Learning Topological Maps: An Alternative Approach
Conference Paper, Proceedings of 13th National Conference on Artificial Intelligence and 8th Innovative Applications of Artificial Intelligence Conference (AAAI '96/IAAI '96), pp. 1380, August, 1996
Abstract
Our goal is autonomous real-time control of a mobile robot. In this paper we want to show a possibility to learn topological maps of a large-scale indoor environment autonomously. In the literature there are two paradigms how to store information on the environment of a robot: as a grid-based (geometric) or as a topological map. While grid-based maps are considerably easy to learn and maintain, topological maps are quite compact and facilitate fast motion-planning.
BibTeX
@conference{Buecken-1996-16234,author = {A. Buecken and Sebastian Thrun},
title = {Learning Topological Maps: An Alternative Approach},
booktitle = {Proceedings of 13th National Conference on Artificial Intelligence and 8th Innovative Applications of Artificial Intelligence Conference (AAAI '96/IAAI '96)},
year = {1996},
month = {August},
pages = {1380},
}
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