Fuzzy Logic-Based Arbitration for Shared Control in Continuous Human–Robot Collaboration

In human–robot collaboration (HRC) tasks, the role of the robot should be naturally and smoothly transitioned between the leader and the follower to guarantee task performance. To realize this, the arbitration of the shared control between the human and the robot needs to be properly designed to assign a degree of leadership to the robot. In this article, we propose a fuzzy logic-based arbitration rule with the help of Kalman filter. Based on this rule, the arbitration can be continuously regulated between zero and one according to the interaction force and the velocity of the human–robot collaboration system with human intention taken into account. Besides, the distance between the system and the obstacle and more generally the environment is also served as a fuzzy input, so that the possible interaction with the environment, e.g., obstacle avoidance, can be considered to ensure system safety. Since our proposed arbitration rule is based on a fuzzy logic, it endows the robot with the capability of continuous reasoning without an explicit form. The effectiveness of the proposed algorithm is evaluated by experiments.