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Guidance Line Identification for Agricultural Mobile Robot Based on Machine Vision

机译:基于机器视觉的农用移动机器人导航线识别

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Conventional navigation path detection algorithms based on machine vision are difficult to guarantee the guidance line accuracy, real-time and anti-interference. This paper carries out research on visual guidance line recognition for monocular vision agricultural mobile robot under natural environment. According to the characteristics of the crop rows in the image, a method of crop lines identification based on improved genetic algorithm was proposed. To approximate the trend of a crop row in the image to a line, two points from image bottom and top side were randomly selected to code as a chromosome. Through multiple genetic evolutions, the chromosome with the highest fitness value is selected as a crop center line and the guidance line can be obtained according to the two adjacent crop lines. Experimental results showed that, the guidance line recognition method based on improved genetic algorithm can quickly and accurately detect the navigation line. Furthermore, it not only has good fitness for different crops but also has nicer adaptability for different growth stages of crop in the farmland.
机译:传统的基于机器视觉的导航路径检测算法难以保证导航线的准确性,实时性和抗干扰性。本文对自然环境下单眼视觉农业移动机器人的视觉引导线识别进行了研究。针对图像中农作物行的特点,提出了一种基于改进遗传算法的农作物行识别方法。为了将图像中的作物行的趋势近似为一条线,从图像底部和顶部的两个点被随机选择以编码为染色体。通过多次遗传进化,选择适合度最高的染色体作为作物中心线,并根据两条相邻的作物线获得指导线。实验结果表明,基于改进遗传算法的导航线识别方法可以快速,准确地检测出导航线。此外,它不仅对不同作物具有良好的适应性,而且对农田中不同作物生长阶段的适应性也更好。

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