Iterative learning-based path control for robot-assisted upper-limb rehabilitation

Abstract In robot-assisted rehabilitation, the performance of robotic assistance is dependent on human user’s dynamics, which are subject to uncertainties. order enhance rehabilitation and in particular provide a constant level assistance, we separate task space into two subspaces where combined scheme adaptive impedance control trajectory learning developed. Human movement speed can vary from person it cannot be predefined for robot. Therefore, direction movement, an iterative approach developed update robot reference according achieve desired interaction force between user. normal trajectory, human’s unintentional may deteriorate tracking performance. adaptation method utilized compensate unknown prevent user drifting away updated trajectory. The proposed was tested experiments that emulated three upper-limb modes: zero force, assistive resistive. Experimental results showed could achieved, despite uncertain dynamics.