Body schema acquisition through active learning

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dc.contributor.author Martínez-Cantín, Rubén
dc.contributor.author Lopes, Manuel
dc.contributor.author Montesano, Luis
dc.date.accessioned 2012-03-21T17:48:43Z
dc.date.available 2012-03-21T17:48:43Z
dc.date.issued 2010-07
dc.identifier.bibliographicCitation 2010 IEEE International Conference on Robotics and Automation (ICRA'10) (pp. 1860-1866). IEEE, 2010
dc.identifier.isbn 978-1-4244-5040-4 (online)
dc.identifier.isbn 978-1-4244-5038-1 (print)
dc.identifier.issn 1050-4729
dc.identifier.uri http://hdl.handle.net/10016/13914
dc.description Proceedings of: 2010 IEEE International Conference on Robotics and Automation (ICRA'10), May 3-8, 2010, Anchorage (Alaska, USA)
dc.description.abstract We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using Recursive Least Squares (RLS) estimation, which outperforms gradient methods usually applied in the literature. In addiction, the method provides the required information to apply an active learning algorithm to find the optimal set of robot configurations and observations to improve the learning process. By selecting the most informative observations, the proposed method minimizes the required amount of data. We have developed an efficient version of the active learning algorithm to select the points in real-time. The algorithms have been tested and compared using both simulated environments and a real humanoid robot.
dc.description.sponsorship European Community's Seventh Framework Program
dc.description.sponsorship This work was supported in part by the FCT Programa Operacional Sociedade de Informaçao (POSC) in the frame of QCA III, PTDC/EEA-ACR/70174/2006 project and SFRH/BPD/48857/2008 grant; and in part by the EU Project Handle (EU-FP7-ICT-231640).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © IEEE
dc.title Body schema acquisition through active learning
dc.type conferenceObject
dc.relation.publisherversion http://dx.doi.org/10.1109/ROBOT.2010.5509406
dc.subject.eciencia Robótica e Informática Industrial
dc.identifier.doi 10.1109/ROBOT.2010.5509406
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/231640
dc.type.version acceptedVersion
dc.relation.eventdate May 3-8, 2010
dc.relation.eventplace Anchorage (Alaska, USA)
dc.relation.eventtitle 2010 IEEE International Conference on Robotics and Automation (ICRA'10)
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 1860
dc.identifier.publicationlastpage 1866
dc.identifier.publicationtitle 2010 IEEE International Conference on Robotics and Automation (ICRA'10)
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