A selective harvesting robot for cherry tomatoes: Design, development, field evaluation analysis

花梗 机器人 温室 机器人末端执行器 人口 人工智能 点云 工程类 农业工程 计算机科学 模拟 计算机视觉 园艺 生物 社会学 人口学
作者
Jiacheng Rong,Lin Hu,Hui Zhou,Guanglin Dai,Ting Yuan,Pengbo Wang
出处
期刊:Journal of Field Robotics [Wiley]
被引量:3
标识
DOI:10.1002/rob.22377
摘要

Abstract With the aging population and increasing labor costs, traditional manual harvesting methods have become less economically efficient. Consequently, research into fully automated harvesting using selective harvesting robots for cherry tomatoes has become a hot topic. However, most of the current research is focused on individual harvesting of large tomatoes, and there is less research on the development of complete systems for harvesting cherry tomatoes in clusters. The purpose of this study is to develop a harvesting robot system capable of picking tomato clusters by cutting their fruit‐bearing pedicels and to evaluate the robot prototype in real greenhouse environments. First, to enhance the grasping stability, a novel end‐effector was designed. This end‐effector utilizes a cam mechanism to achieve asynchronous actions of cutting and grasping with only one power source. Subsequently, a visual perception system was developed to locate the cutting points of the pedicels. This system is divided into two parts: rough positioning of the fruits in the far‐range view and accurate positioning of the cutting points of the pedicels in the close‐range view. Furthermore, it possesses the capability to adaptively infer the approaching pose of the end‐effector based on point cloud features extracted from fruit‐bearing pedicels and stems. Finally, a prototype of the tomato‐harvesting robot was assembled for field trials. The test results demonstrate that in tomato clusters with unobstructed pedicels, the localization success rates for the cutting points were 88.5% and 83.7% in the two greenhouses, respectively, while the harvesting success rates reached 57.7% and 55.4%, respectively. The average cycle time to harvest a tomato cluster was 24 s. The experimental results prove the potential for commercial application of the developed tomato‐harvesting robot and through the analysis of failure cases, discuss directions for future work.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小马甲应助今天开始吃草采纳,获得10
刚刚
魏来完成签到,获得积分10
1秒前
CodeCraft应助开心苠采纳,获得10
1秒前
roger发布了新的文献求助10
3秒前
6秒前
龍龖龘发布了新的文献求助10
6秒前
暴躁小李完成签到,获得积分20
8秒前
李爱国应助阿巴阿巴小聂采纳,获得10
10秒前
da1234应助lsn采纳,获得10
11秒前
友好凡霜发布了新的文献求助10
12秒前
NexusExplorer应助杭谷波采纳,获得10
17秒前
外向半梅关注了科研通微信公众号
19秒前
思源应助害怕的荔枝采纳,获得20
19秒前
烟花应助幸福慕蕊采纳,获得10
20秒前
20秒前
菲雨应助调皮的浩天采纳,获得10
21秒前
量子星尘发布了新的文献求助10
22秒前
22秒前
23秒前
26秒前
26秒前
One完成签到,获得积分10
26秒前
29秒前
29秒前
苏素肃发布了新的文献求助10
29秒前
Bao发布了新的文献求助10
30秒前
。。。完成签到,获得积分10
30秒前
暴躁小李发布了新的文献求助10
30秒前
SYLH应助Aten采纳,获得10
33秒前
35秒前
35秒前
36秒前
李爱国应助baba采纳,获得10
37秒前
爆米花应助多多采纳,获得10
38秒前
One发布了新的文献求助20
38秒前
幽默的溪灵完成签到,获得积分0
39秒前
vent完成签到,获得积分10
39秒前
41秒前
lhx发布了新的文献求助10
41秒前
共享精神应助Ashui采纳,获得10
41秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3959309
求助须知:如何正确求助?哪些是违规求助? 3505589
关于积分的说明 11124738
捐赠科研通 3237345
什么是DOI,文献DOI怎么找? 1789116
邀请新用户注册赠送积分活动 871544
科研通“疑难数据库(出版商)”最低求助积分说明 802844