A dynamic subgoal path planner for unpredictable environments

Although lots of planning algorithms have focused on the planning of fixed manipulators and mobile robots in moderate dynamic environments, seldom planning algorithms can be employed to deal with mobile agents in the presence of large scenario scales and unpredictable changing obstacles. Path planning for mobile robots in unpredictable environments would be an extreme challenge since computational complexity increase dramatically with high dimensionality, unpredictability and large scales. In this paper, a novel and real-time approach is proposed to solve this problem by generating subgoals dynamically according to time and potential values. This dynamic subgoal based approach includes two procedures, the subgoal generator and the inter-subgoal or inner replanner. On the one hand, a set of high-level subgoals is generated dynamically by an improved single shot strategy that could tailor itself adaptively. On the other hand, a roadmap is built during the preprocessing phase by employing a localized Dynamic Roadmap Mapping (local-DRM) for inter-subgoal replanning. Finally these two procedures will collaborate according to the potential field criterion to ensure completeness. Our approach can not only generate paths rapidly enough to satisfy the requirements of an anytime planer but also work for large scenario scales. Experimental results on different kinds of mobile agents, in large scenario scales and in the presence of unpredictable changing obstacles show that our approach can find out a collision free path on an average of 0.11s for a single planning, indicating an anytime planner.