Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
Real time degradation identification of UAV using machine learning techniques
MANUKYAN, Anush; OLIVARES MENDEZ, Miguel Angel; Geist, Matthieu et al.
2017In International Conference on Unmanned Aircraft Systems ICUAS. Miami, USA, 2017
Peer reviewed
 

Documents


Texte intégral
ICUAS_Real_Time_Deg_Ident_UAV.pdf
Postprint Éditeur (1.67 MB)
Télécharger

Tous les documents dans ORBilu sont protégés par une licence d'utilisation.

Envoyer vers



Détails



Mots-clés :
UAV; Quadrotor; Degradation identification; Machine learning; kNN; DTW; Real-Time
Résumé :
[en] The usages and functionalities of Unmanned Aerial Vehicles (UAV) have grown rapidly during the last years. They are being engaged in many types of missions, ranging from military to agriculture passing by entertainment and rescue or even delivery. Nonetheless, for being able to perform such tasks, UAVs have to navigate safely in an often dynamic and partly unknown environment. This brings many challenges to overcome, some of which can lead to damages or degradations of different body parts. Thus, new tools and methods are required to allow the successful analysis and identification of the different threats that UAVs have to manage during their missions or flights. Various approaches, addressing this domain, have been proposed. However, most of them typically identify the changes in the UAVs behavior rather than the issue. This work presents an approach, which focuses not only on identifying degradations of UAVs during flights, but estimate the source of the failure as well.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Automation & Robotics Research Group
Disciplines :
Sciences informatiques
Auteur, co-auteur :
MANUKYAN, Anush ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
OLIVARES MENDEZ, Miguel Angel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Geist, Matthieu;  Université de Lorraine > Laboratoire Interdisciplinaire des Environnements Continentaux
VOOS, Holger  ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Real time degradation identification of UAV using machine learning techniques
Date de publication/diffusion :
13 juin 2017
Nom de la manifestation :
International Conference on Unmanned Aircraft Systems ICUAS
Lieu de la manifestation :
Miami, FL, Etats-Unis
Date de la manifestation :
From 13-06-2017 to 16-06-2017
Manifestation à portée :
International
Titre de l'ouvrage principal :
International Conference on Unmanned Aircraft Systems ICUAS. Miami, USA, 2017
Maison d'édition :
IEEE
Peer reviewed :
Peer reviewed
Disponible sur ORBilu :
depuis le 10 novembre 2017

Statistiques


Nombre de vues
204 (dont 14 Unilu)
Nombre de téléchargements
983 (dont 14 Unilu)

citations Scopus®
 
12
citations Scopus®
sans auto-citations
12
citations WoS
 
0

Bibliographie


Publications similaires



Contacter ORBilu