Online Estimation of 2D Human Arm Stiffness for Peg-in-Hole Tasks with Variable Impedance Control

摘要

This paper proposes an online estimation model for 2D arm stiffness in humans. The proposed model is based on recent physiological findings which suggest that: (1) joint stiffness is linearly related to the magnitude of joint torque and increases to compensate for environmental disturbances; and (2) the endpoint stiffness of the arm is proportional to grasp force. To validate the proposed model, perturbation experiments were conducted under different grasp forces. The model parameters were identified and the accuracy of the model was assessed. The results showed that the proposed model has advantages over previous models for estimating human arm endpoint stiffness, in the sense of simplicity and robustness. The proposed model was also used to design a variable stiffness controller for peg-in-hole tasks, demonstrating the potential of the model for human-robot collaboration.