Asynchronous Real-time Decentralized Multi-Robot Trajectory Planning

Baskin Senbaslar, Gaurav S. Sukhatme

Abstract: We present a novel overconstraining and constraint-discarding method for asynchronous, real-time, decentralized, multi-robot trajectory planning that ensures collision avoidance. Our approach utilizes communication between robots. The communication medium is best-effort: messages may be dropped, re-ordered or delayed. Robots conservatively constrain themselves against others assuming they may be working with outdated information, and discard constraints when they receive update messages from others. Our method can augment existing synchronized decentralized receding horizon planning algorithms that utilize separating hyperplanes for collision avoidance thereby making them applicable to asynchronous setups. As an example, we extend an existing model predictive control based, synchronized, decentralized multi-robot planner using our method. We show our method's effectiveness under asynchronous planning and imperfect communication by comparing our extension to the base version. Our extension does not result in any collisions or synchronization-induced deadlocks to which the base version is prone.