Robot Assisted Training for Upper Limbs using Impedance Control based on Iterative Learning

This paper proposes an approach to improve robot assisted physical training subject to human uncertainties. This approach is based on impedance control which is used to regulate the dynamic relationship between the robot's position and contact force. Repetitive exercise is considered and impedance parameters are adapted in accordance with the human user to provide physical training as needed. Different from the existing approaches, the proposed one has the capacity to deal with time-length-varying cycles, which is a critical issue in physical training of human's upper limbs. By theoretical analysis and experimental results, we show that the approach can effectively learn the required robot's impedance parameters and improve the performance of physical training.