Neural-network-based human intention estimation for physical human-robot interaction

Abstract

To realize physical human-robot interaction, it is essential for the robot to understand the motion intention of its human partner. In this paper, human motion intention is defined as the desired trajectory in human limb model, of which the estimation is obtained based on neural network. The proposed method employs measured interaction force, position and velocity at the interaction point. The estimated human motion intention is integrated to the control design of the robot arm. The validity of the proposed method is verified through simulation.