IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i9p1513-d807334.html
   My bibliography  Save this article

Dynamic Parameters Identification Method of 6-DOF Industrial Robot Based on Quaternion

Author

Listed:
  • Jun Cheng

    (Robotics Institute, Beihang University, Beijing 100191, China)

  • Shusheng Bi

    (Robotics Institute, Beihang University, Beijing 100191, China)

  • Chang Yuan

    (Robotics Institute, Beihang University, Beijing 100191, China)

Abstract

Identifying accurate dynamic parameters is of great significance to improving the control accuracy of industrial robots, but this area is relatively unexplored in the research. In this paper, a new algorithm for accurately identifying the dynamic parameters of a 6-degrees-of-freedom (DOF) robot is proposed by establishing a dynamic model. First, a multibody dynamic model of the robot is established, which can decouple the dynamic parameters of the rigid bodies that make up the robot. Decoupling is the basis of parameters identification. In order to ensure that the model is suitable for large-angle range motion and has good real-time performance, quaternion is used as the angle coordinate, and the model established thereby eliminates the singularity and improves the calculation efficiency. Second, the dynamic model is rewritten, and the dynamic parameters are separated as the parameters to be identified; thus, the parameters identification model is obtained. Furthermore, an identification algorithm based on the least-squares method is proposed, which can realize the accurate identification of dynamic parameters. The algorithm is verified by a simulation example. The results show that the value of the maximum absolute error of the identified parameters is −0.0264, and the maximum relative error is 0.031%, which proves the correctness and accuracy of the algorithm.

Suggested Citation

  • Jun Cheng & Shusheng Bi & Chang Yuan, 2022. "Dynamic Parameters Identification Method of 6-DOF Industrial Robot Based on Quaternion," Mathematics, MDPI, vol. 10(9), pages 1-12, May.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1513-:d:807334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/9/1513/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/9/1513/
    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:jmathe:v:10:y:2022:i:9:p:1513-:d:807334. 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.