Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/53738
DC FieldValueLanguage
dc.contributor.authorZamuda, Alesen_US
dc.contributor.authorHernández Sosa, José Danielen_US
dc.contributor.otherHernandez Sosa, Jose Daniel-
dc.contributor.otherZamuda, Ales-
dc.date.accessioned2019-02-04T18:03:08Z-
dc.date.available2019-02-04T18:03:08Z-
dc.date.issued2014en_US
dc.identifier.issn1568-4946en_US
dc.identifier.urihttp://hdl.handle.net/10553/53738-
dc.description.abstractThis paper presents an approach where differential evolution is applied to underwater glider path planning. The objective of a glider is to reach a target location and gather research data along its path by propelling itself underwater and returning periodically to the surface. The main hypothesis of this work is that gliders operational capabilities will benefit from improved path planning, especially when dealing with opportunistic short-term missions focused on the sampling of dynamic structures. To model a glider trajectory, we evolve a global underwater glider path based on the local kinematic simulation of an underwater glider, considering the daily and hourly sea currents predictions. The global path is represented by control points where the glider is expected to resurface for communication with a satellite and to receive further navigation instructions. Some well known differential evolution instance algorithms are then assessed and compared on 12 test scenarios using the proposed approach. Finally, a real case glider vessel mission was commanded using this approach.en_US
dc.languageengen_US
dc.publisher1568-4946-
dc.relation.ispartofApplied Soft Computing Journalen_US
dc.sourceApplied Soft Computing Journal [ISSN 1568-4946], v. 24, p. 95-108en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject331913 Vehículos submarinosen_US
dc.subject120326 Simulaciónen_US
dc.subject.otherAdapting Control Parameters
dc.subject.otherGlobal Optimization
dc.subject.otherAlgorithm
dc.subject.otherVehicles
dc.subject.otherTrajectories
dc.subject.otherAdaptation
dc.subject.otherStrategies
dc.subject.otherRobot
dc.titleDifferential evolution and underwater glider path planning applied to the short-term opportunistic sampling of dynamic mesoscale ocean structuresen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.asoc.2014.06.048
dc.identifier.scopus84905027298-
dc.identifier.isi000343138500010-
dcterms.isPartOfApplied Soft Computing-
dcterms.sourceApplied Soft Computing[ISSN 1568-4946],v. 24, p. 95-108-
dc.contributor.authorscopusid23975217400-
dc.contributor.authorscopusid50861566500-
dc.description.lastpage108-
dc.description.firstpage95-
dc.relation.volume24-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.identifier.wosWOS:000343138500010-
dc.contributor.daisngid1202017-
dc.contributor.daisngid10298839-
dc.identifier.investigatorRIDL-6203-2014-
dc.identifier.investigatorRIDNo ID-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Zamuda, A
dc.contributor.wosstandardWOS:Sosa, JDH
dc.date.coverdateEnero 2014
dc.identifier.ulpgces
dc.description.sjr1,696
dc.description.jcr2,81
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-3022-7698-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameHernández Sosa, José Daniel-
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