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A Vision Servo System for Automated Harvest of Sweet Pepper in Korean Greenhouse Environment

机译:韩国温室环境中自动收获的视觉伺服系统

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摘要

Recently, farmers of sweet pepper suffer from the increase of its unit production costs due to the rise of labor costs. The rise of unit production costs of sweet pepper, on the other hand, decreases its productivity and causes the lack of its farming expertise, thus resulting in the quality degradation of products. In this regard, it is necessary to introduce an automated robot harvest system into the farming of sweet pepper. In this study, the authors developed an image-based closed-loop control system (a vision servo system) and an automated sweet pepper harvesting robot system and then carried out experiments to verify its efficiency. The working area of the manipulator that detects products through an imaging sensor in the farming environment of sweet pepper, decides whether to harvest it or not, and then informs the location of the product to the control center, which is set up at the distance scope of 350~600 mm from the center of the system and 1000 mm vertically. In order to confirm the performance of the sweet pepper recognition in this study, 269 sweet pepper images were used to extract fruits. Of 269 sweet pepper images, 82.16% were recognized successfully. The harvesting experiment of the system developed in this study was carried out with 100 sweet peppers. The result of experiment with 100 sweet peppers presents the fact that its approach rate to peduncle is about 86.7%, and via four sessions of repetitive harvest experiment it achieves a maximal 70% harvest rate, and its average time of harvest is 51.1 s.
机译:最近,由于劳动力成本的增加,甜椒的农民遭受其单位生产成本的增加。另一方面,甜椒的单位生产成本的兴起降低了其生产率,并导致缺乏农业专业知识,从而导致产品的质量退化。在这方面,有必要将自动机器人收获系统引入甘辣椒的养殖中。在这项研究中,作者开发了一种基于图像的闭环控制系统(视觉伺服系统)和自动甜椒收获机器人系统,然后进行实验以验证其效率。通过甜椒的养殖传感器检测产品的机械手的工作区域,决定是否收获它,然后向控制中心通知产品的位置,该控制中心在距离范围内设置距系统中心350〜600毫米,垂直1000毫米。为了确认本研究中甜椒识别的性能,使用269种甜椒图像来提取水果。在269个甜椒图像中,82.16%被成功认可。本研究开发的系统的收获实验是用100种甜辣椒进行的。用100个甜椒的实验结果提出了其对花梗的方法约为86.7%,并且通过四个重复的收获实验,它实现了最大的70%的收获率,其平均收获时间为51.1秒。

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