LIDAR-based 3D Object Perception

Abstract

Abstract — This paper describes a LIDAR-based perception system for ground robot mobility, consisting of 3D object detection, classification and tracking. The presented system was demonstrated on-board our autonomous ground vehicle MuCAR-3, enabling it to safely navigate in urban traffic-like scenarios as well as in off-road convoy scenarios. The efficiency of our approach stems from the unique combination of 2D and 3D data processing techniques. Whereas fast segmentation of point clouds into objects is done in a 2 1 2 D occupancy grid, classifying the objects is done on raw 3D point clouds. For fast switching of domains, the occupancy grid is enhanced to act like a hash table for retrieval of 3D points. In contrast to most existing work on 3D point cloud classification, where real-time operation is often impossible, this combination allows our system to perform in real-time at 0.1s frame-rate. I.