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dc.contributor.authorCamoriano, Ren
dc.contributor.authorTraversaro, Sen
dc.contributor.authorRosasco, Len
dc.contributor.authorMetta, Gen
dc.contributor.authorNori, Fen
dc.date.accessioned2017-06-23T15:40:09Z
dc.date.available2017-06-23T15:40:09Z
dc.date.issued2016-01-18en
dc.identifier.urihttp://hdl.handle.net/10026.1/9529
dc.description.abstract

This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. This yields to an incremental semiparametric approach, leveraging the advantages of both the parametric and nonparametric models. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot.

en
dc.language.isoenen
dc.subjectstat.MLen
dc.subjectstat.MLen
dc.subjectcs.LGen
dc.subjectcs.ROen
dc.titleIncremental Semiparametric Inverse Dynamics Learningen
dc.typeJournal Article
plymouth.author-urlhttp://arxiv.org/abs/1601.04549v1en
plymouth.publisher-urlhttp://dx.doi.org/10.1109/ICRA.2016.7487177en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
dc.rights.embargoperiodNot knownen
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.typeJournal Article/Reviewen


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