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Title

Learning inverse kinematics: Reduced sampling through decomposition into virtual robots

AuthorsRuiz de Angulo, Vicente ; Torras, Carme
KeywordsFunction approximation
Learning inverse kinematics
Parametrized self-organizing maps (PSOMs)
Robot kinematics
Automatic theorem proving
Issue Date2008
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics 38(6): 1571-1577 (2008)
AbstractWe propose a technique to speed up the learning of the inverse kinematics of a robot manipulator by decomposing it into two or more virtual robot arms. Unlike previous decomposition approaches, this one does not place any requirement on the robot architecture and, thus, it is completely general. Parametrized Self-Organizing Maps (PSOM) are particularly adequate for this type of learning, and permit comparing results obtained directly and through the decomposition. Experimentation shows that time reductions of up to two orders of magnitude are easily attained.
DescriptionAn earlier version of this paper was presented at IWANN-2005.
Publisher version (URL)http://dx.doi.org/10.1109/TSMCB.2008.928232
URIhttp://hdl.handle.net/10261/30608
DOI10.1109/TSMCB.2008.928232
ISSN1083-4419
Appears in Collections:(IRII) Artículos
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