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

IF 4.2 2区 计算机科学 Q2 ROBOTICS
Jiacheng Rong, Lin Hu, Hui Zhou, Guanglin Dai, Ting Yuan, Pengbo Wang
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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.

樱桃番茄选择性收获机器人:设计、开发和实地评估分析
随着人口老龄化和劳动力成本的增加,传统的人工采收方法已经变得越来越不经济。因此,利用选择性采收机器人对樱桃番茄进行全自动采收的研究已成为热门话题。然而,目前的研究大多集中在大番茄的单个采收上,而对成群采收樱桃番茄的完整系统的开发研究较少。本研究的目的是开发一种采收机器人系统,该系统能够通过切割番茄果梗采收番茄簇,并在实际温室环境中对机器人原型进行评估。首先,为了增强抓取稳定性,设计了一种新型末端执行器。该末端执行器采用凸轮机构,只需一个动力源即可实现切割和抓取的异步动作。随后,还开发了一套视觉感知系统,用于定位花梗的切割点。该系统分为两部分:在远距离视图中对水果进行粗略定位,在近距离视图中对果柄切割点进行精确定位。此外,该系统还能根据从果实花梗和茎中提取的点云特征,自适应地推断末端执行器的接近姿态。最后,我们组装了一个西红柿采摘机器人原型进行实地试验。试验结果表明,在两个温室中,在果梗未被遮挡的番茄群中,切割点的定位成功率分别为88.5%和83.7%,而收获成功率分别达到57.7%和55.4%。收获一簇番茄的平均周期为 24 秒。实验结果证明了所开发的番茄收获机器人的商业应用潜力,并通过对故障案例的分析,探讨了未来的工作方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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