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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.

radius_search_2d_outlier_filter_picture

Inputs / Outputs#

This implementation inherits pointcloud_preprocessor::Filter class, please refer README.

Parameters#

Node Parameters#

This implementation inherits pointcloud_preprocessor::Filter class, please refer README.

Core Parameters#

Name Type Description
min_neighbors int If points in the circle centered on reference point is less than min_neighbors, a reference point is judged as outlier
search_radius double Searching number of points included in search_radius

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#

[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

(Optional) Future extensions / Unimplemented parts#

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