autoware_occupancy_grid_map_outlier_filter

Purpose

This node is an outlier filter based on a occupancy grid map. Depending on the implementation of occupancy grid map, it can be called an outlier filter in time series, since the occupancy grid map expresses the occupancy probabilities in time series.

Inner-workings / Algorithms

1. Use the occupancy grid map to separate point clouds into those with low occupancy probability and those with high occupancy probability.

2. The point clouds that belong to the low occupancy probability are not necessarily outliers. In particular, the top of the moving object tends to belong to the low occupancy probability. Therefore, if use_radius_search_2d_filter is true, then apply an radius search 2d outlier filter to the point cloud that is determined to have a low occupancy probability.

   1. For each low occupancy probability point, determine the outlier from the radius (radius_search_2d_filter/search_radius) and the number of point clouds. In this case, the point cloud to be referenced is not only low occupancy probability points, but all point cloud including high occupancy probability points.
   2. The number of point clouds can be multiplied by radius_search_2d_filter/min_points_and_distance_ratio and distance from base link. However, the minimum and maximum number of point clouds is limited.

The following video is a sample. Yellow points are high occupancy probability, green points are low occupancy probability which is not an outlier, and red points are outliers. At around 0:15 and 1:16 in the first video, a bird crosses the road, but it is considered as an outlier.

• movie1
• movie2

Inputs / Outputs

Input

Name	Type	Description
~/input/pointcloud	sensor_msgs/PointCloud2	Obstacle point cloud with ground removed.
~/input/occupancy_grid_map	nav_msgs/OccupancyGrid	A map in which the probability of the presence of an obstacle is occupancy probability map

Output

Name	Type	Description
~/output/pointcloud	sensor_msgs/PointCloud2	Point cloud with outliers removed. trajectory
~/output/debug/outlier/pointcloud	sensor_msgs/PointCloud2	Point clouds removed as outliers.
~/output/debug/low_confidence/pointcloud	sensor_msgs/PointCloud2	Point clouds that had a low probability of occupancy in the occupancy grid map. However, it is not considered as an outlier.
~/output/debug/high_confidence/pointcloud	sensor_msgs/PointCloud2	Point clouds that had a high probability of occupancy in the occupancy grid map. trajectory

Parameters

Name	Type	Description	Default	Range
radius_search_2d_filter.search_radius	float	Radius used when calculating the density.	1.0	≥0.0
radius_search_2d_filter.min_points_and_distance_ratio	float	Threshold value of the number of point clouds per radius when the distance from the base link is 1m.	400.0	≥0.0
radius_search_2d_filter.min_points	integer	Minimum number of point clouds per radius.	4	≥1
radius_search_2d_filter.max_points	integer	Maximum number of point clouds per radius.	70	≥1
radius_search_2d_filter.max_filter_points_nb	integer	Maximum number of point clouds to be filtered.	15000	≥1
map_frame	string	The frame ID for the map.	map	N/A
base_link_frame	string	The frame ID for the base link.	base_link	N/A
cost_threshold	integer	Cost threshold for occupancy grid map (0-100), where 100 indicates a high probability of an obstacle.	45	≥0 ≤100
use_radius_search_2d_filter	boolean	Enable or disable the 2D radius search filter.	True	N/A
enable_debugger	boolean	Enable or disable debugging output.	False	N/A
publish_processing_time_detail	boolean	Enable or disable publishing of processing time details.	False	N/A

Assumptions / Known limits

(Optional) Error detection and handling

(Optional) Performance characterization

(Optional) References/External links

(Optional) Future extensions / Unimplemented parts