Online Calibration for the 6-axis Force Sensor in the Wrist of Industrial Robot Based on Maximum Likelihood Estimation
LIU Yunyi1,2, LI Xiangcheng1,2, HUANG Yue3, TANG Mingfu3, QIN Demao3, NONG Zhen3
1. School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China;
2. Guangxi Key Laboratory of Multimedia Communications and Network Technology, and the Key Laboratory of Multimedia Communications and Information Processing, Nanning 530004, China;
3. Sunrise Instruments Co., Ltd., Nanning 530007, China
刘运毅, 黎相成, 黄约, 唐明福, 秦德茂, 农真. 基于极大似然估计的工业机器人腕部6维力传感器在线标定[J]. 机器人, 2019, 41(2): 216-221,231.DOI: 10.13973/j.cnki.robot.180203.
LIU Yunyi, LI Xiangcheng, HUANG Yue, TANG Mingfu, QIN Demao, NONG Zhen. Online Calibration for the 6-axis Force Sensor in the Wrist of Industrial Robot Based on Maximum Likelihood Estimation. ROBOT, 2019, 41(2): 216-221,231. DOI: 10.13973/j.cnki.robot.180203.
Abstract:An online calibration algorithm based on the maximum likelihood estimation is proposed to monitor the forces on wrist tools in real-time for industrial robots. Firstly, the 6-axis force sensor is installed in the robot end tools to collect the force, the torque and the motion path of the robot tool in real-time. Then, the gravity coordinate of the tool, the installation angle of the robot, the zero offset of the force sensor and the gravity of the load are calculated according to the force relation of the system while considering the motion vibration interferences at different speeds. Finally, the experiments at different speeds between 10 mm/s~1000 mm/s are conducted, and the consistence of the solution results are analyzed and compared with the results of the least square method. The comparison results show that the maximum likelihood estimation method reduces the average standard deviation of the gravity center from 0.67 mm to 0.23 mm, the standard deviation of the force zeros from 0.73 N to 0.27 N, and the standard deviation of the torque zeros from 0.29 N.m to 0.05 N.m. The experimental results show that the maximum likelihood estimation method can effectively resist the interference caused by high-speed motion of the robot, and can be applied to real-time and online zero calibration of the robot in the case of high-speed motion.
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