radius_search_2d_outlier_filter#
Purpose#
The purpose is to remove point cloud noise such as insects and rain.
Inner-workings / Algorithms#
RadiusOutlierRemoval filter which removes all indices in its input cloud that don’t have at least some number of neighbors within a certain range.
The description above is quoted from [1]. pcl::search::KdTree [2] is used to implement this package.
Inputs / Outputs#
This implementation inherits autoware::pointcloud_preprocessor::Filter class, please refer README.
Parameters#
Node Parameters#
This implementation inherits autoware::pointcloud_preprocessor::Filter class, please refer README.
Core Parameters#
| Name | Type | Description | Default | Range |
|---|---|---|---|---|
| min_neighbors | integer | If points in the circle centered on reference point is less than min_neighbors, a reference point is judged as outlier | 5 | ≥0 |
| search_radius | float | Searching number of points included in search_radius | 0.2 | ≥0 |
Assumptions / Known limits#
Since the method is to count the number of points contained in the cylinder with the direction of gravity as the direction of the cylinder axis, it is a prerequisite that the ground has been removed.
(Optional) Error detection and handling#
(Optional) Performance characterization#
References/External links#
[1] https://pcl.readthedocs.io/projects/tutorials/en/latest/remove_outliers.html
[2] https://pcl.readthedocs.io/projects/tutorials/en/latest/kdtree_search.html#kdtree-search