摘要
Some agriculture machinery like the transplanter,needs to operate by following the crop-free ridges.In order to improve working efficiency and quality,some autonomous navigation systems were developed and applied to ridge-following machinery.At present,agricultural navigation systems are mainly the satellite navigation system and the machine vision system.The satellite navigation system is difficult to apply to the machinery that needs to work by following the ridge because it cannot distinguish the shape of the navigated ridge and guide the machinery working along the ridge.In this study,697 cloudy ridge images and 235 sunny ridge images were taken in the field,and these images were used as the dataset.Moreover,a machine vision navigation method based on the color of ridges was proposed.Firstly,the regions of interest(ROI)in the ridge image were extracted according to the reaction time and the forward speed of the machine.Then,a gray reconstruction method was used to enlarge the color difference between the ridge and the furrow.The optimal threshold for the gray image segmenting was calculated real-timely by using the threshold segmentation method.Then,based on the contour detection method,the ridge contour which was not surrounded by holes was extracted.Finally,the approximate quadrilateral method was proposed to recognize the ridge center line as the navigation line.The method proposed in this study was verified by four types of ridges with different colors and textures.The experimental results showed that the recognition success rates of the light ridge,the dark ridge,the film-covered ridge,and the sunny ridge were 100%,97.5%,100%,and 98.7%,respectively.The recognition success rate of the proposed method was at least 8%higher than that of the existing ridge-furrow recognition methods.The results indicate that this method can effectively realize navigation line recognition.This method can provide technical support for the autonomous navigation of agricultural machinery,such as transplanters,seeders,etc.,operating on the ridge without crops.
基金
financially supported by the Construction of Technical System of Green Leafy Vegetable Industry in Shanghai-Development and application of key technologies for high-density transplanting of green leafy vegetables[Shanghai Agricultural Science and Production(2023)No.2]
the Jiangsu Provincial Key Research and Development Program(Grant No.BE2021342)
A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(No.PAPD-2023-87).
作者简介
Wei Liu,PhD,Assistant Researcher,research interest:control theory and technology of intelligent agricultural equipment,Email:Mario_liu@ujs.edu.cn;Jiaxin Liu,Master candidate,research interest:computer vision,Email:xianmoyisheng@163.com;Rencai Yue,Doctoral candidate,research interest:intelligent agricultural equipment design theory and technology,Email:YRC19920318@163.com;Tengfei Zhang,Doctoral candidate,research interest:intelligent agricultural equipment design theory and technology,Email:tengfeizhang2021@163.com;Mengjiao Yao,Master candidate,research interest:theory and application of intelligent agricultural equipment control,Email:2221916042@stmail.ujs.edu.cn;Jing Li,Master candidate,research interest:mechanical modeling and simulation.Email:18860874285@163.com;Corresponding author:Jianping Hu,PhD,Professor,research interest:intelligent agricultural equipment design theory and application.School of Agricultural Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,China.Tel:+86-13852984643,Email:hujp@ujs.edu.cn.
