Tracking control properties of human-robotic systems based on impedance control

Human-robotic systems that include interaction between human operators and robots should be designed with careful consideration for the dynamic property and control ability of a human operator. This paper performs manual tracking control tests on a human-robotic system using an impedance-controlled robot, and investigates control characteristics of a human operator according to the robot impedance properties. Experimental results demonstrate that humans try to maintain dynamic properties of an overall system as constant as possible by adjusting their own impedance properties. Then, a new training system using a neural network for operating a human-robotic system is constructed on the basis of the experimental findings in the human tracking control properties.