@inproceedings{485ba1bc393c4b8fb77996e3311dae21,
title = "Topology learning and recognition using Bayesian Programming for mobile robot navigation",
abstract = "This paper proposes an approach allowing topology learning and recognition in indoor environments by using a probabilistic approach called Bayesian Programming. The main goal of this approach is to cope with the uncertainty, imprecision and incompleteness of handled information. The Bayesian Program for topology recognition and door detection is presented. The method has been successfully tested in indoor environments with the BIBA robot, a fully autonomous robot. The experiments address both the topology learning and topology recognition capabilities of the approach.",
keywords = "Bayesian Programming, Door detection, Topology recognition",
author = "Adriana Tapus and Guy Ramel and Luc Dobler and Roland Siegwart",
year = "2004",
month = dec,
day = "1",
language = "English",
isbn = "0780384636",
series = "2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",
pages = "3139--3144",
booktitle = "2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",
note = "2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ; Conference date: 28-09-2004 Through 02-10-2004",
}