Show simple item record

dc.creatorAgustín Martín, Albaes_ES
dc.creatorOlivares, Albertoes_ES
dc.creatorStaffetti, Ernestoes_ES
dc.date.accessioned2023-09-11T09:33:19Z
dc.date.available2023-09-11T09:33:19Z
dc.date.issued2016
dc.identifier.citationAgustín, A., Olivares, A., Staffetti, E. (2016) Using biased randomization for trajectory optimization in robotic manipulators. En León, R., Muñoz-Torres, M. J., Moneva J. M. (Eds.), Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016: proceedings (pp. 145-154). Springer. https://doi.org/10.1007/978-3-319-40506-3_15.en
dc.identifier.isbn978-3-319-40505-6
dc.identifier.urihttps://hdl.handle.net/2454/46258
dc.description.abstractWe study the problem of optimization of trajectories for a robotic manipulator, with two degrees of freedom, which is constrained to pass through a set of waypoints in the workspace. The aim is to determine the optimal sequence of points and continuous optimal system trajectory. The actual formulation involves an optimal control problem of a dynamic system within integer variables that model the waypoints constrains. The nature of this problem, highly nonlinear and combinatorial, makes it particularly difficult to solve. The proposed method combines a meta-heuristic algorithm to determine the promising sequence of discrete points with a collocation technique to optimize the continuous path of the system. This method does not guarantee the global optimum, but can solve instances of dozens of points in reasonable computation time.en
dc.description.sponsorshipThis work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Catalan Government (2014-CTP-00001).en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringeren
dc.relation.ispartofLeón, R.; Muñoz-Torres, M. J.; Moneva, J. M. (Eds.). Modeling and Simulation in Engineering, Economics and Management: International Conference, MS 2016: proceedings. Berlín: Springer; 2016. p.145-154 978-3-319-40505-6en
dc.rights© 2016 Springer International Publishing Switzerlanden
dc.subjectRoboticsen
dc.subjectOptimal controlen
dc.subjectMotion planningen
dc.subjectMeta-heuristicsen
dc.subjectBiased-randomizationen
dc.titleUsing biased randomization for trajectory optimization in robotic manipulatorsen
dc.typeContribución a congreso / Biltzarrerako ekarpenaes
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.date.updated2023-09-11T08:31:21Z
dc.contributor.departmentEstadística e Investigación Operativaes_ES
dc.contributor.departmentEstatistika eta Ikerketa Operatiboaeu
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.doi10.1007/978-3-319-40506-3_15
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TRA2013-48180-C3-1-P/ES/en
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TRA2015-71883-REDT/ES/en
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-319-40506-3_15
dc.type.versionVersión aceptada / Onetsi den bertsioaes
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record


El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
Logo MinisterioLogo Fecyt