Comparison of EKF and PEKF in a SLAM context

Abstract : This paper introduces an implementation of the Polynomial Extended Kalman Filter (PEKF) to solve the Simultaneous Localization and Map building (SLAM) problem. The proposed solution is a filtering algorithm which is a polynomial transformation of state evolution and measurement equations. The performances of the algorithm have been evaluated through two simulation runs. The first ones underline consistency improvement in comparison with the standard Extended Kalman Filter. The other simulation results show the PEKF efficiency when the values of measurement noises are high. At the end, experiments with Victoria Park data are presented too.
Type de document :
Communication dans un congrès
11th IEEE International Conference on Intelligent Transportation Systems, Oct 2008, Beijing, China. pp.203, 2008
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https://hal.archives-ouvertes.fr/hal-00343543
Contributeur : Paul Checchin <>
Soumis le : lundi 1 décembre 2008 - 23:13:06
Dernière modification le : lundi 8 octobre 2018 - 11:40:01

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  • HAL Id : hal-00343543, version 1

Citation

François Chanier, Paul Checchin, Christophe Blanc, Laurent Trassoudaine. Comparison of EKF and PEKF in a SLAM context. 11th IEEE International Conference on Intelligent Transportation Systems, Oct 2008, Beijing, China. pp.203, 2008. 〈hal-00343543〉

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