Inverse Dynamics of Human Passive Motion Based on Iterative Learning Control

Abstract

Estimation of joint torque is an important objective in the analyses of human motion. In particular, many applications seek to discern torque during a desired human motion, which is equivalent to solving the inverse dynamics. The computed torque method is a conventional means of calculating inverse dynamics. The obtained torque, however, invariably includes errors resulting from inexact inertial and viscoelastic parameters. This paper presents a method for solving the inverse dynamics of a human arm passively during tracking. To achieve precise human motion tracking, iterative learning control is used for motion generation. Some experiments that target a human arm are executed to validate the proposed method.