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Autoren:
Dudek, Adrian; Funk, Franziska; Russ, Martin; Stütz, Peter 
Dokumenttyp:
Konferenzbeitrag / Conference Paper 
Titel:
Cloud Detection System for UAV Sense and Avoid: First Results of Cloud Segmentation in a Simulation Environment 
Titel Konferenzpublikation:
2019 IEEE 5th International Workshop on Metrology for AeroSpace (MetroAeroSpace) 
Konferenztitel:
IEEE International Workshop on Metrology for AeroSpace (5., 2019, Turin) 
Konferenztitel:
MetroAeroSpace 
Tagungsort:
Turin 
Jahr der Konferenz:
2019 
Datum Beginn der Konferenz:
19.06.2019 
Datum Ende der Konferenz:
21.06.2019 
Jahr:
2019 
Seiten von - bis:
533-538 
Sprache:
Englisch 
Stichwörter:
Air traffic control ; Aircraft ; Autonomous aerial vehicles ; Avoid ; Cameras ; Cloud computing ; Cloud detection system ; Cloud distance estimation ; Cloud segmentation ; cCoud segmentation techniques ; Clouds ; Control engineering computing ; Electro-optical sensors ; Functional component ; Image edge detection ; Image segmentation ; Sense ; Simulation environment ; Synthetic images ; UAV ; UAV sense ; Unmanned aerial vehicles ; VFR ; Visual flight rules 
Abstract:
The following paper provides cloud segmentation techniques as a functional component to enable unmanned aerial vehicles (UAV) to automatically detect and avoid clouds using electro-optical sensors. The motivation here is that UAVs not operating under air traffic control have to comply with visual flight rules (VFR). Therefore, minimum distances to clouds must be respected. This paper presents an approach to cloud segmentation in order to facilitate future investigations of cloud distance estimat...    »
 
Fakultät:
Fakultät für Luft- und Raumfahrttechnik 
Institut:
LRT 13 - Institut für Flugsysteme 
Professur:
Stütz, Peter 
Open Access ja oder nein?:
Nein / No