基于YOLOv3算法的智能采茶机关键技术研究  

Research on key technologies of intelligent tea picking machine based on YOLOv3 algorithm

作　　者：马志艳[1,2] 李辉 杨光友[1,2] Ma Zhiyan;Li Hui;Yang Guangyou(Hubei University of Technology,Wuhan,430068,China;Hubei Province Agricultural Machinery Equipment Intelligent Engineering Technology Research Center,Wuhan,430068,China)

机构地区：[1]湖北工业大学,武汉市430068 [2]湖北省农机装备智能化工程技术研究中心,武汉市430068

出　　处：《中国农机化学报》2024年第4期199-204,236,共7页Journal of Chinese Agricultural Mechanization

基　　金：国家重点研发计划基金资助项目(2018YFD0701002-03)。

摘　　要：在复杂背景下精确识别茶叶嫩芽,是实现高端茶叶智能化采摘的关键技术之一。为实现高端茶叶机械化精准采摘,设计一台基于视觉的采茶样机,根据蛛式机械手采摘茶叶的路径规划,将机械手末端的移动坐标问题转换成静平台3个电机转角问题。针对YOLOv3算法进行改进,采用EfficientNet网络替代DarkNet-53网络进行特征提取,并利用目标函数GIOU优化损失函数。试验结果表明:改进的YOLOv3算法在茶叶嫩芽识别方面,其准确率达到86.53%,单张图像平均识别时间为53 ms,相比传统的YOLOv3算法,性能实现明显的提升,可以达到预期目标,满足机器采摘需求。Accurate identification of tea shoots in a complex background is one of the key technologies to realize the intelligent picking of high-end tea.In order to realize the mechanized and precise picking of high-end tea,this paper designs a visual-based tea picking prototype,which converts the moving coordinate problem at the end of the manipulator into the corner problem of three motors of the static platform according to the path planning of the spider manipulator picking tea.The YOLOv3 algorithm is improved,the EfficientNet network is used instead of the DarkNet-53 network for feature extraction,and the objective function GIOU is used to optimize the loss function.The experimental results show that the improved YOLOv3 algorithm has an accuracy rate of 86.53%in tea bud recognition,and the average recognition time for a single image is 53 ms.Compared with the traditional YOLOv3 algorithm,the performance has been significantly improved,which can achieve the expected goal and meet the needs of machine picking.

关 键 词：智能采茶 YOLOv3算法 蛛式机械手 机器学习 图像识别 

分 类 号：S225.99[农业科学—农业机械化工程] TP391.4[农业科学—农业工程]