UGV autonomous driving system design for unstructed environment

Autonomous Unmanned Ground Vehicle (UGV) in complex environments is currently a popular research area. Due to the limitation of sensors and abundant environmental information, it is difficult for UGV to obtain their own status and environmental information in real time. This article proposes an autonomous UGV system based on LiDAR and camera in GNSS-denied scenarios. The camera and LiDAR are used to detect various obstacles in the environment separately. Then, we propose an obstacle detection fusion strategy, which eliminates false detection and improves accuracy of target detection. Finally the real-world experiments show that, based on our multi-sensor fusion detection algorithm, UGV can move autonomously and safely in unstructured environment, which consists of convex and concave obstacles.