Merge remote-tracking branch 'origin/beta/v0.10.1' into experiment/st…

…eer_accel_limit

common/motion_utils/include/motion_utils/marker/marker_helper.hpp

@@ -28,15 +28,18 @@ using geometry_msgs::msg::Pose;
 
 visualization_msgs::msg::MarkerArray createStopVirtualWallMarker(
   const Pose & pose, const std::string & module_name, const rclcpp::Time & now, const int32_t id,
-  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "");
+  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "",
+  const bool is_driving_forward = true);
 
 visualization_msgs::msg::MarkerArray createSlowDownVirtualWallMarker(
   const Pose & pose, const std::string & module_name, const rclcpp::Time & now, const int32_t id,
-  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "");
+  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "",
+  const bool is_driving_forward = true);
 
 visualization_msgs::msg::MarkerArray createDeadLineVirtualWallMarker(
   const Pose & pose, const std::string & module_name, const rclcpp::Time & now, const int32_t id,
-  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "");
+  const double longitudinal_offset = 0.0, const std::string & ns_prefix = "",
+  const bool is_driving_forward = true);
 
 visualization_msgs::msg::MarkerArray createDeletedStopVirtualWallMarker(
   const rclcpp::Time & now, const int32_t id);

common/motion_utils/include/motion_utils/marker/virtual_wall_marker_creator.hpp

@@ -38,6 +38,7 @@ struct VirtualWall
   std::string ns{};
   VirtualWallType style = stop;
   double longitudinal_offset{};
+  bool is_driving_forward{true};
 };
 typedef std::vector<VirtualWall> VirtualWalls;
 
@@ -54,7 +55,7 @@ class VirtualWallMarkerCreator
   using create_wall_function = std::function<visualization_msgs::msg::MarkerArray(
     const geometry_msgs::msg::Pose & pose, const std::string & module_name,
     const rclcpp::Time & now, const int32_t id, const double longitudinal_offset,
-    const std::string & ns_prefix)>;
+    const std::string & ns_prefix, const bool is_driving_forward)>;
 
   VirtualWalls virtual_walls;
   std::unordered_map<std::string, MarkerCount> marker_count_per_namespace;

common/motion_utils/src/marker/marker_helper.cpp

@@ -86,32 +86,35 @@ namespace motion_utils
 {
 visualization_msgs::msg::MarkerArray createStopVirtualWallMarker(
   const geometry_msgs::msg::Pose & pose, const std::string & module_name, const rclcpp::Time & now,
-  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix)
+  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix,
+  const bool is_driving_forward)
 {
-  const auto pose_with_offset =
-    tier4_autoware_utils::calcOffsetPose(pose, longitudinal_offset, 0.0, 0.0);
+  const auto pose_with_offset = tier4_autoware_utils::calcOffsetPose(
+    pose, longitudinal_offset * (is_driving_forward ? 1.0 : -1.0), 0.0, 0.0);
   return createVirtualWallMarkerArray(
     pose_with_offset, module_name, ns_prefix + "stop_", now, id,
     createMarkerColor(1.0, 0.0, 0.0, 0.5));
 }
 
 visualization_msgs::msg::MarkerArray createSlowDownVirtualWallMarker(
   const geometry_msgs::msg::Pose & pose, const std::string & module_name, const rclcpp::Time & now,
-  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix)
+  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix,
+  const bool is_driving_forward)
 {
-  const auto pose_with_offset =
-    tier4_autoware_utils::calcOffsetPose(pose, longitudinal_offset, 0.0, 0.0);
+  const auto pose_with_offset = tier4_autoware_utils::calcOffsetPose(
+    pose, longitudinal_offset * (is_driving_forward ? 1.0 : -1.0), 0.0, 0.0);
   return createVirtualWallMarkerArray(
     pose_with_offset, module_name, ns_prefix + "slow_down_", now, id,
     createMarkerColor(1.0, 1.0, 0.0, 0.5));
 }
 
 visualization_msgs::msg::MarkerArray createDeadLineVirtualWallMarker(
   const geometry_msgs::msg::Pose & pose, const std::string & module_name, const rclcpp::Time & now,
-  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix)
+  const int32_t id, const double longitudinal_offset, const std::string & ns_prefix,
+  const bool is_driving_forward)
 {
-  const auto pose_with_offset =
-    tier4_autoware_utils::calcOffsetPose(pose, longitudinal_offset, 0.0, 0.0);
+  const auto pose_with_offset = tier4_autoware_utils::calcOffsetPose(
+    pose, longitudinal_offset * (is_driving_forward ? 1.0 : -1.0), 0.0, 0.0);
   return createVirtualWallMarkerArray(
     pose_with_offset, module_name, ns_prefix + "dead_line_", now, id,
     createMarkerColor(0.0, 1.0, 0.0, 0.5));

common/motion_utils/src/marker/virtual_wall_marker_creator.cpp

@@ -64,7 +64,7 @@ visualization_msgs::msg::MarkerArray VirtualWallMarkerCreator::create_markers(
     }
     auto markers = create_fn(
       virtual_wall.pose, virtual_wall.text, now, 0, virtual_wall.longitudinal_offset,
-      virtual_wall.ns);
+      virtual_wall.ns, virtual_wall.is_driving_forward);
     for (auto & marker : markers.markers) {
       marker.id = marker_count_per_namespace[marker.ns].current++;
       marker_array.markers.push_back(marker);

common/object_recognition_utils/include/object_recognition_utils/transform.hpp

@@ -15,15 +15,22 @@
 #ifndef OBJECT_RECOGNITION_UTILS__TRANSFORM_HPP_
 #define OBJECT_RECOGNITION_UTILS__TRANSFORM_HPP_
 
+#include <pcl_ros/transforms.hpp>
+
 #include <geometry_msgs/msg/transform.hpp>
+#include <sensor_msgs/msg/point_cloud2.hpp>
+#include <sensor_msgs/msg/point_field.hpp>
 
 #include <boost/optional.hpp>
 
 #include <tf2_ros/buffer.h>
 #include <tf2_ros/transform_listener.h>
 #ifdef ROS_DISTRO_GALACTIC
+#include <tf2_eigen/tf2_eigen.h>
 #include <tf2_geometry_msgs/tf2_geometry_msgs.h>
 #else
+#include <tf2_eigen/tf2_eigen.hpp>
+
 #include <tf2_geometry_msgs/tf2_geometry_msgs.hpp>
 #endif
 
@@ -45,6 +52,23 @@ namespace detail
     return boost::none;
   }
 }
+
+[[maybe_unused]] inline boost::optional<Eigen::Matrix4f> getTransformMatrix(
+  const std::string & in_target_frame, const std_msgs::msg::Header & in_cloud_header,
+  const tf2_ros::Buffer & tf_buffer)
+{
+  try {
+    geometry_msgs::msg::TransformStamped transform_stamped;
+    transform_stamped = tf_buffer.lookupTransform(
+      in_target_frame, in_cloud_header.frame_id, in_cloud_header.stamp,
+      rclcpp::Duration::from_seconds(1.0));
+    Eigen::Matrix4f mat = tf2::transformToEigen(transform_stamped.transform).matrix().cast<float>();
+    return mat;
+  } catch (tf2::TransformException & e) {
+    RCLCPP_WARN_STREAM(rclcpp::get_logger("detail::getTransformMatrix"), e.what());
+    return boost::none;
+  }
+}
 }  // namespace detail
 
 namespace object_recognition_utils
@@ -79,6 +103,46 @@ bool transformObjects(
   }
   return true;
 }
+template <class T>
+bool transformObjectsWithFeature(
+  const T & input_msg, const std::string & target_frame_id, const tf2_ros::Buffer & tf_buffer,
+  T & output_msg)
+{
+  output_msg = input_msg;
+  if (input_msg.header.frame_id != target_frame_id) {
+    output_msg.header.frame_id = target_frame_id;
+    tf2::Transform tf_target2objects_world;
+    tf2::Transform tf_target2objects;
+    tf2::Transform tf_objects_world2objects;
+    const auto ros_target2objects_world = detail::getTransform(
+      tf_buffer, input_msg.header.frame_id, target_frame_id, input_msg.header.stamp);
+    if (!ros_target2objects_world) {
+      return false;
+    }
+    const auto tf_matrix = detail::getTransformMatrix(target_frame_id, input_msg.header, tf_buffer);
+    if (!tf_matrix) {
+      RCLCPP_WARN(
+        rclcpp::get_logger("object_recognition_utils:"), "failed to get transformed matrix");
+      return false;
+    }
+    for (auto & feature_object : output_msg.feature_objects) {
+      // transform object
+      tf2::fromMsg(
+        feature_object.object.kinematics.pose_with_covariance.pose, tf_objects_world2objects);
+      tf_target2objects = tf_target2objects_world * tf_objects_world2objects;
+      tf2::toMsg(tf_target2objects, feature_object.object.kinematics.pose_with_covariance.pose);
+
+      // transform cluster
+      sensor_msgs::msg::PointCloud2 transformed_cluster;
+      pcl_ros::transformPointCloud(*tf_matrix, feature_object.feature.cluster, transformed_cluster);
+      transformed_cluster.header.frame_id = target_frame_id;
+      feature_object.feature.cluster = transformed_cluster;
+    }
+    output_msg.header.frame_id = target_frame_id;
+    return true;
+  }
+  return true;
+}
 }  // namespace object_recognition_utils
 
 #endif  // OBJECT_RECOGNITION_UTILS__TRANSFORM_HPP_

common/object_recognition_utils/package.xml

@@ -17,7 +17,13 @@
   <depend>geometry_msgs</depend>
   <depend>interpolation</depend>
   <depend>libboost-dev</depend>
+  <depend>pcl_conversions</depend>
+  <depend>pcl_ros</depend>
   <depend>rclcpp</depend>
+  <depend>sensor_msgs</depend>
+  <depend>std_msgs</depend>
+  <depend>tf2</depend>
+  <depend>tf2_eigen</depend>
   <depend>tier4_autoware_utils</depend>
 
   <test_depend>ament_cmake_ros</test_depend>

common/rtc_manager_rviz_plugin/src/rtc_manager_panel.cpp

@@ -366,16 +366,28 @@ void RTCManagerPanel::onRTCStatus(const CooperateStatusArray::ConstSharedPtr msg
   rtc_table_->clearContents();
   num_rtc_status_ptr_->setText(
     QString::fromStdString("The Number of RTC Statuses: " + std::to_string(msg->statuses.size())));
-  if (msg->statuses.empty()) return;
+  if (msg->statuses.empty()) {
+    rtc_table_->update();
+    return;
+  }
   // this is to stable rtc display not to occupy too much
   size_t min_display_size{5};
   size_t max_display_size{10};
   // rtc messages are already sorted by distance
   rtc_table_->setRowCount(
     std::max(min_display_size, std::min(msg->statuses.size(), max_display_size)));
   int cnt = 0;
-  for (auto status : msg->statuses) {
-    if (static_cast<size_t>(cnt) >= max_display_size) return;
+
+  auto sorted_statuses = msg->statuses;
+  std::partition(sorted_statuses.begin(), sorted_statuses.end(), [](const auto & status) {
+    return !status.auto_mode && !uint2bool(status.command_status.type);
+  });
+
+  for (auto status : sorted_statuses) {
+    if (static_cast<size_t>(cnt) >= max_display_size) {
+      rtc_table_->update();
+      return;
+    }
     // uuid
     {
       std::stringstream uuid;

control/operation_mode_transition_manager/src/state.cpp

@@ -121,14 +121,24 @@ bool AutonomousMode::isModeChangeCompleted()
   const auto closest_point = trajectory_.points.at(*closest_idx);
 
   // check for lateral deviation
-  const auto dist_deviation = calcDistance2d(closest_point.pose, kinematics_.pose.pose);
+  const auto dist_deviation =
+    motion_utils::calcLateralOffset(trajectory_.points, kinematics_.pose.pose.position);
+  if (std::isnan(dist_deviation)) {
+    RCLCPP_INFO(logger_, "Not stable yet: lateral offset calculation failed.");
+    return unstable();
+  }
   if (dist_deviation > stable_check_param_.dist_threshold) {
     RCLCPP_INFO(logger_, "Not stable yet: distance deviation is too large: %f", dist_deviation);
     return unstable();
   }
 
   // check for yaw deviation
-  const auto yaw_deviation = calcYawDeviation(closest_point.pose, kinematics_.pose.pose);
+  const auto yaw_deviation =
+    motion_utils::calcYawDeviation(trajectory_.points, kinematics_.pose.pose);
+  if (std::isnan(yaw_deviation)) {
+    RCLCPP_INFO(logger_, "Not stable yet: lateral offset calculation failed.");
+    return unstable();
+  }
   if (yaw_deviation > stable_check_param_.yaw_threshold) {
     RCLCPP_INFO(logger_, "Not stable yet: yaw deviation is too large: %f", yaw_deviation);
     return unstable();

launch/tier4_perception_launch/launch/object_recognition/detection/camera_lidar_fusion_based_detection.launch.xml

@@ -1,8 +1,24 @@
 <?xml version="1.0"?>
 <launch>
+  <!-- Interface param -->
+  <arg name="output/objects" default="objects"/>
+
+  <!-- LiDAR param -->
   <arg name="input/pointcloud"/>
   <arg name="input/obstacle_segmentation/pointcloud" default="/perception/obstacle_segmentation/pointcloud"/>
-  <arg name="output/objects" default="objects"/>
+  <arg name="container_name" default="pointcloud_container"/>
+
+  <arg name="lidar_detection_model" default="centerpoint" description="options: `centerpoint`, `apollo`, `pointpainting`, `clustering`"/>
+  <arg name="score_threshold" default="0.35"/>
+
+  <arg name="use_object_filter" default="true" description="use object filter"/>
+  <arg name="use_pointcloud_container" default="false" description="use pointcloud container for detection preprocessor"/>
+  <arg name="use_validator" default="true" description="use obstacle_pointcloud based validator"/>
+  <arg name="remove_unknown" default="true"/>
+  <arg name="trust_distance" default="30.0"/>
+  <arg name="use_roi_based_cluster" default="false"/>
+
+  <!-- Camera param -->
   <arg name="image_raw0" default="/image_raw" description="image raw topic name"/>
   <arg name="camera_info0" default="/camera_info" description="camera info topic name"/>
   <arg name="detection_rois0" default="/perception/object_recognition/detection/rois0" description="detection rois output topic name"/>
@@ -28,16 +44,6 @@
   <arg name="camera_info7" default="/camera_info7"/>
   <arg name="detection_rois7" default="/perception/object_recognition/detection/rois7"/>
   <arg name="image_number" default="1" description="choose image raw number(1-8)"/>
-  <arg name="lidar_detection_model" default="centerpoint" description="options: `centerpoint`, `apollo`, `pointpainting`, `clustering`"/>
-  <arg name="use_pointcloud_map" default="true" description="use pointcloud map in detection"/>
-  <arg name="use_downsample_pointcloud" default="true" description="use downsample pointcloud in perception"/>
-  <arg name="use_object_filter" default="true" description="use object filter"/>
-  <arg name="use_pointcloud_container" default="false" description="use pointcloud container for detection preprocessor"/>
-  <arg name="container_name" default="pointcloud_container"/>
-  <arg name="use_validator" default="true" description="use obstacle_pointcloud based validator"/>
-  <arg name="score_threshold" default="0.35"/>
-  <arg name="remove_unknown" default="true"/>
-  <arg name="trust_distance" default="30.0"/>
 
   <!-- Jetson AGX -->
   <!-- <include file="$(find-pkg-share tensorrt_yolo)/launch/yolo.launch.xml">
@@ -52,29 +58,71 @@
     <arg name="image_number" value="$(var image_number)"/>
   </include> -->
 
-  <!-- Pointcloud map filter -->
+  <!-- Pointcloud filter -->
   <group>
-    <include file="$(find-pkg-share tier4_perception_launch)/launch/object_recognition/detection/pointcloud_map_filter.launch.py" if="$(var use_pointcloud_map)">
+    <include file="$(find-pkg-share tier4_perception_launch)/launch/object_recognition/detection/pointcloud_map_filter.launch.py">
       <arg name="input_topic" value="$(var input/obstacle_segmentation/pointcloud)"/>
       <arg name="output_topic" value="pointcloud_map_filtered/pointcloud"/>
       <arg name="use_intra_process" value="true"/>
       <arg name="use_multithread" value="true"/>
       <arg name="use_pointcloud_container" value="$(var use_pointcloud_container)"/>
       <arg name="container_name" value="$(var container_name)"/>
+      <arg name="use_pointcloud_map" value="$(var use_pointcloud_map)"/>
     </include>
   </group>
 
   <!-- Clustering -->
   <group>
     <push-ros-namespace namespace="clustering"/>
     <group>
-      <let name="clustering/input/pointcloud" value="/perception/object_recognition/detection/pointcloud_map_filtered/pointcloud" if="$(var use_pointcloud_map)"/>
-      <let name="clustering/input/pointcloud" value="$(var input/obstacle_segmentation/pointcloud)" unless="$(var use_pointcloud_map)"/>
+      <let name="euclidean_cluster_output" value="euclidean_cluster/clusters" if="$(var use_roi_based_cluster)"/>
+      <let name="euclidean_cluster_output" value="clusters" unless="$(var use_roi_based_cluster)"/>
       <include file="$(find-pkg-share euclidean_cluster)/launch/voxel_grid_based_euclidean_cluster.launch.xml">
-        <arg name="input_pointcloud" value="$(var clustering/input/pointcloud)"/>
-        <arg name="output_clusters" value="clusters"/>
-        <arg name="use_pointcloud_map" value="false"/>
-        <arg name="use_downsample_pointcloud" value="$(var use_downsample_pointcloud)"/>
+        <arg name="input_pointcloud" value="/perception/object_recognition/detection/pointcloud_map_filtered/pointcloud"/>
+        <arg name="output_clusters" value="$(var euclidean_cluster_output)"/>
+        <arg name="use_low_height_cropbox" value="$(var use_low_height_cropbox)"/>
+      </include>
+    </group>
+
+    <!-- roi based clustering -->
+    <group>
+      <include file="$(find-pkg-share image_projection_based_fusion)/launch/roi_pointcloud_fusion.launch.xml" if="$(var use_roi_based_cluster)">
+        <arg name="input/camera_info0" value="$(var camera_info0)"/>
+        <arg name="input/rois0" value="$(var detection_rois0)"/>
+        <arg name="input/camera_info1" value="$(var camera_info1)"/>
+        <arg name="input/rois1" value="$(var detection_rois1)"/>
+        <arg name="input/camera_info2" value="$(var camera_info2)"/>
+        <arg name="input/rois2" value="$(var detection_rois2)"/>
+        <arg name="input/camera_info3" value="$(var camera_info3)"/>
+        <arg name="input/rois3" value="$(var detection_rois3)"/>
+        <arg name="input/camera_info4" value="$(var camera_info4)"/>
+        <arg name="input/rois4" value="$(var detection_rois4)"/>
+        <arg name="input/camera_info5" value="$(var camera_info5)"/>
+        <arg name="input/rois5" value="$(var detection_rois5)"/>
+        <arg name="input/camera_info6" value="$(var camera_info6)"/>
+        <arg name="input/rois6" value="$(var detection_rois6)"/>
+        <arg name="input/camera_info7" value="$(var camera_info7)"/>
+        <arg name="input/rois7" value="$(var detection_rois7)"/>
+        <arg name="input/rois_number" value="$(var image_number)"/>
+        <arg name="input/image0" value="$(var image_raw0)"/>
+        <arg name="input/image1" value="$(var image_raw1)"/>
+        <arg name="input/image2" value="$(var image_raw2)"/>
+        <arg name="input/image3" value="$(var image_raw3)"/>
+        <arg name="input/image4" value="$(var image_raw4)"/>
+        <arg name="input/image5" value="$(var image_raw5)"/>
+        <arg name="input/image6" value="$(var image_raw6)"/>
+        <arg name="input/image7" value="$(var image_raw7)"/>
+        <arg name="input/pointcloud" value="/perception/object_recognition/detection/pointcloud_map_filtered/pointcloud"/>
+        <arg name="output_clusters" value="roi_cluster/clusters"/>
+      </include>
+    </group>
+
+    <!-- simple_cluster_merger -->
+    <group>
+      <include file="$(find-pkg-share cluster_merger)/launch/cluster_merger.launch.xml" if="$(var use_roi_based_cluster)">
+        <arg name="input/cluster0" value="euclidean_cluster/clusters"/>
+        <arg name="input/cluster1" value="roi_cluster/clusters"/>
+        <arg name="output/clusters" value="clusters"/>
       </include>
     </group>
 
@@ -89,6 +137,8 @@
       <let name="input/clustering" value="/perception/object_recognition/detection/clustering/clusters"/>
       <push-ros-namespace namespace="camera_lidar_fusion"/>
       <!-- Fusion camera-lidar to classify -->
+
+      <!-- euclidean clustering -->
       <group>
         <include file="$(find-pkg-share image_projection_based_fusion)/launch/roi_cluster_fusion.launch.xml">
           <arg name="input/camera_info0" value="$(var camera_info0)"/>