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We propose a decentralized collision-avoidance mechanism for a group ofindependently controlled robots moving on a shared workspace. Existingalgorithms achieve multi-robot collision avoidance either (a) in a centralizedsetting, or (b) in a decentralized setting with collaborative robots. We focuson the setting with competitive robots in a decentralized environment, whererobots may strategically reveal their information to get prioritized. Wepropose the mechanism SPARCAS in this setting that, using principles ofmechanism design, ensures truthful revelation of the robots' privateinformation and provides locally efficient movement of the robots. It is freefrom collisions and deadlocks, and handles a dynamic arrival of robots. Inpractice, this mechanism scales well for a large number of robots where theoptimal collision-avoiding path-finding algorithm (M*) does not scale. Yet,SPARCAS does not compromise the path optimality too much. Our mechanismprioritizes the robots in the order of their `true' higher needs, but for ahigher payment. It uses monetary transfers which is small enough compared tothe value received by the robots.

SPARCAS: A Decentralized, Truthful Multi-Agent Collision-free Path Finding Mechanism