IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i1d10.1007_s13198-022-01630-4.html
   My bibliography  Save this article

Using flood-fill algorithms for an autonomous mobile robot maze navigation

Author

Listed:
  • Mohamed Nadour

    (University of Djelfa)

  • Lakhmissi Cherroun

    (University of Djelfa)

Abstract

Autonomous robotic navigation in unknown and complex environment as mazes is an important task for the wheeled mobile robots. Different algorithms have been used to deal with this problem, where the most known are based on optimization processes in order to find the optimal path safely. The present paper describes an implementation of a simple maze-solving algorithms based on Arduino-UNO card. The two versions of flood-fill algorithms are used for mobile robot maze navigation: the basic version of flood-fill algorithm (FFA) and the modified flood-fill algorithm (MFFA). Ultrasonic sensors are used to perceive, detect walls and the maze shape. The obtained experimental results demonstrate the efficiency of these implemented algorithms to autonomous robot navigation. In all cases, the controlled wheeled mobile robot is able to move in the maze safely, and can solve it effectively and autonomously.

Suggested Citation

  • Mohamed Nadour & Lakhmissi Cherroun, 2022. "Using flood-fill algorithms for an autonomous mobile robot maze navigation," 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. 13(1), pages 546-555, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-022-01630-4
    DOI: 10.1007/s13198-022-01630-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-022-01630-4
    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/s13198-022-01630-4?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:13:y:2022:i:1:d:10.1007_s13198-022-01630-4. 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.