000131458 001__ 131458 000131458 005__ 20240209155915.0 000131458 0247_ $$2doi$$a10.1109/ROBOT.2010.5509406 000131458 0248_ $$2sideral$$a132278 000131458 037__ $$aART-2010-132278 000131458 041__ $$aeng 000131458 100__ $$0(orcid)0000-0002-6741-844X$$aMartinez-Cantin, Ruben 000131458 245__ $$aBody schema acquisition through active learning 000131458 260__ $$c2010 000131458 5060_ $$aAccess copy available to the general public$$fUnrestricted 000131458 5203_ $$aWe present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using Recursive Least Squares (RLS) estimation, which outperforms gradient methods usually applied in the literature. In addiction, the method provides the required information to apply an active learning algorithm to find the optimal set of robot configurations and observations to improve the learning process. By selecting the most informative observations, the proposed method minimizes the required amount of data. We have developed an efficient version of the active learning algorithm to select the points in real-time. The algorithms have been tested and compared using both simulated environments and a real humanoid robot. 000131458 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000131458 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000131458 700__ $$aLopes, Manuel 000131458 700__ $$0(orcid)0000-0003-1183-349X$$aMontesano, Luis$$uUniversidad de Zaragoza 000131458 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf. 000131458 773__ $$g2010 (2010), [7 pp.]$$pIEEE Int. conf. robot. autom.$$tIEEE International Conference on Robotics and Automation$$x2152-4092 000131458 8564_ $$s325886$$uhttps://zaguan.unizar.es/record/131458/files/texto_completo.pdf$$yPostprint 000131458 8564_ $$s3010387$$uhttps://zaguan.unizar.es/record/131458/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000131458 909CO $$ooai:zaguan.unizar.es:131458$$particulos$$pdriver 000131458 951__ $$a2024-02-09-14:29:59 000131458 980__ $$aARTICLE