131458 20240209155915.0 doi 10.1109/ROBOT.2010.5509406 sideral 132278 ART-2010-132278 eng Martinez-Cantin, Ruben (orcid)0000-0002-6741-844X Body schema acquisition through active learning 2010 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. Access copy available to the general public Unrestricted info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Lopes, Manuel Montesano, Luis Universidad de Zaragoza (orcid)0000-0003-1183-349X 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 2010 (2010), [7 pp.] IEEE Int. conf. robot. autom. IEEE International Conference on Robotics and Automation 2152-4092 325886 http://zaguan.unizar.es/record/131458/files/texto_completo.pdf Postprint 3010387 http://zaguan.unizar.es/record/131458/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:131458 articulos driver 2024-02-09-14:29:59 ARTICLE