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Hi, I was wondering if there is a way to offset the depth voxels.
I have a robot where the depth cloud actually corresponds to what I measure, but the voxels are closer and this way the costmap (resolution 0.04) will show presence of obstacle about 0.1m closer than they actually are.
rgbd_obstacle_layer:
enabled: true
voxel_decay: 1 # seconds if linear, e^n if exponential
decay_model: -1 # 0=linear, 1=exponential, -1=persistent
voxel_size: 0.04 # meters
track_unknown_space: true # default space is known
observation_persistence: 0.0
max_obstacle_height: 0.4 # meters
unknown_threshold: 15 # voxel height
mark_threshold: 0 # voxel height
update_footprint_enabled: true
combination_method: 1 # 1=max, 0=override
obstacle_range: 2.5 # meters
origin_z: 0.0 # meters
publish_voxel_map: true # default off
transform_tolerance: 0.3 # seconds
mapping_mode: false # default off, saves map not for navigation
map_save_duration: 60 # default 60s, how often to autosave
observation_sources: rgbd1_mark rgbd1_clear
rgbd1_mark:
data_type: PointCloud2
topic: /camera/depth/color/points
marking: true
clearing: false
min_obstacle_height: 0.06 # default 0, meters
max_obstacle_height: 0.4 # default 3, meters
expected_update_rate: 0.0 # default 0, if not updating at this rate at least, remove from buffer
observation_persistence: 0.0 # default 0, use all measurements taken during now-value, 0=latest
inf_is_valid: false # default false, for laser scans
filter: "passthrough" # default passthrough, apply "voxel", "passthrough", or no filter to sensor data, recommend on
voxel_min_points: 2 # default 0, minimum points per voxel for voxel filter
clear_after_reading: false # default false, clear the buffer after the layer gets readings from it
rgbd1_clear:
data_type: PointCloud2
topic: /camera/depth/color/points
marking: false
clearing: true
max_z: 6.0 # default 0, meters
min_z: 0.0 # default 10, meters
vertical_fov_angle: 1
horizontal_fov_angle: 1.5
decay_acceleration: 15.0 # default 0, 1/s^2. If laser scanner MUST be 0
model_type: 0 # default 0, model type for frustum. 0=depth camera, 1=3d lidar like VLP16 or similar
`
Lowering the resolution for both stvl and local costmap solved the problem, so it probably is just the size of the grid that matters. But unfotunately my raspberry pi is already pushing hard and lowering the resolution creates too much lag. Is there a way to add an offset to the depth? Something like a negative inflation?
Thank you
The text was updated successfully, but these errors were encountered:
Hi, I was wondering if there is a way to offset the depth voxels.
I have a robot where the depth cloud actually corresponds to what I measure, but the voxels are closer and this way the costmap (resolution 0.04) will show presence of obstacle about 0.1m closer than they actually are.
`
Lowering the resolution for both stvl and local costmap solved the problem, so it probably is just the size of the grid that matters. But unfotunately my raspberry pi is already pushing hard and lowering the resolution creates too much lag. Is there a way to add an offset to the depth? Something like a negative inflation?
Thank you
The text was updated successfully, but these errors were encountered: