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Markov Based Localization Device for a Mobile Robot

Franck Gechter 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This paper presents a vision based localization system which can be used on a wide range of mobile vehicles. The principle of the algorithm developed is to merge the information given by a vision system with the data extracted from the moves of the vehicle. The image processing level is performed by using principal components analysis that allows low cost position estimation by using a representative set of images obtained during an initial exploration of the environment. This set of images makes it possible to represent the environment as a partially observable Markov decision process. The originality of this approach is the resulting data fusion process that uses both image matching and decision made by the robot in order to estimate the set of plausible positions of the robot and the associated probabilities. Furthermore, this stochastic localisation device shows better results compared with the classical methods such as static neighborhoods. The main characteristics of this localization device are its robustness, its accuracy and its low cost compared with usual localization methods.
Mots-clés : vision robotique robotics. partially observable markov decision processes karhunen-loeve transform principal component analysis computer vision mobile vehicle pomdp robot mobile transformation de krhunen et loeve
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Conference papers
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https://hal.inria.fr/inria-00100551
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Submitted on : Tuesday, September 26, 2006 - 2:47:24 PM
Last modification on : Friday, February 26, 2021 - 3:28:04 PM

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  • HAL Id : inria-00100551, version 1

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INRIA | CNRS | LORIA | UNIV-LORRAINE

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Franck Gechter, François Charpillet. Markov Based Localization Device for a Mobile Robot. The 6th International Symposium on Artificial Intelligence, Robotics and Automation in Space: A New Space Odyssey - i-SAIRAS 2001, 2001, Montréal, Canada, 7 p. ⟨inria-00100551⟩

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