Invariant EKF Design for Scan Matching-aided Localization

Martin Barczyk 1 Silvère Bonnabel 1 Jean-Emmanuel Deschaud 1 François Goulette 1
1 CAOR - Centre de Robotique
Abstract : Localization in indoor environments is a technique that estimates the robot's pose by fusing data from onboard motion sensors with readings of the environment, in our case obtained by scan matching point clouds captured by a low-cost Kinect depth camera. We develop both an invariant extended Kalman filter (IEKF)-based and a multiplicative extended Kalman filter-based solution to this problem. The two designs are successfully validated in experiments and demonstrate the advantage of the IEKF design.
Keywords : Additive noise covariance matrices iterative closest point (ICP) algorithm Kalman filters least squares methods mobile robots state estimation.
Type de document :
Article dans une revue
IEEE Transactions on Control Systems Technology, Institute of Electrical and Electronics Engineers, 2015, 23 (6), pp.2440-2448. 〈10.1109/TCST.2015.2413933〉
Liste complète des métadonnées

Littérature citée [24 références]  Voir  Masquer  Télécharger
https://hal-mines-paristech.archives-ouvertes.fr/hal-01256770
Contributeur : François Goulette <>
Soumis le : vendredi 15 janvier 2016 - 12:23:12
Dernière modification le : lundi 12 novembre 2018 - 10:56:16
Document(s) archivé(s) le : samedi 16 avril 2016 - 10:32:50

Fichier

TCST.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

ENSMP | INSTITUT-TELECOM | ENSMP_CAOR | PARISTECH | PSL

Citation

Martin Barczyk, Silvère Bonnabel, Jean-Emmanuel Deschaud, François Goulette. Invariant EKF Design for Scan Matching-aided Localization. IEEE Transactions on Control Systems Technology, Institute of Electrical and Electronics Engineers, 2015, 23 (6), pp.2440-2448. 〈10.1109/TCST.2015.2413933〉. 〈hal-01256770〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

233

Téléchargements de fichiers

204

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD