智能化农业装备学报（中英文）2025，Vol.6Issue(1)：41-50,10.DOI:10.12398/j.issn.2096-7217.2025.01.004
基于机器视觉与YOLO v5的裂纹蛋分拣机器人设计与试验
Design and experiment of cracked egg sorting robot based on machine vision and YOLO v5
摘要
Abstract
With the improvement of our national living standard,consumers have higher requirements for the quality of eggs.The detection of cracked eggs is an important step before packing eggs.In order to solve the problems of high labor intensity and heavy workload in manual sorting of cracked eggs,a cracked egg sorting robot based on machine vision and YOLO v5 was designed.Firstly,the rotation Angle of each steering gear of the manipulator was obtained by inverse kinematics and converted into PWM duty cycle to realize the control of the three-axis series manipulator.Secondly,a high-definition 120° wide-angle camera was used as the image acquisition core to quickly acquire the image information of egg surface and label the 1 000 images collected.YOLO v5 models with different gradient descent batch sizes were then trained respectively,among which the model with gradient descent batch size of 8 had the highest mAP with a value of 98.92%.Finally,the model was called on the main board of the upper computer of the mechanical arm,and after the recognition and judgment of normal eggs and cracked eggs,the sorting stroke of the mechanical arm was started.In addition,the end pickup mechanism of the egg sorting robot was a pneumatic suction cup,which was mounted on the mechanical arm to achieve non-destructive absorption of eggs.The test results showed that the robot can identify the two kinds of eggs with the accuracy of 93.33%and 99.17%respectively,the average success rate of sorting is 94.34%,and the average sorting rate was 7.55 s/egg,which basically met the requirements.The research results can provide technical support for the screening of cracked eggs,and provide solutions for crack detection and sorting of eggs,which has high practical significance.关键词
裂纹蛋品/YOLO v5/机器视觉/三轴机械臂/智能分拣Key words
cracked egg/YOLO v5/machine vision/three-axis mechanical arm/intelligent sorting分类
农业科技引用本文复制引用
蔡家一,刘世伟,单龙祥,刘勇,沈红怡,王巧华..基于机器视觉与YOLO v5的裂纹蛋分拣机器人设计与试验[J].智能化农业装备学报（中英文）,2025,6(1):41-50,10.基金项目
国家自然科学基金(52005203,52375542) （52005203,52375542）
中央高校基本科研业务费专项基金(2662022GXQD002) （2662022GXQD002）
电磁能技术全国重点实验室基金(61422172220507) （61422172220507）
湖北省大学生创新创业训练项目(S202310504167) National Natural Science Foundation of China(52005203,52375542) （S202310504167）
Fundamental Research Funds for the Central Universities(2662022GXQD002) （2662022GXQD002）
National Key Laboratory of Electromagnetic Energy Technology Fund(61422172220507) （61422172220507）
Provincial Innovation and Entrepreneurship Training Program for Undergraduate(S202310504167) （S202310504167）
