Automated guided vehicles (AGVs) are becoming increasingly necessary for modern manufacturing plants to boost efficiency and profitability. With businesses rushing to automate their operations using AI and robotics, AGVs are the cornerstone of today's strategic initiatives to beat the competition. AGV types include Automated Guided Carts (AGCs), Forklift AGVs, Unit-load AGVs, Towing AGVs, Heavy Burden Carriers, Hybrid AGVs, and Autonomous Mobile Robots (AMRs). AGVs consist of a navigation system, a steering mechanism, a traffic control system, and a battery charging method. They are used to transport raw materials, finished goods, and work-in-process, as well as handle pallets, trailers, and rolls. The technology offers several benefits, including reduced labor costs, enhanced workplace safety, speed, and accuracy. However, AGVs also have challenges, such as being unsuitable for non-repetitive tasks, requiring regular maintenance to ensure sensor accuracy, and needing sufficient warehouse space. Computer vision can enhance AGV operations by providing flexible navigation, precision, better safety, defect detection, and data-driven decision-making capabilities.