基于YOLOv5-7.0草莓采摘分级机器人的设计与试验

doi:10.3969/j.issn.1004-1524.20240875

浙江农业学报 ›› 2025, Vol. 37 ›› Issue (11): 2364-2375.DOI: 10.3969/j.issn.1004-1524.20240875

基于YOLOv5-7.0草莓采摘分级机器人的设计与试验

邱琰¹^,²(), 叶自然², 谭向峰², 代梦迪², 葛世豪³, 阮贇杰³, 赵先亮¹^,^*(), 孔德栋²^,^*()

1.浙江科技大学生物与化学工程学院,浙江杭州 310023
2.浙江省农业科学院数字农业研究所,浙江杭州 310021
3.浙江大学生物系统工程与食品科学学院,浙江杭州 310058

收稿日期:2024-10-12 出版日期:2025-11-25 发布日期:2025-12-08
作者简介:邱琰(1997—),男,江苏睢宁人,硕士,主要从事农业机械化自动化研究。E-mail:87359948@qq.com
通讯作者: ^*赵先亮,E-mail:zlzhao@zust.edu.cn;孔德栋,E-mail: kongdd@zaas.ac.cn
基金资助:
浙江省农业科学院地方合作项目(SY202301);浙江省农业关键核心技术攻关项目

Design and experiment of strawberry picking and grading robot based on YOLOv5-7.0

QIU Yan¹^,²(), YE Ziran², TAN Xiangfeng², DAI Mengdi², GE Shihao³, RUAN Yunjie³, ZHAO Xianliang¹^,^*(), KONG Dedong²^,^*()

1. School of Biological & Chemistry Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
2. Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
3. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China

Received:2024-10-12 Online:2025-11-25 Published:2025-12-08

摘要/Abstract

摘要：

针对当前草莓植物工厂中采摘分级工作量大、人工操作难等问题,设计了一种适用于植物工厂的智能草莓采摘分级机器人。分析了整机结构及工作原理,基于理论分析与选型计算优化设计了阿克曼式底盘移动控制系统、伸缩式电动剪刀及仿人型机械手;本文利用YOLOv5-7.0算法实现了草莓分级判定与果梗生长方向预测,最后开展了整机采摘分级性能测试。试验结果表明,该机器人工作性能稳定,采摘与分级动作连贯,草莓平均分级准确率达到87.44%,实现了精准定位和轻柔抓取目标,显著提高了工作效率。

关键词: 农业机器人, 草莓, 植物工厂, 采摘, 分级

Abstract:

In order to solve the problems of large workload and difficult manual picking in strawberry plant factories, an intelligent strawberry picking and grading robot for plant factories was designed. The structure and working principle of the robot were analyzed, and its key components were optimized based on theoretical analysis and selection calculations, including the Ackermann type chassis movement control system, telescopic electric scissors, and the structure of humanoid underactuated manipulator. The YOLOv5-7.0 algorithm was employed to achieve strawberry grading and predict the direction of peduncle growth. Ultimately, a performance test of the machine’s picking and grading capabilities was conducted. The test results showed that the robot exhibited stable performance and consistent actions in picking and grading, with an average accuracy of 87.44% for strawberry grading. This achievement enables precise targeting and gentle grasping of the fruit, significantly enhancing work efficiency.

Key words: agricultural robot, strawberry, plant factory, picking, grading

中图分类号:

S225

邱琰, 叶自然, 谭向峰, 代梦迪, 葛世豪, 阮贇杰, 赵先亮, 孔德栋. 基于YOLOv5-7.0草莓采摘分级机器人的设计与试验[J]. 浙江农业学报, 2025, 37(11): 2364-2375.

QIU Yan, YE Ziran, TAN Xiangfeng, DAI Mengdi, GE Shihao, RUAN Yunjie, ZHAO Xianliang, KONG Dedong. Design and experiment of strawberry picking and grading robot based on YOLOv5-7.0[J]. Acta Agriculturae Zhejiangensis, 2025, 37(11): 2364-2375.

图/表 19

图1 草莓采摘分级机器人结构 1,深度相机RGB-D435; 2,伸缩式电动剪刀; 3,仿人型欠驱动机械手; 4,六轴机械臂;5,收集装置;6.阿克曼式底盘。

Fig.1 The structure of strawberry picking and grading robot 1, Depth camera RGB-D435; 2, Telescopic motorized scissors; 3, Humanoid underactuated manipulator; 4, 6-DOF robot arm; 5, Collection device; 6, Ackermann-type chassis.

图2 机器人工作流程

Fig.2 Robot workflow

图3 移动控制系统结构图

Fig.3 Structure of mobile control system

图4 伸缩式电动剪刀结构图 1,步进电机;2,滑轨;3,滑块;4,光电传感器;5,推杆电机;6,连杆;7,刀口;8,刀片。

Fig.4 The structure of retractable electric scissors 1, Stepping motor; 2, Slide rail; 3, Slider; 4, Photoelectric sensor; 5, Pusher motor; 6, Linkage; 7, Cutter; 8, Blade.

图5 仿人型欠驱机械手结构图 1,手指;2,转盘;3,绳索;4,舵机;5,推杆电机。

Fig.5 The structure of humanoid underactuated manipulator 1, Finger; 2, Turntable; 3, Rope; 4, Servo; 5, Pusher motor.

图6 手指理论力学模型

Fig.6 Theoretical mechanical model of finger

表1 手指DH参数

Table 1 Finger DH parameters

i	b_i_-1/mm	y_i/rad
1	0	y₁
2	36	y₂
3	25	y₃

图7 手指运动范围

Fig.7 Range of motion of finger

图8 草莓姿态

Fig.8 The posture of strawberry

图9 草莓的理论抓取点分析

Fig.9 Theoretical grasping point analysis

图10 抓取算法的结构模型

Fig.10 The structural model of grasping algorithm

图11 草莓识别和生长方向判断

Fig.11 Strawberry identification and growth direction judgment

图12 果梗切割点假设

Fig.12 Fruit stalk cutting point assumptions

表2 草莓等级判定

Table 2 Strawberry grade judgment

形状Shape	判定系数K	等级Grade
圆形、纺锤形、(短)圆锥形、(短)楔形	K>0.126	大Big
Circular, spindle-shaped, (short) conical, (short) wedge-shaped	0.110≤K≤0.126	中Medium
	K<0.110	小Small

图13 草莓采摘试验现场

Fig.13 Strawberry picking experiment site

图14 草莓采摘分级机器人整机

Fig.14 The complete set of strawberry picking and grading robot

图15 实际抓取状态

Fig.15 Actual envelope state

表3 草莓分级结果

Table 3 Strawberry grading results

分级类型 Grading type	序号 No.	准确率 Accuracy/%
大果Big fruit	1	84.21
	2	88.00
	3	85.19
中果Medium fruit	1	91.70
	2	86.96
	3	89.28
小果Small fruit	1	87.35
	2	90.91
	3	83.33
平均Average		87.44

图16 草莓分级

Fig.16 Strawberry grading

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基于YOLOv5-7.0草莓采摘分级机器人的设计与试验

Design and experiment of strawberry picking and grading robot based on YOLOv5-7.0

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