IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v14y2023i2d10.1007_s13198-021-01255-z.html
   My bibliography  Save this article

Obstacle avoidance trajectory planning of redundant robots based on improved Bi-RRT

Author

Listed:
  • Huixing Xi

    (Anshan Normal University Liaoning China)

Abstract

In order to improve the effectiveness of the avoidance trajectory planning method of redundant robot, based on the simplification of the redundant seven-degree-of-freedom structure, this paper conducts kinematics and dynamics modeling of the manipulator, and analyzes the inverse kinematics of the seven-degree-of-freedom manipulator. Moreover, this paper studies the path planning algorithm based on RRT, and applies the Bi-RRT algorithm to perform path planning. In addition, this paper combines the obstacle avoidance requirements and path planning requirements of redundant robots to construct an intelligent model to realize automatic obstacle avoidance trajectory planning. Finally, this paper verifies the effect through simulation experiments. The experimental research results show that the obstacle avoidance trajectory planning method of redundant robots based on improved Bi-RRT proposed in this paper has good results and can effectively improve the efficiency of redundant robot trajectory planning.

Suggested Citation

  • Huixing Xi, 2023. "Obstacle avoidance trajectory planning of redundant robots based on improved Bi-RRT," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(2), pages 548-557, April.
  • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:2:d:10.1007_s13198-021-01255-z
    DOI: 10.1007/s13198-021-01255-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01255-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-021-01255-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:ijsaem:v:14:y:2023:i:2:d:10.1007_s13198-021-01255-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.