Incremental Semiparametric Inverse Dynamics Learning
dc.contributor.author | Camoriano, R | en |
dc.contributor.author | Traversaro, S | en |
dc.contributor.author | Rosasco, L | en |
dc.contributor.author | Metta, G | en |
dc.contributor.author | Nori, F | en |
dc.date.accessioned | 2017-06-23T15:40:09Z | |
dc.date.available | 2017-06-23T15:40:09Z | |
dc.date.issued | 2016-01-18 | en |
dc.identifier.uri | http://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.iso | en | en |
dc.subject | stat.ML | en |
dc.subject | stat.ML | en |
dc.subject | cs.LG | en |
dc.subject | cs.RO | en |
dc.title | Incremental Semiparametric Inverse Dynamics Learning | en |
dc.type | Journal Article | |
plymouth.author-url | http://arxiv.org/abs/1601.04549v1 | en |
plymouth.publisher-url | http://dx.doi.org/10.1109/ICRA.2016.7487177 | en |
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.embargoperiod | Not known | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en |
rioxxterms.type | Journal Article/Review | en |