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Volume 21 Issue 02 - Publication Date: 1 February 2002
 
Maximum Likelihood Identification of a Dynamic Robot Model : Implementation Issues
 
Martin M. Olsen The Maersk Mc-Kinney Moller Institute for Production Technology, SDU, Odense University, Campusvej 55, DK-5230 Odense Denmark , Jan Swevers and Walter Verdonck Division Production Engineering, Machine Design and Automation (PMA), Katholieke Universiteit Leuven, Celestijnenlaan 300B, B-3001 Hevelee, Belgium
 
This paper considers the practical implementation of a new maximum likelihood robot identification method, developed by Olsen and Petersen. In particular, the practical issue concerning the estimation of the joint velocities and accelerations from joint angle measurements, and its consequence on the parameter estimation and accu-racy, is considered. Simulation and experimental results on a KUKA IR 361 industrial robot are discussed, and compared with models obtained using a much simpler weighted least squares method.
 
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