Human-Robot Collision Detection and Identification Based on Wrist and Base Force/Torque Sensors

Abstract

In this paper, a collision detection and identification method of a manipulator, using base and wrist force/torque sensors, is presented. An impact model is used to simulate the interaction between the manipulator and the human or environment. A neural network approach and a model based method are developed to detect the collision forces and disturbance torques on the joints of the manipulator. The experimental results illustrate the validity of the developed collision detection and identification scheme.