Vision-based Gyroscope Fault Detection for UAVs - Archive ouverte HAL
Communication Dans Un Congrès Année : 2019

Vision-based Gyroscope Fault Detection for UAVs

Résumé

This paper presents a vision-based fault detection and isolation architecture for unmanned aerial vehicles. The vehicle’s attitude is computed from visual input through a horizon tracking algorithm, independently of any other sensor. In a second stage, two Kalman filters are used for fault detection and identification in two gyroscopes. The loosely coupled architecture is suitable for real-time application. The algorithm was implemented with the ROS framework and the system’s performance is evaluated in a real-time application scenario with artificially introduced sensor faults.
Fichier principal
Vignette du fichier
Simlinger_Ducard_IEEESAS2019_acceptedversion.pdf (864.45 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
Copyright (Tous droits réservés)

Dates et versions

hal-02143320 , version 1 (16-11-2023)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Benedict Simlinger, Guillaume Ducard. Vision-based Gyroscope Fault Detection for UAVs. 2019 IEEE Sensors Applications Symposium (SAS), IEEE, Mar 2019, Sophia Antipolis, France. pp.1-6, ⟨10.1109/SAS.2019.8705965⟩. ⟨hal-02143320⟩
69 Consultations
52 Téléchargements

Altmetric

Partager

More