Effective localization of humanoid with fish-eye lens using field line detection

This paper presents a real-time technique for efficient localization of a humanoid robot in a soccer field using a fish-eye lens. We propose a novel method that uses node merging to provide a robust and an accurate estimate of positions of the intersection points in the field lines. The distances to...

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Bibliographic Details
Published in2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) pp. 72 - 78
Main Authors Kar, Pratyush, Jain, Archit, Rout, B. K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2016
Subjects
Cameras
Feature extraction
fish-eye lens
Humanoid robots
Image segmentation
inverse perspective mapping
Lenses
Localization
monte carlo
robocup
Robustness
x-t detection
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Summary:This paper presents a real-time technique for efficient localization of a humanoid robot in a soccer field using a fish-eye lens. We propose a novel method that uses node merging to provide a robust and an accurate estimate of positions of the intersection points in the field lines. The distances to these points are calculated using Inverse Perspective Mapping and fed to the particle filter for the purpose of localization. The proposed algorithms have been implemented and tested on the humanoid robot platform AcYut, being developed at the Centre for Robotics and Intelligent Systems (CRIS), BITS Pilani.
DOI:10.1109/ACIRS.2016.7556191