Hybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradient

dc.contributor.authorHamed, Oussama
dc.contributor.authorHamlich, Mohamed
dc.coverage.issue2cs
dc.coverage.volume27cs
dc.date.accessioned2022-01-26T08:21:44Z
dc.date.available2022-01-26T08:21:44Z
dc.date.issued2021-12-21cs
dc.description.abstractThe cooperation between mobile robots is one of the most important topics of interest to researchers, especially in the many areas in which it can be applied. Hunting a moving target with random behavior is an application that requires robust cooperation between several robots in the multi-robot system. This paper proposed a hybrid formation control for hunting a dynamic target which is based on wolves’ hunting behavior in order to search and capture the prey quickly and avoid its escape and Multi Agent Deep Deterministic Policy Gradient (MADDPG) to plan an optimal accessible path to the desired position. The validity and the effectiveness of the proposed formation control are demonstrated with simulation results.en
dc.formattextcs
dc.format.extent23-29cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2021 vol. 27, č. 2, s. 23-29. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2021.2.023en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/203388
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/147cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectReinforcement learningen
dc.subjectMulti-Robot Systemen
dc.subjectCooperative huntingen
dc.subjectPath Planningen
dc.subjectMobile roboten
dc.subjectCollaborative robotsen
dc.titleHybrid Formation Control for Multi-Robot Hunters Based on Multi-Agent Deep Deterministic Policy Gradienten
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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