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Fuzzy-based adaptive motion control of a virtual iCub robot in human-robot-interaction

In this paper, in order to combine intelligence of human operator and automatic function of the robot, we design a control scheme for the bimanual robot manipulation, in which the leading robot arm is directly manipulated by a human operator through a haptic device and the following robot arm will automatically adjust its motion to match the operator's motion. In this paper, we propose a fuzzy-based adaptive feedforward compensation controller and apply it into the robot control. According to the comparison results in the simulated experiment, we conclude that the fuzzy-adaptive controller performs better than the non-fuzzy controller, although they can both complete the specified task by tracking the leading robot arm controlled by the human operator. The techniques developed in this paper could be very useful for our future study on adaptation in human-robot interaction in improving the reliability, safety and intelligence.