Advanced Multi-Sensor Person-Following System on a Mobile Robot: Design, Construction and Measurements

A wide range of collaborative human-robot applications across diverse domains, encompassing manufacturing, industry, and social interactions, necessitate an autonomous robot to follow its human companion. However, the great degree of flexibility and unpredictability of human mobility makes the integration of multi-sensor measurements for human-following difficult. This paper addresses these challenges by demonstrating the design and implementation of a multi-sensor person-following system. On the one hand, a target tracking control method based on detection of center boxes is proposed. On the other hand, the positioning, navigation and tracking modules are integrated into the robot system. Exhaustive functional verification is conducted on an Ackermann-steering mobile robot, in which an embedded device is the core algorithm board. Notably, we discuss the degradation phenomenon of Light Detection and Ranging (LiDAR) odometry. The positioning error of our system is 2.42%, which is much smaller than other advanced methods. In indoor experiments, our system enables the robot to stably track the target at a distance of approximately 1.5 m. The effectiveness of the entire system is verified, demonstrating its advantage in real-time performance.