APPLICATION OF THE WEIGHTED LEAST-SQUARES PARAMETER-ESTIMATION METHODTO THE ROBOT CALIBRATION

Significant attention has been paid recently to the topic of robot cal ibration. To improve the robot's accuracy, various approaches to the m easurement of the robot's position and orientation (pose) and correcti on of its kinematic model have been proposed. Little attention, howeve r, has been given to the method of estimation of the kinematic paramet ers from the measurement data. Typically, a least-squares solution met hod is used to estimate the corrections to the parameters of the model . In this paper, a method of kinematic parameter estimation is propose d where a standard least-squares estimation procedure is replaced by w eighted least-squares. The weighting factors are calculated based on a ll the a priori available statistical information about the robot and the pose-measuring system. By giving greater weight to the measurement s made where the standard deviation of the noise in the data is expect ed to be lower, a significant reduction in the error of the kinematic parameter estimates is made possible. The improvement in the calibrati on results was verified using a calibration simulation algorithm.