Distributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Search

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dc.contributor.authorOsaba, Eneko
dc.contributor.authorDel Ser, Javier
dc.contributor.authorJubeto, Xabier
dc.contributor.authorIglesias, Andrés
dc.contributor.authorFister, Iztok
dc.contributor.authorGálvez, Akemi
dc.contributor.editorAnalide, Cesar
dc.contributor.editorNovais, Paulo
dc.contributor.editorCamacho, David
dc.contributor.editorYin, Hujun
dc.contributor.institutionQuantum
dc.contributor.institutionIA
dc.date.issued2020-10-27
dc.descriptionPublisher Copyright: © 2020, Springer Nature Switzerland AG.
dc.description.abstractThe term Swarm Robotics collectively refers to a population of robotic devices that efficiently undertakes diverse tasks in a collaborative way by virtue of computational intelligence techniques. This paradigm has given rise to a profitable stream of contributions in recent years, all sharing a clear consensus on the performance benefits derived from the increased exploration capabilities offered by Swarm Robotics. This manuscript falls within this topic: specifically, it gravitates on an heterogeneous Swarm Robotics system that relies on Stochastic Diffusion Search (SDS) as the coordination heuristics for the exploration, location and delimitation of areas scattered over the area in which robots are deployed. The swarm is composed by agents of diverse kind, which can be ground robots or flying devices. These agents communicate to each other and cooperate towards the accomplishment of the exploration tasks comprising the mission of the overall swarm. Furthermore, maps contain several obstacles and dangers, implying that in order to enter a specific area, robots should meet certain conditions. Experiments are conducted over three different maps and three implemented solving approaches. Conclusions are drawn from the obtained results, confirming that i) SDS allows for a lightweight, heuristic mechanism for the coordination of the robots; and ii) the most efficient swarming approach is the one comprising a heterogeneity of ground and aerial robots.en
dc.description.statusPeer reviewed
dc.format.extent13
dc.format.extent2080805
dc.identifier.citationOsaba , E , Del Ser , J , Jubeto , X , Iglesias , A , Fister , I & Gálvez , A 2020 , Distributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Search . in C Analide , P Novais , D Camacho & H Yin (eds) , unknown . vol. 12490 , 0302-9743 , Springer , pp. 79-91 , 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 , Guimaraes , Portugal , 4/11/20 . https://doi.org/10.1007/978-3-030-62365-4_8
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-62365-4_8
dc.identifier.isbn978-3-030-62365-4; 978-3-030-62364-7
dc.identifier.isbn9783030623647
dc.identifier.otherresearchoutputwizard: 11556/1033
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85097208461&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofunknown
dc.relation.ispartofseries0302-9743
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsSwarm Robotics
dc.subject.keywordsStochastic Diffusion Search
dc.subject.keywordsSwarm Intelligence
dc.subject.keywordsUnmanned Aerial Vehicles
dc.subject.keywordsRobotics
dc.subject.keywordsSwarm Robotics
dc.subject.keywordsStochastic Diffusion Search
dc.subject.keywordsSwarm Intelligence
dc.subject.keywordsUnmanned Aerial Vehicles
dc.subject.keywordsRobotics
dc.subject.keywordsTheoretical Computer Science
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsFunding Info
dc.subject.keywordsBasque Government for its support through the EMAITEK and ELKARTEK (Elkarbot project) programs. Javier Del Ser also receives support from the Consolidated Research Group MATHMODE (IT1294-19) granted by the Department of Education of this institution.
dc.subject.keywordsBasque Government for its support through the EMAITEK and ELKARTEK (Elkarbot project) programs. Javier Del Ser also receives support from the Consolidated Research Group MATHMODE (IT1294-19) granted by the Department of Education of this institution.
dc.titleDistributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Searchen
dc.typeconference output
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