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研究生: 李奕融
Li, Yi-Rong
論文名稱: 混合式視覺伺服控制在農作採收之應用
Application of Hybrid Visual Servo Control in Agricultural Harvesting
指導教授: 陳俊達
Chen, Chun-Ta
口試委員: 鄭江河 鄭鴻儀 陳俊達
Chen, Chun-Ta
口試日期: 2022/01/14
學位類別: 碩士
Master
系所名稱: 機電工程學系
Department of Mechatronic Engineering
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 156
中文關鍵詞: 農業機器人視覺伺服機器視覺玉女番茄採收
英文關鍵詞: Agricultural robots, Visual servoing, Machine vision, Cherry tomato harvesting
DOI URL: http://doi.org/10.6345/NTNU202200105
論文種類: 學術論文
相關次數: 點閱:132下載:16
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  • 本論文「混合式視覺伺服控制在農作採收之應用」旨在利用不同視覺伺服控制方法開發可應用於溫室農作物採收之農業機器人。研究中利用一台深度攝影機即可獲取玉女番茄在三維空間中的姿態,可針對實際中不同角度生長方向之番茄進行視覺伺服,也探討了不同視覺伺服控制方法,包含基於位置之視覺伺服(Position-Based Visual Servo, PBVS)與基於圖像之視覺伺服(Image-Based Visual Servo, IBVS),並提出了基於模糊動態控制參數之混合式視覺伺服控制(Hybrid Visual Servoing Control, HVSC),探討不同視覺伺服控制方法之特性,並應用在實際農作採收中。結果顯示本研究所開發之混合式視覺伺服控制對玉女番茄之平均採收時間為9.40s/per,平均採收成功率為96.25%。

    This paper "Application of Hybrid Visual Servo Control in Agricultural Harvesting " aims to develop agricultural robots that can be applied to greenhouse crop harvesting by using different visual servo control methods. In the research, a depth camera can be used to obtain 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.Hybrid Visual Servoing Control (HVSC) based on the fuzzy dynamic control parameters. Discuss the characteristics of different visual servo control methods were discussed, and then applied to 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.

    第一章 緒論 1 1.1 前言 1 1.2 文獻回顧 3 1.3 研究目的 15 1.4 論文架構研究方法 16 第二章 採收機器人設計 17 2.1 玉女番茄採收系統架構 17 2.2 機器手臂硬體 19 2.3 D435i深度攝影機 22 2.4 末端剪切機構 23 2.4.1 MG996R步進馬達 23 第三章 影像處理與視覺伺服控制器設計 25 3.1 番茄影像算法 25 3.1.1 番茄偵測與標定特徵點 25 3.1.2 番茄生長方向 26 3.2 視覺伺服控制 28 3.3 基於位置之視覺伺服控制 29 3.4 基於圖像之視覺伺服控制 34 3.5 IBVS控制設計 36 3.5.1 誤差定義 37 3.5.2 基於IBVS之PD-SMC控制 39 3.5.3 PD-SMC穩定性證明 40 3.5.4 基於Fuzzy之PD-SMC增益參數控制 43 3.6 混合式之視覺伺服控制系統 50 第四章 實驗分析與結果 52 4.1 番茄單一生長方向視覺伺服控制 52 4.1.1 IBVS_PD-SMC控制參數探討 53 4.1.2 PBVS控制法 58 4.1.3 IBVS_PD-SMC(飽和函數)控制法 60 4.1.4 IBVS_PD-SMC(雙曲函數)控制法 62 4.1.5 HVSC控制法 64 4.1.6 實驗結果與討論 66 4.2 IBVS動態參數探討 68 4.2.1 IBVS_PD-SMC(飽和函數)之固定控制參數 68 4.2.2 IBVS_PD-SMC(雙曲函數)之固定控制參數 71 4.2.3 IBVS_PD-SMC(飽和函數)之Fuzzy動態參數 74 4.2.4 IBVS_PD-SMC(雙曲函數)之Fuzzy動態參數 77 4.2.5 實驗結果與討論 80 4.3 番茄生長五方向之HVSC 82 4.3.1 30度前傾角之固定控制參數 87 4.3.2 30度前傾角之Fuzzy動態參數 90 4.3.3 45度前傾角之固定控制參數 93 4.3.4 45度前傾角之Fuzzy動態參數 96 4.3.5 60度前傾角之固定控制參數 99 4.3.6 60度前傾角之Fuzzy動態參數 102 4.3.7 實驗結果與比較 105 第五章 番茄實際採收實驗 107 5.1 不同視覺伺服控制方法採收實驗 108 5.1.1 PBVS採收實驗 109 5.1.2 IBVS採收實驗 115 5.1.3 HVSC採收實驗 120 5.1.4 結果與討論 126 5.2 HVSC採收實驗 129 5.2.1 15度隨機生長方向之HVSC採收實驗 129 5.2.2 30度隨機生長方向之HVSC採收實驗 133 5.2.3 45度隨機生長方向之HVSC採收實驗 136 5.2.4 60度隨機生長方向之HVSC採收實驗 139 5.2.5 結果與討論 142 5.3 HVSC之角度加入Fuzzy動態控制參數採收實驗 145 5.3.1 45度隨機生長方向之Fuzzy角度HVSC採收實驗 145 5.3.2 60度隨機生長方向之Fuzzy角度HVSC採收實驗 148 5.3.3 結果與討論 151 第六章 結論與未來展望 153 參考文獻 154

    [1] 吳惠卿,「當前農業人力資源面結構之探討」,農業試驗所技術服務季刊,118期,36-39,2019。
    [2] 蔡宜潔,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,343期,89頁,2021
    [3] 蔡宜潔,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,338期,71頁,2020
    [4] 蔡宜潔,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,326期,67頁,2019
    [5] 蔡宜潔,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,319期,87頁,2019
    [6] 蔡宜潔,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,314期,55頁,2018
    [7] 許鈺佩,葉志忠,袁麗惠,黃淑玲,「農業產銷概況」,農政與農情,309期,63頁,2018
    [8] https://zh.wikipedia.org/wiki/%E5%90%84%E5%9B%BD%E5%AE%B6%E5%92%8C%E5%9C%B0%E5%8C%BA%E4%BA%BA%E5%8F%A3%E5%88%97%E8%A1%A8
    [9] O.Calicioglu, A.Flammini, S.Bracco, L.Bellù, R.Sims, “The Future Challenges of Food and Agriculture: An Integrated Analysis of Trends and Solutions”, MDPI Sustainability, Vol. 11, No.1, pp.222, January 2019
    [10] Yuanshen Zhao, Liang Gong, Yixiang Huang, Chengliang Liu, “A review of key techniques of vision-based control for harvesting robot”, Computers and Electronics in Agricultire, Vol.127, pp.311-323, September 2016
    [11] Yuan Ting, Lv Lin, Zhang Fan, Fu Jun, Gao Jin, Zhang Junxiong, Li Wei, Zhang Chunlong, Zhang Wenqiang, “Robust Cherry Tomatoes Detection Algorithm in Greenhouse Scene Based on SSD”, MDPI Agriculture, Vol.10, No.6, pp.160, May 2020
    [12] Jiang Ping, Yoshiyuki Ishihara, Nobukatsu Sugiyama, Junji Oaki, Seiji Tokura, Atsushi Sugahara, Akihito Ogawa, “Depth Image–Based Deep Learning of Grasp Planning for Textureless Planar-Faced Objects in Vision-Guided Robotic Bin-Picking”, MDPI Sensors, Vol.20, No.3, pp.706, January 2020
    [13] Li Shipeng, Di Li, Chunhua Zhang, Jiafu Wan, Mingyou Xie, “RGB-D Image Processing Algorithm for Target Recognition and Pose Estimation of Visual Servo System”, MDPI Sensors, Vol.20, No.2, pp.430, January 2020
    [14] J. Jun, J. Kim, J. Seol, J. Kim, H. I. Son, “Towards an Efficient Tomato Harvesting Robot: 3D Perception, Manipulation, and End-Effector”, IEEE Access, Vol.9, pp.17631-17640, 2021
    [15] Ying Wang, Guan-lu Zhang, Haoxiang Lang, Bashan Zuo, Clarence W. de Silva, “A modified image-based visual servo controller with hybrid camera configuration for robust robotic grasping”, Robotics and Autonomous Systems, Vol.62, No.10, pp.1398-1407, 2014
    [16] Shih Ching-Long, Yi Lee, “A Simple Robotic Eye-In-Hand Camera Positioning and Alignment Control Method Based on Parallelogram Features”, MDPI Robotics, Vol.7, No.2, pp.31, June 2018
    [17] H. Seo, S. Kim, H. J. Kim, “Aerial grasping of cylindrical object using visual servoing based on stochastic model predictive control”, IEEE International Conference on Robotics and Automation (ICRA), pp. 6362-6368, 2017
    [18] S. Li, W. Xie, Y. Gao, “Enhanced IBVS controller for a 6DOF manipulator using hybrid PD-SMC method”, IECON 2017 - 43rd annual conference of the IEEE industrial electronics society, pp. 2852-2857, 2017
    [19] S. S. Mehta, W. MacKunis, T. F. Burks, “Nonlinear Robust Visual Servo Control for Robotic Citrus Harvesting”, Proceedings of the 19th World Congress The International Federation of Automatic Control(IFAC), pp.24-29, 2014
    [20] J. Gamba, P. J. From, A. C. Leite, “A visual servoing approach for robotic fruit harvesting in the presence of parametric uncertainties”, in Proc. CBA Volumes, 22nd Congresso Brasileiro de Automática, 2018
    [21] 莊鴻榮,機器手臂在農作採收之最佳姿態分析─數據驅動法,臺灣師範大學機電工程學系,2020
    [22] S. Hutchinson, G. D. Hager, P. I. Corke, “A tutorial on visual servo control”, IEEE Transactions on Robotics and Automation, Vol.12, No.5, pp.651-670, 1996
    [23] 陳柏安,利用電腦視覺作自走車之障礙物定位與環境掃描,國立成功大學工程科學系,2004
    [24] Spong, Mark W, Seth Hutchinson, Mathukumalli Vidyasagar. Robot modeling and control, Wiley, 2005.
    [25] E.H. Mamdani, S. Assilian, An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, Vol.7, No.1, pp.1-13, 1975

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