DocumentCode :
2936932
Title :
Supervised Learning of Places from Range Data using AdaBoost
Author :
Mozos, Oscar Martinez ; Stachniss, Cyrill ; Burgard, Wolfram
Author_Institution :
University of Freiburg, Department of Computer Science, D-79110 Freiburg, Germany
fYear :
2005
fDate :
18-22 April 2005
Firstpage :
1730
Lastpage :
1735
Abstract :
This paper addresses the problem of classifying places in the environment of a mobile robot into semantic categories. We believe that semantic information about the type of place improves the capabilities of a mobile robot in various domains including localization, path-planning, or human-robot interaction. Our approach uses AdaBoost, a supervised learning algorithm, to train a set of classifiers for place recognition based on laser range data. In this paper we describe how this approach can be applied to distinguish between rooms, corridors, doorways, and hallways. Experimental results obtained in simulation and with real robots demonstrate the effectiveness of our approach in various environments.
Keywords :
Buildings; Clustering algorithms; Computer science; Indoor environments; Laser beams; Mobile robots; Path planning; Robot sensing systems; Supervised learning; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
Type :
conf
DOI :
10.1109/ROBOT.2005.1570363
Filename :
1570363
Link To Document :
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