Bidirectional Search Strategy for Incremental Search-based Path Planning

Abstract

Planning a collision-free path efficiently among obstacles is crucial in robotics. Conventional one-shot unidirectional path planning algorithms work well in the static environment, but cannot respond to the environment changes timely in the dynamic environment. To tackle this issue and improve the search efficiency, we propose a bidirectional incremental search method, Bidirectional Lifelong Planning A* (BLPA*), which searches in the forward and backward directions and performs incremental search bidirectionally when the environment changes. Furthermore, inspired by the robot perception range limitation and BLPA*, we propose the fractional bidirectional D* Lite (fBD* Lite(dp)), which constraints the forward search to the robot perception range and uses the backward search to expand the rest area. Our simulation results demonstrate BLPA* and mD* Lite(dp) can achieve superior performance in the dynamic environment. It reveals that the bidirectional incremental search strategy can be a general and efficient technique for graph-search-based robot path planning methods.