Multi-robot collaborative obstacle avoidance based on hierarchical path planning methods

To achieve collision-free cooperative obstacle avoidance in complex dynamic environments, this paper proposes a hierarchical path planning method considering three-dimensional spatiotemporal characteristics. The framework consists of two levels. At the global level, the Jump Point Search algorithm is improved by introducing a safety distance constraint between robots and obstacles and an angle-based priority search strategy, enabling the generation of globally optimal paths with improved safety and efficiency. At the local level, a three-dimensional spatiotemporal grid model replaces the traditional two-dimensional plane graph to predict potential conflicts between robots and dynamic obstacles. Different coordination strategies are then applied according to conflict types, ensuring safe and efficient avoidance. Simulation results show that, compared with the A-star algorithm, the improved Jump Point Search reduces path length by about 13 % and turning points by 50 %, while computation time decreases by nearly 89 %. Compared with the original Jump Point Search, path length is shortened by 8 %, turning points by 36 %, and computation time by 49 %. In the coordination stage, robots can dynamically adjust trajectories to achieve collision-free planning. These results demonstrate that the proposed hierarchical method not only improves planning efficiency and generates smoother, safer paths, but also effectively resolves inter-robot conflicts in dynamic environments, ensuring high levels of safety, real-time performance, and collaboration.

Authors

• Yanjuan Wu
• Hui Li

Keywords

• Hierarchical path planning
• Multi-robot cooperation
• Three-dimensional spatiotemporal grid
• Improved jump point search algorithm