Decoupling of Kinematic Parameter Identification for Articulated Arm Coordinate Measuring Machines

• Main Authors: Guanbin Gao, Jun Zhao, Jing Na
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Parameter identification; kinematics; decoupling; least squares method
• Online Access: https://ieeexplore.ieee.org/document/8454440/

Kinematic parameter identification is an effective method to improve the accuracy of articulated arm coordinate measuring machines (AACMMs). However, not all the parameters of AACMM can be identified accurately due to the influence of strong non-linear couplings. In this paper, we study the coupling relationship and then propose a decoupling method of AACMM parameters, which could retain the effectiveness of decoupling on parameter identification. The kinematic model of AACMM is established based on the DH method. The coupling relationship between kinematic parameters is obtained via the singular value decomposition. Then, the identification and compensation models are established. The least squares method is used to solve the identification model, and the kinematic parameters of the AACMM are identified. Simulation and experimental studies are carried out to verify the effectiveness of the proposed decoupling and identification methods. The results show that after decoupling, the accuracy of identification of the related coupling kinematic parameters is improved and the computational efficiency of identification is increased greatly.