Plane Seg

Uses normal-based clustering to effectively handle noisy depth data, proven in real-world applications like ANYmal climbing stairs, as shown in the README videos and performance metrics.

Directly processes ROS PointCloud2 and GridMap data types with dedicated launch files, enabling quick integration into existing ROS-based robotic systems for perception pipelines.

Achieves ~0.3 seconds processing time on 18k-point elevation maps from real robot data, making it suitable for real-time navigation tasks in unstructured environments.

Extracts line segments from detected planes to identify steps and obstacles, enhancing terrain perception for autonomous robots, as detailed in the edge detection package.