Towards coordination in human-robot interaction by adaptation of robot's cost function

Abstract

In this work, we propose a method to adapt the robot's cost function, so that the human's control objective can be achieved with the help of the robot. We first employ game theory for linear systems and formulate the problem under study as a two-agent game. Then, we solve the problem of unknown human's cost function by developing an estimation method based on the measured interaction force. In particular, the human's target position and control gain are estimated, respectively. At last, the estimated cost function is used as the robot's cost function to generate the robot control. Eventually, human-robot coordination is achieved which indicates that the robot is able to interact with the human according to the human's control objective. Rigorous analysis and simulation studies are conducted to show the validity of the proposed method.