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dc.contributor.authorPavone, Marco
dc.contributor.authorArsie, Alessandro
dc.contributor.authorFrazzoli, Emilio
dc.contributor.authorBullo, Francesco
dc.date.accessioned2013-10-21T16:06:25Z
dc.date.available2013-10-21T16:06:25Z
dc.date.issued2011-08
dc.date.submitted2010-12
dc.identifier.issn0018-9286
dc.identifier.issn1558-2523
dc.identifier.urihttp://hdl.handle.net/1721.1/81455
dc.description.abstractA widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multiagent systems, this principle directly leads to equitable partitioning policies whereby: 1) the environment is equitably divided into subregions of equal measure; 2) one agent is assigned to each subregion; and 3) each agent is responsible for service requests originating within its own subregion. The current lack of distributed algorithms for the computation of equitable partitions limits the applicability of equitable partitioning policies to limited-size multiagent systems operating in known, static environments. In this paper, first we design provably correct and spatially distributed algorithms that allow a team of agents to compute a convex and equitable partition of a convex environment. Second, we discuss how these algorithms can be extended so that a team of agents can compute, in a spatially distributed fashion, convex and equitable partitions with additional features, e.g., equitable and median Voronoi diagrams. Finally, we discuss two application domains for our algorithms, namely dynamic vehicle routing for mobile robotic networks and wireless ad hoc networks. Through these examples, we show how one can couple the algorithms presented in this paper with equitable partitioning policies to make these amenable to distributed implementation. More in general, we illustrate a systematic approach to devise spatially distributed control policies for a large variety of multiagent coordination problems. Our approach is related to the classic Lloyd algorithm and exploits the unique features of power diagrams.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 0705451)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant 0705453)en_US
dc.description.sponsorshipUnited States. Office of Naval Research (Grant N00014-07-1-0721)en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/tac.2011.2112410en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT Web domainen_US
dc.titleDistributed Algorithms for Environment Partitioning in Mobile Robotic Networksen_US
dc.typeArticleen_US
dc.identifier.citationPavone, Marco, Alessandro Arsie, Emilio Frazzoli, and Francesco Bullo. “Distributed Algorithms for Environment Partitioning in Mobile Robotic Networks.” IEEE Transactions on Automatic Control 56, no. 8 (August 2011): 1834-1848.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Information and Decision Systemsen_US
dc.contributor.mitauthorFrazzoli, Emilioen_US
dc.relation.journalIEEE Transactions on Automatic Controlen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPavone, Marco; Arsie, Alessandro; Frazzoli, Emilio; Bullo, Francescoen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0505-1400
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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