Particle-Filter-Based self-localization using landmarks and directed lines

Authors:
Thomas Röfer;Tim Laue;Dirk Thomas
Affiliations:
Center for Computing Technology (TZI), FB 3, Universität Bremen;Center for Computing Technology (TZI), FB 3, Universität Bremen;Fachgebiet Simulation und Systemoptimierung, Fachbereich Informatik, Technische Universität Darmstadt, Darmstadt, Germany
Venue:
RoboCup 2005
Year:
2006

Citing 1
Cited 1

Monte Carlo localization: efficient position estimation for mobile robots

AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence

Line point registration: a technique for enhancing robot localization in a soccer environment

Robot Soccer World Cup XV

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents the self-localization approach used by the World Champion in the Sony Four-Legged Robot League 2004. The method is based on a particle filter that makes use of different features from the environment (beacons, goals, field lines, field wall) that provide different kinds of localization information and that are recognized with different frequencies. In addition, it is discussed how the vision system acquires these features, especially, how the orientation of field lines is determined at low computational costs.