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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. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3323–3328, 2012.

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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-agent Partially Observable Markov Decision Process (POMDPs) while maintaining cooperation between robots by using POMDP policy auctions. Also, communication models in the multi-agent POMDP literature severely mismatch with real inter-robot communication. We address this issue by applying a decentralized data fusion method in order to efficiently maintain a joint belief state among the robots. The paper focuses on a cooperative tracking application, in which several robots have to jointly track a moving target of interest. The proposed ideas are illustrated in real multi-robot experiments, showcasing the flexible and robust cooperation that our techniques can provide.

BibTeX Entry

@InProceedings{Capitan12icra,
  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}},
  booktitle =    {Proceedings of the IEEE International Conference on
                  Robotics and Automation},
  year =         2012,
  pages =        {3323--3328}
}

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