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dc.contributor.authorProrok , Amanda
dc.contributor.authorAni Hsieh , M.
dc.contributor.authorKumar , Vijay
dc.date.accessioned2017-02-09T11:26:25Z
dc.date.available2017-02-09T11:26:25Z
dc.date.issued2016
dc.identifier.citationActa Polytechnica. 2016, vol. 56, no. 1, p. 67-75.
dc.identifier.issn1210-2709 (print)
dc.identifier.issn1805-2363 (online)
dc.identifier.urihttp://hdl.handle.net/10467/67241
dc.description.abstractWe present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type) is defined by the traits (capabilities) that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherČeské vysoké učení technické v Prazecs
dc.publisherCzech Technical University in Pragueen
dc.relation.ispartofseriesActa Polytechnica
dc.relation.urihttps://ojs.cvut.cz/ojs/index.php/ap/article/view/3438
dc.rightsCreative Commons Attribution 4.0 International Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectheterogeneous multi-robot systemsen
dc.subjectswarm roboticsen
dc.subjectstochastic systemsen
dc.subjecttask allocationen
dc.titleADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS
dc.typearticleen
dc.date.updated2017-02-09T11:26:25Z
dc.identifier.doihttps://doi.org/10.14311/APP.2016.56.0067
dc.rights.accessopenAccess
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion


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Creative Commons Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International License