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Titel:

Off-Design Mission Performance Prediction for Unmanned Aerial Vehicles Based on Machine Learning

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Klaproth, Tim; Hornung, Mirko
Abstract:
This paper presents an approach to estimate the off-design mission performance of unmanned aerial vehicles (UAVs) using supervised machine learning. The basis of this work is a procedure for the mission-based design of civil UAVs. The procedure optimally tailors UAVs to exemplary design missions by evaluating their mission performance (sensor data quality, fuel demand, and detection probability of targets to be searched) inside a conceptual design optimization loop. This is achieved by carrying...     »
Stichworte:
ADEBO, UAV Mission Performance, Machine Learning
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Kongress- / Buchtitel:
2022 IEEE Aerospace Conference (AERO)
Jahr:
2022
Seiten:
1-13
Nachgewiesen in:
Scopus
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/AERO53065.2022.9843480
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