O. Martinez Mozos, C. Stachniss, and W. Burgard

Supervised Learning of Places from Range Data using Adaboost

Proc. of the IEEE International Conference on Robotics and Automation (ICRA)


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.

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Bibtex 

@string{ICRA = "Proc. of the IEEE International Conference on Robotics and Automation (ICRA)"}

@InProceedings{martinez05icra,
   TITLE =	 {Supervised Learning of Places from Range Data using Adaboost},
   AUTHOR =	 {Mart\'{i}nez Mozos, O. and Stachniss, C. and Burgard, W.},
   BOOKTITLE =	 ICRA,
   YEAR =	 {2005},
   PAGES =        {1742--1747},
}