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Recursive non-linear bayesian state estimation and model recognition with application to contouring tasks

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3 Author(s)
T. Lefebvre ; Katholieke Universiteit Leuven ; H. Bruyninckx ; J. De Schutter

This paper presents a new filter developed for exact nonlinear Bayesian state estimation and model recognition. The filter is able to deal (i) with static systems with any kind of nonlinear measurement function subject to additive Gaussian measurement uncertainty, and (ii) with a limited class of dynamic systems. Experimental position estimation and shape recognition results during a contouring task show the strength of the new nonlinear filtering approach.

Published in:

Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on  (Volume:5 )

Date of Conference:

April 26 2004-May 1 2004