Yan Zhang, Tuanjie Li, Xiantao Li, and Yuming Ning
Multi-robot, A, TEB, autonomous navigation, motion planning
Multi-robot motion planning (MRMP) necessitates that each robot possesses strong local planning capabilities while maintaining consistency with global strategies. However, existing research often fails to address both global and local planning concurrently, leading to conflicts and discrepancies in real-time path execution. The A algorithm is a widely adopted global planning method, renowned for its adaptability to diverse environments and efficient search capabilities. Meanwhile, the time elastic band (TEB) algorithm is a prominent local path planner for multi-robot systems, characterised by its time elasticity, robustness, adaptability, real-time capability, and scalability. We propose a comprehensive motion planning framework that integrates an enhanced A algorithm with the TEB strategy, aiming to address both global motion planning and local trajectory optimisation. This approach is designed to offer a robust solution for multi-robot systems operating in complex environments. By incorporating steering costs and dynamic weights into the A algorithm, we augment its flexibility and adaptability within dynamic environments. Simulation experiments conducted with ROS confirmed the feasibility of the method. Within the move base framework, we developed a collaborative motion planner based on this approach to implement multi-robot motion planning in real-world scenarios.
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