Kinematic calibration for industrial robots using articulated arm coordinate machines

Abstract

To improve the position accuracy of industrial robots, a novel kinematic model and calibration method using articulated arm coordinate machines (AACMM) is proposed in this paper. The end of the industrial robot is connected to the probe of an AACMM, thus forming a closed kinematic chain. The coordinate systems of the double arms were established, based on which the mapping of the joint angles and the position of the end were derived as well as the nominal value of the kinematic parameters of the industrial robot. A two-step search method was presented for kinematic parameter identification of the industrial robot. The identified kinematic parameters were used to compensate the errors of the nominal kinematic parameters in the controller of the industrial robot. Experiments were conducted to verify the calibration method, which show that after calibration, the average position errors of the industrial robot were decreased greatly.

Error identification and compensation of 1T2R parallel power head based on trajectory optimization and principal component analysis

“…In essence, error parameter identification is a parameter estimation problem in regression analysis. To realize the parameter identification of geometric error, one must construct a regression model using error measurement data and then use the identification algorithm to estimate the geometric error parameters of the corresponding mechanism (Gao et al , 2019). Therefore, selecting an appropriate measurement configuration and effective parameter identification algorithm is essential for ensuring better parameter identification and final error compensation.…”