Online sub-optimal obstacle avoidance

Abstract

This paper presents an online planner for suboptimal obstacle avoidance. It generates near-shortest paths incrementally by avoiding obstacles optimally one at a time. In known environments, the obstacles are avoided in an order determined by a global criterion, whereas in unknown environment, obstacles are avoided as they are detected by on-board sensors. This avoidance strategy converges globally to the goal, regardless of the order in which the obstacles are selected. The planner is demonstrated for a point robot moving amongst general planar polygonal obstacles.