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Coverage path planning optimization based on Q-learning algorithm

dc.contributor.authorPiardi, Luis
dc.contributor.authorLima, José
dc.contributor.authorPereira, Ana I.
dc.contributor.authorCosta, Paulo Gomes da
dc.date.accessioned2020-04-01T09:22:22Z
dc.date.available2020-04-01T09:22:22Z
dc.date.issued2019
dc.description.abstractMobile robot applications are increasing its usability in industries and services (examples: vacuum cleaning, painting and farming robots, among others). Some of the applications require that the robot moves in an environment between two positions while others require that the robot scans all the positions (Coverage Path Planning). Optimizing the traveled distance or the time to scan the path, should be done in order to reduce the costs. This paper addresses an optimization approach of the coverage path planning using Q-Learning algorithm. Comparison with other methods allows to validate the methodology.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPiardi, Luis; Lima, José; Pereira, Ana I.; Costa, Paulo (2019). Coverage path planning optimization based on Q-learning algorithm. In 16th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2018). Rhodes, Greecept_PT
dc.identifier.doi10.1063/1.5114220pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/21315
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherAIP Conference Proceedingspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleCoverage path planning optimization based on Q-learning algorithmpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceRhodes, Greecept_PT
oaire.citation.startPage220002pt_PT
oaire.citation.title16th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2018)pt_PT
oaire.citation.volume2133pt_PT
person.familyNamePiardi
person.familyNameLima
person.familyNamePereira
person.givenNameLuís
person.givenNameJosé
person.givenNameAna I.
person.identifierR-000-8GD
person.identifier.ciencia-idC51A-82DB-016F
person.identifier.ciencia-id6016-C902-86A9
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0000-0003-1627-8210
person.identifier.orcid0000-0001-7902-1207
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridL-3370-2014
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id55851941311
person.identifier.scopus-author-id15071961600
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication643e9664-ec9b-4b2f-b93c-6f3f8335fd61
relation.isAuthorOfPublicationd88c2b2a-efc2-48ef-b1fd-1145475e0055
relation.isAuthorOfPublicatione9981d62-2a2b-4fef-b75e-c2a14b0e7846
relation.isAuthorOfPublication.latestForDiscovery643e9664-ec9b-4b2f-b93c-6f3f8335fd61

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