IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i3p381-d767178.html
   My bibliography  Save this article

Task Space Model Predictive Control for Vineyard Spraying with a Mobile Manipulator

Author

Listed:
  • Ivo Vatavuk

    (Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

  • Goran Vasiljević

    (Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

  • Zdenko Kovačić

    (Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, 10000 Zagreb, Croatia)

Abstract

In this paper, a Model Predictive Control (MPC)-based approach for vineyard spraying is presented, able to adapt to different vine row structures and suitable for real-time applications. In the presented approach, the mobile base moves along a row of vines while the robotic arm controls the position and orientation of the spray nozzle. A reference lawnmower pattern trajectory is generated from the vine canopy description, with the aim of minimizing waste while ensuring vine coverage. MPC is used to compute the trajectory of the vehicle along the row and the manipulator tool trajectory, which follow the spray reference, while minimizing vehicle acceleration and tool displacement. The manipulator tool velocity commands provided by the MPC algorithm are tracked using task space control. The presented approach is evaluated in two experiments: a vineyard spraying scenario and an external evaluation scenario in an indoor environment equipped with the Optitrack camera system.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:3:p:381-:d:767178
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/3/381/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/3/381/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. 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.
    2. 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.
    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.

    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:3:p:381-:d:767178. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.