浙江农业学报2025，Vol.37Issue(3)：701-711,11.DOI:10.3969/j.issn.1004-1524.20240167
基于实例分割的叶菜垄间导航线提取算法研究
Study on navigation line extraction algorithm for leaf vegetable ridges based on instance seg-mentations
摘要
Abstract
To improve the mobile navigation accuracy of field management equipment for leafy vegetables under facil-ity ridge cultivation mode,a deep learning based algorithm for extracting navigation lines between leafy vegetable rid-ges was proposed.Firstly,the model was trained on the navigation path dataset between leafy vegetable ridges.An improved YOLOv5s-Seg convolutional neural network was used to extract feature points from greenhouse operation road images,and the navigation line was generated through least squares fitting.In the experiment,a series of im-provements were made to the internal structure of the model,which improved the accuracy and computational speed of the algorithm.By collecting 800 images of the growth of leafy vegetables under ridge planting mode,and expan-ding the total number of datasets to four times of the original through data augmentation,the overall segmentation av-erage precision was 99.50％on an independent test set composed of 320 images.The precision of images were 94.33％,97.77％and 96.23％respectively at germination stage,seedling stage,and formation stage.The average deviation between the fitted navigation line and the manually observed navigation line was 5.60 cm.The results showed that the navigation algorithm could meet the navigation requirements of intelligent management of mobile e-quipment for leafy vegetables in the ridge planting mode within the facility.关键词
设施温室/垄作模式/实例分割/深度学习/导航线Key words
facility greenhouse/ridge planting mode/instance segmentation/deep learning/navigation line分类
农业科技引用本文复制引用
郑航,冯昊栋,薛向磊,叶云翔,于健麟,俞国红..基于实例分割的叶菜垄间导航线提取算法研究[J].浙江农业学报,2025,37(3):701-711,11.基金项目
浙江省"领雁"科技计划项目(2023C02053) （2023C02053）
浙江省农业科学院成果推广项目(2023R30CB001) （2023R30CB001）
