Ground Segmentation

Ground segmentation, the process of separating ground points from other objects in 3D point cloud data (e.g., from LiDAR sensors), is crucial for various applications, particularly autonomous navigation and robotics. Current research emphasizes developing fast and robust algorithms, often employing grid-based methods, range image processing, or Gaussian Processes, to achieve accurate segmentation even in challenging environments like unstructured roads or rough terrains. These advancements improve the reliability of perception systems by enabling more precise object detection, path planning, and map building, ultimately enhancing the safety and efficiency of autonomous systems.