node, used] : b) { - a.push_back(std::make_pair(node, used && uses)); - } + struct_.parent = parent_->index(); + struct_.child = child_->index(); + struct_.is_leaf = child_->is_leaf(); } -auto resolve(const BaseUnit::NodeDict & dict, const std::vector & children) +void UnitLink::initialize_status() { - std::vector result; - for (const auto & child : children) { - result.push_back(dict.configs.at(child)); - } - return result; + // Do nothing. } -BaseUnit::BaseUnit(const std::string & path) : path_(path) +BaseUnit::BaseUnit(const UnitLoader & unit) { - index_ = 0; - level_ = DiagnosticStatus::OK; + index_ = unit.index(); + parents_ = unit.parents(); } -BaseUnit::NodeData BaseUnit::status() const +bool BaseUnit::update() { - if (path_.empty()) { - return {level_, links_}; - } else { - return {level_, {std::make_pair(this, true)}}; + // Update the level of this unit. + update_status(); + + // If the level does not change, it will not affect the parents. + const auto curr_level = level(); + if (curr_level == prev_level_) return false; + prev_level_ = curr_level; + + // If the level changes, the parents also need to be updated. + bool result = false; + for (const auto & link : parents_) { + const auto unit = link->parent(); + result = result || unit->update(); } + return result; } -BaseUnit::NodeData BaseUnit::report() const +NodeUnit::NodeUnit(const UnitLoader & unit) : BaseUnit(unit) { - return {level_, links_}; + struct_.path = unit.path(); + status_.level = DiagnosticStatus::STALE; } -void DiagUnit::init(const UnitConfig::SharedPtr & config, const NodeDict &) +void NodeUnit::initialize_struct() { - name_ = config->data.take_text("diag"); - timeout_ = config->data.take("timeout", 1.0); + struct_.type = type(); } -void DiagUnit::update(const rclcpp::Time & stamp) +void NodeUnit::initialize_status() { - if (diagnostics_) { - const auto updated = diagnostics_.value().first; - const auto elapsed = (stamp - updated).seconds(); - if (timeout_ < elapsed) { - diagnostics_ = std::nullopt; - } - } + if (child_links().size() == 0) update(); +} - if (diagnostics_) { - level_ = diagnostics_.value().second.level; - } else { - level_ = DiagnosticStatus::STALE; - } +LeafUnit::LeafUnit(const UnitLoader & unit) : BaseUnit(unit) +{ + const auto node = unit.data().required("node").text(); + const auto name = unit.data().required("name").text(); + const auto sep = node.empty() ? "" : ": "; + + struct_.path = unit.path(); + struct_.name = node + sep + name; + status_.level = DiagnosticStatus::STALE; } -void DiagUnit::callback(const rclcpp::Time & stamp, const DiagnosticStatus & status) +void LeafUnit::initialize_struct() { - diagnostics_ = std::make_pair(stamp, status); + struct_.type = type(); } -AndUnit::AndUnit(const std::string & path, bool short_circuit) : BaseUnit(path) +void LeafUnit::initialize_status() { - short_circuit_ = short_circuit; + if (child_links().size() == 0) update(); } -void AndUnit::init(const UnitConfig::SharedPtr & config, const NodeDict & dict) +DiagUnit::DiagUnit(const UnitLoader & unit) : LeafUnit(unit) { - children_ = resolve(dict, config->children); + timeout_ = unit.data().optional("timeout").real(1.0); } -void AndUnit::update(const rclcpp::Time &) +void DiagUnit::update_status() { - if (children_.empty()) { - return; - } + // Do nothing. The level is updated by on_diag and on_time. +} - bool uses = true; - level_ = DiagnosticStatus::OK; - links_ = LinkList(); +bool DiagUnit::on_diag(const rclcpp::Time & stamp, const DiagnosticStatus & status) +{ + last_updated_time_ = stamp; + status_.level = status.level; + status_.message = status.message; + status_.hardware_id = status.hardware_id; + status_.values = status.values; + return update(); +} - for (const auto & child : children_) { - const auto status = child->status(); - level_ = std::max(level_, status.level); - merge(links_, status.links, uses); - if (short_circuit_ && level_ != DiagnosticStatus::OK) { - uses = false; +bool DiagUnit::on_time(const rclcpp::Time & stamp) +{ + if (last_updated_time_) { + const auto updated = last_updated_time_.value(); + const auto elapsed = (stamp - updated).seconds(); + if (timeout_ < elapsed) { + last_updated_time_ = std::nullopt; + status_ = DiagLeafStatus(); + status_.level = DiagnosticStatus::STALE; } } - level_ = std::min(level_, DiagnosticStatus::ERROR); + return update(); } -void OrUnit::init(const UnitConfig::SharedPtr & config, const NodeDict & dict) +MaxUnit::MaxUnit(const UnitLoader & unit) : NodeUnit(unit) { - children_ = resolve(dict, config->children); + links_ = unit.children(); } -void OrUnit::update(const rclcpp::Time &) +void MaxUnit::update_status() { - if (children_.empty()) { - return; + DiagnosticLevel level = DiagnosticStatus::OK; + for (const auto & link : links_) { + level = std::max(level, link->child()->level()); } + status_.level = std::min(level, DiagnosticStatus::ERROR); +} - level_ = DiagnosticStatus::ERROR; - links_ = LinkList(); - - for (const auto & child : children_) { - const auto status = child->status(); - level_ = std::min(level_, status.level); - merge(links_, status.links, true); +void ShortCircuitMaxUnit::update_status() +{ + // TODO(Takagi, Isamu): update link flags. + DiagnosticLevel level = DiagnosticStatus::OK; + for (const auto & link : links_) { + level = std::max(level, link->child()->level()); } - level_ = std::min(level_, DiagnosticStatus::ERROR); + status_.level = std::min(level, DiagnosticStatus::ERROR); } -RemapUnit::RemapUnit(const std::string & path, DiagnosticLevel remap_warn) : BaseUnit(path) +MinUnit::MinUnit(const UnitLoader & unit) : NodeUnit(unit) { - remap_warn_ = remap_warn; + links_ = unit.children(); } -void RemapUnit::init(const UnitConfig::SharedPtr & config, const NodeDict & dict) +void MinUnit::update_status() { - if (config->children.size() != 1) { - throw error("list size must be 1", config->data); + DiagnosticLevel level = DiagnosticStatus::OK; + if (!links_.empty()) { + level = DiagnosticStatus::STALE; + for (const auto & link : links_) { + level = std::min(level, link->child()->level()); + } } - children_ = resolve(dict, config->children); + status_.level = std::min(level, DiagnosticStatus::ERROR); +} + +RemapUnit::RemapUnit(const UnitLoader & unit) : NodeUnit(unit) +{ + link_ = unit.child(); +} + +void RemapUnit::update_status() +{ + const auto level = link_->child()->level(); + status_.level = (level == level_from_) ? level_to_ : level; +} + +WarnToOkUnit::WarnToOkUnit(const UnitLoader & unit) : RemapUnit(unit) +{ + level_from_ = DiagnosticStatus::WARN; + level_to_ = DiagnosticStatus::OK; } -void RemapUnit::update(const rclcpp::Time &) +WarnToErrorUnit::WarnToErrorUnit(const UnitLoader & unit) : RemapUnit(unit) { - const auto status = children_.front()->status(); - level_ = status.level; - links_ = status.links; + level_from_ = DiagnosticStatus::WARN; + level_to_ = DiagnosticStatus::ERROR; +} - if (level_ == DiagnosticStatus::WARN) level_ = remap_warn_; +void ConstUnit::update_status() +{ + // Do nothing. This unit always returns the same level. +} + +OkUnit::OkUnit(const UnitLoader & unit) : ConstUnit(unit) +{ + status_.level = DiagnosticStatus::OK; } -DebugUnit::DebugUnit(const std::string & path, DiagnosticLevel level) : BaseUnit(path) +WarnUnit::WarnUnit(const UnitLoader & unit) : ConstUnit(unit) { - level_ = level; // overwrite + status_.level = DiagnosticStatus::WARN; } -void DebugUnit::init(const UnitConfig::SharedPtr &, const NodeDict &) +ErrorUnit::ErrorUnit(const UnitLoader & unit) : ConstUnit(unit) { + status_.level = DiagnosticStatus::ERROR; } -void DebugUnit::update(const rclcpp::Time &) +StaleUnit::StaleUnit(const UnitLoader & unit) : ConstUnit(unit) { + status_.level = DiagnosticStatus::STALE; } } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/common/graph/units.hpp b/system/diagnostic_graph_aggregator/src/common/graph/units.hpp index dce223b30f728..f478fa9ef1a2a 100644 --- a/system/diagnostic_graph_aggregator/src/common/graph/units.hpp +++ b/system/diagnostic_graph_aggregator/src/common/graph/units.hpp @@ -15,120 +15,212 @@ #ifndef COMMON__GRAPH__UNITS_HPP_ #define COMMON__GRAPH__UNITS_HPP_ -#include "config.hpp" +#include "names.hpp" #include "types.hpp" #include -#include #include #include -#include -#include #include namespace diagnostic_graph_aggregator { +class UnitLink +{ +public: + void initialize_object(BaseUnit * parent, BaseUnit * child); + void initialize_struct(); + void initialize_status(); + DiagLinkStruct create_struct() const { return struct_; } + DiagLinkStatus create_status() const { return status_; } + BaseUnit * parent() const { return parent_; } + BaseUnit * child() const { return child_; } + +private: + BaseUnit * parent_; + BaseUnit * child_; + DiagLinkStruct struct_; + DiagLinkStatus status_; +}; + class BaseUnit { public: - struct NodeDict - { - std::unordered_map configs; - std::unordered_map paths; - }; - struct NodeData - { - DiagnosticLevel level; - std::vector> links; - }; - using UniquePtr = std::unique_ptr; - using UniquePtrList = std::vector>; - - explicit BaseUnit(const std::string & path); + explicit BaseUnit(const UnitLoader & unit); virtual ~BaseUnit() = default; - virtual void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) = 0; - virtual void update(const rclcpp::Time & stamp) = 0; + virtual DiagnosticLevel level() const = 0; + virtual std::string path() const = 0; virtual std::string type() const = 0; - - NodeData status() const; - NodeData report() const; - DiagnosticLevel level() const { return level_; } - - auto path() const { return path_; } - auto children() const { return children_; } - + virtual std::vector child_links() const = 0; + virtual bool is_leaf() const = 0; size_t index() const { return index_; } - void set_index(const size_t index) { index_ = index; } + size_t parent_size() const { return parents_.size(); } protected: - DiagnosticLevel level_; - std::string path_; - std::vector children_; - std::vector> links_; + bool update(); private: + virtual void update_status() = 0; size_t index_; + std::vector parents_; + std::optional prev_level_; +}; + +class NodeUnit : public BaseUnit +{ +public: + explicit NodeUnit(const UnitLoader & unit); + void initialize_struct(); + void initialize_status(); + bool is_leaf() const override { return false; } + DiagNodeStruct create_struct() const { return struct_; } + DiagNodeStatus create_status() const { return status_; } + DiagnosticLevel level() const override { return status_.level; } + std::string path() const override { return struct_.path; } + +protected: + DiagNodeStruct struct_; + DiagNodeStatus status_; }; -class DiagUnit : public BaseUnit +class LeafUnit : public BaseUnit { public: - using BaseUnit::BaseUnit; - void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) override; - void update(const rclcpp::Time & stamp) override; - std::string type() const override { return "diag"; } + explicit LeafUnit(const UnitLoader & unit); + void initialize_struct(); + void initialize_status(); + bool is_leaf() const override { return true; } + DiagLeafStruct create_struct() const { return struct_; } + DiagLeafStatus create_status() const { return status_; } + DiagnosticLevel level() const override { return status_.level; } + std::string name() const { return struct_.name; } + std::string path() const override { return struct_.path; } - std::string name() const { return name_; } - void callback(const rclcpp::Time & stamp, const DiagnosticStatus & status); +protected: + DiagLeafStruct struct_; + DiagLeafStatus status_; +}; + +class DiagUnit : public LeafUnit +{ +public: + explicit DiagUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::diag; } + std::vector child_links() const override { return {}; } + bool on_time(const rclcpp::Time & stamp); + bool on_diag(const rclcpp::Time & stamp, const DiagnosticStatus & status); private: + void update_status() override; double timeout_; - std::optional> diagnostics_; - std::string name_; + std::optional last_updated_time_; +}; + +class MaxUnit : public NodeUnit +{ +public: + explicit MaxUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::max; } + std::vector child_links() const override { return links_; } + +protected: + std::vector links_; + +private: + void update_status() override; +}; + +class ShortCircuitMaxUnit : public MaxUnit +{ +public: + using MaxUnit::MaxUnit; + std::string type() const override { return unit_name::short_circuit_max; } + +private: + void update_status() override; }; -class AndUnit : public BaseUnit +class MinUnit : public NodeUnit { public: - AndUnit(const std::string & path, bool short_circuit); - void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) override; - void update(const rclcpp::Time & stamp) override; - std::string type() const override { return short_circuit_ ? "short-circuit-and" : "and"; } + explicit MinUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::min; } + std::vector child_links() const override { return links_; } + +protected: + std::vector links_; private: - bool short_circuit_; + void update_status() override; +}; + +class RemapUnit : public NodeUnit +{ +public: + explicit RemapUnit(const UnitLoader & unit); + std::vector child_links() const override { return {link_}; } + +protected: + UnitLink * link_; + DiagnosticLevel level_from_; + DiagnosticLevel level_to_; + +private: + void update_status() override; +}; + +class WarnToOkUnit : public RemapUnit +{ +public: + explicit WarnToOkUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::warn_to_ok; } }; -class OrUnit : public BaseUnit +class WarnToErrorUnit : public RemapUnit { public: - using BaseUnit::BaseUnit; - void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) override; - void update(const rclcpp::Time & stamp) override; - std::string type() const override { return "or"; } + explicit WarnToErrorUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::warn_to_error; } }; -class RemapUnit : public BaseUnit +class ConstUnit : public NodeUnit { public: - RemapUnit(const std::string & path, DiagnosticLevel remap_warn); - void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) override; - void update(const rclcpp::Time & stamp) override; - std::string type() const override { return "remap"; } + using NodeUnit::NodeUnit; + std::vector child_links() const override { return {}; } private: - DiagnosticLevel remap_warn_; + void update_status() override; +}; + +class OkUnit : public ConstUnit +{ +public: + explicit OkUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::ok; } +}; + +class WarnUnit : public ConstUnit +{ +public: + explicit WarnUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::warn; } +}; + +class ErrorUnit : public ConstUnit +{ +public: + explicit ErrorUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::error; } }; -class DebugUnit : public BaseUnit +class StaleUnit : public ConstUnit { public: - DebugUnit(const std::string & path, DiagnosticLevel level); - void init(const UnitConfig::SharedPtr & config, const NodeDict & dict) override; - void update(const rclcpp::Time & stamp) override; - std::string type() const override { return "const"; } + explicit StaleUnit(const UnitLoader & unit); + std::string type() const override { return unit_name::stale; } }; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/node/aggregator.cpp b/system/diagnostic_graph_aggregator/src/node/aggregator.cpp index cd16ce8e33e59..3287d30d4de18 100644 --- a/system/diagnostic_graph_aggregator/src/node/aggregator.cpp +++ b/system/diagnostic_graph_aggregator/src/node/aggregator.cpp @@ -15,6 +15,7 @@ #include "aggregator.hpp" #include +#include #include namespace diagnostic_graph_aggregator @@ -22,51 +23,78 @@ namespace diagnostic_graph_aggregator AggregatorNode::AggregatorNode() : Node("aggregator") { + const auto stamp = now(); + // Init diagnostics graph. { - const auto file = declare_parameter("graph_file"); - graph_.init(file); + const auto graph_file = declare_parameter("graph_file"); + std::ostringstream id; + id << std::hex << stamp.nanoseconds(); + graph_.create(graph_file, id.str()); } // Init plugins. if (declare_parameter("use_operation_mode_availability")) { - modes_ = std::make_unique(*this, graph_.nodes()); + modes_ = std::make_unique(*this, graph_); } // Init ros interface. { - using std::placeholders::_1; const auto qos_input = rclcpp::QoS(declare_parameter("input_qos_depth")); - const auto qos_graph = rclcpp::QoS(declare_parameter("graph_qos_depth")); - - const auto callback = std::bind(&AggregatorNode::on_diag, this, _1); + const auto qos_unknown = rclcpp::QoS(1); // TODO(Takagi, Isamu): parameter + const auto qos_struct = rclcpp::QoS(1).transient_local(); + const auto qos_status = rclcpp::QoS(declare_parameter("graph_qos_depth")); + const auto callback = std::bind(&AggregatorNode::on_diag, this, std::placeholders::_1); sub_input_ = create_subscription("/diagnostics", qos_input, callback); - pub_graph_ = create_publisher("/diagnostics_graph", qos_graph); + pub_unknown_ = create_publisher("/diagnostics_graph/unknowns", qos_unknown); + pub_struct_ = create_publisher("/diagnostics_graph/struct", qos_struct); + pub_status_ = create_publisher("/diagnostics_graph/status", qos_status); const auto rate = rclcpp::Rate(declare_parameter("rate")); timer_ = rclcpp::create_timer(this, get_clock(), rate.period(), [this]() { on_timer(); }); } - // Init debug mode. - debug_ = declare_parameter("use_debug_mode"); + // Send structure topic once. + pub_struct_->publish(graph_.create_struct(stamp)); } AggregatorNode::~AggregatorNode() { - // for unique_ptr + // For unique_ptr members. +} + +DiagnosticArray AggregatorNode::create_unknown_diags(const rclcpp::Time & stamp) +{ + DiagnosticArray msg; + msg.header.stamp = stamp; + for (const auto & [name, diag] : unknown_diags_) msg.status.push_back(diag); + return msg; } void AggregatorNode::on_timer() { + // Check timeout of diag units. const auto stamp = now(); - pub_graph_->publish(graph_.report(stamp)); - if (debug_) graph_.debug(); + graph_.update(stamp); + + // Publish status. + pub_status_->publish(graph_.create_status(stamp)); + pub_unknown_->publish(create_unknown_diags(stamp)); if (modes_) modes_->update(stamp); } -void AggregatorNode::on_diag(const DiagnosticArray::ConstSharedPtr msg) +void AggregatorNode::on_diag(const DiagnosticArray & msg) { - graph_.callback(now(), *msg); + // Update status. Store it as unknown if it does not exist in the graph. + const auto & stamp = msg.header.stamp; + for (const auto & status : msg.status) { + if (!graph_.update(stamp, status)) { + unknown_diags_[status.name] = status; + } + } + + // TODO(Takagi, Isamu): Publish immediately when graph status changes. + // pub_status_->publish(); } } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/node/aggregator.hpp b/system/diagnostic_graph_aggregator/src/node/aggregator.hpp index 6bf9aead9754d..8a0e12edb25e5 100644 --- a/system/diagnostic_graph_aggregator/src/node/aggregator.hpp +++ b/system/diagnostic_graph_aggregator/src/node/aggregator.hpp @@ -15,13 +15,14 @@ #ifndef NODE__AGGREGATOR_HPP_ #define NODE__AGGREGATOR_HPP_ +#include "availability.hpp" #include "graph/graph.hpp" -#include "graph/types.hpp" -#include "plugin/modes.hpp" #include #include +#include +#include namespace diagnostic_graph_aggregator { @@ -34,14 +35,17 @@ class AggregatorNode : public rclcpp::Node private: Graph graph_; - std::unique_ptr modes_; + std::unique_ptr modes_; rclcpp::TimerBase::SharedPtr timer_; rclcpp::Subscription::SharedPtr sub_input_; - rclcpp::Publisher::SharedPtr pub_graph_; + rclcpp::Publisher::SharedPtr pub_unknown_; + rclcpp::Publisher::SharedPtr pub_struct_; + rclcpp::Publisher::SharedPtr pub_status_; + DiagnosticArray create_unknown_diags(const rclcpp::Time & stamp); void on_timer(); - void on_diag(const DiagnosticArray::ConstSharedPtr msg); + void on_diag(const DiagnosticArray & msg); - bool debug_; + std::unordered_map unknown_diags_; }; } // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/node/plugin/modes.cpp b/system/diagnostic_graph_aggregator/src/node/availability.cpp similarity index 66% rename from system/diagnostic_graph_aggregator/src/node/plugin/modes.cpp rename to system/diagnostic_graph_aggregator/src/node/availability.cpp index c73de86cba439..60ad418799716 100644 --- a/system/diagnostic_graph_aggregator/src/node/plugin/modes.cpp +++ b/system/diagnostic_graph_aggregator/src/node/availability.cpp @@ -12,10 +12,10 @@ // See the License for the specific language governing permissions and // limitations under the License. -#include "modes.hpp" +#include "availability.hpp" -#include "graph/config.hpp" #include "graph/error.hpp" +#include "graph/graph.hpp" #include "graph/units.hpp" #include @@ -25,38 +25,38 @@ namespace diagnostic_graph_aggregator { -OperationModes::OperationModes(rclcpp::Node & node, const std::vector & graph) +ModesAvailability::ModesAvailability(rclcpp::Node & node, const Graph & graph) { pub_ = node.create_publisher("/system/operation_mode/availability", rclcpp::QoS(1)); using PathDict = std::unordered_map; PathDict paths; - for (const auto & node : graph) { - paths[node->path()] = node; + for (const auto & unit : graph.units()) { + paths[unit->path()] = unit; } - const auto find_node = [](const PathDict & paths, const std::string & name) { + const auto find_unit = [](const PathDict & paths, const std::string & name) { const auto iter = paths.find(name); if (iter != paths.end()) { return iter->second; } - throw error("summary node is not found", name); + throw ModeNotFound(name); }; // clang-format off - stop_mode_ = find_node(paths, "/autoware/modes/stop"); - autonomous_mode_ = find_node(paths, "/autoware/modes/autonomous"); - local_mode_ = find_node(paths, "/autoware/modes/local"); - remote_mode_ = find_node(paths, "/autoware/modes/remote"); - emergency_stop_mrm_ = find_node(paths, "/autoware/modes/emergency_stop"); - comfortable_stop_mrm_ = find_node(paths, "/autoware/modes/comfortable_stop"); - pull_over_mrm_ = find_node(paths, "/autoware/modes/pull_over"); + stop_mode_ = find_unit(paths, "/autoware/modes/stop"); + autonomous_mode_ = find_unit(paths, "/autoware/modes/autonomous"); + local_mode_ = find_unit(paths, "/autoware/modes/local"); + remote_mode_ = find_unit(paths, "/autoware/modes/remote"); + emergency_stop_mrm_ = find_unit(paths, "/autoware/modes/emergency_stop"); + comfortable_stop_mrm_ = find_unit(paths, "/autoware/modes/comfortable_stop"); + pull_over_mrm_ = find_unit(paths, "/autoware/modes/pull_over"); // clang-format on } -void OperationModes::update(const rclcpp::Time & stamp) const +void ModesAvailability::update(const rclcpp::Time & stamp) const { - const auto is_ok = [](const BaseUnit * node) { return node->level() == DiagnosticStatus::OK; }; + const auto is_ok = [](const BaseUnit * unit) { return unit->level() == DiagnosticStatus::OK; }; // clang-format off Availability message; diff --git a/system/diagnostic_graph_aggregator/src/node/plugin/modes.hpp b/system/diagnostic_graph_aggregator/src/node/availability.hpp similarity index 85% rename from system/diagnostic_graph_aggregator/src/node/plugin/modes.hpp rename to system/diagnostic_graph_aggregator/src/node/availability.hpp index 1ed22c7d9d058..c91db089266f5 100644 --- a/system/diagnostic_graph_aggregator/src/node/plugin/modes.hpp +++ b/system/diagnostic_graph_aggregator/src/node/availability.hpp @@ -12,8 +12,8 @@ // See the License for the specific language governing permissions and // limitations under the License. -#ifndef NODE__PLUGIN__MODES_HPP_ -#define NODE__PLUGIN__MODES_HPP_ +#ifndef NODE__AVAILABILITY_HPP_ +#define NODE__AVAILABILITY_HPP_ #include "graph/types.hpp" @@ -21,15 +21,13 @@ #include -#include - namespace diagnostic_graph_aggregator { -class OperationModes +class ModesAvailability { public: - OperationModes(rclcpp::Node & node, const std::vector & graph); + ModesAvailability(rclcpp::Node & node, const Graph & graph); void update(const rclcpp::Time & stamp) const; private: @@ -48,4 +46,4 @@ class OperationModes } // namespace diagnostic_graph_aggregator -#endif // NODE__PLUGIN__MODES_HPP_ +#endif // NODE__AVAILABILITY_HPP_ diff --git a/system/diagnostic_graph_aggregator/src/node/converter.cpp b/system/diagnostic_graph_aggregator/src/node/converter.cpp deleted file mode 100644 index f0b2108374017..0000000000000 --- a/system/diagnostic_graph_aggregator/src/node/converter.cpp +++ /dev/null @@ -1,133 +0,0 @@ -// Copyright 2023 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "converter.hpp" - -#include - -namespace diagnostic_graph_aggregator -{ - -std::string level_to_string(DiagnosticLevel level) -{ - switch (level) { - case DiagnosticStatus::OK: - return "OK"; - case DiagnosticStatus::WARN: - return "WARN"; - case DiagnosticStatus::ERROR: - return "ERROR"; - case DiagnosticStatus::STALE: - return "STALE"; - } - return "UNKNOWN"; -} - -std::string parent_path(const std::string & path) -{ - return path.substr(0, path.rfind('/')); -} - -auto create_tree(const DiagnosticGraph & graph) -{ - std::map, std::greater> tree; - for (const auto & node : graph.nodes) { - tree.emplace(node.status.name, std::make_unique(true)); - } - for (const auto & node : graph.nodes) { - std::string path = node.status.name; - while (path = parent_path(path), !path.empty()) { - if (tree.count(path)) break; - tree.emplace(path, std::make_unique(false)); - } - } - for (const auto & [path, node] : tree) { - const auto parent = parent_path(path); - node->parent = parent.empty() ? nullptr : tree[parent].get(); - } - return tree; -} - -ConverterNode::ConverterNode() : Node("converter") -{ - using std::placeholders::_1; - const auto qos_graph = rclcpp::QoS(1); - const auto qos_array = rclcpp::QoS(1); - - const auto callback = std::bind(&ConverterNode::on_graph, this, _1); - sub_graph_ = create_subscription("/diagnostics_graph", qos_graph, callback); - pub_array_ = create_publisher("/diagnostics_agg", qos_array); - - initialize_tree_ = false; - complement_tree_ = declare_parameter("complement_tree"); -} - -void ConverterNode::on_graph(const DiagnosticGraph::ConstSharedPtr msg) -{ - DiagnosticArray message; - message.header.stamp = msg->stamp; - message.status.reserve(msg->nodes.size()); - for (const auto & node : msg->nodes) { - message.status.push_back(node.status); - for (const auto & link : node.links) { - diagnostic_msgs::msg::KeyValue kv; - const auto & status = msg->nodes[link.index].status; - kv.key = status.name; - kv.value = level_to_string(status.level); - if (link.used) { - message.status.back().values.push_back(kv); - } - } - } - - if (complement_tree_ && !initialize_tree_) { - initialize_tree_ = true; - tree_ = create_tree(*msg); - } - - if (complement_tree_) { - for (const auto & [path, node] : tree_) { - node->level = DiagnosticStatus::OK; - } - for (const auto & node : msg->nodes) { - tree_[node.status.name]->level = node.status.level; - } - for (const auto & [path, node] : tree_) { - if (!node->parent) continue; - node->parent->level = std::max(node->parent->level, node->level); - } - for (const auto & [path, node] : tree_) { - if (node->leaf) continue; - message.status.emplace_back(); - message.status.back().name = path; - message.status.back().level = node->level; - } - } - - pub_array_->publish(message); -} - -} // namespace diagnostic_graph_aggregator - -int main(int argc, char ** argv) -{ - using diagnostic_graph_aggregator::ConverterNode; - rclcpp::init(argc, argv); - rclcpp::executors::SingleThreadedExecutor executor; - auto node = std::make_shared(); - executor.add_node(node); - executor.spin(); - executor.remove_node(node); - rclcpp::shutdown(); -} diff --git a/system/diagnostic_graph_aggregator/src/tool/plantuml.cpp b/system/diagnostic_graph_aggregator/src/tool/plantuml.cpp index bfbb382a78fcb..9f7eb34bf3454 100644 --- a/system/diagnostic_graph_aggregator/src/tool/plantuml.cpp +++ b/system/diagnostic_graph_aggregator/src/tool/plantuml.cpp @@ -12,7 +12,8 @@ // See the License for the specific language governing permissions and // limitations under the License. -#include "utils/loader.hpp" +#include "graph/graph.hpp" +#include "graph/units.hpp" #include @@ -21,18 +22,19 @@ namespace diagnostic_graph_aggregator void dump_root(const std::string & path) { - const auto graph = load_graph_nodes(path); - const auto color = "#FFFFFF"; + const auto color = "#EEEEEE"; + Graph graph; + graph.create(path); - for (const auto & node : graph.nodes) { - std::cout << "card " << node << " " << color << " [" << std::endl; - std::cout << node->path << std::endl; + for (const auto & unit : graph.units()) { + std::cout << "card " << unit << " " << color << " [" << std::endl; + std::cout << unit->path() << std::endl; std::cout << "]" << std::endl; } - for (const auto & node : graph.nodes) { - for (const auto & child : node->children) { - std::cout << node << " --> " << child << std::endl; + for (const auto & unit : graph.units()) { + for (const auto & link : unit->child_links()) { + std::cout << unit << " --> " << link->child() << std::endl; } } } diff --git a/system/diagnostic_graph_aggregator/src/tool/tree.cpp b/system/diagnostic_graph_aggregator/src/tool/tree.cpp index 9dbbc539b3b91..1e6fe93b18a80 100644 --- a/system/diagnostic_graph_aggregator/src/tool/tree.cpp +++ b/system/diagnostic_graph_aggregator/src/tool/tree.cpp @@ -12,47 +12,49 @@ // See the License for the specific language governing permissions and // limitations under the License. -#include "utils/loader.hpp" +#include "graph/graph.hpp" +#include "graph/units.hpp" #include namespace diagnostic_graph_aggregator { -void dump_node(const GraphNode * node, const std::string & indent = "", bool root = true) +void dump_unit(const BaseUnit * unit, const std::string & indent = "", bool root = true) { - const auto path = node->path.empty() ? "" : node->path + " "; - const auto type = "(" + node->type + ")"; + const auto path = unit->path().empty() ? "" : unit->path() + " "; + const auto type = "(" + unit->type() + ")"; std::cout << indent << "- " << path << type << std::endl; - if (root || node->parents.size() == 1) { - for (const auto child : node->children) { - dump_node(child, indent + " ", false); + if (root || unit->parent_size() == 1) { + for (const auto link : unit->child_links()) { + dump_unit(link->child(), indent + " ", false); } } } void dump_root(const std::string & path) { - const auto graph = load_graph_nodes(path); + Graph graph; + graph.create(path); - std::cout << "===== root nodes =================================" << std::endl; - for (const auto & node : graph.nodes) { - if (node->parents.size() == 0 && node->children.size() != 0) { - dump_node(node); + std::cout << "===== Top-level trees ============================" << std::endl; + for (const auto & unit : graph.units()) { + if (unit->parent_size() == 0 && unit->child_links().size() != 0) { + dump_unit(unit); } } - std::cout << "===== intermediate nodes =========================" << std::endl; - for (const auto & node : graph.nodes) { - if (node->parents.size() >= 2) { - dump_node(node); + std::cout << "===== Subtrees ===================================" << std::endl; + for (const auto & unit : graph.units()) { + if (unit->parent_size() >= 2 && unit->child_links().size() != 0) { + dump_unit(unit); } } - std::cout << "===== isolated nodes =============================" << std::endl; - for (const auto & node : graph.nodes) { - if (node->parents.size() == 0 && node->children.size() == 0) { - dump_node(node); + std::cout << "===== Isolated units =============================" << std::endl; + for (const auto & unit : graph.units()) { + if (unit->parent_size() == 0 && unit->child_links().size() == 0) { + dump_unit(unit); } } } diff --git a/system/diagnostic_graph_aggregator/src/tool/utils/loader.cpp b/system/diagnostic_graph_aggregator/src/tool/utils/loader.cpp deleted file mode 100644 index a2e6ce8b85334..0000000000000 --- a/system/diagnostic_graph_aggregator/src/tool/utils/loader.cpp +++ /dev/null @@ -1,57 +0,0 @@ -// Copyright 2023 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "loader.hpp" - -#include -#include - -namespace diagnostic_graph_aggregator -{ - -GraphRoot load_graph_nodes(const std::string & path) -{ - GraphRoot result; - { - std::unordered_map mapping; - Graph graph; - graph.init(path); - - for (const auto & node : graph.nodes()) { - auto data = std::make_unique(); - data->path = node->path(); - data->type = node->type(); - mapping[node] = std::move(data); - } - - for (const auto & [node, data] : mapping) { - for (const auto & link : node->children()) { - const auto parent = data.get(); - const auto child = mapping.at(link).get(); - child->parents.push_back(parent); - parent->children.push_back(child); - } - } - - for (auto & [node, data] : mapping) { - result.owner.push_back(std::move(data)); - } - for (const auto & node : result.owner) { - result.nodes.push_back(node.get()); - } - } - return result; -} - -} // namespace diagnostic_graph_aggregator diff --git a/system/diagnostic_graph_aggregator/src/tool/utils/loader.hpp b/system/diagnostic_graph_aggregator/src/tool/utils/loader.hpp deleted file mode 100644 index 70e01ec2a77b4..0000000000000 --- a/system/diagnostic_graph_aggregator/src/tool/utils/loader.hpp +++ /dev/null @@ -1,48 +0,0 @@ -// Copyright 2023 The Autoware Contributors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#ifndef TOOL__UTILS__LOADER_HPP_ -#define TOOL__UTILS__LOADER_HPP_ - -#include "graph/graph.hpp" -#include "graph/types.hpp" -#include "graph/units.hpp" - -#include -#include -#include - -namespace diagnostic_graph_aggregator -{ - -struct GraphNode -{ - using UniquePtr = std::unique_ptr; - std::string type; - std::string path; - std::vector children; - std::vector parents; -}; - -struct GraphRoot -{ - std::vector owner; - std::vector nodes; -}; - -GraphRoot load_graph_nodes(const std::string & path); - -} // namespace diagnostic_graph_aggregator - -#endif // TOOL__UTILS__LOADER_HPP_ diff --git a/system/diagnostic_graph_aggregator/test/files/test1/field-not-found.yaml b/system/diagnostic_graph_aggregator/test/files/test1/field-not-found.yaml index 9e2b3708c049a..6070f690a3882 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/field-not-found.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/field-not-found.yaml @@ -1,2 +1,2 @@ -nodes: +units: - test-type: test-type diff --git a/system/diagnostic_graph_aggregator/test/files/test1/graph-circulation.yaml b/system/diagnostic_graph_aggregator/test/files/test1/graph-circulation.yaml index 4c014bdcec3f9..980d0670a7ccf 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/graph-circulation.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/graph-circulation.yaml @@ -1,4 +1,4 @@ -nodes: +units: - path: /foo/bar type: and list: diff --git a/system/diagnostic_graph_aggregator/test/files/test1/invalid-dict-type.yaml b/system/diagnostic_graph_aggregator/test/files/test1/invalid-dict-type.yaml index 6499b05ab8b7d..6c4cb8701ceea 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/invalid-dict-type.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/invalid-dict-type.yaml @@ -1 +1 @@ -nodes: test-object +units: test-object diff --git a/system/diagnostic_graph_aggregator/test/files/test1/invalid-list-type.yaml b/system/diagnostic_graph_aggregator/test/files/test1/invalid-list-type.yaml index 4fc5d96c08c62..34fd1436ed496 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/invalid-list-type.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/invalid-list-type.yaml @@ -1,3 +1,3 @@ -nodes: +units: - type: and list: test-list diff --git a/system/diagnostic_graph_aggregator/test/files/test1/path-conflict.yaml b/system/diagnostic_graph_aggregator/test/files/test1/path-conflict.yaml index ea3e536b74216..280276b7077db 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/path-conflict.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/path-conflict.yaml @@ -1,4 +1,4 @@ -nodes: +units: - path: /foo/bar type: and - path: /foo/bar diff --git a/system/diagnostic_graph_aggregator/test/files/test1/path-not-found.yaml b/system/diagnostic_graph_aggregator/test/files/test1/path-not-found.yaml index 6b0b10dfa94f4..f9d3021bb2a74 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/path-not-found.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/path-not-found.yaml @@ -1,4 +1,4 @@ -nodes: +units: - path: /foo/bar type: and - link: /foo/baz diff --git a/system/diagnostic_graph_aggregator/test/files/test1/unknown-node-type.yaml b/system/diagnostic_graph_aggregator/test/files/test1/unknown-unit-type.yaml similarity index 74% rename from system/diagnostic_graph_aggregator/test/files/test1/unknown-node-type.yaml rename to system/diagnostic_graph_aggregator/test/files/test1/unknown-unit-type.yaml index a3d66fbfa43cb..865e535dc7173 100644 --- a/system/diagnostic_graph_aggregator/test/files/test1/unknown-node-type.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test1/unknown-unit-type.yaml @@ -1,2 +1,2 @@ -nodes: +units: - type: test-type diff --git a/system/diagnostic_graph_aggregator/test/files/test2/and.yaml b/system/diagnostic_graph_aggregator/test/files/test2/and.yaml index 0c9b651f89b2e..479a281ff9d08 100644 --- a/system/diagnostic_graph_aggregator/test/files/test2/and.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test2/and.yaml @@ -1,10 +1,12 @@ -nodes: +units: - path: output type: and list: - path: input-0 type: diag - diag: "test: input-0" + node: test + name: input-0 - path: input-1 type: diag - diag: "test: input-1" + node: test + name: input-1 diff --git a/system/diagnostic_graph_aggregator/test/files/test2/or.yaml b/system/diagnostic_graph_aggregator/test/files/test2/or.yaml index c7f37a6c32064..cb8440829891e 100644 --- a/system/diagnostic_graph_aggregator/test/files/test2/or.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test2/or.yaml @@ -1,10 +1,12 @@ -nodes: +units: - path: output type: or list: - path: input-0 type: diag - diag: "test: input-0" + node: test + name: input-0 - path: input-1 type: diag - diag: "test: input-1" + node: test + name: input-1 diff --git a/system/diagnostic_graph_aggregator/test/files/test2/warn-to-error.yaml b/system/diagnostic_graph_aggregator/test/files/test2/warn-to-error.yaml index 816bf4fd6e1bf..42eef3d976151 100644 --- a/system/diagnostic_graph_aggregator/test/files/test2/warn-to-error.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test2/warn-to-error.yaml @@ -1,7 +1,8 @@ -nodes: +units: - path: output type: warn-to-error - list: - - path: input-0 - type: diag - diag: "test: input-0" + item: + path: input-0 + type: diag + node: test + name: input-0 diff --git a/system/diagnostic_graph_aggregator/test/files/test2/warn-to-ok.yaml b/system/diagnostic_graph_aggregator/test/files/test2/warn-to-ok.yaml index 1f5cf18978e3c..90a10cfd42bc5 100644 --- a/system/diagnostic_graph_aggregator/test/files/test2/warn-to-ok.yaml +++ b/system/diagnostic_graph_aggregator/test/files/test2/warn-to-ok.yaml @@ -1,7 +1,8 @@ -nodes: +units: - path: output type: warn-to-ok - list: - - path: input-0 - type: diag - diag: "test: input-0" + item: + path: input-0 + type: diag + node: test + name: input-0 diff --git a/system/diagnostic_graph_aggregator/test/src/test1.cpp b/system/diagnostic_graph_aggregator/test/src/test1.cpp index 48a0e1f45ce07..ea157852675ec 100644 --- a/system/diagnostic_graph_aggregator/test/src/test1.cpp +++ b/system/diagnostic_graph_aggregator/test/src/test1.cpp @@ -23,59 +23,59 @@ using namespace diagnostic_graph_aggregator; // NOLINT(build/namespaces) TEST(ConfigFile, RootNotFound) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/fake-file-name.yaml")), FileNotFound); + EXPECT_THROW(graph.create(resource("test1/fake-file-name.yaml")), FileNotFound); } TEST(ConfigFile, FileNotFound) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/file-not-found.yaml")), FileNotFound); + EXPECT_THROW(graph.create(resource("test1/file-not-found.yaml")), FileNotFound); } TEST(ConfigFile, UnknownSubstitution) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/unknown-substitution.yaml")), UnknownType); + EXPECT_THROW(graph.create(resource("test1/unknown-substitution.yaml")), UnknownSubstitution); } TEST(ConfigFile, UnknownNodeType) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/unknown-node-type.yaml")), UnknownType); + EXPECT_THROW(graph.create(resource("test1/unknown-unit-type.yaml")), UnknownUnitType); } TEST(ConfigFile, InvalidDictType) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/invalid-dict-type.yaml")), InvalidType); + EXPECT_THROW(graph.create(resource("test1/invalid-dict-type.yaml")), InvalidType); } TEST(ConfigFile, InvalidListType) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/invalid-list-type.yaml")), InvalidType); + EXPECT_THROW(graph.create(resource("test1/invalid-list-type.yaml")), InvalidType); } TEST(ConfigFile, FieldNotFound) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/field-not-found.yaml")), FieldNotFound); + EXPECT_THROW(graph.create(resource("test1/field-not-found.yaml")), FieldNotFound); } TEST(ConfigFile, PathConflict) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/path-conflict.yaml")), PathConflict); + EXPECT_THROW(graph.create(resource("test1/path-conflict.yaml")), PathConflict); } TEST(ConfigFile, PathNotFound) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/path-not-found.yaml")), PathNotFound); + EXPECT_THROW(graph.create(resource("test1/path-not-found.yaml")), PathNotFound); } TEST(ConfigFile, GraphCirculation) { Graph graph; - EXPECT_THROW(graph.init(resource("test1/graph-circulation.yaml")), GraphStructure); + EXPECT_THROW(graph.create(resource("test1/graph-circulation.yaml")), GraphStructure); } diff --git a/system/diagnostic_graph_aggregator/test/src/test2.cpp b/system/diagnostic_graph_aggregator/test/src/test2.cpp index 1098ff9efb0db..b010994f5a1ca 100644 --- a/system/diagnostic_graph_aggregator/test/src/test2.cpp +++ b/system/diagnostic_graph_aggregator/test/src/test2.cpp @@ -56,11 +56,14 @@ DiagnosticArray create_input(const std::vector & levels) return array; }; -uint8_t get_output(const DiagnosticGraph & graph) +uint8_t get_output(const Graph & graph, const rclcpp::Time & stamp) { - for (const auto & node : graph.nodes) { - if (node.status.name == "output") { - return node.status.level; + const auto struct_nodes = graph.create_struct(stamp).nodes; + const auto status_nodes = graph.create_status(stamp).nodes; + + for (size_t i = 0; i < struct_nodes.size(); ++i) { + if (struct_nodes[i].path == "output") { + return status_nodes[i].level; } } throw std::runtime_error("output node is not found"); @@ -68,13 +71,17 @@ uint8_t get_output(const DiagnosticGraph & graph) TEST_P(GraphTest, Aggregation) { - const auto param = GetParam(); const auto stamp = rclcpp::Clock().now(); + const auto param = GetParam(); Graph graph; - graph.init(resource(param.config)); - graph.callback(stamp, create_input(param.inputs)); + graph.create(resource(param.config)); + + const auto array = create_input(param.inputs); + for (const auto & status : array.status) { + graph.update(stamp, status); + } - const auto output = get_output(graph.report(stamp)); + const auto output = get_output(graph, stamp); EXPECT_EQ(output, param.result); } diff --git a/system/diagnostic_graph_utils/CMakeLists.txt b/system/diagnostic_graph_utils/CMakeLists.txt new file mode 100644 index 0000000000000..48af5e8fc304f --- /dev/null +++ b/system/diagnostic_graph_utils/CMakeLists.txt @@ -0,0 +1,20 @@ +cmake_minimum_required(VERSION 3.14) +project(diagnostic_graph_utils) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +ament_auto_add_library(${PROJECT_NAME} SHARED + src/lib/graph.cpp + src/lib/subscription.cpp +) + +ament_auto_add_executable(dump + src/node/dump.cpp +) + +ament_auto_add_executable(converter + src/node/converter.cpp +) + +ament_auto_package() diff --git a/system/diagnostic_graph_utils/README.md b/system/diagnostic_graph_utils/README.md new file mode 100644 index 0000000000000..a06d664622bff --- /dev/null +++ b/system/diagnostic_graph_utils/README.md @@ -0,0 +1,13 @@ +# diagnostic_graph_utils + +This package is a utility for diagnostic graph published by [diagnostic_graph_aggregator](../diagnostic_graph_aggregator/README.md). + +## ROS node + +- [dump](./doc/node/dump.md) +- [converter](./doc/node/converter.md) + +## C++ library + +- [DiagGraph](./include/diagnostic_graph_utils/graph.hpp) +- [DiagGraphSubscription](./include/diagnostic_graph_utils/subscription.hpp) diff --git a/system/diagnostic_graph_utils/doc/node/converter.md b/system/diagnostic_graph_utils/doc/node/converter.md new file mode 100644 index 0000000000000..c3db547167474 --- /dev/null +++ b/system/diagnostic_graph_utils/doc/node/converter.md @@ -0,0 +1,31 @@ +# Converter tool + +This tool converts `/diagnostics_graph` to `/diagnostics_array` so it can be read by tools such as `rqt_runtime_monitor`. + +## Usage + +```bash +ros2 run diagnostic_graph_utils converter +``` + +## Examples + +Terminal 1: + +```bash +ros2 launch diagnostic_graph_aggregator example-main.launch.xml +``` + +Terminal 2: + +```bash +ros2 run diagnostic_graph_utils converter +``` + +Terminal 3: + +```bash +ros2 run rqt_runtime_monitor rqt_runtime_monitor --ros-args -r diagnostics:=diagnostics_array +``` + +![rqt_runtime_monitor](./images/rqt_runtime_monitor.png) diff --git a/system/diagnostic_graph_utils/doc/node/dump.md b/system/diagnostic_graph_utils/doc/node/dump.md new file mode 100644 index 0000000000000..090e9679676b6 --- /dev/null +++ b/system/diagnostic_graph_utils/doc/node/dump.md @@ -0,0 +1,46 @@ +# Dump tool + +This tool displays `/diagnostics_graph` in table format. + +## Usage + +```bash +ros2 run diagnostic_graph_utils dump +``` + +## Examples + +Terminal 1: + +```bash +ros2 launch diagnostic_graph_aggregator example-main.launch.xml +``` + +Terminal 2: + +```bash +ros2 run diagnostic_graph_utils dump +``` + +Output: + +```txt +|----|-------|----------------------------------|------|----------| +| No | Level | Path | Type | Children | +|----|-------|----------------------------------|------|----------| +| 1 | OK | /autoware/modes/stop | ok | | +| 2 | ERROR | /autoware/modes/autonomous | and | 8 9 | +| 3 | OK | /autoware/modes/local | and | 13 | +| 4 | OK | /autoware/modes/remote | and | 14 | +| 5 | OK | /autoware/modes/emergency_stop | ok | | +| 6 | OK | /autoware/modes/comfortable_stop | and | 9 | +| 7 | ERROR | /autoware/modes/pull_over | and | 8 9 | +| 8 | ERROR | /functions/pose_estimation | and | 10 | +| 9 | OK | /functions/obstacle_detection | or | 11 12 | +| 10 | ERROR | /sensing/lidars/top | diag | | +| 11 | OK | /sensing/lidars/front | diag | | +| 12 | OK | /sensing/radars/front | diag | | +| 13 | OK | /external/joystick_command | diag | | +| 14 | OK | /external/remote_command | diag | | + +``` diff --git a/system/diagnostic_graph_aggregator/doc/tool/images/rqt_runtime_monitor.png b/system/diagnostic_graph_utils/doc/node/images/rqt_runtime_monitor.png similarity index 100% rename from system/diagnostic_graph_aggregator/doc/tool/images/rqt_runtime_monitor.png rename to system/diagnostic_graph_utils/doc/node/images/rqt_runtime_monitor.png diff --git a/system/diagnostic_graph_utils/include/diagnostic_graph_utils/graph.hpp b/system/diagnostic_graph_utils/include/diagnostic_graph_utils/graph.hpp new file mode 100644 index 0000000000000..b2c6fc752e463 --- /dev/null +++ b/system/diagnostic_graph_utils/include/diagnostic_graph_utils/graph.hpp @@ -0,0 +1,133 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef DIAGNOSTIC_GRAPH_UTILS__GRAPH_HPP_ +#define DIAGNOSTIC_GRAPH_UTILS__GRAPH_HPP_ + +#include + +#include +#include +#include + +#include +#include +#include +#include +#include + +namespace diagnostic_graph_utils +{ + +class DiagLink; +class DiagUnit +{ +public: + using DiagnosticStatus = diagnostic_msgs::msg::DiagnosticStatus; + using DiagnosticLevel = DiagnosticStatus::_level_type; + + struct DiagChild + { + DiagLink * link; + DiagUnit * unit; + }; + + virtual DiagnosticStatus create_diagnostic_status() const = 0; + virtual DiagnosticLevel level() const = 0; + virtual std::string type() const = 0; + virtual std::string path() const = 0; + virtual std::vector children() const = 0; +}; + +class DiagLink +{ +public: + using DiagLinkStruct = tier4_system_msgs::msg::DiagLinkStruct; + using DiagLinkStatus = tier4_system_msgs::msg::DiagLinkStatus; + explicit DiagLink(const DiagLinkStruct & msg) : struct_(msg) {} + void update(const DiagLinkStatus & msg) { status_ = msg; } + +private: + DiagLinkStruct struct_; + DiagLinkStatus status_; +}; + +class DiagNode : public DiagUnit +{ +public: + using DiagNodeStruct = tier4_system_msgs::msg::DiagNodeStruct; + using DiagNodeStatus = tier4_system_msgs::msg::DiagNodeStatus; + explicit DiagNode(const DiagNodeStruct & msg) : struct_(msg) {} + void update(const DiagNodeStatus & msg) { status_ = msg; } + + DiagnosticStatus create_diagnostic_status() const override; + DiagnosticLevel level() const override { return status_.level; } + std::string type() const override { return struct_.type; } + std::string path() const override { return struct_.path; } + std::vector children() const override { return children_; } + void add_child(const DiagChild & child) { children_.push_back(child); } + +private: + DiagNodeStruct struct_; + DiagNodeStatus status_; + std::vector children_; +}; + +class DiagLeaf : public DiagUnit +{ +public: + using DiagLeafStruct = tier4_system_msgs::msg::DiagLeafStruct; + using DiagLeafStatus = tier4_system_msgs::msg::DiagLeafStatus; + explicit DiagLeaf(const DiagLeafStruct & msg) : struct_(msg) {} + void update(const DiagLeafStatus & msg) { status_ = msg; } + + DiagnosticStatus create_diagnostic_status() const override; + DiagnosticLevel level() const override { return status_.level; } + std::string type() const override { return struct_.type; } + std::string path() const override { return struct_.path; } + std::vector children() const override { return {}; } + +private: + DiagLeafStruct struct_; + DiagLeafStatus status_; +}; + +class DiagGraph +{ +public: + using DiagGraphStruct = tier4_system_msgs::msg::DiagGraphStruct; + using DiagGraphStatus = tier4_system_msgs::msg::DiagGraphStatus; + using SharedPtr = std::shared_ptr; + using ConstSharedPtr = std::shared_ptr; + void create(const DiagGraphStruct & msg); + bool update(const DiagGraphStatus & msg); + rclcpp::Time created_stamp() const { return created_stamp_; } + rclcpp::Time updated_stamp() const { return updated_stamp_; } + std::vector units() const; + std::vector nodes() const; + std::vector diags() const; + std::vector links() const; + +private: + rclcpp::Time created_stamp_; + rclcpp::Time updated_stamp_; + std::string id_; + std::vector> nodes_; + std::vector> diags_; + std::vector> links_; +}; + +} // namespace diagnostic_graph_utils + +#endif // DIAGNOSTIC_GRAPH_UTILS__GRAPH_HPP_ diff --git a/system/diagnostic_graph_utils/include/diagnostic_graph_utils/subscription.hpp b/system/diagnostic_graph_utils/include/diagnostic_graph_utils/subscription.hpp new file mode 100644 index 0000000000000..5aebde7ea3a38 --- /dev/null +++ b/system/diagnostic_graph_utils/include/diagnostic_graph_utils/subscription.hpp @@ -0,0 +1,53 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef DIAGNOSTIC_GRAPH_UTILS__SUBSCRIPTION_HPP_ +#define DIAGNOSTIC_GRAPH_UTILS__SUBSCRIPTION_HPP_ + +#include "diagnostic_graph_utils/graph.hpp" + +#include + +#include +#include + +namespace diagnostic_graph_utils +{ + +class DiagGraphSubscription +{ +public: + using CallbackType = std::function; + DiagGraphSubscription(); + DiagGraphSubscription(rclcpp::Node & node, size_t depth); + void subscribe(rclcpp::Node & node, size_t depth); + void register_create_callback(const CallbackType & callback); + void register_update_callback(const CallbackType & callback); + +private: + using DiagGraphStruct = tier4_system_msgs::msg::DiagGraphStruct; + using DiagGraphStatus = tier4_system_msgs::msg::DiagGraphStatus; + void on_struct(const DiagGraphStruct & msg); + void on_status(const DiagGraphStatus & msg); + rclcpp::Subscription::SharedPtr sub_struct_; + rclcpp::Subscription::SharedPtr sub_status_; + + DiagGraph::SharedPtr graph_; + CallbackType create_callback_; + CallbackType update_callback_; +}; + +} // namespace diagnostic_graph_utils + +#endif // DIAGNOSTIC_GRAPH_UTILS__SUBSCRIPTION_HPP_ diff --git a/system/diagnostic_graph_utils/package.xml b/system/diagnostic_graph_utils/package.xml new file mode 100644 index 0000000000000..42d44efb6697e --- /dev/null +++ b/system/diagnostic_graph_utils/package.xml @@ -0,0 +1,23 @@ + + + + diagnostic_graph_utils + 0.1.0 + The diagnostic_graph_utils package + Takagi, Isamu + Apache License 2.0 + + ament_cmake_auto + autoware_cmake + + diagnostic_msgs + rclcpp + tier4_system_msgs + + ament_lint_auto + autoware_lint_common + + + ament_cmake + + diff --git a/system/diagnostic_graph_utils/src/lib/graph.cpp b/system/diagnostic_graph_utils/src/lib/graph.cpp new file mode 100644 index 0000000000000..f1177c1047bdb --- /dev/null +++ b/system/diagnostic_graph_utils/src/lib/graph.cpp @@ -0,0 +1,109 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "diagnostic_graph_utils/graph.hpp" + +namespace diagnostic_graph_utils +{ + +DiagUnit::DiagnosticStatus DiagNode::create_diagnostic_status() const +{ + DiagnosticStatus status; + status.level = level(); + status.name = path(); + return status; +} + +DiagUnit::DiagnosticStatus DiagLeaf::create_diagnostic_status() const +{ + DiagnosticStatus status; + status.level = level(); + status.name = path(); + status.message = status_.message; + status.hardware_id = status_.hardware_id; + status.values = status_.values; + return status; +} + +void DiagGraph::create(const DiagGraphStruct & msg) +{ + created_stamp_ = msg.stamp; + id_ = msg.id; + for (const auto & node : msg.nodes) nodes_.push_back(std::make_unique(node)); + for (const auto & diag : msg.diags) diags_.push_back(std::make_unique(diag)); + + const auto get_child = [this](bool is_leaf, size_t index) -> DiagUnit * { + if (is_leaf) { + return diags_.at(index).get(); + } else { + return nodes_.at(index).get(); + } + }; + + for (const auto & data : msg.links) { + DiagNode * parent = nodes_.at(data.parent).get(); + DiagUnit * child = get_child(data.is_leaf, data.child); + const auto link = links_.emplace_back(std::make_unique(data)).get(); + parent->add_child({link, child}); + } +} + +bool DiagGraph::update(const DiagGraphStatus & msg) +{ + if (id_ != msg.id) return false; + updated_stamp_ = msg.stamp; + for (size_t i = 0; i < msg.nodes.size(); ++i) nodes_[i]->update(msg.nodes[i]); + for (size_t i = 0; i < msg.diags.size(); ++i) diags_[i]->update(msg.diags[i]); + for (size_t i = 0; i < msg.links.size(); ++i) links_[i]->update(msg.links[i]); + return true; +} + +template +void extend_ptrs(std::vector & result, const std::vector> & list) +{ + for (const auto & item : list) result.push_back(item.get()); +} + +template +std::vector create_ptrs(const std::vector> & list) +{ + std::vector result; + extend_ptrs(result, list); + return result; +} + +std::vector DiagGraph::units() const +{ + std::vector result; + extend_ptrs(result, nodes_); + extend_ptrs(result, diags_); + return result; +} + +std::vector DiagGraph::nodes() const +{ + return create_ptrs(nodes_); +} + +std::vector DiagGraph::diags() const +{ + return create_ptrs(diags_); +} + +std::vector DiagGraph::links() const +{ + return create_ptrs(links_); +} + +} // namespace diagnostic_graph_utils diff --git a/system/diagnostic_graph_utils/src/lib/subscription.cpp b/system/diagnostic_graph_utils/src/lib/subscription.cpp new file mode 100644 index 0000000000000..655544c2e1f28 --- /dev/null +++ b/system/diagnostic_graph_utils/src/lib/subscription.cpp @@ -0,0 +1,67 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "diagnostic_graph_utils/subscription.hpp" + +namespace diagnostic_graph_utils +{ + +DiagGraphSubscription::DiagGraphSubscription() +{ + graph_ = std::make_shared(); +} + +DiagGraphSubscription::DiagGraphSubscription(rclcpp::Node & node, size_t depth) +{ + graph_ = std::make_shared(); + subscribe(node, depth); +} + +void DiagGraphSubscription::subscribe(rclcpp::Node & node, size_t depth) +{ + const auto qos_struct = rclcpp::QoS(1).transient_local(); + const auto qos_status = rclcpp::QoS(depth); + + sub_struct_ = node.create_subscription( + "/diagnostics_graph/struct", qos_struct, + std::bind(&DiagGraphSubscription::on_struct, this, std::placeholders::_1)); + sub_status_ = node.create_subscription( + "/diagnostics_graph/status", qos_status, + std::bind(&DiagGraphSubscription::on_status, this, std::placeholders::_1)); +} + +void DiagGraphSubscription::register_create_callback(const CallbackType & callback) +{ + create_callback_ = callback; +} + +void DiagGraphSubscription::register_update_callback(const CallbackType & callback) +{ + update_callback_ = callback; +} + +void DiagGraphSubscription::on_struct(const DiagGraphStruct & msg) +{ + graph_->create(msg); + if (create_callback_) create_callback_(graph_); +} + +void DiagGraphSubscription::on_status(const DiagGraphStatus & msg) +{ + if (graph_->update(msg)) { + if (update_callback_) update_callback_(graph_); + } +} + +} // namespace diagnostic_graph_utils diff --git a/system/diagnostic_graph_utils/src/node/converter.cpp b/system/diagnostic_graph_utils/src/node/converter.cpp new file mode 100644 index 0000000000000..e9e40fa0a0756 --- /dev/null +++ b/system/diagnostic_graph_utils/src/node/converter.cpp @@ -0,0 +1,53 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "converter.hpp" + +#include + +namespace diagnostic_graph_utils +{ + +ConverterNode::ConverterNode() : Node("converter") +{ + using std::placeholders::_1; + pub_array_ = create_publisher("/diagnostics_array", rclcpp::QoS(1)); + sub_graph_.register_update_callback(std::bind(&ConverterNode::on_update, this, _1)); + sub_graph_.subscribe(*this, 1); +} + +void ConverterNode::on_update(DiagGraph::ConstSharedPtr graph) +{ + DiagnosticArray array; + array.header.stamp = graph->updated_stamp(); + for (const auto & unit : graph->units()) { + if (unit->path().empty()) continue; + array.status.push_back(unit->create_diagnostic_status()); + } + pub_array_->publish(array); +} + +} // namespace diagnostic_graph_utils + +int main(int argc, char ** argv) +{ + using diagnostic_graph_utils::ConverterNode; + rclcpp::init(argc, argv); + rclcpp::executors::SingleThreadedExecutor executor; + auto node = std::make_shared(); + executor.add_node(node); + executor.spin(); + executor.remove_node(node); + rclcpp::shutdown(); +} diff --git a/system/diagnostic_graph_aggregator/src/node/converter.hpp b/system/diagnostic_graph_utils/src/node/converter.hpp similarity index 56% rename from system/diagnostic_graph_aggregator/src/node/converter.hpp rename to system/diagnostic_graph_utils/src/node/converter.hpp index 1f98abed4d619..09ce62d7293ec 100644 --- a/system/diagnostic_graph_aggregator/src/node/converter.hpp +++ b/system/diagnostic_graph_utils/src/node/converter.hpp @@ -1,4 +1,4 @@ -// Copyright 2023 The Autoware Contributors +// Copyright 2024 The Autoware Contributors // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. @@ -15,41 +15,29 @@ #ifndef NODE__CONVERTER_HPP_ #define NODE__CONVERTER_HPP_ -#include "graph/types.hpp" +#include "diagnostic_graph_utils/subscription.hpp" #include -#include -#include // Use map for sorting keys. -#include -#include -#include +#include +#include -namespace diagnostic_graph_aggregator +namespace diagnostic_graph_utils { -struct TreeNode -{ - explicit TreeNode(bool leaf) : leaf(leaf) {} - bool leaf; - TreeNode * parent; - uint8_t level; -}; - class ConverterNode : public rclcpp::Node { public: ConverterNode(); private: - bool initialize_tree_; - bool complement_tree_; - std::map, std::greater> tree_; - rclcpp::Subscription::SharedPtr sub_graph_; + using DiagnosticArray = diagnostic_msgs::msg::DiagnosticArray; + using DiagnosticStatus = diagnostic_msgs::msg::DiagnosticStatus; + void on_update(DiagGraph::ConstSharedPtr graph); rclcpp::Publisher::SharedPtr pub_array_; - void on_graph(const DiagnosticGraph::ConstSharedPtr msg); + DiagGraphSubscription sub_graph_; }; -} // namespace diagnostic_graph_aggregator +} // namespace diagnostic_graph_utils #endif // NODE__CONVERTER_HPP_ diff --git a/system/diagnostic_graph_utils/src/node/dump.cpp b/system/diagnostic_graph_utils/src/node/dump.cpp new file mode 100644 index 0000000000000..5fa4922dec1a5 --- /dev/null +++ b/system/diagnostic_graph_utils/src/node/dump.cpp @@ -0,0 +1,145 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#include "dump.hpp" + +#include +#include +#include +#include +#include +#include + +namespace diagnostic_graph_utils +{ + +DumpNode::DumpNode() : Node("dump") +{ + using std::placeholders::_1; + sub_graph_.register_create_callback(std::bind(&DumpNode::on_create, this, _1)); + sub_graph_.register_update_callback(std::bind(&DumpNode::on_update, this, _1)); + sub_graph_.subscribe(*this, 1); +} + +void DumpNode::on_create(DiagGraph::ConstSharedPtr graph) +{ + // Initialize table line information. + const std::string title_index = "No"; + const std::string title_level = "Level"; + const std::string title_path = "Path"; + const std::string title_type = "Type"; + const std::string title_link = "Children"; + + // Cache units. + const auto units = graph->units(); + + // Assign merged units index. + int table_index = 0; + for (const auto & unit : units) { + TableLine line; + line.index = ++table_index; + table_.emplace(unit, line); + } + + // Create link index text. Use text2 as a temporary variable. + for (const auto & unit : units) { + std::string links; + for (const auto & child : unit->children()) { + links += std::to_string(table_.at(child.unit).index) + " "; + } + if (!links.empty()) { + links.pop_back(); + } + table_.at(unit).text2 = links; + } + + // Calculate table cell width. + const auto width_index = std::max(title_index.length(), std::to_string(units.size()).length()); + const auto width_level = title_level.length(); + auto width_path = title_path.length(); + auto width_type = title_type.length(); + auto width_link = title_link.length(); + for (const auto & unit : units) { + const auto & line = table_.at(unit); + width_path = std::max(width_path, unit->path().length()); + width_type = std::max(width_type, unit->type().length()); + width_link = std::max(width_link, line.text2.length()); + } + + // Create table lines. + for (const auto & unit : units) { + auto & line = table_.at(unit); + std::ostringstream text1; + std::ostringstream text2; + text1 << "| " << std::right << std::setw(width_index) << line.index << " |"; + text2 << "| " << std::left << std::setw(width_path) << unit->path() << " "; + text2 << "| " << std::left << std::setw(width_type) << unit->type() << " "; + text2 << "| " << std::left << std::setw(width_link) << line.text2 << " |"; + line.text1 = text1.str() + " "; + line.text2 = " " + text2.str(); + } + + // Create table header. + { + std::ostringstream header; + header << "| " << std::left << std::setw(width_index) << title_index << " "; + header << "| " << std::left << std::setw(width_level) << title_level << " "; + header << "| " << std::left << std::setw(width_path) << title_path << " "; + header << "| " << std::left << std::setw(width_type) << title_type << " "; + header << "| " << std::left << std::setw(width_link) << title_link << " "; + header << "|"; + header_ = header.str(); + + border_ += "|" + std::string(width_index + 2, '-'); + border_ += "|" + std::string(width_level + 2, '-'); + border_ += "|" + std::string(width_path + 2, '-'); + border_ += "|" + std::string(width_type + 2, '-'); + border_ += "|" + std::string(width_link + 2, '-'); + border_ += "|"; + } +} + +void DumpNode::on_update(DiagGraph::ConstSharedPtr graph) +{ + const auto text_level = [](DiagUnit::DiagnosticLevel level) { + if (level == DiagUnit::DiagnosticStatus::OK) return "OK "; + if (level == DiagUnit::DiagnosticStatus::WARN) return "WARN "; + if (level == DiagUnit::DiagnosticStatus::ERROR) return "ERROR"; + if (level == DiagUnit::DiagnosticStatus::STALE) return "STALE"; + return "-----"; + }; + + std::cout << border_ << std::endl; + std::cout << header_ << std::endl; + std::cout << border_ << std::endl; + + for (const auto & unit : graph->units()) { + const auto & line = table_.at(unit); + std::cout << line.text1 << text_level(unit->level()) << line.text2 << std::endl; + } +} + +} // namespace diagnostic_graph_utils + +int main(int argc, char ** argv) +{ + using diagnostic_graph_utils::DumpNode; + rclcpp::init(argc, argv); + rclcpp::executors::SingleThreadedExecutor executor; + auto node = std::make_shared(); + executor.add_node(node); + executor.spin(); + executor.remove_node(node); + rclcpp::shutdown(); +} diff --git a/system/diagnostic_graph_utils/src/node/dump.hpp b/system/diagnostic_graph_utils/src/node/dump.hpp new file mode 100644 index 0000000000000..e37a1ea971bf5 --- /dev/null +++ b/system/diagnostic_graph_utils/src/node/dump.hpp @@ -0,0 +1,52 @@ +// Copyright 2024 The Autoware Contributors +// +// Licensed under the Apache License, Version 2.0 (the "License"); +// you may not use this file except in compliance with the License. +// You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, software +// distributed under the License is distributed on an "AS IS" BASIS, +// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +// See the License for the specific language governing permissions and +// limitations under the License. + +#ifndef NODE__DUMP_HPP_ +#define NODE__DUMP_HPP_ + +#include "diagnostic_graph_utils/subscription.hpp" + +#include + +#include +#include + +namespace diagnostic_graph_utils +{ + +class DumpNode : public rclcpp::Node +{ +public: + DumpNode(); + +private: + void on_create(DiagGraph::ConstSharedPtr graph); + void on_update(DiagGraph::ConstSharedPtr graph); + DiagGraphSubscription sub_graph_; + + struct TableLine + { + int index; + std::string text1; + std::string text2; + }; + + std::unordered_map table_; + std::string header_; + std::string border_; +}; + +} // namespace diagnostic_graph_utils + +#endif // NODE__DUMP_HPP_ diff --git a/system/hazard_status_converter/package.xml b/system/hazard_status_converter/package.xml index 082aa85cba97a..35ff28998ee80 100644 --- a/system/hazard_status_converter/package.xml +++ b/system/hazard_status_converter/package.xml @@ -12,6 +12,7 @@ autoware_adapi_v1_msgs autoware_auto_system_msgs + diagnostic_graph_utils diagnostic_msgs rclcpp rclcpp_components diff --git a/system/hazard_status_converter/src/converter.cpp b/system/hazard_status_converter/src/converter.cpp index 58282306491dd..9aa354c124bba 100644 --- a/system/hazard_status_converter/src/converter.cpp +++ b/system/hazard_status_converter/src/converter.cpp @@ -17,180 +17,104 @@ #include #include -namespace -{ - -using autoware_auto_system_msgs::msg::HazardStatus; -using autoware_auto_system_msgs::msg::HazardStatusStamped; -using diagnostic_msgs::msg::DiagnosticStatus; -using tier4_system_msgs::msg::DiagnosticGraph; -using tier4_system_msgs::msg::DiagnosticNode; -using DiagnosticLevel = DiagnosticStatus::_level_type; - -enum class HazardLevel { NF, SF, LF, SPF }; - -struct TempNode -{ - const DiagnosticNode & node; - bool is_root_tree; -}; - -HazardLevel get_hazard_level(const TempNode & node, DiagnosticLevel root_mode_level) +namespace hazard_status_converter { - // Convert the level according to the table below. - // The Level other than auto mode is considered OK. - // |-------|-------------------------------| - // | Level | Root level | - // |-------|-------------------------------| - // | | OK | WARN | ERROR | STALE | - // | OK | NF | NF | NF | NF | - // | WARN | SF | LF | LF | LF | - // | ERROR | SF | LF | SPF | SPF | - // | STALE | SF | LF | SPF | SPF | - // |-------|-------------------------------| - - const auto root_level = node.is_root_tree ? root_mode_level : DiagnosticStatus::OK; - const auto node_level = node.node.status.level; - - if (node_level == DiagnosticStatus::OK) { - return HazardLevel::NF; - } - if (root_level == DiagnosticStatus::OK) { - return HazardLevel::SF; - } - if (node_level == DiagnosticStatus::WARN) { - return HazardLevel::LF; - } - if (root_level == DiagnosticStatus::WARN) { - return HazardLevel::LF; - } - return HazardLevel::SPF; -} -void set_root_tree(std::vector & nodes, int index) +Converter::Converter(const rclcpp::NodeOptions & options) : Node("converter", options) { - TempNode & node = nodes[index]; - if (node.is_root_tree) { - return; - } - - node.is_root_tree = true; - for (const auto & link : node.node.links) { - set_root_tree(nodes, link.index); - } + using std::placeholders::_1; + pub_hazard_ = create_publisher("~/hazard_status", rclcpp::QoS(1)); + sub_graph_.register_create_callback(std::bind(&Converter::on_create, this, _1)); + sub_graph_.register_update_callback(std::bind(&Converter::on_update, this, _1)); + sub_graph_.subscribe(*this, 1); } -HazardStatusStamped convert_hazard_diagnostics( - const DiagnosticGraph & graph, const std::string & root, bool ignore) +void Converter::on_create(DiagGraph::ConstSharedPtr graph) { - // Create temporary tree for conversion. - std::vector nodes; - nodes.reserve(graph.nodes.size()); - for (const auto & node : graph.nodes) { - nodes.push_back({node, false}); - } - - // Mark nodes included in the auto mode tree. - DiagnosticLevel root_mode_level = DiagnosticStatus::STALE; - if (!root.empty() && !ignore) { - for (size_t index = 0; index < nodes.size(); ++index) { - const auto & status = nodes[index].node.status; - if (status.name == root) { - set_root_tree(nodes, index); - root_mode_level = status.level; - } + const auto find_auto_mode_root = [](const DiagGraph & graph) { + for (const auto & unit : graph.units()) { + if (unit->path() == "/autoware/modes/autonomous") return unit; } - } + return static_cast(nullptr); + }; - // Calculate hazard level from node level and root level. - HazardStatusStamped hazard; - for (const auto & node : nodes) { - switch (get_hazard_level(node, root_mode_level)) { - case HazardLevel::NF: - hazard.status.diag_no_fault.push_back(node.node.status); - break; - case HazardLevel::SF: - hazard.status.diag_safe_fault.push_back(node.node.status); - break; - case HazardLevel::LF: - hazard.status.diag_latent_fault.push_back(node.node.status); - break; - case HazardLevel::SPF: - hazard.status.diag_single_point_fault.push_back(node.node.status); - break; + const auto make_auto_mode_tree = [](DiagUnit * root) { + std::unordered_set result; + std::unordered_set buffer; + if (root) { + buffer.insert(root); } - } - return hazard; -} - -} // namespace - -namespace hazard_status_converter -{ - -Converter::Converter(const rclcpp::NodeOptions & options) : Node("converter", options) -{ - pub_hazard_ = create_publisher("~/hazard_status", rclcpp::QoS(1)); - sub_graph_ = create_subscription( - "~/diagnostics_graph", rclcpp::QoS(3), - std::bind(&Converter::on_graph, this, std::placeholders::_1)); - sub_state_ = create_subscription( - "/autoware/state", rclcpp::QoS(1), - std::bind(&Converter::on_state, this, std::placeholders::_1)); - sub_mode_ = create_subscription( - "/system/operation_mode/state", rclcpp::QoS(1).transient_local(), - std::bind(&Converter::on_mode, this, std::placeholders::_1)); -} + while (!buffer.empty()) { + const auto unit = *buffer.begin(); + buffer.erase(buffer.begin()); + result.insert(unit); + for (const auto & child : unit->children()) buffer.insert(child.unit); + } + return result; + }; -void Converter::on_state(const AutowareState::ConstSharedPtr msg) -{ - state_ = msg; + auto_mode_root_ = find_auto_mode_root(*graph); + auto_mode_tree_ = make_auto_mode_tree(auto_mode_root_); } -void Converter::on_mode(const OperationMode::ConstSharedPtr msg) +void Converter::on_update(DiagGraph::ConstSharedPtr graph) { - mode_ = msg; -} + using DiagnosticStatus = diagnostic_msgs::msg::DiagnosticStatus; + using DiagnosticLevel = DiagnosticStatus::_level_type; + using HazardStatus = autoware_auto_system_msgs::msg::HazardStatus; + using HazardLevel = HazardStatus::_level_type; + + const auto get_hazard_level = [](DiagnosticLevel unit_level, DiagnosticLevel root_level) { + // Convert the level according to the table below. + // The Level other than auto mode is considered OK. + // |-------|-------------------------------| + // | Level | Root level | + // |-------|-------------------------------| + // | | OK | WARN | ERROR | STALE | + // | OK | NF | NF | NF | NF | + // | WARN | SF | LF | LF | LF | + // | ERROR | SF | LF | SPF | SPF | + // | STALE | SF | LF | SPF | SPF | + // |-------|-------------------------------| + if (unit_level == DiagnosticStatus::OK) return HazardStatus::NO_FAULT; + if (root_level == DiagnosticStatus::OK) return HazardStatus::SAFE_FAULT; + if (unit_level == DiagnosticStatus::WARN) return HazardStatus::LATENT_FAULT; + if (root_level == DiagnosticStatus::WARN) return HazardStatus::LATENT_FAULT; + return HazardStatus::SINGLE_POINT_FAULT; + }; -void Converter::on_graph(const DiagnosticGraph::ConstSharedPtr msg) -{ const auto get_system_level = [](const HazardStatus & status) { - if (!status.diag_single_point_fault.empty()) { - return HazardStatus::SINGLE_POINT_FAULT; - } - if (!status.diag_latent_fault.empty()) { - return HazardStatus::LATENT_FAULT; - } - if (!status.diag_safe_fault.empty()) { - return HazardStatus::SAFE_FAULT; - } + if (!status.diag_single_point_fault.empty()) return HazardStatus::SINGLE_POINT_FAULT; + if (!status.diag_latent_fault.empty()) return HazardStatus::LATENT_FAULT; + if (!status.diag_safe_fault.empty()) return HazardStatus::SAFE_FAULT; return HazardStatus::NO_FAULT; }; - const auto is_ignore = [this]() { - if (mode_ && state_) { - if (mode_->mode == OperationMode::AUTONOMOUS || mode_->mode == OperationMode::STOP) { - if (state_->state == AutowareState::WAITING_FOR_ROUTE) return true; - if (state_->state == AutowareState::PLANNING) return true; - } - if (state_->state == AutowareState::INITIALIZING) return true; - if (state_->state == AutowareState::FINALIZING) return true; - } - return false; + const auto get_hazards_vector = [](HazardStatus & status, HazardLevel level) { + if (level == HazardStatus::SINGLE_POINT_FAULT) return &status.diag_single_point_fault; + if (level == HazardStatus::LATENT_FAULT) return &status.diag_latent_fault; + if (level == HazardStatus::SAFE_FAULT) return &status.diag_safe_fault; + if (level == HazardStatus::NO_FAULT) return &status.diag_no_fault; + return static_cast *>(nullptr); }; - const auto get_root = [this]() { - if (mode_) { - if (mode_->mode == OperationMode::STOP) return "/autoware/modes/stop"; - if (mode_->mode == OperationMode::AUTONOMOUS) return "/autoware/modes/autonomous"; - if (mode_->mode == OperationMode::LOCAL) return "/autoware/modes/local"; - if (mode_->mode == OperationMode::REMOTE) return "/autoware/modes/remote"; - } - return ""; - }; + if (!auto_mode_root_) { + RCLCPP_ERROR_STREAM_THROTTLE(get_logger(), *get_clock(), 10000, "No auto mode unit."); + return; + } - HazardStatusStamped hazard = convert_hazard_diagnostics(*msg, get_root(), is_ignore()); - hazard.stamp = msg->stamp; + // Calculate hazard level from unit level and root level. + HazardStatusStamped hazard; + for (const auto & unit : graph->units()) { + if (unit->path().empty()) continue; + const bool is_auto_tree = auto_mode_tree_.count(unit); + const auto root_level = is_auto_tree ? auto_mode_root_->level() : DiagnosticStatus::OK; + const auto unit_level = unit->level(); + if (auto diags = get_hazards_vector(hazard.status, get_hazard_level(unit_level, root_level))) { + diags->push_back(unit->create_diagnostic_status()); + } + } + hazard.stamp = graph->updated_stamp(); hazard.status.level = get_system_level(hazard.status); hazard.status.emergency = hazard.status.level == HazardStatus::SINGLE_POINT_FAULT; hazard.status.emergency_holding = false; diff --git a/system/hazard_status_converter/src/converter.hpp b/system/hazard_status_converter/src/converter.hpp index 04e84cfb3c0c4..ad14ddde2bf5c 100644 --- a/system/hazard_status_converter/src/converter.hpp +++ b/system/hazard_status_converter/src/converter.hpp @@ -15,16 +15,12 @@ #ifndef CONVERTER_HPP_ #define CONVERTER_HPP_ +#include #include -#include -#include #include -#include -#include -#include -#include +#include namespace hazard_status_converter { @@ -35,20 +31,16 @@ class Converter : public rclcpp::Node explicit Converter(const rclcpp::NodeOptions & options); private: - using AutowareState = autoware_auto_system_msgs::msg::AutowareState; - using OperationMode = autoware_adapi_v1_msgs::msg::OperationModeState; - using DiagnosticGraph = tier4_system_msgs::msg::DiagnosticGraph; using HazardStatusStamped = autoware_auto_system_msgs::msg::HazardStatusStamped; - rclcpp::Subscription::SharedPtr sub_state_; - rclcpp::Subscription::SharedPtr sub_mode_; - rclcpp::Subscription::SharedPtr sub_graph_; + using DiagGraph = diagnostic_graph_utils::DiagGraph; + using DiagUnit = diagnostic_graph_utils::DiagUnit; + void on_create(DiagGraph::ConstSharedPtr graph); + void on_update(DiagGraph::ConstSharedPtr graph); + diagnostic_graph_utils::DiagGraphSubscription sub_graph_; rclcpp::Publisher::SharedPtr pub_hazard_; - void on_state(const AutowareState::ConstSharedPtr msg); - void on_mode(const OperationMode::ConstSharedPtr msg); - void on_graph(const DiagnosticGraph::ConstSharedPtr msg); - AutowareState::ConstSharedPtr state_; - OperationMode::ConstSharedPtr mode_; + DiagUnit * auto_mode_root_; + std::unordered_set auto_mode_tree_; }; } // namespace hazard_status_converter diff --git a/system/mrm_emergency_stop_operator/include/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.hpp b/system/mrm_emergency_stop_operator/include/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.hpp index 19e41397fe4da..5b91f56973ae9 100644 --- a/system/mrm_emergency_stop_operator/include/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.hpp +++ b/system/mrm_emergency_stop_operator/include/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.hpp @@ -27,6 +27,7 @@ // ROS 2 core #include +#include namespace mrm_emergency_stop_operator { using autoware_auto_control_msgs::msg::AckermannControlCommand; @@ -48,6 +49,10 @@ class MrmEmergencyStopOperator : public rclcpp::Node private: // Parameters Parameters params_; + OnSetParametersCallbackHandle::SharedPtr set_param_res_; + + rcl_interfaces::msg::SetParametersResult onParameter( + const std::vector & parameters); // Subscriber rclcpp::Subscription::SharedPtr sub_control_cmd_; diff --git a/system/mrm_emergency_stop_operator/package.xml b/system/mrm_emergency_stop_operator/package.xml index 251e79a07a73d..6ca4e3a815f72 100644 --- a/system/mrm_emergency_stop_operator/package.xml +++ b/system/mrm_emergency_stop_operator/package.xml @@ -17,6 +17,7 @@ rclcpp_components std_msgs std_srvs + tier4_autoware_utils tier4_system_msgs ament_lint_auto diff --git a/system/mrm_emergency_stop_operator/src/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.cpp b/system/mrm_emergency_stop_operator/src/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.cpp index 08814dbbd710d..9ee9d7a685df3 100644 --- a/system/mrm_emergency_stop_operator/src/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.cpp +++ b/system/mrm_emergency_stop_operator/src/mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.cpp @@ -14,6 +14,8 @@ #include "mrm_emergency_stop_operator/mrm_emergency_stop_operator_core.hpp" +#include + namespace mrm_emergency_stop_operator { @@ -49,6 +51,23 @@ MrmEmergencyStopOperator::MrmEmergencyStopOperator(const rclcpp::NodeOptions & n // Initialize status_.state = MrmBehaviorStatus::AVAILABLE; is_prev_control_cmd_subscribed_ = false; + + // Parameter Callback + set_param_res_ = add_on_set_parameters_callback( + std::bind(&MrmEmergencyStopOperator::onParameter, this, std::placeholders::_1)); +} + +rcl_interfaces::msg::SetParametersResult MrmEmergencyStopOperator::onParameter( + const std::vector & parameters) +{ + using tier4_autoware_utils::updateParam; + updateParam(parameters, "target_acceleration", params_.target_acceleration); + updateParam(parameters, "target_jerk", params_.target_jerk); + + rcl_interfaces::msg::SetParametersResult result; + result.successful = true; + result.reason = "success"; + return result; } void MrmEmergencyStopOperator::onControlCommand(AckermannControlCommand::ConstSharedPtr msg) diff --git a/system/system_diagnostic_monitor/CMakeLists.txt b/system/system_diagnostic_monitor/CMakeLists.txt new file mode 100644 index 0000000000000..b253b5dbc0529 --- /dev/null +++ b/system/system_diagnostic_monitor/CMakeLists.txt @@ -0,0 +1,13 @@ +cmake_minimum_required(VERSION 3.14) +project(system_diagnostic_monitor) + +find_package(autoware_cmake REQUIRED) +autoware_package() + +install(PROGRAMS + script/component_state_diagnostics.py + RENAME component_state_diagnostics + DESTINATION lib/${PROJECT_NAME} +) + +ament_auto_package(INSTALL_TO_SHARE config launch) diff --git a/system/system_diagnostic_monitor/README.md b/system/system_diagnostic_monitor/README.md new file mode 100644 index 0000000000000..94f5897076ff6 --- /dev/null +++ b/system/system_diagnostic_monitor/README.md @@ -0,0 +1,16 @@ +# system_diagnostic_monitor + +This package contains default configurations of diagnostic graph and scripts for system integration. + +## Configs + +| Name | Description | +| ------------------------------------------------- | ------------------------------------------------------------ | +| [autoware-main.yaml](./config/autoware-main.yaml) | Diagnostic graphs for basic monitoring of Autoware. | +| [autoware-psim.yaml](./config/autoware-psim.yaml) | Diagnostic graph with some units disabled for the simulator. | + +## Scripts + +| Name | Description | +| ---------------------------------------------------------------------- | --------------------------------------------------- | +| [component_state_diagnostics](./script/component_state_diagnostics.py) | Node that converts component states to diagnostics. | diff --git a/system/system_diagnostic_monitor/config/autoware-main.yaml b/system/system_diagnostic_monitor/config/autoware-main.yaml new file mode 100644 index 0000000000000..26f3fee2863d0 --- /dev/null +++ b/system/system_diagnostic_monitor/config/autoware-main.yaml @@ -0,0 +1,70 @@ +files: + - { path: $(find-pkg-share system_diagnostic_monitor)/config/map.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/localization.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/planning.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/perception.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/control.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/vehicle.yaml } + - { path: $(find-pkg-share system_diagnostic_monitor)/config/system.yaml } + +units: + - path: /autoware/modes/stop + type: ok + + - path: /autoware/modes/autonomous + type: and + list: + - { type: link, link: /autoware/map } + - { type: link, link: /autoware/localization } + - { type: link, link: /autoware/planning } + - { type: link, link: /autoware/perception } + - { type: link, link: /autoware/control } + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + + - path: /autoware/modes/local + type: and + list: + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + - { type: link, link: /autoware/control/local } + + - path: /autoware/modes/remote + type: and + list: + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + - { type: link, link: /autoware/control/remote } + + - path: /autoware/modes/emergency_stop + type: and + list: + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + + - path: /autoware/modes/comfortable_stop + type: and + list: + - { type: link, link: /autoware/map } + - { type: link, link: /autoware/localization } + - { type: link, link: /autoware/planning } + - { type: link, link: /autoware/perception } + - { type: link, link: /autoware/control } + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + + - path: /autoware/modes/pull_over + type: and + list: + - { type: link, link: /autoware/map } + - { type: link, link: /autoware/localization } + - { type: link, link: /autoware/planning } + - { type: link, link: /autoware/perception } + - { type: link, link: /autoware/control } + - { type: link, link: /autoware/vehicle } + - { type: link, link: /autoware/system } + + - path: /autoware/debug/tools + type: and + list: + - { type: link, link: /autoware/system/service_log_checker } diff --git a/system/system_diagnostic_monitor/config/autoware-psim.yaml b/system/system_diagnostic_monitor/config/autoware-psim.yaml new file mode 100644 index 0000000000000..3d55079229280 --- /dev/null +++ b/system/system_diagnostic_monitor/config/autoware-psim.yaml @@ -0,0 +1,11 @@ +files: + - { path: $(find-pkg-share system_diagnostic_monitor)/config/autoware-main.yaml } + +edits: + - { type: remove, path: /autoware/map/topic_rate_check/pointcloud_map } + - { type: remove, path: /autoware/localization/scan_matching_status } + - { type: remove, path: /autoware/localization/accuracy } + - { type: remove, path: /autoware/localization/sensor_fusion_status } + - { type: remove, path: /autoware/localization/topic_rate_check/pose_twist_fusion } + - { type: remove, path: /autoware/perception/topic_rate_check/pointcloud } + - { type: remove, path: /autoware/control/emergency_braking } diff --git a/system/system_diagnostic_monitor/config/control.yaml b/system/system_diagnostic_monitor/config/control.yaml new file mode 100644 index 0000000000000..57bf1b86c2bfc --- /dev/null +++ b/system/system_diagnostic_monitor/config/control.yaml @@ -0,0 +1,73 @@ +units: + - path: /autoware/control + type: and + list: + - { type: link, link: /autoware/control/topic_rate_check/trajectory_follower } + - { type: link, link: /autoware/control/topic_rate_check/control_command } + - { type: link, link: /autoware/control/node_alive_monitoring/vehicle_cmd_gate } + - { type: link, link: /autoware/control/emergency_braking } + - { type: link, link: /autoware/control/performance_monitoring/lane_departure } + - { type: link, link: /autoware/control/performance_monitoring/trajectory_deviation } + - { type: link, link: /autoware/control/performance_monitoring/control_state } + + - path: /autoware/control/local + type: and + list: + - { type: link, link: /autoware/control/topic_rate_check/selector } + - { type: link, link: /autoware/control/topic_rate_check/local } + + - path: /autoware/control/remote + type: and + list: + - { type: link, link: /autoware/control/topic_rate_check/selector } + - { type: link, link: /autoware/control/topic_rate_check/remote } + + - path: /autoware/control/topic_rate_check/trajectory_follower + type: diag + node: topic_state_monitor_trajectory_follower_control_cmd + name: control_topic_status + + - path: /autoware/control/topic_rate_check/control_command + type: diag + node: topic_state_monitor_control_command_control_cmd + name: control_topic_status + + - path: /autoware/control/node_alive_monitoring/vehicle_cmd_gate + type: diag + node: vehicle_cmd_gate + name: heartbeat + + - path: /autoware/control/emergency_braking + type: diag + node: autonomous_emergency_braking + name: aeb_emergency_stop + + - path: /autoware/control/performance_monitoring/lane_departure + type: diag + node: lane_departure_checker_node + name: lane_departure + + - path: /autoware/control/performance_monitoring/trajectory_deviation + type: diag + node: lane_departure_checker_node + name: trajectory_deviation + + - path: /autoware/control/performance_monitoring/control_state + type: diag + node: controller_node_exe + name: control_state + + - path: /autoware/control/topic_rate_check/selector + type: diag + node: external_cmd_selector + name: heartbeat + + - path: /autoware/control/topic_rate_check/local + type: diag + node: joy_controller + name: joy_controller_connection + + - path: /autoware/control/topic_rate_check/remote + type: diag + node: external_cmd_converter + name: remote_control_topic_status diff --git a/system/system_diagnostic_monitor/config/hardware.yaml b/system/system_diagnostic_monitor/config/hardware.yaml new file mode 100644 index 0000000000000..d73f723670f98 --- /dev/null +++ b/system/system_diagnostic_monitor/config/hardware.yaml @@ -0,0 +1,121 @@ +# TODO(Takagi, Isamu): This file is under construction. +units: + - path: /autoware/system/resources/clock/offset + diag: ": NTP Offset" + timeout: 10.0 + + - path: /autoware/system/resources/cpu/offset + diag: ": CPU Temperature" + timeout: 3.0 + + - path: /autoware/system/resources/cpu/usage + diag: ": CPU Usage" + timeout: 3.0 + + - path: /autoware/system/resources/cpu/thermal_throttling + diag: ": CPU Thermal Throttling" + timeout: 3.0 + + - path: /autoware/system/resources/cpu/frequency + diag: ": CPU Frequency" + timeout: 3.0 + + - path: /autoware/system/resources/cpu/load_average + diag: ": CPU Load Average" + timeout: 3.0 + + - path: /autoware/system/resources/gpu/temperature + diag: ": GPU Temperature" + timeout: 3.0 + + - path: /autoware/system/resources/gpu/usage + diag: ": GPU Usage" + timeout: 3.0 + + - path: /autoware/system/resources/gpu/memory_usage + diag: ": GPU Memory Usage" + timeout: 3.0 + + - path: /autoware/system/resources/gpu/thermal_throttling + diag: ": GPU Thermal Throttling" + timeout: 3.0 + + - path: /autoware/system/resources/gpu/frequency + diag: ": GPU Frequency" + timeout: 3.0 + + - path: /autoware/system/resources/memory/usage + diag: ": Memory Usage" + timeout: 3.0 + + - path: /autoware/system/resources/network/usage + diag: ": Network Usage" + timeout: 3.0 + + - path: /autoware/system/resources/network/traffic + diag: ": Network Traffic" + timeout: 3.0 + + - path: /autoware/system/resources/network/crc + diag: ": Network CRC Error" + timeout: 3.0 + + - path: /autoware/system/resources/network/packet_reassembles + diag: ": IP Packet Reassembles Failed" + timeout: 3.0 + + - path: /autoware/system/resources/storage/temperature + diag: ": HDD Temperature" + timeout: 3.0 + + - path: /autoware/system/resources/storage/recovered_error + diag: ": HDD RecoveredError" + timeout: 3.0 + + - path: /autoware/system/resources/storage/read_data_rate + diag: ": HDD ReadDataRate" + timeout: 3.0 + + - path: /autoware/system/resources/storage/write_data_rate + diag: ": HDD WriteDataRate" + timeout: 3.0 + + - path: /autoware/system/resources/storage/read_iops + diag: ": HDD ReadIOPS" + timeout: 3.0 + + - path: /autoware/system/resources/storage/write_iops + diag: ": HDD WriteIOPS" + timeout: 3.0 + + - path: /autoware/system/resources/storage/usage + diag: ": HDD Usage" + timeout: 3.0 + + - path: /autoware/system/resources/storage/power_on_hours + diag: ": HDD PowerOnHours" + timeout: 3.0 + + - path: /autoware/system/resources/storage/total_data_written + diag: ": HDD TotalDataWritten" + timeout: 3.0 + + - path: /autoware/system/resources/storage/connection + diag: ": HDD Connection" + timeout: 3.0 + + - path: /autoware/system/resources/process/high_load + diag: ": High-load" + timeout: 3.0 + + - path: /autoware/system/resources/process/high_mem + diag: ": High-mem" + timeout: 3.0 + + - path: /autoware/system/resources/process/tasks_summary + diag: ": Tasks Summary" + timeout: 3.0 + + - path: /autoware/system/resources/voltage/battery + diag: ": CMOS Battery Status" + timeout: 3.0 diff --git a/system/system_diagnostic_monitor/config/localization.yaml b/system/system_diagnostic_monitor/config/localization.yaml new file mode 100644 index 0000000000000..62bf17775c3fb --- /dev/null +++ b/system/system_diagnostic_monitor/config/localization.yaml @@ -0,0 +1,43 @@ +units: + - path: /autoware/localization + type: short-circuit-and + list: + - type: link + link: /autoware/localization/state + - type: and + list: + - { type: link, link: /autoware/localization/topic_rate_check/transform } + - { type: link, link: /autoware/localization/topic_rate_check/pose_twist_fusion } + - { type: link, link: /autoware/localization/scan_matching_status } + - { type: link, link: /autoware/localization/accuracy } + - { type: link, link: /autoware/localization/sensor_fusion_status } + + - path: /autoware/localization/state + type: diag + node: component_state_diagnostics + name: localization_state + + - path: /autoware/localization/topic_rate_check/transform + type: diag + node: topic_state_monitor_transform_map_to_base_link + name: localization_topic_status + + - path: /autoware/localization/topic_rate_check/pose_twist_fusion + type: diag + node: topic_state_monitor_pose_twist_fusion_filter_pose + name: localization_topic_status + + - path: /autoware/localization/scan_matching_status + type: diag + node: ndt_scan_matcher + name: scan_matching_status + + - path: /autoware/localization/accuracy + type: diag + node: localization + name: localization_error_monitor + + - path: /autoware/localization/sensor_fusion_status + type: diag + node: localization + name: ekf_localizer diff --git a/system/system_diagnostic_monitor/config/map.yaml b/system/system_diagnostic_monitor/config/map.yaml new file mode 100644 index 0000000000000..45c1db294119f --- /dev/null +++ b/system/system_diagnostic_monitor/config/map.yaml @@ -0,0 +1,16 @@ +units: + - path: /autoware/map + type: and + list: + - { type: link, link: /autoware/map/topic_rate_check/vector_map } + - { type: link, link: /autoware/map/topic_rate_check/pointcloud_map } + + - path: /autoware/map/topic_rate_check/vector_map + type: diag + node: topic_state_monitor_vector_map + name: map_topic_status + + - path: /autoware/map/topic_rate_check/pointcloud_map + type: diag + node: topic_state_monitor_pointcloud_map + name: map_topic_status" diff --git a/system/system_diagnostic_monitor/config/perception.yaml b/system/system_diagnostic_monitor/config/perception.yaml new file mode 100644 index 0000000000000..24e3c4eed5295 --- /dev/null +++ b/system/system_diagnostic_monitor/config/perception.yaml @@ -0,0 +1,16 @@ +units: + - path: /autoware/perception + type: and + list: + - { type: link, link: /autoware/perception/topic_rate_check/objects } + - { type: link, link: /autoware/perception/topic_rate_check/pointcloud } + + - path: /autoware/perception/topic_rate_check/objects + type: diag + node: topic_state_monitor_object_recognition_objects + name: perception_topic_status + + - path: /autoware/perception/topic_rate_check/pointcloud + type: diag + node: topic_state_monitor_obstacle_segmentation_pointcloud + name: perception_topic_status diff --git a/system/system_diagnostic_monitor/config/planning.yaml b/system/system_diagnostic_monitor/config/planning.yaml new file mode 100644 index 0000000000000..c403fec2371c3 --- /dev/null +++ b/system/system_diagnostic_monitor/config/planning.yaml @@ -0,0 +1,90 @@ +units: + - path: /autoware/planning + type: short-circuit-and + list: + - type: link + link: /autoware/planning/routing/state + - type: and + list: + - { type: link, link: /autoware/planning/topic_rate_check/route } + - { type: link, link: /autoware/planning/topic_rate_check/trajectory } + - { type: link, link: /autoware/planning/trajectory_validation } + + - path: /autoware/planning/trajectory_validation + type: and + list: + - { type: link, link: /autoware/planning/trajectory_validation/finite } + - { type: link, link: /autoware/planning/trajectory_validation/interval } + - { type: link, link: /autoware/planning/trajectory_validation/curvature } + - { type: link, link: /autoware/planning/trajectory_validation/angle } + - { type: link, link: /autoware/planning/trajectory_validation/lateral_acceleration } + - { type: link, link: /autoware/planning/trajectory_validation/acceleration } + - { type: link, link: /autoware/planning/trajectory_validation/deceleration } + - { type: link, link: /autoware/planning/trajectory_validation/steering } + - { type: link, link: /autoware/planning/trajectory_validation/steering_rate } + - { type: link, link: /autoware/planning/trajectory_validation/velocity_deviation } + + - path: /autoware/planning/routing/state + type: diag + node: component_state_diagnostics + name: route_state + + - path: /autoware/planning/topic_rate_check/route + type: diag + node: topic_state_monitor_mission_planning_route + name: planning_topic_status + + - path: /autoware/planning/topic_rate_check/trajectory + type: diag + node: topic_state_monitor_scenario_planning_trajectory + name: planning_topic_status + + - path: /autoware/planning/trajectory_validation/finite + type: diag + node: planning_validator + name: trajectory_validation_finite + + - path: /autoware/planning/trajectory_validation/interval + type: diag + node: planning_validator + name: trajectory_validation_interval + + - path: /autoware/planning/trajectory_validation/curvature + type: diag + node: planning_validator + name: trajectory_validation_curvature + + - path: /autoware/planning/trajectory_validation/angle + type: diag + node: planning_validator + name: trajectory_validation_relative_angle + + - path: /autoware/planning/trajectory_validation/lateral_acceleration + type: diag + node: planning_validator + name: trajectory_validation_lateral_acceleration + + - path: /autoware/planning/trajectory_validation/acceleration + type: diag + node: planning_validator + name: trajectory_validation_acceleration + + - path: /autoware/planning/trajectory_validation/deceleration + type: diag + node: planning_validator + name: trajectory_validation_deceleration + + - path: /autoware/planning/trajectory_validation/steering + type: diag + node: planning_validator + name: trajectory_validation_steering + + - path: /autoware/planning/trajectory_validation/steering_rate + type: diag + node: planning_validator + name: trajectory_validation_steering_rate + + - path: /autoware/planning/trajectory_validation/velocity_deviation + type: diag + node: planning_validator + name: trajectory_validation_velocity_deviation diff --git a/system/system_diagnostic_monitor/config/system.yaml b/system/system_diagnostic_monitor/config/system.yaml new file mode 100644 index 0000000000000..cb96c2cd7f276 --- /dev/null +++ b/system/system_diagnostic_monitor/config/system.yaml @@ -0,0 +1,27 @@ +units: + - path: /autoware/system + type: and + list: + - { type: link, link: /autoware/system/duplicated_node_checker } + - { type: link, link: /autoware/system/topic_rate_check/emergency_control_command } + - { type: link, link: /autoware/system/emergency_stop_operation } + + - path: /autoware/system/duplicated_node_checker + type: diag + node: duplicated_node_checker + name: duplicated_node_checker + + - path: /autoware/system/service_log_checker + type: diag + node: service_log_checker + name: response_status + + - path: /autoware/system/topic_rate_check/emergency_control_command + type: diag + node: topic_state_monitor_system_emergency_control_cmd + name: system_topic_status + + - path: /autoware/system/emergency_stop_operation + type: diag + node: vehicle_cmd_gate + name: emergency_stop_operation diff --git a/system/system_diagnostic_monitor/config/vehicle.yaml b/system/system_diagnostic_monitor/config/vehicle.yaml new file mode 100644 index 0000000000000..e040e3c3c305e --- /dev/null +++ b/system/system_diagnostic_monitor/config/vehicle.yaml @@ -0,0 +1,16 @@ +units: + - path: /autoware/vehicle + type: and + list: + - { type: link, link: /autoware/vehicle/topic_rate_check/velocity } + - { type: link, link: /autoware/vehicle/topic_rate_check/steering } + + - path: /autoware/vehicle/topic_rate_check/velocity + type: diag + node: topic_state_monitor_vehicle_status_velocity_status + name: vehicle_topic_status + + - path: /autoware/vehicle/topic_rate_check/steering + type: diag + node: topic_state_monitor_vehicle_status_steering_status + name: vehicle_topic_status diff --git a/system/system_diagnostic_monitor/launch/system_diagnostic_monitor.launch.xml b/system/system_diagnostic_monitor/launch/system_diagnostic_monitor.launch.xml new file mode 100644 index 0000000000000..b00fcb8a26f68 --- /dev/null +++ b/system/system_diagnostic_monitor/launch/system_diagnostic_monitor.launch.xml @@ -0,0 +1,7 @@ + + + + + + + diff --git a/system/system_diagnostic_monitor/package.xml b/system/system_diagnostic_monitor/package.xml new file mode 100644 index 0000000000000..a54a3dd0d109a --- /dev/null +++ b/system/system_diagnostic_monitor/package.xml @@ -0,0 +1,25 @@ + + + + system_diagnostic_monitor + 0.1.0 + The system_diagnostic_monitor package + Takagi, Isamu + Apache License 2.0 + + ament_cmake_auto + autoware_cmake + + autoware_adapi_v1_msgs + diagnostic_graph_aggregator + diagnostic_msgs + rclpy + tier4_system_msgs + + ament_lint_auto + autoware_lint_common + + + ament_cmake + + diff --git a/system/system_diagnostic_monitor/script/component_state_diagnostics.py b/system/system_diagnostic_monitor/script/component_state_diagnostics.py new file mode 100755 index 0000000000000..9117f818e60fd --- /dev/null +++ b/system/system_diagnostic_monitor/script/component_state_diagnostics.py @@ -0,0 +1,102 @@ +#!/usr/bin/env python3 + +# Copyright 2023 The Autoware Contributors +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from autoware_adapi_v1_msgs.msg import LocalizationInitializationState as LocalizationState +from autoware_adapi_v1_msgs.msg import RouteState +from diagnostic_msgs.msg import DiagnosticArray +from diagnostic_msgs.msg import DiagnosticStatus +import rclpy +import rclpy.node +import rclpy.qos +import rclpy.time + + +class ComponentStateDiagnostics: + def __init__(self, node, diag_name, topic_name, topic_type, topic_qos, diag_func): + self.node = node + self.name = diag_name + self.func = diag_func + self.sub = node.create_subscription(topic_type, topic_name, self.callback, topic_qos) + self.level = DiagnosticStatus.STALE + self.stamp = None + + def callback(self, msg): + self.level = DiagnosticStatus.OK if self.func(msg) else DiagnosticStatus.ERROR + self.stamp = self.node.get_clock().now() + + def update(self, stamp): + if self.stamp: + elapsed = (stamp - self.stamp).nanoseconds * 1e-9 + if 3.0 < elapsed: + self.level = DiagnosticStatus.STALE + self.stamp = None + + def message(self): + status = DiagnosticStatus() + status.name = self.name + status.level = self.level + return status + + +class ComponentStateDiagnosticsNode(rclpy.node.Node): + def __init__(self): + super().__init__("component_state_diagnostics") + durable_qos = rclpy.qos.QoSProfile( + depth=1, + durability=rclpy.qos.DurabilityPolicy.TRANSIENT_LOCAL, + reliability=rclpy.qos.ReliabilityPolicy.RELIABLE, + ) + + self.timer = self.create_timer(0.5, self.on_timer) + self.pub = self.create_publisher(DiagnosticArray, "/diagnostics", 1) + self.states = [] + self.states.append( + ComponentStateDiagnostics( + self, + "component_state_diagnostics: localization_state", + "/api/localization/initialization_state", + LocalizationState, + durable_qos, + lambda msg: msg.state == LocalizationState.INITIALIZED, + ) + ) + self.states.append( + ComponentStateDiagnostics( + self, + "component_state_diagnostics: route_state", + "/api/routing/state", + RouteState, + durable_qos, + lambda msg: msg.state != RouteState.UNSET, + ) + ) + + def on_timer(self): + stamp = self.get_clock().now() + array = DiagnosticArray() + array.header.stamp = stamp.to_msg() + for state in self.states: + array.status.append(state.message()) + self.pub.publish(array) + + +if __name__ == "__main__": + try: + rclpy.init() + rclpy.spin(ComponentStateDiagnosticsNode()) + rclpy.shutdown() + except KeyboardInterrupt: + pass diff --git a/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml b/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml index 9ed82304036cc..14226a0371193 100644 --- a/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml +++ b/system/system_error_monitor/config/diagnostic_aggregator/localization.param.yaml @@ -18,10 +18,10 @@ type: diagnostic_aggregator/AnalyzerGroup path: performance_monitoring analyzers: - matching_score: + scan_matching_status: type: diagnostic_aggregator/GenericAnalyzer - path: matching_score - contains: ["ndt_scan_matcher"] + path: scan_matching_status + contains: ["ndt_scan_matcher: scan_matching_status"] timeout: 1.0 localization_error_ellipse: diff --git a/system/system_error_monitor/config/system_error_monitor.param.yaml b/system/system_error_monitor/config/system_error_monitor.param.yaml index 2b58f5b42c0be..d3fc221bac768 100644 --- a/system/system_error_monitor/config/system_error_monitor.param.yaml +++ b/system/system_error_monitor/config/system_error_monitor.param.yaml @@ -23,7 +23,7 @@ /autoware/control/autonomous_emergency_braking/performance_monitoring/emergency_stop: { sf_at: "none", lf_at: "warn", spf_at: "error", auto_recovery: "false"} /autoware/localization/node_alive_monitoring: default - /autoware/localization/performance_monitoring/matching_score: { sf_at: "warn", lf_at: "none", spf_at: "none" } + /autoware/localization/performance_monitoring/scan_matching_status: { sf_at: "warn", lf_at: "none", spf_at: "none" } /autoware/localization/performance_monitoring/localization_error_ellipse: default /autoware/map/node_alive_monitoring: default diff --git a/system/system_error_monitor/config/system_error_monitor.planning_simulation.param.yaml b/system/system_error_monitor/config/system_error_monitor.planning_simulation.param.yaml index f1031444394d0..43e8c56353a36 100644 --- a/system/system_error_monitor/config/system_error_monitor.planning_simulation.param.yaml +++ b/system/system_error_monitor/config/system_error_monitor.planning_simulation.param.yaml @@ -23,7 +23,7 @@ /autoware/control/autonomous_emergency_braking/performance_monitoring/emergency_stop: { sf_at: "none", lf_at: "warn", spf_at: "error", auto_recovery: "false"} /autoware/localization/node_alive_monitoring: default - # /autoware/localization/performance_monitoring/matching_score: { sf_at: "warn", lf_at: "none", spf_at: "none" } + # /autoware/localization/performance_monitoring/scan_matching_status: { sf_at: "warn", lf_at: "none", spf_at: "none" } # /autoware/localization/performance_monitoring/localization_error_ellipse: default /autoware/map/node_alive_monitoring: default diff --git a/system/system_monitor/src/net_monitor/net_monitor.cpp b/system/system_monitor/src/net_monitor/net_monitor.cpp index c8775e585765e..0b5bc4c1ee7ec 100644 --- a/system/system_monitor/src/net_monitor/net_monitor.cpp +++ b/system/system_monitor/src/net_monitor/net_monitor.cpp @@ -258,7 +258,7 @@ void NetMonitor::monitor_traffic(diagnostic_updater::DiagnosticStatusWrapper & s if (line.empty()) continue; boost::split(list, line, boost::is_any_of("\t"), boost::token_compress_on); - if (list.size() >= 3) { + if (list.size() > 3) { status.add(fmt::format("nethogs {}: program", index), list[3].c_str()); status.add(fmt::format("nethogs {}: sent (KB/s)", index), list[1].c_str()); status.add(fmt::format("nethogs {}: received (KB/sec)", index), list[2].c_str()); diff --git a/vehicle/accel_brake_map_calibrator/src/accel_brake_map_calibrator_node.cpp b/vehicle/accel_brake_map_calibrator/src/accel_brake_map_calibrator_node.cpp index ecfc312d2bdfd..37f0a11165df3 100644 --- a/vehicle/accel_brake_map_calibrator/src/accel_brake_map_calibrator_node.cpp +++ b/vehicle/accel_brake_map_calibrator/src/accel_brake_map_calibrator_node.cpp @@ -703,17 +703,19 @@ void AccelBrakeMapCalibrator::takeConsistencyOfAccelMap() { const double bit = std::pow(1e-01, precision_); for (std::size_t ped_idx = 0; ped_idx < update_accel_map_value_.size() - 1; ped_idx++) { - for (std::size_t vel_idx = 0; vel_idx < update_accel_map_value_.at(0).size() - 1; vel_idx++) { + for (std::size_t vel_idx = update_accel_map_value_.at(0).size() - 1;; vel_idx--) { + if (vel_idx == 0) break; + const double current_acc = update_accel_map_value_.at(ped_idx).at(vel_idx); const double next_ped_acc = update_accel_map_value_.at(ped_idx + 1).at(vel_idx); - const double next_vel_acc = update_accel_map_value_.at(ped_idx).at(vel_idx + 1); + const double prev_vel_acc = update_accel_map_value_.at(ped_idx).at(vel_idx - 1); - if (current_acc <= next_vel_acc) { + if (current_acc + bit >= prev_vel_acc) { // the higher the velocity, the lower the acceleration - update_accel_map_value_.at(ped_idx).at(vel_idx + 1) = current_acc - bit; + update_accel_map_value_.at(ped_idx).at(vel_idx - 1) = current_acc + bit; } - if (current_acc >= next_ped_acc) { + if (current_acc + bit >= next_ped_acc) { // the higher the accel pedal, the higher the acceleration update_accel_map_value_.at(ped_idx + 1).at(vel_idx) = current_acc + bit; }