Multiple-Robots Motion Planner
Duong Le / October 2020 (92 Words, 1 Minutes)
Link To Paper: Cooperative Multi-Robot Sampling-Based Motion Planning with Dynamics
This paper combines sampling-based motion plan- ning with multi-agent search to efficiently solve challenging multi- robot motion-planning problems with dynamics. This idea has shown promise in prior work which developed a centralized approach to expand a motion tree in the composite state space of all the robots along routes obtained by multi-agent search over a discrete abstraction. Still, the centralized expansion imposes a significant bottleneck due to the curse of dimensionality associated with the high-dimensional composite state space. To improve efficiency and scalability, we propose a coordinated expansion of the motion tree along routes obtained by the multi- agent search. We first develop a single-robot sampling-based approach to closely follow a given route σi. The salient aspect of the proposed coordinated expansion is to invoke the route follower one robot at a time, ensuring that robot i follows σi while avoiding not only the obstacles but also robots 1,…,i−1. In the next iteration, the motion tree could be expanded from another state along other routes. This enables the approach to progress rapidly and achieve significant speedups over a centralized approach.
Multi-robot planning to exchance locations via a narrow tunnel