Self-Localization in Dynamic Environments based on Laser and Vision Data

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“Self-Localization in Dynamic Environments based on Laser and Vision Data” by E. Schulenburg, T. Weigel, and A. Kleiner. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots & Systems (IROS), November 17 2003, pp. 998-1004.

Abstract

For a robot situated in a dynamic real world environment the knowledge of its position and orientation is very advantageous and sometimes essential for carrying out a given task. Particularly, one would appreciate a robust, accurate and efficient selflocalization method which allows a global localization of the robot. In certain polygonal environments a laser based localization method is capable of combining all these properties by correlating observed lines with an a priori line model of the environment [5] . However, often line features can rather be detected by a vision system than by a laser range finder. For this reason we propose an extension of the laser based approach for the simultaneous use with lines detected by an omni-directional camera. The approach is evaluated in the RoboCup domain and experimental evidence is given for its robustness, accuracy and efficiency, as well as for its capability of global localization.

Download: Paper (pdf), Video (mpeg 3MB).

BibTeX entry:

@inproceedings{schulenberg_et_al_03,
   author = {E. Schulenburg and T. Weigel and A. Kleiner},
   title = {Self-Localization in Dynamic Environments based on Laser and
	Vision Data},
   booktitle = {Proc. of the {IEEE/RSJ} Int. Conf. on Intelligent Robots
	& Systems {(IROS)}},
   pages = {998--1004},
   month = {November~17},
   year = {2003},
   language = {en}
}

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