Unsupervised Fault Detection on Unmanned Aerial Vehicles: Encoding and Thresholding Approach †

Unmanned Aerial Vehicles are expected to create enormous benefits to society, but there are safety concerns in recognizing faults at the vehicle’s control component. Prior studies proposed various fault detection approaches leveraging heuristics-based rules and supervised learning-based models, but...

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Detalles Bibliográficos
Autores principales: Park, Kyung Ho, Park, Eunji, Kim, Huy Kang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004241/
https://www.ncbi.nlm.nih.gov/pubmed/33809830
http://dx.doi.org/10.3390/s21062208

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004241/
https://www.ncbi.nlm.nih.gov/pubmed/33809830
http://dx.doi.org/10.3390/s21062208

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