Reference : Real time degradation identification of UAV using machine learning techniques

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/32968

Title :	Real time degradation identification of UAV using machine learning techniques
Language :	English
Author, co-author :	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)]
Publication date :	13-Jun-2017
Main document title :	International Conference on Unmanned Aircraft Systems ICUAS. Miami, USA, 2017
Publisher :	IEEE
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	International Conference on Unmanned Aircraft Systems ICUAS
Event date :	From 13-06-2017 to 16-06-2017
Event place (city) :	Miami, FL
Event country :	USA
Keywords :	[en] UAV ; Quadrotor ; Degradation identification ; Machine learning ; kNN ; DTW ; Real-Time
Abstract :	[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.
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Automation & Robotics Research Group
Target :	Researchers ; Professionals ; Students ; General public ; Others
Permalink :	http://hdl.handle.net/10993/32968

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