Abstract: In order to autonomously navigate in an unknown environment, a robotic vehicle must be able to sense obstacles, determine their velocities, and select a collision-free path that will lead quickly to a goal. However, the perceived location and motion of the obstacles will be uncertain due to the limited accuracy of the robot’s sensors. Thus, it is necessary to develop a system that can avoid moving obstacles using uncertain sensor data. The method proposed here is based on an occupancy grid – which has been used to avoid stationary obstacles in an uncertain environment – in conjunction with velocity obstacles – which allow a robot to avoid well-known moving obstacles. The combination of these techniques leads to Velocity Occupancy Space (VOS): a search space which allows the robot to avoid moving obstacles and navigate efficiently to a goal using uncertain sensor data. The proposed method is validated by numerous simulation trials.
Impact: Collision-avoidance for unmanned ground vehicles, with low-cost sensors, is important if these vehicles are to be used in close-proximity with humans and human-operated vehicles.
Journal: Published online as an accepted paper in the International Journal of Vehicle Autonomous Systems, anticipated print date 07/31/2012.
Submitted by A. Galip Ulsoy, the C D Mote, Jr Distinguished University
Professor of Mechanical Engineering and Professor of Mechanical
Engineering, College of Engineering. firstname.lastname@example.org