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dc.contributor.authorUlbrich, Stefan
dc.contributor.authorRuiz de Angulo García, Vicente
dc.contributor.authorTorras, Carme
dc.contributor.authorAsfour, Tamim
dc.contributor.authorDillmann, Rudiger
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2013-01-14T18:06:08Z
dc.date.available2013-01-14T18:06:08Z
dc.date.created2012
dc.date.issued2012
dc.identifier.citationUlbrich, S. [et al.]. Kinematic Bézier maps. "IEEE transactions on systems man and cybernetics Part B-Cybernetics", 2012, vol. 42, núm. 4, p. 1215-1230.
dc.identifier.issn1083-4419
dc.identifier.urihttp://hdl.handle.net/2117/17357
dc.description.abstractThe kinematics of a robot with many degrees of freedom is a very complex function. Learning this function for a large workspace with a good precision requires a huge number of training samples, i.e., robot movements. In this paper, we introduce the Kinematic Bézier Map (KB-Map), a parameterizable model without the generality of other systems but whose structure readily incorporates some of the geometric constraints of a kinematic function. In this way, the number of training samples required is drastically reduced. Moreover, the simplicity of the model reduces learning to solving a linear least squares problem. Systematic experiments have been carried out showing the excellent interpolation and extrapolation capabilities of KB-Maps and their relatively low sensitivity to noise.
dc.format.extent16 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshArtificial intelligence
dc.subject.otherlearning (artificial intelligence) robot kinematics robots PARAULES AUTOR: learning
dc.subject.otherrobot kinematics
dc.subject.otherhumanoid robots
dc.titleKinematic Bézier maps
dc.typeArticle
dc.subject.lemacIntel·ligència artificial
dc.contributor.groupUniversitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
dc.identifier.doi10.1109/TSMCB.2012.2188507
dc.subject.inspecClassificació INSPEC::Cybernetics::Artificial intelligence
dc.relation.publisherversionhttp://dx.doi.org/10.1109/TSMCB.2012.2188507
dc.rights.accessOpen Access
drac.iddocument10837212
dc.description.versionPreprint
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/269959/EU/Intelligent observation and execution of Actions and manipulations/INTELLACT
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/215821/EU/Emergence of Cognitive Grasping through Emulation, Introspection, and Surprise/GRASP
upcommons.citation.authorUlbrich, S.; Ruiz De Angulo, V.; Torras, C.; Asfour, T.; Dillmann, R.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameIEEE transactions on systems man and cybernetics Part B-Cybernetics
upcommons.citation.volume42
upcommons.citation.number4
upcommons.citation.startingPage1215
upcommons.citation.endingPage1230


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