Motion planning in dynamic environments using velocity obstacles

This paper presents a method for robot motion planning in dynamic environments. It consists of selecting avoidance maneuvers to avoid static and moving obstacles in the velocity space, based on the current positions and velocities of the robot and obstacles. It is a first-order method, since it does not integrate velocities to yield positions as functions of time. The avoidance maneuvers are generated by selecting robot velocities outside of the velocity obstacles, which represent the set of robot velocities that would result in a collision with a given obstacle that moves at a given velocity, at some future time. To ensure that the avoidance maneuver is dynamically feasible, the set of avoidance velocities is intersected with the set of admissible velocities, defined by the robot's acceleration constraints. Computing new avoidance maneuvers at regular time intervals accounts for general obstacle trajectories. The trajectory from start to goal is computed by searching a tree of feasible avoidance maneuvers, computed at discrete time intervals. An exhaustive search of the tree yields near-optimal trajectories that either minimize distance or motion time. A heuristic search of the tree is applicable to on-line planning. The method is demonstrated for point and disk robots among static and moving obstacles, and for an automated vehicle in an intelligent vehicle highway system scenario.