IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i4p552-d792274.html
   My bibliography  Save this article

Design and Performance Test of a Jujube Pruning Manipulator

Author

Listed:
  • Bin Zhang

    (School of Information and Communication Engineering, Hainan University, Haikou 570228, China
    Mechanical and Electrical Engineering College, Hainan University, Haikou 570228, China)

  • Xuegeng Chen

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China)

  • Huiming Zhang

    (Mechanical and Electrical Engineering College, Hainan University, Haikou 570228, China)

  • Congju Shen

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
    Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832003, China)

  • Wei Fu

    (School of Information and Communication Engineering, Hainan University, Haikou 570228, China
    Mechanical and Electrical Engineering College, Hainan University, Haikou 570228, China)

Abstract

To solve the problems of poor working conditions and high labor intensity for artificially pruning jujube trees, a pruning scheme using a manipulator is put forward in the present paper. A pruning manipulator with five degrees of freedom for jujube trees is designed. The key components of the manipulator are designed and the dimension parameters of each joint component are determined. The homogeneous transformation of the DH parameter method is used to solve the kinematic equation of the jujube pruning manipulator, and the kinematic theoretical model of the manipulator is established. Finally, the relative position and attitude relationship among the coordinate systems is obtained. A three-dimensional mathematical simulation model of the jujube pruning manipulator is established, based on MATLAB Robotics Toolbox. The Monte Carlo method is used to carry out the manipulator workspace simulation, and the results of the simulation analysis show that the working space of the manipulator is −600~800 mm, −800~800 mm, and −200~1800 mm in the X, Y, and Z direction, respectively. It can be concluded that the geometric size of the jujube pruning manipulator meets the needs of jujube pruning in a dwarf and densely planted jujube garden. Then, based on the high-speed camera technology, the performance test of the manipulator is carried out. The results show that the positioning error of the manipulator at different pruning points of jujube trees is less than 10 mm, and the pruning success rate of a single jujube tree is higher than 85.16%. This study provides a theoretical basis and technical support for the intelligent pruning of jujube trees in an orchard.

Suggested Citation

  • Bin Zhang & Xuegeng Chen & Huiming Zhang & Congju Shen & Wei Fu, 2022. "Design and Performance Test of a Jujube Pruning Manipulator," Agriculture, MDPI, vol. 12(4), pages 1-21, April.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:4:p:552-:d:792274
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/4/552/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/4/552/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivo Vatavuk & Goran Vasiljević & Zdenko Kovačić, 2022. "Task Space Model Predictive Control for Vineyard Spraying with a Mobile Manipulator," Agriculture, MDPI, vol. 12(3), pages 1-20, March.
    2. Md Nafiul Islam & Md Zafar Iqbal & Mohammod Ali & Milon Chowdhury & Md Shaha Nur Kabir & Tusan Park & Yong-Joo Kim & Sun-Ok Chung, 2020. "Kinematic Analysis of a Clamp-Type Picking Device for an Automatic Pepper Transplanter," Agriculture, MDPI, vol. 10(12), pages 1-17, December.
    3. Tan Wang & Xianbao Xu & Cong Wang & Zhen Li & Daoliang Li, 2021. "From Smart Farming towards Unmanned Farms: A New Mode of Agricultural Production," Agriculture, MDPI, vol. 11(2), pages 1-26, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang Xu & Changjie Han & Jing Zhang & Bin Hu & Xu Ma & Hanping Mao, 2024. "Innovative Designs for Cotton Bionic Topping Manipulator," Agriculture, MDPI, vol. 14(9), pages 1-23, August.
    2. Xinwu Du & Zhihao Yun & Xin Jin & Pengfei Li & Kaihang Gao, 2023. "Design and Experiment of Automatic Adjustable Transplanting End-Effector Based on Double-Cam," Agriculture, MDPI, vol. 13(5), pages 1-15, April.
    3. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.
    4. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Research on an Intelligent Agricultural Machinery Unmanned Driving System," Agriculture, MDPI, vol. 13(10), pages 1-19, September.
    5. Chuanxing Du & Weiquan Fang & Dianlei Han & Xuegeng Chen & Xinzhong Wang, 2024. "Design and Experimental Study of a Biomimetic Pod-Pepper-Picking Drum Based on Multi-Finger Collaboration," Agriculture, MDPI, vol. 14(2), pages 1-18, February.
    6. Juan D. Borrero & Jesús Mariscal, 2022. "A Case Study of a Digital Data Platform for the Agricultural Sector: A Valuable Decision Support System for Small Farmers," Agriculture, MDPI, vol. 12(6), pages 1-15, May.
    7. Tengxiang Yang & Chengqian Jin & Youliang Ni & Zhen Liu & Man Chen, 2023. "Path Planning and Control System Design of an Unmanned Weeding Robot," Agriculture, MDPI, vol. 13(10), pages 1-15, October.
    8. Yehong Liu & Xin Wang & Dong Dai & Can Tang & Xu Mao & Du Chen & Yawei Zhang & Shumao Wang, 2023. "Knowledge Discovery and Diagnosis Using Temporal-Association-Rule-Mining-Based Approach for Threshing Cylinder Blockage," Agriculture, MDPI, vol. 13(7), pages 1-21, June.
    9. Akshat Jain & Prateek Jain, 2022. "Advances in Sustainable Agri Business Paradigm: Developing an Innovative Business and Marketing Model to abridge human labour predicting Neural Behaviour," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 65(4), pages 1193-1208, December.
    10. Chongyang Han & Jinhong Lv & Chengju Dong & Jiehao Li & Yuanqiang Luo & Weibin Wu & Mohamed Anwer Abdeen, 2024. "Classification, Advanced Technologies, and Typical Applications of End-Effector for Fruit and Vegetable Picking Robots," Agriculture, MDPI, vol. 14(8), pages 1-37, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:12:y:2022:i:4:p:552-:d:792274. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.