A SURVEY ON LINE FOLLOWING ROBOT: NAVIGATION STRATEGIES, CONTROL ARCHITECTURES, AND APPLICATIONS IN SERVICE ROBOTICS

Abstract

Line-following robots (LFRs) are widely studied mobile robots that are increasingly used in factories, schools, and restaurants. This paper reviews several studies published between 2022 and 2026 to show how LFR sensors, steering systems, parts, and real-world uses have improved. The reviewed research covers a variety of methods, including simple rule-based programming, smooth PID control, and advanced AI models like CNNs and LSTMs. Additionally, the paper looks at real-world uses, such as IoT systems for restaurant delivery robots using the ESP32 chip, as well as virtual testing tracks built using the Unity computer simulation program. The results show that PID control gives the best mix of accuracy and speed for small computer chips, keeping steering errors as low as 1.18 cm and working 43% better than simple ON/OFF steering. Advanced AI methods are great at adapting to different tracks, but they need too much computer power and get confused easily when the room changes. IoT systems help these robots do more, like changing routes on the spot, taking wireless orders, and delivering items in real business settings. This review points out the main design choices, unsolved problems, and future ideas to help people build cheap and useful line-following robots.