Compared with other commonly used equipment in material conveying, the activity area of AGV does not require fixed devices such as tracks and support frames, and is less affected by the site, roads, and space. Therefore, in automated logistics systems, the automation and flexibility can be fully reflected, achieving efficient, economical, and flexible unmanned production.

　　At present, the widely used AGV navigation methods in the market mainly include magnetic stripe navigation, QR code navigation, laser navigation, etc. However, the only truly mature and large-scale applications currently available are traditional magnetic stripes, QR codes, and emerging laser navigation.

　　Comparison of advantages and disadvantages of several mainstream navigation methods

　　1. Magnetic stripe navigation

　　Advantages: AGV positioning is precise, and the laying, changing, or expanding of paths is relatively easy compared to electromagnetic navigation, with lower costs

　　Disadvantages: The AGV car intelligently travels according to the magnetic strip, which cannot achieve the task of changing, and the magnetic strip is prone to damage, requiring regular maintenance

　　2. QR code navigation

　　Advantages: Accurate positioning, compact and flexible, easy to lay and change paths, easy to control communication, no interference to sound and light

　　Disadvantages: The path requires regular maintenance, and if the site is complex, the QR code needs to be replaced frequently

　　3. Laser SLAM navigation

　　Advantages: Flexible path planning, accurate positioning, flexible and varied driving paths, convenient construction, and the ability to use multiple environments

　　Disadvantage: Relatively high price

        With the development of SLAM algorithm, SLAM has become the preferred advanced navigation method for many AGV manufacturers. The SLAM method does not require other positioning facilities, and the form path is flexible and adaptable to various on-site environments. I believe that with the maturity of algorithms and the compression of hardware costs, SLAM will undoubtedly become the mainstream navigation method for AGVs in the future.

　　Multi sensor fusion is currently the trend in SLAM 3D stereo vision research. The Quick Intelligent Unmanned Forklift (DiNiu AGV) is equipped with SLAM technology, with a depth error of up to 10 centimeters. It is suitable for complex environments such as indoor and outdoor environments, darkness, etc., and can easily avoid obstacles, navigate, and drive automatically.