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CIRA
2007
IEEE

Local Online Support Vector Regression for Learning Control

9 years 10 months ago
Local Online Support Vector Regression for Learning Control
—Support vector regression (SVR) is a class of machine learning technique that has been successfully applied to low-level learning control in robotics. Because of the large amount of computation required by SVR, however, most studies have used a batch mode. Although a recently developed online form of SVR shows faster learning performance than batch SVR, the amount of computation required by online SVR prevent its use in real-time robot learning control, which requires short sampling time. Here, we present a novel method, Local online SVR for Learning control, or LoSVR, that extends online SVR with a windowing method. We demonstrate the performance of LoSVR in learning the inverse dynamics of both a simulated two-joint robot and a real one-link robot arm. Our results show that, in both cases, LoSVR can learn the inverse dynamics on-line faster and with a better accuracy than batch SVR.
Younggeun Choi, Shin-Young Cheong, Nicolas Schweig
Added 02 Jun 2010
Updated 02 Jun 2010
Type Conference
Year 2007
Where CIRA
Authors Younggeun Choi, Shin-Young Cheong, Nicolas Schweighofer
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