Invariant Unscented Kalman Filter with application to attitude estimation - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Invariant Unscented Kalman Filter with application to attitude estimation

(1) , (2) , (3)
1
2
3

Résumé

The Invariant UKF, named IUKF, is a recently introduced algorithm dedicated to nonlinear systems possessing symmetries as illustrated by the quaternion-based kinematics modeling of a mini-UAV (Unmanned Aircraft Vehicle) considered in this paper. Within an invariant framework, this algorithm suggests a systematic approach to determine all the symmetry-preserving terms, without requiring any compatibility condition such as proposed in the PI-IUKF, by introducing both notion of invariant output errors and UKF algorithm formulation. We propose in this paper to evaluate the applicability of our proposed IUKF observer to the caseof attitude estimation for small UAVs using low-cost sensors. The IUKF algorithm is successfully validated in experiments and demonstrates that nonlinear state estimation converges on a much bigger set of trajectories than for more traditional approaches.
Fichier principal
Vignette du fichier
LCSS_2017_IUKF.pdf (2.19 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01509884 , version 1 (08-06-2017)

Identifiants

Citer

Jean-Philippe Condomines, Cédric Seren, Gautier Hattenberger. Invariant Unscented Kalman Filter with application to attitude estimation. CDC 2017, 56th IEEE conference on decision and control, Dec 2017, Melbourne, Australia. pp.ISBN: 978-1-5090-2874-0, ⟨10.1109/CDC.2017.8264063⟩. ⟨hal-01509884⟩
175 Consultations
662 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More