Distributed and Safe Replanning for Communicating Vehicles
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Consider the problem of coordinating multiple vehicles with kinodynamic constraints that operate in the same partially-known environment. The vehicles are able to communicate with a limited range. Their objective is to avoid collisions between them and with the obstacles, while the vehicles move towards their individual goals. An important issue of real-time planning for systems with bounded acceleration is that inevitable collision states must also be avoided. The focus of this work is to guarantee safety despite the dynamic constraints with a decentralized motion planning technique that employs only local information. We propose a coordination framework that allows vehicles to generate and select compatible sets of valid trajectories and prove that this scheme guarantees collision-avoidance in the specified setup. The theoretical results have been also experimentally confirmed with a distributed simulator where each vehicle replans online with a sampling-based, kinodynamic motion planner and uses message-passing to communicate with neighboring agents.
