N. Aghannan, On invariant asymptotic observers, Proceedings of the 41st IEEE Conference on Decision and Control, 2002., pp.10-13, 2002.
DOI : 10.1109/CDC.2002.1184728
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.65.5942

M. Barczyk, Invariant EKF Design for Scan Matching-Aided Localization, IEEE Transactions on Control Systems Technology, vol.23, issue.6, pp.2440-2448, 2015.
DOI : 10.1109/TCST.2015.2413933
URL : https://hal.archives-ouvertes.fr/hal-01256770

A. Barrau, Intrinsic Filtering on Lie Groups With Applications to Attitude Estimation, IEEE Transactions on Automatic Control, vol.60, issue.2, pp.436-449, 2015.
DOI : 10.1109/TAC.2014.2342911
URL : http://arxiv.org/abs/1310.2539

S. Bonnabel, Non-Linear Symmetry-Preserving Observers on Lie Groups, IEEE Transactions on Automatic Control, vol.54, issue.7, pp.1709-1713, 2009.
DOI : 10.1109/TAC.2009.2020646
URL : http://arxiv.org/pdf/0707.2286v2.pdf

S. Bonnabel, Invariant Extended Kalman Filter: theory and application to a velocity-aided attitude estimation problem, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, pp.16-18, 2009.
DOI : 10.1109/CDC.2009.5400372
URL : https://hal.archives-ouvertes.fr/hal-00494342

S. Bonnabel, Symmetry-Preserving Observers, IEEE Transactions on Automatic Control, vol.53, issue.11, p.53, 2008.
DOI : 10.1109/TAC.2008.2006929
URL : https://hal.archives-ouvertes.fr/hal-00449206

G. Bourmaud, Discrete extended Kalman filter on Lie groups, Proceedings of the 21st European, 2013.
DOI : 10.1007/s10851-014-0517-0
URL : https://hal.archives-ouvertes.fr/hal-00903252

G. Bourmaud, Continuous-Discrete Extended Kalman Filter on Matrix Lie Groups Using Concentrated Gaussian Distributions, Journal of Mathematical Imaging and Vision, vol.2, issue.11???12, 2014.
DOI : 10.1007/s10851-014-0517-0
URL : https://hal.archives-ouvertes.fr/hal-01311170

J. Condomines, Pi-Invariant Unscented Kalman Filter for sensor fusion, 53rd IEEE Conference on Decision and Control, pp.15-17, 2014.
DOI : 10.1109/CDC.2014.7039518
URL : https://hal.archives-ouvertes.fr/hal-01109001

J. Condomines, Nonlinear state estimation using an invariant unscented Kalman filter, AIAA Guidance, Navigation, and Control (GNC) Conference, pp.19-21, 2013.
DOI : 10.2514/6.2013-4869
URL : https://hal.archives-ouvertes.fr/hal-00933568

J. P. Condomines, Optimal Invariant Observers Theory for Nonlinear State Estimation. Multisensor Attitude Estimation Fundamental Concepts and Applications Edited by, pp.391-408, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01395580

J. L. Crassidis, Survey of Nonlinear Attitude Estimation Methods, Journal of Guidance, Control, and Dynamics, vol.30, issue.1, pp.12-28, 2007.
DOI : 10.2514/1.22452

J. L. Crassidis, Optimal Estimation of Dynamic Systems, 2004.
DOI : 10.1201/9780203509128

S. Diemer, An invariant Linear Quadratic Gaussian controller for a simplified car, 2015 IEEE International Conference on Robotics and Automation (ICRA), pp.26-30, 2015.
DOI : 10.1109/ICRA.2015.7139037

S. Hauberg, Unscented Kalman filter on Riemannian manifolds, J. Math. Imaging Vis, pp.1-18, 2013.

S. J. Julier, Unscented Filtering and Nonlinear Estimation, Proceedings of the IEEE (Invited Paper), pp.401-422, 2004.
DOI : 10.1109/JPROC.2003.823141
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.6539

A. Khosravian, Observers for invariant systems on Lie groups with biased input measurements and homogeneous outputs, Automatica, vol.55, pp.55-74, 2015.
DOI : 10.1016/j.automatica.2015.02.030

D. Li, Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors, Micromachines, vol.81, issue.4, pp.487-522, 2015.
DOI : 10.1007/s00138-005-0006-y

P. Martin, Invariant observers for attitude and heading estimation from low-cost inertial and magnetic sensors, 2007 46th IEEE Conference on Decision and Control, pp.12-14, 2007.
DOI : 10.1109/CDC.2007.4435006
URL : https://hal.archives-ouvertes.fr/hal-00533306

Q. Rentmeesters, An efficient particle filtering technique on the Grassmann manifold, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010.
DOI : 10.1109/ICASSP.2010.5495828

S. Sarkka, On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems, IEEE Transactions on Automatic Control, vol.52, issue.9, pp.1631-1641, 2007.
DOI : 10.1109/TAC.2007.904453

H. Snoussi and A. Mohammad-djafari, Particle Filtering on Riemannian Manifolds, AIP Conference Proceedings, p.219, 2006.
DOI : 10.1063/1.2423278
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.645.8210

F. Tompkins and P. Wolfe, Bayesian Filtering on the Stiefel Manifold, 2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2007.
DOI : 10.1109/CAMSAP.2007.4498015