IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/358269.html
   My bibliography  Save this article

Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms

Author

Listed:
  • Hsu-Chih Huang
  • Sendren Sheng-Dong Xu
  • Huan-Shiuan Hsu

Abstract

This paper presents a hybrid Taguchi deoxyribonucleic acid (DNA) swarm intelligence for solving the inverse kinematics redundancy problem of six degree-of-freedom (DOF) humanoid robot arms. The inverse kinematics problem of the multi-DOF humanoid robot arm is redundant and has no general closed-form solutions or analytical solutions. The optimal joint configurations are obtained by minimizing the predefined performance index in DNA algorithm for real-world humanoid robotics application. The Taguchi method is employed to determine the DNA parameters to search for the joint solutions of the six-DOF robot arms more efficiently. This approach circumvents the disadvantage of time-consuming tuning procedure in conventional DNA computing. Simulation results are conducted to illustrate the effectiveness and merit of the proposed methods. This Taguchi-based DNA (TDNA) solver outperforms the conventional solvers, such as geometric solver, Jacobian-based solver, genetic algorithm (GA) solver and ant, colony optimization (ACO) solver.

Suggested Citation

  • Hsu-Chih Huang & Sendren Sheng-Dong Xu & Huan-Shiuan Hsu, 2014. "Hybrid Taguchi DNA Swarm Intelligence for Optimal Inverse Kinematics Redundancy Resolution of Six-DOF Humanoid Robot Arms," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-9, July.
    • Handle: RePEc:hin:jnlmpe:358269
    DOI: 10.1155/2014/358269
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2014/358269.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2014/358269.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/358269?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
    ---><---

    More about this item

    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:hin:jnlmpe:358269. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.