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Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning

dc.contributor.authorSalgado, Paulo
dc.contributor.authorIgrejas, Getúlio
dc.contributor.authorAfonso, Paulo Alexandre Ferreira
dc.date.accessioned2020-04-27T09:14:53Z
dc.date.available2020-04-27T09:14:53Z
dc.date.issued2017
dc.description.abstractThis paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generation gives us continuous, smooth and optimized path trajectories. Simulation and experimental results demonstrate the effectiveness of the proposed method.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSalgado, Paulo; Igrejas, Getúlio; Afonso, Paulo (2017). Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning. In 2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES). Larnaca, Chiprept_PT
dc.identifier.doi10.1109/INES.2017.8118542pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/21819
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleHybrid PSO-cubic spline for autonomous robots optimal trajectory planningpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceLarnaca, Chiprept_PT
oaire.citation.endPage000136pt_PT
oaire.citation.startPage000131pt_PT
oaire.citation.title2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)pt_PT
person.familyNameIgrejas
person.givenNameGetúlio
person.identifier.orcid0000-0002-6820-8858
person.identifier.ridM-8571-2013
person.identifier.scopus-author-id47761255900
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isAuthorOfPublication.latestForDiscoveryab4092ec-d1b1-4fe0-b65a-efba1310fd5a

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