IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8030374.html
   My bibliography  Save this article

Adaptive Path Following and Locomotion Optimization of Snake-Like Robot Controlled by the Central Pattern Generator

Author

Listed:
  • Zhengcai Cao
  • Dong Zhang
  • Biao Hu
  • Jinguo Liu

Abstract

This work investigates locomotion efficiency optimization and adaptive path following of snake-like robots in a complex environment. To optimize the locomotion efficiency, it takes energy consumption and forward velocity into account to investigate the optimal locomotion parameters of snake-like robots controlled by a central pattern generator (CPG) controller. A cuckoo search (CS) algorithm is applied to optimize locomotion parameters of the robot for environments with variable fractions and obstacle distribution. An adaptive path following method is proposed to steer the snake-like robot forward and along a desired path. The efficiency and accuracy of the proposed path following method is researched. In addition, a control framework that includes a CPG network, a locomotion efficiency optimization algorithm, and an adaptive path following method is designed to control snake-like robots move in different environments. Simulation and experimental results are presented to illustrate the performance of the proposed locomotion optimization method and adaptive path following controller for snake-like robots in complexity terrains.

Suggested Citation

  • Zhengcai Cao & Dong Zhang & Biao Hu & Jinguo Liu, 2019. "Adaptive Path Following and Locomotion Optimization of Snake-Like Robot Controlled by the Central Pattern Generator," Complexity, Hindawi, vol. 2019, pages 1-13, January.
  • Handle: RePEc:hin:complx:8030374
    DOI: 10.1155/2019/8030374
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/8030374.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2019/8030374.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2019/8030374?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
    ---><---

    Citations

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


    Cited by:

    1. T. O. Ayogu & O. O. Obe, 2021. "Modelling, Design and Kinematic Control Strategies for Snake-like Robot locomotion – A Review," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 8(2), pages 17-23, February.

    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:complx:8030374. 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.