Decentralized multi-robot cooperation with auctioned POMDPs

J. Capitan, M. Spaan, L. Merino and A. Ollero. , Decentralized multi-robot cooperation with auctioned POMDPs, International Journal of Robotics Research, 32 (6): 650-671, 2013

Abstract: 
Planning under uncertainty faces a scalability problem when considering multi-robot teams, as the information space scales exponentially with the number of robots. To address this issue, this paper proposes to decentralize multi-robot Partially Observable Markov Decision Processes (POMDPs) while maintaining cooperation between robots by using POMDP policy auctions. Auctions provide a flexible way of coordinating individual policies modeled by POMDPs and have low communication requirements. Additionally, communication models in the multi-agent POMDP literature severely mismatch with real inter-robot communication. We address this issue by exploiting a decentralized data fusion method in order to efficiently maintain a joint belief state among the robots. The paper presents two different applications: environmental monitoringwith UnmannedAerial Vehicles (UAVs); and cooperative tracking, in which several robots have to jointly track a moving target of interest. The first one is used as a proof of concept and illustrates the proposed ideas through different simulations. The second one adds real multi-robot experiments, showcasing the flexibility and robust coordination that our techniques can provide.
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