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autoware_euclidean_cluster#

Purpose#

autoware_euclidean_cluster is a package for clustering points into smaller parts to classify objects.

This package has two clustering methods: euclidean_cluster and voxel_grid_based_euclidean_cluster.

Inner-workings / Algorithms#

euclidean_cluster#

pcl::EuclideanClusterExtraction is applied to points. See official document for details.

voxel_grid_based_euclidean_cluster#

  1. A centroid in each voxel is calculated by pcl::VoxelGrid.
  2. The centroids are clustered by pcl::EuclideanClusterExtraction.
  3. The input points are clustered based on the clustered centroids.

Inputs / Outputs#

Input#

Name Type Description
input sensor_msgs::msg::PointCloud2 input pointcloud

Output#

Name Type Description
output tier4_perception_msgs::msg::DetectedObjectsWithFeature cluster pointcloud
debug/clusters sensor_msgs::msg::PointCloud2 colored cluster pointcloud for visualization

Parameters#

Core Parameters#

euclidean_cluster#

Name Type Description Default Range
max_cluster_size integer The maximum number of points that a cluster needs to contain in order to be considered valid. 1000 N/A
min_cluster_size integer The minimum number of points that a cluster needs to contain in order to be considered valid. 10 N/A
tolerance float The spatial cluster tolerance as a measure in the L2 Euclidean space. 0.7 N/A
use_height boolean Whether to use point.z for clustering. 0 N/A

voxel_grid_based_euclidean_cluster#

Name Type Description Default Range
tolerance float The spatial cluster tolerance as a measure in the L2 Euclidean space. 0.7 N/A
voxel_leaf_size float The voxel leaf size of x and y. 0.3 N/A
min_points_number_per_voxel integer The minimum number of points required per voxel. 1 N/A
min_cluster_size integer The minimum number of points that a cluster needs to contain in order to be considered valid. 10 N/A
max_cluster_size integer The maximum number of points that a cluster needs to contain in order to be considered valid. 3000 N/A
use_height boolean Use point.z for clustering. False N/A
input_frame string The reference frame for input data processing. base_link N/A
max_x float Maximum X coordinate for the low height crop box filter. 200.0 N/A
min_x float Minimum X coordinate for the low height crop box filter. -200.0 N/A
max_y float Maximum Y coordinate for the low height crop box filter. 200.0 N/A
min_y float Minimum Y coordinate for the low height crop box filter. -200.0 N/A
max_z float Maximum Z coordinate for the low height crop box filter. 2.0 N/A
min_z float Minimum Z coordinate for the low height crop box filter. -10.0 N/A
negative boolean Whether to invert the crop box filtering effect. False N/A
Name Type Description
use_height bool use point.z for clustering
min_cluster_size int the minimum number of voxels that a cluster needs to contain in order to be considered valid
max_cluster_size int the maximum number of voxels that a cluster needs to contain in order to be considered valid
tolerance float the spatial cluster tolerance as a measure in the L2 Euclidean space
voxel_leaf_size float the voxel leaf size of x and y
min_points_number_per_voxel int the minimum number of points for a voxel
min_voxel_cluster_size_for_filtering int The minimum voxel cluster size for a cluster to be checked for being a large cluster.
max_points_per_voxel_in_large_cluster int The maximum points per voxel allowed in large clusters (used for filtering dense clusters).
max_voxel_cluster_for_output int The maximum number of voxel clusters to output. If the voxels exceeds this value, the cluster will be skipped.

Assumptions / Known limits#

(Optional) Error detection and handling#

(Optional) Performance characterization#

(Optional) Future extensions / Unimplemented parts#

The use_height option of voxel_grid_based_euclidean_cluster isn't implemented yet.