Autonomous Navigation System for Library Service Robot Based on Unitree Go2 Edu
2026-06-02 • Robotics
Robotics
AI summaryⓘ
The authors developed a robot system that helps a four-legged robot move quietly and safely in libraries, avoiding obstacles like chairs and bags. They used special sensors and software to help the robot map the library, know where it is, and plan paths around things. The robot was tested in real library settings and was very successful at navigating both when the library was empty and when people were around. The authors also checked how accurate the robot's map was and found it to be quite precise.
ROS 2quadruped robot4D LiDARdepth cameraIMUSLAMAMCLEKFNav2path planning
Authors
Aoduo Li, Haoran Lv, Bingquan Ou, Jianfeng Li, Yingdong Li, Zimeng Li
Abstract
Libraries require autonomous robots to move quietly through narrow aisles while remaining safe around readers, chairs, bags, and carts. This paper presents a ROS 2 navigation system for a Unitree Go2 Edu quadruped equipped with a 4D LiDAR, a front depth camera, and an IMU. Rather than assuming the library is rough terrain, we target the practical mobility discontinuities of real deployments, including floor transitions, temporary clutter, and partially blocked passages where low-clearance wheeled platforms are less tolerant. RTAB-Map is used for visual-LiDAR SLAM, AMCL and EKF-based sensor fusion provide localization, and a Nav2 stack with A* and DWA supports planning and local avoidance. In a real library, the system achieves 100%, 96%, and 88% success rates in static, low-density dynamic, and high-density dynamic scenes, while map validation against surveyed control distances yields a mean metric error of 3.7 cm.