Torque estimation of robot joint with harmonic drive transmission using a redundant adaptive robust extended Kalman filter

A torque estimation method with adaptive robustness and optimality adjustment according to the load for modular and reconfigurable robot joint with harmonic drive transmission is proposed, on the basis of harmonic drive compliance model and redundant adaptive robust extended Kalman filter (RAREKF). The proposed approach can adapt torque estimation filtering optimality and robustness to the load variations by self-tuning the filtering gain and self-switching the filtering modes between optimal and robust. The redundant factor of RAREKF is designed as a function of the load to provide desirable tolerant capability to the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial sensor, and the results have demonstrated the effectiveness of the proposed torque estimation technique.