3D-Lidar Based Negative Obstacle Detection in Unstructured Environment

Abstract

Negative obstacles like pits and ditches are common distributed in the unstructured road environment. For autonomous navigation of unmanned ground vehicle, negative obstacle avoidance is very important but difficult, as there are always bumpy roads during movement and the perception results are usually unstable. We proposed a negative obstacle detection method based on 3D-Lidar perception. Negative obstacles are divided into two types: negative obstacles within the road plane and negative obstacles on both sides of the road. For the former, point clouds scanned to the posterior wall of negative obstacles are used to extract geometric features. For the latter, the gap between valid point clouds are an important basis for negative obstacle detection. Besides, virtual point clouds are used to construct the area over negative obstacles. Meanwhile we do a lot of work to reduce false detection, as there are many small potholes on the rough roads which are not dangerous for driving. Experiments show that the proposed detection method is very effective and has good robustness in unstructured environment.