Skip to content

probabilistic_occupancy_grid_map#

Purpose#

This package outputs the probability of having an obstacle as occupancy grid map. pointcloud_based_occupancy_grid_map_sample_image

Settings#

Occupancy grid map is generated on map_frame, and grid orientation is fixed.

You may need to choose scan_origin_frame and gridmap_origin_frame which means sensor origin and gridmap origin respectively. Especially, set your main LiDAR sensor frame (e.g. velodyne_top in sample_vehicle) as a scan_origin_frame would result in better performance.

image_for_frame_parameter_visualization

Each config parameters#

Config parameters are managed in config/*.yaml and here shows its outline.

  • Pointcloud based occupancy grid map
Ros param name Default value
map_frame "map"
base_link_frame "base_link"
scan_origin_frame "base_link"
gridmap_origin_frame "base_link"
use_height_filter true
enable_single_frame_mode false
filter_obstacle_pointcloud_by_raw_pointcloud false
map_length 150.0 [m]
map_resolution 0.5 [m]
use_projection false
projection_dz_threshold 0.01
obstacle_separation_threshold 1.0
input_obstacle_pointcloud true
input_obstacle_and_raw_pointcloud true
  • Laserscan based occupancy grid map
Ros param name Default value
map_length 150 [m]
map_width 150 [m]
map_resolution 0.5 [m]
use_height_filter true
enable_single_frame_mode false
map_frame "map"
base_link_frame "base_link"
scan_origin_frame "base_link"
gridmap_origin_frame "base_link"

Other parameters#

Additional argument is shown below:

Name Default Description
use_multithread false whether to use multithread
use_intra_process false
map_origin `` parameter to override map_origin_frame which means grid map origin
scan_origin `` parameter to override scan_origin_frame which means scanning center
output occupancy_grid output name
use_pointcloud_container false
container_name occupancy_grid_map_container
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
# 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
# downsampled raw and obstacle pointcloud
/perception/occupancy_grid_map/obstacle/downsample/pointcloud
/perception/occupancy_grid_map/<sensor_name>/raw/downsample/pointcloud

Test#

This package provides unit tests using gtest. You can run the test by the following command.

colcon test --packages-select probabilistic_occupancy_grid_map --event-handlers console_direct+

Test contains the following.

  • Unit test for cost value conversion function
  • Unit test for utility functions
  • Unit test for occupancy grid map fusion functions
  • Input/Output test for pointcloud based occupancy grid map