Detection and Compensation of Landmark Errors in Monte Carlo Localization

Abstract : This paper studies a new Monte Carlo vision-based localization algorithm which performs on-line detection and compensation of measurement biases. For that purpose, the state vector is augmented to include the mobile coordinates and orientation, but also discrete latent variables indicating the validity of each landmark angular measurement. An appropriate particle filter is then proposed to solve the resulting non-linear filtering problem. The efficiency of this filter is guarantied by using relevant models for the different kinds of systematic errors corrupting the angular measurements. Simulation results illustrate the gain of the proposed approach when compared to a more conventional method.
Type de document :
Communication dans un congrès
IEEE conference on Aerospace, Mar 2008, Big Sky, France. pp.10.1109/AERO.2008.4526443, 2008
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https://hal.archives-ouvertes.fr/hal-00339406
Contributeur : Audrey Giremus <>
Soumis le : lundi 17 novembre 2008 - 17:55:37
Dernière modification le : mercredi 12 septembre 2018 - 17:46:01

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  • HAL Id : hal-00339406, version 1

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Audrey Giremus, Rémi Mégret, Jean-Yves Tourneret. Detection and Compensation of Landmark Errors in Monte Carlo Localization. IEEE conference on Aerospace, Mar 2008, Big Sky, France. pp.10.1109/AERO.2008.4526443, 2008. 〈hal-00339406〉

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