Robust and Efficient Object Recognition for a Humanoid Soccer Robot

  • Alexander Härtl
  • Ubbo Visser
  • Thomas Röfer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8371)


Static color classification as a first processing step of an object recognition system is still the de facto standard in the RoboCup Standard Platform League (SPL). Despite its efficiency, this approach lacks robustness with regard to changing illumination. We propose a new object recognition system where objects are found based on color similarities. Our experiments with line, goal, and ball recognition show that the new system is real-time capable on a contemporary NAO (version 3.2 and above). We show that the detection rate is comparable to color-table-based object recognition under static lighting conditions and substantially better under changing illumination.


Object Recognition Center Circle Goal Post Line Detection Hough Transformation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Alexander Härtl
    • 1
  • Ubbo Visser
    • 1
  • Thomas Röfer
    • 2
  1. 1.Department of Computer ScienceUniversity of MiamiCoral GablesUSA
  2. 2.Cyber-Physical SystemsDeutsches Forschungszentrum für Künstliche IntelligenzBremenGermany

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