Title :
Fast, accurate, and robust self-localization in polygonal environments
Author :
Gutmann, Jens-Steffen ; Weigel, Thilo ; Nebel, Bernhard
Author_Institution :
Inst. fur Inf., Albert-Ludwigs-Univ., Freiburg, Germany
Abstract :
Self-localization is important in almost all robotic tasks. For playing an aesthetic and effective game of robotic soccer, self-localization is a necessary prerequisite. When we designed our robotic soccer team for RoboCup´98, it turned out that all existing approaches did not meet our requirements of being fast, accurate, and robust. For this reason, we developed a new method, which is presented and analyzed in the paper We additionally present experimental evidence that our method outperforms other methods in the RoboCup environment
Keywords :
Kalman filters; feature extraction; filtering theory; laser ranging; mobile robots; multi-robot systems; path planning; robot vision; RoboCup´98; polygonal environments; robotic soccer; self-localization; Computer vision; Data mining; Feature extraction; Impedance matching; Machine vision; Robot sensing systems; Robot vision systems; Robustness; Sonar; Testing;
Conference_Titel :
Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on
Conference_Location :
Kyongju
Print_ISBN :
0-7803-5184-3
DOI :
10.1109/IROS.1999.811677
