Online Calibration for the 6-axis Force Sensor in the Wrist of Industrial Robot Based on Maximum Likelihood Estimation

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.