Implementation of a ROS-Based LiDAR Target Following System for Smart Cart
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Abstract
As an important branch of robotics, intelligent vehicles have become a major research focus for improving the flexibility, adaptability, and autonomy of material handling in modern manufacturing facilities. Benefiting from advances in electromagnetic sensing and real-time signal processing, LiDAR-based perception technologies provide reliable environmental information for autonomous navigation and target tracking. This paper investigates the development of a LiDAR target-following intelligent vehicle system based on the Robot Operating System (ROS), with particular emphasis on the design and implementation of node communication and data transmission mechanisms within the ROS framework. The system accomplishes target-following tasks through multiple functionally distinct yet collaboratively operating ROS nodes, including a LiDAR driver node, a target detection node, a tracking node, and an Extended Kalman Filter (EKF)-based pose estimation node. Experimental results demonstrate stable and reliable target-tracking performance across diverse environments. The proposed system provides both a theoretical basis and a practical engineering solution for intelligent vehicles in autonomous navigation, medical applications, and automated material transport, while offering useful insights into electromagnetic perception and real-time sensing systems.
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