Ground Filtering

Ground filtering aims to separate ground points from non-ground objects within 3D point cloud data acquired from various sensors like LiDAR and sonar. Current research focuses on developing efficient and robust algorithms, including those based on Gaussian processes, B-splines, and voxel structures, to accurately estimate ground surfaces even in challenging environments with varying terrain and data density. These advancements are crucial for applications such as autonomous vehicle navigation, 3D scene reconstruction, and underwater robotics, improving the reliability and performance of these systems.