Interactive Bayesian identification of kinematic mechanisms

This paper addresses the problem of identifying mechanisms based on data gathered while interacting with them. We present a decision-theoretic formulation of this problem, using Bayesian filtering techniques to maintain a distributional estimate of the mechanism type and parameters. In order to redu...

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Bibliographic Details
Main Authors: Barragan, Patrick R. (Contributor), Lozano-Perez, Tomas (Contributor), Kaelbling, Leslie P. (Contributor)
Other Authors: Massachusetts Institute of Technology. Materials Processing Center (Contributor), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2016-01-06T16:21:52Z.
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