Hierarchical Real-time Motion Planning for Safe Multi-robot Manipulation in Dynamic Environments*

Motion planning for multi-robot cooperation in dynamic environments is challenging due to the high-dimensional nature of multi-robot systems and the presence of unpredictable obstacles. Existing motion planning algorithms often struggle to balance between motion optimality and real-time responsiveness. This paper proposes a hierarchical real-time motion planning framework to address the above challenges. We decompose the motion planning problem into two layers: a high-level centralized global planning layer and a lower-level decentralized local planning layer. The global planner is designed to perform coordinated motion optimization for long-horizon task execution trajectories of multiple robots. Concurrently, each robot is equipped with a local planner, which is capable of rapidly generating reactive motion to avoid dynamic obstacles. Simulations and experiments are conducted to validate the effectiveness of the proposed framework. The results consistently demonstrate that the hierarchical framework is capable of facilitating both efficient and safe multi-robot manipulation in dynamic environments.