Coordinate transformation learning of hand position feedback controller based on disturbance noise and feedback error signal

In order to grasp an object, we need to solve the inverse kinematics problem, i.e., the coordinate transformation from the visual coordinates to the joint angle vector coordinates of the arm. In human motion control, the learning of the hand position error feedback controller in the inverse kinematics solver is important. Although several models of coordinate transformation learning have been proposed, they suffer from a number of drawbacks. This paper proposes a novel model of the coordinate transformation learning of the human visual feedback controller by using disturbance noise and feedback error signal. The feasibility of the proposed model is illustrated using numerical simulations