Clément Chahbazian — accepted AI-conference papers

2022

Generalized Laplace Particle Filter on Lie Groups Applied to Ambiguous Doppler Navigation

Clément Chahbazian, Nicolas Merlinge, Karim Dahia, Bénédicte Winter-Bonnet, Aurélien Blanc, Christian Musso

IROS 2022poster

Particle filters are suited to solve nonlinear and non-Gaussian estimation problems which find numerous applications in autonomous systems navigation. Previous works on Laplace Particle Filter on Lie groups (LG-LPF) demonstrated its robustness and accuracy on challenging navigation scenarios compare…

Cited by 4 Source ↗Scholar ↗

2022

Improved Kalman-Particle Kernel Filter on Lie Groups Applied to Angles-Only UAV Navigation

Clément Chahbazian, Karim Dahia, Nicolas Merlinge, Bénedicte Winter-Bonnet, Kévin Honore, Christian Musso

ICRA 2022poster

Kalman-Particle Kernel Filter (KPKF) is a sub-class of Particle Filter (PF) that uses Gaussian kernels as particles, which enables a local Kalman update for each measurement in addition to the usual weight update. Besides, recent research about filtering on Lie groups brought powerful theoretical re…

Cited by 6 Source ↗Scholar ↗

2020

A real-time unscented Kalman filter on manifolds for challenging AUV navigation

Théophile Cantelobre, Clément Chahbazian, Arnaud Croux, Silvère Bonnabel

IROS 2020poster

We consider the problem of localization and navigation of Autonomous Underwater Vehicles (AUV) in the context of high performance subsea asset inspection missions in deep water. We propose a solution based on the recently introduced Unscented Kalman Filter on Manifolds (UKF-M) for onboard navigation…

Cited by 34 Source ↗Scholar ↗