IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i18p1912-d1745654.html
   My bibliography  Save this article

Design and Development of an Intelligent Robotic Feeding Control System for Sheep

Author

Listed:
  • Haina Jiang

    (College of Electromechanical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Haijun Li

    (College of Electromechanical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Guoxing Cai

    (College of Electromechanical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

Abstract

With the widespread adoption of intelligent technologies in animal husbandry, traditional manual feeding methods can no longer meet the demands for precision and efficiency in modern sheep farming. To address this gap, we present an intelligent robotic feeding system designed to enhance feeding efficiency, reduce labor intensity, and enable precise delivery of feed. This system, developed on the ROS platform, integrates LiDAR-based SLAM with point cloud rendering and an Octomap 3D grid map. It combines an improved bidirectional RRT* algorithm with Dynamic Window Approach (DWA) for efficient path planning and uses 3D LiDAR data along with the RANSAC algorithm for slope detection and navigation information extraction. The YOLOv8s model is utilized for precise sheep pen marker identification, while integration with weighing sensors and a farm management system ensures accurate feed distribution control. The main research contribution lies in the development of a comprehensive, multi-sensor fusion system capable of achieving autonomous feeding in dynamic and complex environments. Experimental results show that the system achieves centimeter-level accuracy in localization and attitude control, with FAST-LIO2 maintaining precision within 1° of attitude angle errors. Compared to baseline performance, the system reduces node count by 17.67%, shortens path length by 0.58 cm, and cuts computation time by 42.97%. At a speed of 0.8 m/s, the robot achieves a maximum longitudinal deviation of 7.5 cm and a maximum heading error of 5.6°, while straight-line deviation remains within ±2.2 cm. In a 30 kg feeding task, the system demonstrates zero feed wastage, highlighting its potential for intelligent feeding in modern sheep farming.

Suggested Citation

  • Haina Jiang & Haijun Li & Guoxing Cai, 2025. "Design and Development of an Intelligent Robotic Feeding Control System for Sheep," Agriculture, MDPI, vol. 15(18), pages 1-20, September.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:18:p:1912-:d:1745654
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/18/1912/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/18/1912/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Akay, Rustu & Yildirim, Mustafa Yusuf, 2025. "SBA*: An efficient method for 3D path planning of unmanned vehicles," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 231(C), pages 294-317.
    Full references (including those not matched with items on IDEAS)

    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.

      More about this item

      Keywords

      ;
      ;
      ;
      ;
      ;

      Statistics

      Access and download statistics

      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:15:y:2025:i:18:p:1912-:d:1745654. 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.