An efficient RRT cache method in dynamic environments for path planning

This paper is concentrated on path planning for robots working in a dynamic environment to satisfy real-time needs. An efficient bias-goal factor RRT (EBG-RRT), which is multiple-query sampling-based replanning algorithm, is proposed with rapid response and high success rate. Specifically, a relay node method is proposed to get a position where the robot and dynamic obstacles will be no-collision and help robots to move without suspended. Based on the relay node method, Connection strategy performs minimal modifications to maintain the interrupted path. In order to overcome the short of Waypoint Cache method, an efficient and optimal Waypoint Cache (EOWC) method is proposed to make use of potential cache information and find an optimal path to repair. The EOWC method is combined with the BG-RRT algorithm according to the iterative characteristics. Finally, the EBG-RRT algorithm is verified on ROS with Aubo-i5 manipulator. Simulation results provide the EBG-RRT algorithm is outperformed both in static and dynamic environments. © 2020 Elsevier B.V.