Practical Extensions to Vision-Based Monte Carlo Localization Methods for Robot Soccer Domain

  • Kemal Kaplan
  • Buluç Çelik
  • Tekin Meriçli
  • Çetin Meriçli
  • H. Levent Akın
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4020)

Abstract

This paper proposes a set of practical extensions to the vision-based Monte Carlo localization (MCL) for RoboCup Sony AIBO legged robot soccer domain. The main disadvantage of AIBO robots is that they have a narrow field of view so the number of landmarks seen in one frame is usually not enough for geometric calculation. MCL methods have been shown to be accurate and robust in legged robot soccer domain but there are some practical issues that should be handled in order to maintain stability/elasticity ratio in a reasonable level. In this work, we presented four practical extensions in which two of them are novel approaches and the remaining ones are different from the previous implementations.

Keywords

Monte Carlo localization Vision based navigation mobile robotics robot soccer 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kemal Kaplan
    • 1
  • Buluç Çelik
    • 1
  • Tekin Meriçli
    • 2
  • Çetin Meriçli
    • 1
  • H. Levent Akın
    • 1
  1. 1.Department of Computer EngineeringBoğaziçi UniversityBebek, ÍstanbulTurkey
  2. 2.Department of Computer EngineeringMarmara UniversityGöztepe, ÍstanbulTurkey

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