IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i10p1923-d1251720.html
   My bibliography  Save this article

Study on the Fragrant Pear-Picking Sequences Based on the Multiple Weighting Method

Author

Listed:
  • Wenhong Ma

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

  • Zhouyang Yang

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

  • Xiaochen Qi

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

  • Yu Xu

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

  • Dan Liu

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

  • Housen Tan

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

  • Yongbin Li

    (College of Water & Architechtural Engineering, Shihezi University, Shihezi 832003, China)

  • Xuhai Yang

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
    Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 8832003, China
    Xinjiang Production and Construction Corps Key Laboratory of Modern Agriculture Machinery, Shihezi 832003, China)

Abstract

The production of the Korla fragrant pear is significant, but the optimal harvesting time is short; therefore, the reasonable use of mechanical arms for harvesting is conducive to promoting the sustainable development of the fragrant pear industry. The efficiency of a robot arm when picking fragrant pears is not only determined by the successful extraction of fragrant pears in a complex environment, but the picking sequence of fragrant pears also directly affects the efficiency of the robot arm. In order to simulate an orchard-picking scenario, this paper built three fragrant pear tree models indoors. The number of fragrant pears on the fragrant pear trees was 5, 10, and 20. Three sets of experiments were designed for comparison with real-world conditions. The main steps were as follows: calibrate the three-dimensional coordinates of each fragrant pear on the fragrant pear trees; determine the end position of the robotic arm at each picking point; find the inverse solution for each group; transform the solutions into matrix form using the rated power of each joint as the weight, and identify the minimum value, which is the angle of each joint in the robotic arm when picking the fragrant pear; use the intelligent socket to find the average energy consumption and average time consumed for picking each group of fragrant pears; and determine the loss ratio of the robotic arm based on the amount of rotation in each joint during picking. The experimental results show that the multiple weighting method reduced the energy consumption by 10.627%, 16.072%, and 24.417%, and the time consumption by 11.988%, 14.428%, and 22.561%, respectively, relative to the hybrid ant colony–particle swarm optimization algorithm, which proves the rationality of the fragrant pear picking order delineated using the multiple weighting method.

Suggested Citation

  • Wenhong Ma & Zhouyang Yang & Xiaochen Qi & Yu Xu & Dan Liu & Housen Tan & Yongbin Li & Xuhai Yang, 2023. "Study on the Fragrant Pear-Picking Sequences Based on the Multiple Weighting Method," Agriculture, MDPI, vol. 13(10), pages 1-18, September.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:10:p:1923-:d:1251720
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/10/1923/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/13/10/1923/
    Download Restriction: no
    ---><---

    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:13:y:2023:i:10:p:1923-:d:1251720. 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.