Structural parameter identification for 6 DOF industrial robots. (December 2018)

• Record Type: Journal Article
• Authors: Gao, Guanbin; Sun, Guoqing; Na, Jing; Guo, Yu; Wu, Xing
• Is Part Of: Mechanical systems and signal processing. Volume 113(2018)
• Page Start: 145
• Page End: 155
• Publication Date: 2018-12
• Subjects: Industrial robot -- Parameter identification -- Movement uncertainty -- Kinematic model -- Redundant parameters; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2017.08.011
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Identification method is studied for industrial robots to improve the accuracy. A kinematic model of a 6 degree of freedom industrial robot is developed. The redundant parameters are determined and removed to improve efficacy and accuracy. We propose an iteration identification procedure based on the least square method. Reduction of movement uncertainties over 80% was obtained based on experiments. Abstract: To decrease the movement uncertainty of industrial robots, a parameter identification method based on the Denavit-Hartenberg (DH) model is presented in this paper, where the redundant parameters are particularly addressed in the identifier procedure. In order to be consistent with the kinematic model used in robot controllers, we use DH method to establish the kinematic model instead of the modified DH (MDH) method that was used in most identification schemes. The kinematic model of a 6 degree of freedom (DOF) industrial robot is first developed, which is linearized to obtain the parameter identification coefficient matrix. Further analysis shows that this matrix is not with full rank, which means some parameters in this matrix are linearly dependant. This fact makes the direct identification of unknown parameters in this matrix unfeasible. To solve this problem, singular value decomposition (SVD) is used to determine the redundant parameters, which are then removed from the matrix. Then, an alternative identification algorithm with a modified least-square scheme is suggested to estimate the structural parameters of the robot. For this purpose, an identification calculation scheme is designed to minimize the residual movement uncertainties. Experimental studies based on a 6 DOF industrial robot show that the proposed identification method, which detects and removes the redundant parameters, can greatly reduce the residual movement uncertainties and calculation costs. Thus, this newly proposed method can improve the movement accuracy of the industrial robot significantly.