{"title":"Application of Hybrid Visual Servo Control in Agricultural Harvesting","authors":"Yi-Rong Li, Wei-Yuan Lian, Shao-Heng Liu, Zhiheng Huang, Chun-Ta Chen","doi":"10.1109/ICSSE55923.2022.9947362","DOIUrl":null,"url":null,"abstract":"This paper aims to develop agricultural robots that can be applied to greenhouse crop harvesting by using a hybrid visual servo control method (HVSC). In the research, a depth camera was used to acquire the posture of the tomato in three-dimensional space, and visual servo control can be carried out for the tomato growing at different angles in practice. Different visual servo control methods are also discussed, including the Position-Based Visual Servo (PBVS), Image-Based Visual Servo (IBVS) and the proposed HVSC with the fuzzy dynamic control parameters. Characteristics of different visual servo control methods were discussed, and then applied to the actual harvesting. The results show that the hybrid visual servo control developed in this research has an average harvesting time of 9.40s/per and an average harvesting success rate of 96.25% for cherry tomato.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE55923.2022.9947362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper aims to develop agricultural robots that can be applied to greenhouse crop harvesting by using a hybrid visual servo control method (HVSC). In the research, a depth camera was used to acquire the posture of the tomato in three-dimensional space, and visual servo control can be carried out for the tomato growing at different angles in practice. Different visual servo control methods are also discussed, including the Position-Based Visual Servo (PBVS), Image-Based Visual Servo (IBVS) and the proposed HVSC with the fuzzy dynamic control parameters. Characteristics of different visual servo control methods were discussed, and then applied to the actual harvesting. The results show that the hybrid visual servo control developed in this research has an average harvesting time of 9.40s/per and an average harvesting success rate of 96.25% for cherry tomato.