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Guidance Line Identification for Agricultural Mobile Robot Based on Machine Vision

机译:基于机器视觉的农业移动机器人指导线识别

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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:常规导航路径检测算法基于机器视觉难以保证引导线精度,实时和抗干扰。本文对自然环境下的单眼视觉农业移动机器人进行了视觉指导线路识别研究。根据图像中作物行的特征,提出了一种基于改进遗传算法的作物线识别方法。为了将图像中的作物行的趋势近似到一行,从图像底部和顶侧的两个点随机选择为代码作为染色体。通过多种遗传演进,选择具有最高的适应值的染色体作为作物中心线,并且引导线可以根据两个相邻的作物线获得。实验结果表明,基于改进的遗传算法的引导线识别方法可以快速准确地检测导航线。此外,它不仅具有良好的不同作物的健身,而且对农田的不同生长阶段也具有更好的适应性。

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