Development of an integrated sensor system for obstacle detection and terrain evaluation for application to unmanned ground vehicles

This paper describes the development and performance of a sensor system that was utilized for autonomous navigation of an unmanned ground vehicle. Four different sensor types were integrated to identify obstacles in the vicinity of the vehicle and to identify smooth terrain that could be traversed at speeds up to thirty miles per hour. The paper also describes a sensor fusion approach that was developed whereby the output of all sensors was in a common grid based format. The environment around the vehicle was modeled by a 120×120 grid where each grid cell was 0.5m× 0.5m in size and where the orientation of the grid lines was always maintained parallel to the north-south and east-west lines. Every sensor output an estimate of the traversability of each grid cell. For the three dimensional obstacle avoidance sensors (rotating ladar and stereo vision) the three dimensional point data was projected onto the grid plane. The terrain traversability sensors, i.e. fixed ladar and monocular vision, estimated traversability based on smoothness of the spatial plane fitted to the range data or the commonality in appearance of pixels in the grid cell to those directly in front of the vehicle, respectively.