IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i2p433-d480578.html
   My bibliography  Save this article

Energy Efficiency of a Quadruped Robot with Neuro-Inspired Control in Complex Environments

Author

Listed:
  • Paolo Arena

    (Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Viale A. Doria 6, 95100 Catania, Italy
    Institute for Systems Analysis and Computer Science “Antonio Ruberti”, IASI-CNR, Via dei Taurini 19, 00185 Roma, Italy
    These authors contributed equally to this work.)

  • Luca Patanè

    (Dipartimento di Ingegneria, Università degli Studi di Messina, Contrada di Dio, 98166 Messina, Italy
    These authors contributed equally to this work.)

  • Salvatore Taffara

    (Dipartimento di Ingegneria Elettrica Elettronica e Informatica, University of Catania, Viale A. Doria 6, 95100 Catania, Italy
    These authors contributed equally to this work.)

Abstract

This paper proposes an analysis of the energy efficiency of a small quadruped robotic structure, designed based on the MIT Mini Cheetah, controlled using a central pattern generator based on the FitzHugh–Nagumo neuron. The robot’s performance evaluated on structurally complex terrain in a dynamic simulation environment is compared with other robotic structures on wheels and with hybrid architectures. The energy cost involved in carrying out an assigned task involving the need to traverse uneven terrain is calculated as a relevant index to be taken into account. In particular, simple control strategies impacting the leg trajectories are taken into account as the main factors affecting the energy efficiency in different terrain configurations. The adaptation of the leg trajectories is evaluated depending on the terrain characteristics, improving the locomotion performance.

Suggested Citation

  • Paolo Arena & Luca Patanè & Salvatore Taffara, 2021. "Energy Efficiency of a Quadruped Robot with Neuro-Inspired Control in Complex Environments," Energies, MDPI, vol. 14(2), pages 1-16, January.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:2:p:433-:d:480578
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/2/433/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/2/433/
    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:jeners:v:14:y:2021:i:2:p:433-:d:480578. 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.