Automated guided vehicle systems using AprilTag and ant colony optimization ESP32-based

This paper presents the development of a prototype automated guided vehicle (AGV) using the ESP32 microcontroller, integrated with AprilTag fiducial markers for visual positioning and the Ant Colony Optimization (ACO). The aim is to design a low-cost AGV system capable of autonomous navigation in structured environments, such as container terminals. The AGV prototype employs an IP camera for real- time AprilTag detection, providing accurate localization data to the ESP32, which processes movement commands. The ACO algorithm is implemented to calculate the optimal route from the AGV’s starting position to the target destination while avoiding obstacles. Experimental results demonstrate reliable AprilTag detection with a success rate exceeding 95% under proper lighting conditions. The use of ACO reduced overall travel distance by approximately 15% compared to manual routing methods. The combination of AprilTag and ACO provides an effective, low-cost solution for enhancing AGV navigation performance in industrial settings.