A probabilistic model for appearance-based robot localization

Reference : A probabilistic model for appearance-based robot localization


	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/11078

Title :	A probabilistic model for appearance-based robot localization
Language :	English
Author, co-author :	Krose, B. J. A. [> >]
	Vlassis, Nikos [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Bunschoten, Roland [> >]
	Motomura, Y. [> >]
Publication date :	2001
Journal title :	Image and Vision Computing
Publisher :	Elsevier Science
Volume :	19
Issue/season :	6
Pages :	381-391
Peer reviewed :	Yes (verified by ORBi^lu)
ISSN :	0262-8856
Keywords :	[en] robot localization ; feature extraction ; probabilistic modeling
Abstract :	[en] In this paper we present a method for an appearance-based modeling of the environment of a mobile robot. We describe the task (localization of the robot) in a probabilistic framework. Linear image features are extracted using a Principal Component Analysis. The appearance model is represented as a probability density function of the image feature vector given the location of the robot. We estimate this density model from the data with a kernel estimation method. We show how the parameters of the model influence the localization performance. We also study how many features and which features are needed for good localization. (C) 2001 Elsevier Science B.V. All rights reserved.
Permalink :	http://hdl.handle.net/10993/11078

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