Design of a Marker-Based Human–Robot Following Motion Control Strategy

Abstract

To address the challenges of jerky movements and poor tracking performance in outdoor environments for a following-type mobile robot, a novel marker-based human–machine following-motion control strategy is explored. This strategy decouples the control of linear velocity and angular velocity, handling them separately. First, in the design of linear-velocity control, using the identification of markers to determine the distance between the human and the robot, an enhanced virtual spring model is developed. This involves designing a weighted dynamic damping coefficient to address the rationality issues of the range and trend of the robot's following speed, thereby improving its smoothness and reducing the risk of target loss. Second, in the design of angular velocity control, a new concept of an ‘insensitive zone’ based on the offset of the marker's centre point is proposed, combined with a fuzzy controller to address the issue of robot jitter and enhance its resistance to interference. The experimental results indicate that the average variance in the human–robot distance is 1.037 m, whereas the average variance in the robot's linear velocity is 0.345 m/s. Due to the design of an insensitive region in parameter-adaptive fuzzy control, the average variance of angular velocity is only 0.031 rad/s. When the human–robot distance exhibits significant fluctuations, the fluctuations in both linear and angular velocities are comparatively small, allowing for stable and smooth following movements. This demonstrates the effectiveness of the motion control strategy designed in this study.