A Human Decision-Making Behavior Model for Human-Robot Interaction in Multi-Robot Systems

In this paper, a novel human decision-making behavior model is proposed for human-robot interaction (HRI) for the control of multi-robot systems (MRS). The proposed human drift diffusion model (HDDM) combines the traditional drift diffusion model (DDM) and the null-space-based behavioral control (NSBC) method by introducing a data-processing station and a human cognitive system. In the HDDM, the evolution of human-decision information is computed. By using a threshold of such information to trigger human interaction, accurate human decision-making timing can be obtained. In addition, a cooperative controller is designed for robots to follow human instructions. Simulations under various scenarios show that by using the proposed HDDM and the controller, robots can complete human instructions more accurately comparing to traditional methods. An experiment using a group of quadrotors subject to external wind disturbances also demonstrate the effectiveness of the proposed HDDM in real-world uncertain environments.