D-PBS: Dueling Priority-Based Search for Multiple Nonholonomic Robots Motion Planning in Congested Environments

This letter focuses on the multiple nonholonomic robots motion planning (MRMP) problem in congested and complex environments, where the complexity escalates dramatically with the increase in the number of robots, frequently leading to deadlocks. We present the Dueling Priority-Based Search (mathtt {Dtext{-}PBS}), an efficient and scalable priority-based motion planner for multiple nonholonomic car-like robots, capable of enabling robots to move safely to destinations in spatially-constrained settings. We achieve this by adopting the alternate dueling collision resolution approach, coupled with the exploration of comprehensive priority relationships, effectively addressing the deadlock situations. We also introduce a novel priority-binding algorithm to enhance the scalability of our planner in restricted spaces densely populated with robots. Experimental evaluations in various scenarios demonstrate that mathtt {Dtext{-}PBS} outperforms standard approaches to MRMP, offering superior path quality and scalability for larger robot swarms.