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dc.contributor.authorLee, Sung G.
dc.contributor.authorEgerstedt, Magnus B.
dc.date.accessioned2014-10-16T19:55:22Z
dc.date.available2014-10-16T19:55:22Z
dc.date.issued2013-09
dc.identifier.citationS. Lee and M. Egerstedt. Controlled Coverage Using Time-Varying Density Functions. IFAC Workshop on Distributed Estimation and Control in Networked Systems, Koblenz, Germany, Sept. 2013, pp. 220-226.en_US
dc.identifier.issn1474-6670
dc.identifier.urihttp://hdl.handle.net/1853/52659
dc.descriptionCopyright©2013 IFACen_US
dc.descriptionPresented at the 4th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys'13), 25-26 September 2013, Koblenz, Germany.
dc.descriptionDOI: 10.3182/20130925-2-DE-4044.00030
dc.description.abstractA new approach for controlling a system of multiple agents by choosing a time-varying density function is presented, employing optimal coverage ideas. In this approach, we specify a time- varying density function that represents where it is that want the agents to monitor, and how important it is for each point to be covered. A new algorithm is presented under which the agents track the time-varying density function while providing optimal coverage of the density function. Results from robot implementation show that the proposed algorithm guides the agents well over the chosen density functions, and that the effectiveness of the coverage is higher than other comparable algorithmsen_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectCentroidal Voronoi tessellationsen_US
dc.subjectControl algorithmsen_US
dc.subjectCoverage controlen_US
dc.subjectMobile robotsen_US
dc.subjectTime-varying systemsen_US
dc.subjectTracking systemsen_US
dc.titleControlled Coverage Using Time-Varying Density Functionsen_US
dc.typePre-printen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineeringen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machinesen_US
dc.publisher.originalInternational Federation of Automatic Control (IFAC)
dc.identifier.doi10.3182/20130925-2-DE-4044.00030
dc.embargo.termsnullen_US


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