Adaptive torque estimation of robot joint with harmonic drive transmission

作者：Shi, Zhiguo; Li, Yuankai; Liu, Guangjun^*

来源：Mechanical Systems and Signal Processing, 2017, 96: 1-15.

DOI：10.1016/j.ymssp.2017.03.041

• Robot
• Joint torque estimation
• Harmonic drive transmission
• Kalman filter

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARICF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

• 出版日期2017-11
• 单位电子科技大学