Abstract
Automated Guided Vehicles (AGVs) have emerged as a crucial element of intelligent logistics and automated warehousing systems, with enormous potential for a variety of uses, thanks to the quick development of manufacturing and logistics. Given its advantages over other AGV navigation techniques—such as precise location, inexpensive hardware costs, and flexible routing—visual navigation has drawn more attention from researchers. This article examines the visual navigation of AGVs' motion control system within the framework of a smart manufacturing workshop. In this study, the AGV motion control system's general design is described. The algorithm for visual placement is designed and presented second. The study then looks into a fuzzy PID control self-tuning technique. AGV path-tracking error models are created, and MATLAB simulation is used to compare fuzzy PID and traditional PID models and show the advantages and disadvantages of each control technique. The motion control system's functional implementation is finally covered. The external device interface circuits are constructed, and the hardware platform is chosen using the high-performance multi-core video processor, TMS320DM8148. The software architecture of the motion control system is built, and the development of the visual positioning and path-tracking algorithms, along with other functional modules, is finished, all while utilizing the performance benefits of ARM and DSP processors.
Published Version
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