Decentralized multi-agent path selection using minimal information

Abstract

This work studies conflict avoidance between moving, noncommunicating agents with minimum sensing information. While safety can be provided by reactive obstacle avoidance methods for holonomic systems, deadlock avoidance requires reasoning over different homotopic paths in cluttered scenes. A method to compute the “interaction cost” of a path is proposed, which considers only the neighboring agents’ observed positions.Minimizing the interaction cost in a prototypical challenge with two agents moving through two corridors from opposing sides guarantees the selection of non-conflicting paths. More complex scenes, however, are more challenging. This leads to a study of alternatives for decentralized path selection. Simulations indicate that following a “minimum-conflict” path given the other agents’ observed positions provides deadlock avoidance. A scheme that selects between the minimum-conflict path and a set of shortest paths given their interaction cost improves path quality while still achieving deadlock avoidance. Finally, learning to select between the minimum-conflict and one of the shortest paths allows agents to be adaptive to the behavior of their neighbors and can be achieved using regret minimization.