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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.

Velocity occupancy space: autonomous navigation in an uncertain, dynamic environment