Bayesian robot system identification with input and output noise

DOI10.1016/j.neunet.2010.08.011zbMath1217.93115OpenAlexW2149600126WikidataQ45962611 ScholiaQ45962611MaRDI QIDQ553249

Jo-Anne Ting, Aaron D'Souza, Stefan Schaal

Publication date: 26 July 2011

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2010.08.011

zbMATH Keywords

rigid body dynamicsparameter identificationhigh-dimensional regressionvariational Bayesian methodsinput noise

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Automated systems (robots, etc.) in control theory (93C85)

Uses Software

• VanHuffel
• BayesDA

Cites Work

• Bayesian learning for neural networks
• Modelling and control of robot manipulators.
• Gaussian elimination is not optimal
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