An intelligent Interactive Learning and Adaptation framework for robot-based vocational training

Abstract

In this paper, we propose an Interactive Learning and Adaptation framework for Human-Robot Interaction in a vocational setting. We show how Interactive Reinforcement Learning (RL) techniques can be applied to such HRI applications in order to promote effective interaction. We present the framework by showing two different use cases in a vocational setting. In the first use case, the robot acts as a trainer, assisting the user while the user is solving the Towers of Hanoi problem. In the second use case, a robot and a human operator collaborate towards solving a synergistic construction or assembly task. We show how RL is used in the proposed framework and discuss its effectiveness in the two different vocational use cases, the Robot Assisted Training and the Human-Robot Collaboration case.