A Dual Closed-Loop Control Strategy for Human-Following Robots Respecting Social Space

Human following for mobile robots has emerged as a promising technique with widespread applications. To ensure psychological comfort while collaborating, coexisting, and interacting with humans, robots need to respect the social space of the target person. In this study, we propose a dual closed-loop human-following control strategy that combines model predictive control (MPC) and impedance control. The outer-loop MPC ensures precise control of the robot's posture while tracking the target person's velocity and direction to coordinate the motion between them. The inner-loop impedance controller is employed to regulate the robot's motion and interaction force with the target person, enabling the robot to maintain a respectful and comfortable distance from the target person. Concretely, the social interaction dynamics characteristics between the robot and the target person are described by human-robot interaction dynamics, which considers the rules of social space. Furthermore, an obstacle avoidance component constructed using behavioral dynamics is integrated into the impedance controller. Experimental results demonstrate the effectiveness of the proposed method in achieving human following and obstacle avoidance without intruding into the intimate zone of the target person.