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Decentralized Multi-Robot Cooperation with Auctioned POMDPs

J. Capitan, M. Spaan, L. Merino, and A. Ollero. Decentralized Multi-Robot Cooperation with Auctioned POMDPs. In Proceedings of the IEEE International Conference on Robotics and Automation, ICRA, pp. 3323–3328, 2012.

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Abstract

Planning under uncertainty faces a scalabilityproblem when considering multi-robot teams, as the informationspace scales exponentially with the number of robots.To address this issue, this paper proposes to decentralizemultiagent Partially Observable Markov Decision Process(POMDPs) while maintaining cooperation between robots byusing POMDP policy auctions. Furthermore, communicationmodels in the multiagent POMDP literature severely mismatchwith real inter-robot communication. We address this issueby applying a decentralized data fusion method in order toefficiently maintain a joint belief state among the robots.The paper focuses on a cooperative tracking application, inwhich several robots have to jointly track a moving target ofinterest. The proposed ideas are illustrated in real multi-robotexperiments, showcasing the flexible and robust cooperationthat our techniques can provide.

BibTeX Entry

@INPROCEEDINGS{capitan_icra12,
  author = {J. Capitan and M. Spaan and L. Merino and A. Ollero},
  title = {{D}ecentralized {M}ulti-{R}obot {C}ooperation with {A}uctioned {POMDP}s},
  booktitle = ICRA,
  year = {2012},
  pages = {3323--3328},
  doi = {10.1109/ICRA.2012.6224917},
  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
multiagent Partially Observable Markov Decision Process
(POMDPs) while maintaining cooperation between robots by
using POMDP policy auctions. Furthermore, communication
models in the multiagent 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.},
}

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