Robust and Efficient Field Features Detection for Localization

In some Robocup leagues, specially in the four-legged league, robots make use of coloured landmarks for localisation. Because these landmarks have no correlation with real soccer, it seems a natural approach to remove them. But for this to be a reality, there are some difficulties that need to be solved, mainly an efficient and robust field features detection and an efficient localisation technique to manage such type of information. In this paper we deal with an approach for field features detection based on finding intersections between field lines which runs at frame rate in the AIBO robots. We also present some experimental results of the vision system and a comparison of the traditional coloured landmark localisation and the field features only localisation, both using a fuzzy-Markov localisation technique.

[1]  Patric Jensfelt,et al.  Active global localization for a mobile robot using multiple hypothesis tracking , 2001, IEEE Trans. Robotics Autom..

[2]  Thomas Röfer,et al.  Fast and Robust Edge-Based Localization in the Sony Four-Legged Robot League , 2003, RoboCup.

[3]  Alessandro Saffiotti,et al.  Fuzzy Self-Localization Using Natural Features in the Four-Legged League , 2004, RoboCup.

[4]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  Dirk Thomas,et al.  Particle-Filter-Based Self-localization Using Landmarks and Directed Lines , 2005, RoboCup.

[6]  Alessandro Saffiotti,et al.  Fuzzy landmark-based localization for a legged robot , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).