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dc.contributor.authorBaras, John S.en_US
dc.contributor.authorTan, Xiaoboen_US
dc.date.accessioned2007-05-23T10:14:57Z
dc.date.available2007-05-23T10:14:57Z
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/1903/6419
dc.description.abstractA distributed control approach is proposed for self-organization of autonomous swarms. The swarm is modeled as a Markov random field (MRF) on a graph where the (mobile) nodes and their communication/sensing links constitute the vertices and the edges of the graph, respectively. The movement of nodes is governed by the Gibbs sampler. The Gibbs potentials, local in nature, are designed to reflect collective goals such as gathering, dispersion, and linear formation. The algorithm can be run completely in parallel, and hence it is robust and scalable. Simulation results are provided to illustrate the proposed method.en_US
dc.format.extent375534 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2004-12en_US
dc.relation.ispartofseriesSEIL; TR 2004-1en_US
dc.subjectSensor-Actuator Networksen_US
dc.titleControl of Autonomous Swarms Using Gibbs Samplingen_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US
dc.contributor.departmentSEILen_US


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