Research on Guide Line Identification and Lateral Motion Control of AGV in Complex Environments

Abstract

During actual operations, Automatic Guided Vehicles (AGV) will inevitably encounter the phenomena of overexposure or shadowy areas, and unclear or even damaged guide wires, which interfere with the identification of guide wires. Therefore, this paper aims to solve the shortcomings of existing technology at the software level. Firstly, a Fast Guide Filter (FGF) is adopted with the two-dimensional gamma function with variable parameters, and an image preprocessing algorithm in a complex illumination environment is designed to get rid of the interference of illumination. Secondly, an ant colony edge detection algorithm is proposed, and the guide wire is accurately extracted by secondary screening combined with the guide wire characteristics; A variable universe Fuzzy Sliding Mode Control (FSMC) algorithm is designed as a lateral motion control method to realize the accurate tracking of AGV. Finally, the experimental platform is used to comprehensively verify the series of algorithms designed in this paper. The experimental results show that the maximum deviation can be limited to 1.2 mm, and the variance of the deviation is less than 0.2688 mm2.