3D traversability analysis and path planning based on mechanical effort for UGVs in forest environments

Abstract

Autonomous navigation in rough and dynamic 3D environments is a major challenge for modern robotics. This paper presents a novel traversability analysis and path planning technique that processes 3D point cloud maps to compute terrain gradient information and detect the presence of obstacles to generate efficient paths. These avoid unnecessary slope changes when more conservative paths are available, potentially promoting fuel economy, reducing the wear on the equipment and the associated risks. The proposed approach is shown to outperform existing techniques both in 3D simulation scenarios as well as in a real forest dataset, in which it also generates paths that are comparable to the ones drawn by humans with different backgrounds and expertise levels.