A Vision Servo System for Automated Harvest of Sweet Pepper in Korean Greenhouse Environment
| Autor: | Donghwan Kam, Ji-Ho Hwa, ByeongRo Min, Bongki Lee, SeBu Oh |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Farming environment Greenhouse 02 engineering and technology Agricultural engineering Servomechanism lcsh:Technology cylindrical robot law.invention lcsh:Chemistry image processing-based 020901 industrial engineering & automation law sweet pepper harvesting automation Pepper General Materials Science vision servo system Manipulator lcsh:QH301-705.5 Instrumentation Mathematics Fluid Flow and Transfer Processes Sweet Peppers momentum backpropagation lcsh:T business.industry Process Chemistry and Technology General Engineering 04 agricultural and veterinary sciences lcsh:QC1-999 Computer Science Applications Robotic systems lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 Agriculture 040103 agronomy & agriculture 0401 agriculture forestry and fisheries lcsh:Engineering (General). Civil engineering (General) business lcsh:Physics |
| Zdroj: | Applied Sciences Volume 9 Issue 12 Applied Sciences, Vol 9, Iss 12, p 2395 (2019) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app9122395 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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