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Avoiding collisions is the core problem in multi-agent navigation. Indecentralized settings, when agents have limited communication and sensorycapabilities, collisions are typically avoided in a reactive fashion, relyingon local observations/communications. Prominent collision avoidance techniques,e.g. ORCA, are computationally efficient and scale well to a large number ofagents. However, in numerous scenarios, involving navigation through the tightpassages or confined spaces, deadlocks are likely to occur due to the egoisticbehaviour of the agents and as a result, the latter can not achieve theirgoals. To this end, we suggest an application of the locally confinedmulti-agent path finding (MAPF) solvers that coordinate sub-groups of theagents that appear to be in a deadlock (to detect the latter we suggest asimple, yet efficient ad-hoc routine). We present a way to build a grid-basedMAPF instance, typically required by modern MAPF solvers. We evaluate two ofthem in our experiments, i.e. Push and Rotate and a bounded-suboptimal versionof Conflict Based Search (ECBS), and show that their inclusion into thenavigation pipeline significantly increases the success rate, from 15% to 99%in certain cases.

Distributed Multi-agent Navigation Based on Reciprocal Collision Avoidance and Locally Confined Multi-agent Path Finding