Torens, Christoph und Jünger, Franz und Schirmer, Sebastian und Schopferer, Simon und Maienschein, Theresa Diana und Dauer, Johann C. (2022) Machine Learning Verification and Safety for Unmanned Aircraft - A Literature Study. In: AIAA SciTech 2022 Forum. AIAA SCITECH 2022 Forum, 2022-01-03 - 2022-01-07, San Diego, California. doi: 10.2514/6.2022-1133. ISBN 978-162410631-6.
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Offizielle URL: https://arc.aiaa.org/doi/10.2514/6.2022-1133
Kurzfassung
Machine learning (ML) has proven to be the tool of choice for achieving human-like or even super-human performance with automation on specific tasks. As a result, this data-driven approach is currently experiencing massive interest in all industry domains. This increased use also applies for the safety critical aviation domain. With no human pilot on board, the potential use cases of ML for unmanned aircraft are particularly promising. Even upcoming Urban Air Mobility (UAM) concepts are planning to remove the onboard pilot and instead use ML to support a remote pilot, possibly supervising a fleet of vehicles. However, the verification of ML algorithms is a challenging problem, since established safety standards and assurance methods are not applicable. Thus, this work comprises a literature study on the topic of ML verification and safety. This research paper uses a systematic approach to map and categorize the research and focus on specific subtopics that are of particular interest in the context of existing guidance documents.
elib-URL des Eintrags: | https://elib.dlr.de/148341/ | ||||||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||||||
Titel: | Machine Learning Verification and Safety for Unmanned Aircraft - A Literature Study | ||||||||||||||||||||||||||||
Autoren: |
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Datum: | 3 Januar 2022 | ||||||||||||||||||||||||||||
Erschienen in: | AIAA SciTech 2022 Forum | ||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||||||||||
DOI: | 10.2514/6.2022-1133 | ||||||||||||||||||||||||||||
ISBN: | 978-162410631-6 | ||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||
Stichwörter: | literature study, machine learning, verification and validation, certification, safety-critical, taxonomy, artificial intelligence | ||||||||||||||||||||||||||||
Veranstaltungstitel: | AIAA SCITECH 2022 Forum | ||||||||||||||||||||||||||||
Veranstaltungsort: | San Diego, California | ||||||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||||||
Veranstaltungsbeginn: | 3 Januar 2022 | ||||||||||||||||||||||||||||
Veranstaltungsende: | 7 Januar 2022 | ||||||||||||||||||||||||||||
Veranstalter : | AIAA SCITECH 2022 Forum | ||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||
HGF - Programm: | Luftfahrt | ||||||||||||||||||||||||||||
HGF - Programmthema: | Komponenten und Systeme | ||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Luftfahrt | ||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | L CS - Komponenten und Systeme | ||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | L - Unbemannte Flugsysteme | ||||||||||||||||||||||||||||
Standort: | Braunschweig | ||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Flugsystemtechnik > Unbemannte Luftfahrzeuge Institut für Flugsystemtechnik | ||||||||||||||||||||||||||||
Hinterlegt von: | Torens, Christoph | ||||||||||||||||||||||||||||
Hinterlegt am: | 01 Feb 2022 13:38 | ||||||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:46 |
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