In order to improve the absolute positioning accuracy of the robot, a kinematic calibration method based on the Articulated Coordinate Measuring Machine(ACMM) is proposed in this paper. To identify the kinematic parameters, kinematic model based on D-H(Denavit-Hartenberg) and kinematic calibration model based on distance errors are established. Then, the ACMM is used as the measurement instrument in the calibration process. Finally, the kinematic parameters are identified by the Extended Kalman Filter(EKF) algorithm. Experiments have been carried out in this paper, the experimental results show that this method is suitable for the identification of robot kinematic parameters and can effectively improve the absolute positioning accuracy of the robot.
With the continuous improvement of equipment measurement accuracy and production efficiency requirements, calibration method with external reference standard can no longer meet the quality and efficiency requirements. In order to solve the online calibration problem and effectively improve the calibration efficiency of the Articulated Arm Coordinate Measuring Machines (AACMMs) in practical application, a self-calibration system of circular grating angle sensor which is applied to joints of the AACMMs was established. Based on the harmonic analysis of the angle measurement error, this paper deduces and analyzes the error suppression principle of the layout of the scanning heads on the calibration result, and establishes a non-uniform layout of the scanning heads to eliminate more and higher order harmonic errors. The simulation and test results show that the self-calibration method using this layout form of multiple reading heads can effectively reduce the measurement angle error without increasing the number of scanning heads, and improve the calibration efficiency and measurement accuracy of AACMMs.