segmenters_lib
A ROS library for LiDAR point cloud segmentation, enabling ground removal and object clustering for autonomous vehicle perception.
What is segmenters_lib?
segmenters_lib is a ROS library for segmenting LiDAR point clouds, specifically designed for autonomous vehicle perception. It processes raw LiDAR data to separate ground points from non-ground points and clusters the latter into candidate objects for further detection and tracking. The library implements multiple segmentation algorithms from academic research to handle different environmental conditions and sensor configurations.
Autonomous vehicle and robotics engineers building LiDAR-based perception stacks, particularly those working on object detection, tracking, and environmental mapping in ROS environments.
It provides a modular, research-backed collection of segmentation algorithms in a ready-to-use ROS package, saving development time compared to implementing algorithms from scratch. The library's flexibility allows engineers to mix and match components and tune parameters for specific sensor setups and use cases.
Overview
The LiDAR segmenters library, for segmentation-based detection.
Use Cases
Best For
- Building LiDAR perception pipelines for autonomous vehicles
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