Application of the Weighted Least Squares Parameter Estimation Method to the Robot Calibration

[+] Author and Article Information
G. Zak, B. Benhabib, R. G. Fenton, I. Saban

Computer Integrated Manufacturing Laboratory, Department of Mechanical Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario, Canada M5S 1A4

J. Mech. Des 116(3), 890-893 (Sep 01, 1994) (4 pages) doi:10.1115/1.2919465 History: Received August 01, 1991; Online June 02, 2008


Significant attention has been paid recently to the topic of robot calibration. To improve the robot’s accuracy, various approaches to the measurement of the robot’s position and orientation (pose) and correction of its kinematic model have been proposed. Little attention, however, has been given to the method of estimation of the kinematic parameters from the measurement data. Typically, a least-squares solution method is used to estimate the corrections to the parameters of the model. In this paper, a method of kinematic parameter estimation is proposed where a standard least-squares estimation procedure is replaced by weighted least-squares. The weighting factors are calculated based on all the a priori available statistical information about the robot and the pose-measuring system. By giving greater weight to the measurements made where the standard deviation of the noise in the data is expected to be lower, a significant reduction in the error of the kinematic parameter estimates is made possible. The improvement in the calibration results was verified using a calibration simulation algorithm.

Copyright © 1994 by The American Society of Mechanical Engineers
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