Authors

Abstract

With the development of information technology, precision agriculture has also ushered in new development prospects. The use of farm robots to accurately identify the navigation path is of great significance for achieving accurate positioning of agriculture. In this study, when analysing the extraction algorithm of farm robot visual navigation based on dark primary colours, a method for pre-processing and edge detection of farmland images based on dark primary colours is proposed. At the same time, the least square method of linear fitting is used for the navigation path of agricultural robot, and then the fitting program is executed. On this basis, combined with the actual situation of outdoor farming and greenhouse cultivation of crops, the effectiveness of the robotic visual navigation extraction algorithm was verified. The research results show that for any form of farmland cultivation, image extraction technology based on dark primary colours can effectively distinguish between soil and crops, and the visual navigation path of farm robots fitted with least squares is basically linear, which is consistent with the commonly used crops for farm planting. The legal route is basically the same, and then the effectiveness of the extraction algorithm is verified. It is hoped that this study will provide a certain reference and reference for the analysis of the field navigation robot visual navigation extraction algorithm based on dark primary colours.

Abstract in Chinese

随着信息技术的发展，精准农业也迎来了新的发展前景。使用农业机器人准确识别导航路径对实现农业的精确定位具有重要意义。本文在分析基于深色原色的农用机器人视觉导航提取算法的基础上，提出了一种基于深色原色的农田图像预处理和边缘检测方法。同时，线性拟合的最小二乘方法用于农用机器人的导航路径。执行拟合。在此基础上，结合野外耕作和温室大棚栽培的实际情况，验证了机器人视觉导航提取算法的有效性。研究结果表明，对于任何形式的农田耕作，基于深色原色的图像提取技术都可以有效地区分土壤和农作物，配备最小二乘法的农场机器人的视觉导航路径基本上是线性的，这与通常的做法是一致的。用于农作物种植的农作物。合法路径基本相同，然后验证了提取算法的有效性。希望这项研究为基于深色原色的野外导航机器人视觉导航提取算法的分析提供一定的参考和借鉴。