Maximum Likelihood Identification of a Dynamic Robot Model: Implementation Issues

Author:

Olsen Martin M.1,Swevers Jan2,Verdonck Walter2

Affiliation:

1. The Maersk Mc-Kinney Moller Institute for Production Technology SDU, Odense University Campusvej 55, DK-5230 Odense, Denmark

2. Division Production Engineering Machine Design and Automation (PMA) Katholieke Universiteit Leuven Celestijnenlaan 300 B, B-3001 Hevelee, Belgium

Abstract

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 accuracy, 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.

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software

Reference13 articles.

1. On Finding Exciting Trajectories for Identification Experiments Involving Systems with Nonlinear Dynamics

2. Estimation of Inertial Parameters of Manipulator Loads and Links

3. Fisette, P., Raucent, B., and Samin, J.C. 1993. Minimal dynamic characterization of tree-like multibody systems. In Computer-Aided Analysis of Rigid and Flexible Machan. Syst, NATO-Advanced Study Inst., Vol. II, Troia, Portugal, pp. 111-129.

4. Exciting Trajectories for the Identification of Base Inertial Parameters of Robots

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