Multi-robot Path Planning Based on Improved JPS Algorithm Fused with DWA
Shenghui Cheng, Zhenggang Wang, Shuhong Song · 2024
An enhanced Jump Point Search method is proposed, aiming at the issues of numerous inflection points, easily traversed barriers, and lengthy path search time of the conventional Jump Point Search (JPS) algorithm. First, the cost function in the heuristic of the original JPS algorithm is improved to reduce redundant nodes generated during the search path. This also increases the safety distance between the robot and obstacles, enhancing the path's safety and effectiveness. Secondly, by introducing the Dynamic Window Approach (DWA) for local path planning, the robot gains flexible obstacle avoidance capabilities in dynamic environments. This also results in a smoother path, further improving the obstacle avoidance efficiency and task completion rate of the multi-robot system. Finally, the enhanced JPS algorithm is coupled with the DWA algorithm to allow for real-time sharing of path information and obstacle locations. This enables coordinated movement and division of labor among robots, thereby improving the efficiency and safety of path planning. The simulation experiments show that the proposed fusion improvement algorithm significantly enhances search time, path length, and the number of turning points. This verifies the stable obstacle avoidance capability of the improved algorithm in dynamic environments.