Supervised Learning of Places from Range Data using AdaBoost
- 1 April 2005
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1730-1735
- https://doi.org/10.1109/robot.2005.1570363
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
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