TY - GEN
T1 - Kinematic Parameter Calibration Method of Light Weight Robots Based on Sequence Quadratic Programming Algorithm
AU - Min, Kang
AU - Ni, Fenglei
AU - Shu, Xin
AU - Ji, Zhu
AU - Liu, Hong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Kinematic parameter calibration can improve the absolute positioning accuracy of the robot tool center point (TCP). However, the current least-squares (LS) iterative method for calibration is sensitive to noise and ineffective when the Jacobian matrix is close to singular. In addition, the robot kinematic parameter errors cannot be directly compensated because its structure needs to satisfy Pieper's criterion. Thus, a kinematic parameter calibration based on sequence quadratic programming (SQP) algorithm is proposed to solve the above two issues. Firstly, the kinematics and its error model of TCP positions are established. Then, the kinematic parameter errors are identified by SQP algorithm. Finally, the identified kinematic parameter errors are converted into joint angle errors for error compensation. The simulations and experiments are carried out on the self-developed light weight robot. Simulation results show that the proposed calibration method is insensitive to noise. Experimental results reveal that mean positioning accuracy has increased 88.17% and 63.58% than that of the before calibration in sampling and verification regions, respectively.
AB - Kinematic parameter calibration can improve the absolute positioning accuracy of the robot tool center point (TCP). However, the current least-squares (LS) iterative method for calibration is sensitive to noise and ineffective when the Jacobian matrix is close to singular. In addition, the robot kinematic parameter errors cannot be directly compensated because its structure needs to satisfy Pieper's criterion. Thus, a kinematic parameter calibration based on sequence quadratic programming (SQP) algorithm is proposed to solve the above two issues. Firstly, the kinematics and its error model of TCP positions are established. Then, the kinematic parameter errors are identified by SQP algorithm. Finally, the identified kinematic parameter errors are converted into joint angle errors for error compensation. The simulations and experiments are carried out on the self-developed light weight robot. Simulation results show that the proposed calibration method is insensitive to noise. Experimental results reveal that mean positioning accuracy has increased 88.17% and 63.58% than that of the before calibration in sampling and verification regions, respectively.
UR - https://www.scopus.com/pages/publications/85141204190
U2 - 10.1109/CYBER55403.2022.9907503
DO - 10.1109/CYBER55403.2022.9907503
M3 - 会议稿件
AN - SCOPUS:85141204190
T3 - 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022
SP - 259
EP - 264
BT - 2022 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022
Y2 - 27 July 2022 through 31 July 2022
ER -