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Adaptive Field Detection and Localization in Robot Soccer

  • Yongbo Qian
  • Daniel D. Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)

Abstract

Major rule updates for the RoboCup Standard Platform League (SPL) in recent years pose significant perception challenges for recognizing objects with similar color. Despite the frequent color changes to goalpost, soccer ball and jerseys, the soccer field itself remains unaffected, which makes green the only reliable color feature that can be exploited. In this paper, we propose an efficient approach for adaptive soccer field detection model utilizing NAO’s two-camera system. Building upon real-time image histogram analysis between top and bottom camera frames, the field color classifier is robust under inconsistent lighting conditions, and can be further processed to generate field boundaries. This approach could also be useful for other object detection modules and robot’s self-localization.

Keywords

Image histogram Color segmentation Boundary detection Natural lighting Self-localization 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.GRASP LabUniversity of PennsylvaniaPhiladelphiaUSA

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