IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i21p4509-d1272347.html
   My bibliography  Save this article

Trajectory Smoothing Planning of Delta Parallel Robot Combining Cartesian and Joint Space

Author

Listed:
  • Dachang Zhu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Yonglong He

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Xuezhe Yu

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

  • Fangyi Li

    (School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China)

Abstract

Delta parallel robots have been widely used in precision processing, handling, sorting, and the assembly of parts, and their high efficiency and motion stability are important indexes of their performance.Corners created by small line segments in trajectory planning cause abrupt changes in a tangential discontinuous trajectory, and the vibration and shock caused by such changes seriously affect the robot’s high-speed and high-precision performance. In this study, a trajectory-planning method combining Cartesian space and joint space is proposed. Firstly, the vector method and microelement integration method were used to establish the complete kinematic and dynamic equations of a delta parallel robot, and an inverse kinematic/dynamic model-solving program was written based on the MATLAB software R2020a. Secondly, the end-effector trajectory of the delta parallel robot was planned in Cartesian space, and the data points and inverse control points of the end effector’s trajectory were obtained using the normalization method. Finally, the data points and control points were mapped to the joint space through the inverse kinematic equation, and the fifth-order B-spline curve was adopted for quadratic trajectory planning, which allowed the high-order continuous smoothing of the trajectory planning to be realized. The simulated and experimental results showed that the trajectory-smoothing performance in continuous high-order curvature changes could be improved with the proposed method. The peak trajectory tracking error was reduced by 10.53 % , 41.18 % , and 44.44 % , respectively, and the peak torque change of the three joints was reduced by 3.5 % , 11.6 % , and 1.6 % , respectively.

Suggested Citation

  • Dachang Zhu & Yonglong He & Xuezhe Yu & Fangyi Li, 2023. "Trajectory Smoothing Planning of Delta Parallel Robot Combining Cartesian and Joint Space," Mathematics, MDPI, vol. 11(21), pages 1-16, November.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:21:p:4509-:d:1272347
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/21/4509/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/21/4509/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Dachang Zhu & Yonglong He & Fangyi Li, 2024. "Trajectory Tracking of Delta Parallel Robot via Adaptive Backstepping Fractional-Order Non-Singular Sliding Mode Control," Mathematics, MDPI, vol. 12(14), pages 1-14, 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:jmathe:v:11:y:2023:i:21:p:4509-:d:1272347. 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.