Automated Guided Vehicle

Abstract: Automated Guided Vehicles (AGVs) are autonomous robots designed to navigate structured environments using sensory and control systems. This paper presents the design and development of a line-following AGV, incorporating infrared sensors, ultrasonic sensors, and a microcontroller-based control system. The AGV is capable of detecting and following a predefined path while dynamically adapting to obstacles and environmental variations. The study explores key technologies, including sensor fusion, path-planning algorithms, and proportional-integral-derivative (PID) control, to enhance navigation accuracy. The implementation of AGVs in industrial automation, logistics, and commercial applications highlights their efficiency in reducing manual labor and improving material handling processes. Despite challenges in unstructured environments, advancements in artificial intelligence, machine learning, and real-time path adjustment are enhancing AGV adaptability. This research contributes to the growing field of autonomous robotics by addressing AGV limitations and exploring future trends in automation and intelligent transportation systems