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Tracking Moving Optima Using Kalman-Based Predictions

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dc.affiliation.dptoUC3M. Departamento de Ingeniería de Sistemas y Automáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Laboratorio de Robótica (Robotics Lab)es
dc.contributor.authorRossi, Claudio
dc.contributor.authorAbderrahim Fichouche, Mohamed
dc.contributor.authorDíaz Cabrera, Julio César
dc.date.accessioned2010-12-20T16:10:34Z
dc.date.available2010-12-20T16:10:34Z
dc.date.issued2008-03
dc.description30 pages, 23 figures.
dc.description.abstractThe dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a time-changing fitness landscape. In this paper we compare different techniques for integrating motion information into an evolutionary algorithm, in the case it has to follow a time-changing optimum, under the assumption that the changes follow a nonrandom law. Such a law can be estimated in order to improve the optimum tracking capabilities of the algorithm. In particular, we will focus on first order dynamical laws to track moving objects. A vision-based tracking robotic application is used as testbed for experimental comparison.
dc.description.sponsorshipThe work of the first and second authors has been carried out under a "Ramón y Cajal" research fellowship from the Ministerio de Ciencia y Tecnología of Spain, and partially funded by projects DPI2005-04302 and DPI2006-03444.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationEvolutionary Computation, 2008, v. 16, n. 1, p. 1-30
dc.identifier.doi10.1162/evco.2008.16.1.1
dc.identifier.issn1063-6560
dc.identifier.urihttps://hdl.handle.net/10016/9848
dc.language.isoeng
dc.publisherMIT Press
dc.relation.publisherversionhttp://dx.doi.org/10.1162/evco.2008.16.1.1
dc.rights.accessRightsopen access
dc.subject.ecienciaRobótica e Informática Industrial
dc.subject.otherEvolutionary algorithms
dc.subject.otherVision-based tracking
dc.subject.otherDynamic optimization problem
dc.subject.otherTime-varying fitness function
dc.titleTracking Moving Optima Using Kalman-Based Predictions
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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