IDEAS home Printed from https://ideas.repec.org/a/igg/jiit00/v16y2020i4p68-86.html
   My bibliography  Save this article

Visual Perception System of EROS Humanoid Robot Soccer

Author

Listed:
  • Aulia Khilmi Rizgi

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Anhar Risnumawan

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Fernando Ardila

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Edi Sutoyo

    (Telkom University, Indonesia)

  • Ryan Satria Wijaya

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Ilham Fakhrul Arifin

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Martianda Erste Anggraeni

    (Politeknik Elektronika Negeri Surabaya, Indonesia)

  • Tutut Herawan

    (Ambarrukmo Tourism Institute, Indonesia & AMCS Research Center, Indonesia)

Abstract

In this paper, a humanoid robot soccer perception system, consisting of a ball, field detection, and localization, is developed in order to deal with the new rules in RoboCup. Color segmentation and image morphology are improved together with a more sophisticated machine learning algorithm to detect a soccer ball robustly. Those algorithms are still favorable due to its real-time running in most of the embedded platform. For localization, the field is divided into pre-deðned grids and employing k-NN (k-nearest neighbor) to determine the robot location in the grids. Pre-defined grids are used to reduce computation due to matching with a map. Experiment results show that the developed system relatively well for adapting to the new rules update.

Suggested Citation

  • Aulia Khilmi Rizgi & Anhar Risnumawan & Fernando Ardila & Edi Sutoyo & Ryan Satria Wijaya & Ilham Fakhrul Arifin & Martianda Erste Anggraeni & Tutut Herawan, 2020. "Visual Perception System of EROS Humanoid Robot Soccer," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 16(4), pages 68-86, October.
    • Handle: RePEc:igg:jiit00:v:16:y:2020:i:4:p:68-86
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIIT.2020100105
    Download Restriction: no
    ---><---

    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:igg:jiit00:v:16:y:2020:i:4:p:68-86. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.