This paper proposes a decentralized control strategy to assign tasks to Autonomous Guided Vehicles (AGV) and coordinate their paths to avoid deadlock and collisions. We consider a zone-controlled guidepath network where a set of intelligent vehicles (agents) has to autonomously reach a consensus about the distribution of a set of tasks, i.e., a set of zones to be reached. To this aim the agents apply a discrete consensus algorithm in order to locally minimize the global cost for reaching the destination zone. Moreover, we present a decentralized coordination protocol that is based on a zone-controlled approach with the aim of avoiding deadlock and collisions.
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