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Decentralized Multi-robot Cooperation with Auctioned POMDPs

Jesús Capitán, Matthijs T. J. Spaan, Luis Merino, and An\'ibal Ollero. Decentralized Multi-robot Cooperation with Auctioned POMDPs. International Journal of Robotics Research, 32(6):650–671, 2013.

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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. In addition, 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 monitoring with unmanned aerial 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.

BibTeX Entry

@Article{Capitan13ijrr,
  author =       {Jes\'us Capit\'an and Matthijs T. J. Spaan and Luis
                  Merino and An\'ibal Ollero},
  title =        {Decentralized Multi-robot Cooperation with Auctioned
                  {POMDPs}},
  journal =      {International Journal of Robotics Research},
  year =         2013,
  volume =       32,
  number =       6,
  pages =        {650--671}
}

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