A Human Tracking System for the Rocker-Bogie Mobile Robot Utilizing the YOLOv8 Network

Abstract

Nowadays, mobile robots are applied in a variety of fields to assist humans in doing complicated work such as disaster situations, rescue missions, security and tracking systems, military campaigns, and planetary discovery. When performing these tasks, climbing uneven terrain and detecting targets are two of the most important requirements for the mobile robot. The Rocker-Bogie design developed by the NASA Mars Exploration Rover (MER) Project has become a proven mobility application during the last decade. The stability and obstacle-climbing capability of this model are evaluated as suitable choices for mobile robots. In this paper, a prototype of a Rocker-Bogie mobile robot featuring a human tracking system is proposed. To be more detailed, the modified YOLOv8 network is designed to detect humans and corresponds to the operation of the robot in real time. The computer then computes the associated speeds of the robot according to the detection targets. The velocity signal is transmitted back to the robot, which then executes the appropriate maneuver. The experimental result demonstrates an average success rate of 91% for tracking missions on an actual mobile robot platform under different scenarios.