Neural Network Based Runway Landing Guidance for General Aviation Autoland

Balduzzi, Giovanni; Ferrari Bravo, Martino; Chernova, Anna; Cruceru,Calin; van Dijk, Luuk; de Lange, Peter; Jerez, Juan; Koehler, Nathanaël; Koerner, Mathias; Perret-Gentil, Corentin; Pillio, Zoltan; Polak, Ruben; Silva, Hugo; Valentin, Romeo; Whittington,Ian; Yakushev, Grigory; Daedalean AG

doi:10.21949/1524481

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Neural Network Based Runway Landing Guidance for General Aviation Autoland

2021-11-27
By Balduzzi, Giovanni ; Ferrari Bravo, Martino ; Chernova, Anna ; ...

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Creators:

Balduzzi, Giovanni ; Ferrari Bravo, Martino ; Chernova, Anna ; Cruceru,Calin ; van Dijk, Luuk ; ... More +

Balduzzi, Giovanni ; Ferrari Bravo, Martino ; Chernova, Anna ; Cruceru,Calin ; van Dijk, Luuk ; de Lange, Peter ; Jerez, Juan ; Koehler, Nathanaël ; Koerner, Mathias ; Perret-Gentil, Corentin ; Pillio, Zoltan ; Polak, Ruben ; Silva, Hugo ; Valentin, Romeo ; Whittington,Ian ; Yakushev, Grigory Less -
Corporate Creators:

Daedalean AG
Corporate Contributors:

United States. Department of Transportation. Federal Aviation Administration. William J. Hughes Technical Center
Subject/TRT Terms:

[+]

Artificial Intelligence Computer Vision Landing Aids Machine Learning
Publication/ Report Number:

DOT/FAA/TC-21/48
DOI:

https://doi.org/10.21949/1524481
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Department of Transportation. Federal Aviation Administration. William J. Hughes Technical Center
Abstract:

The results of a year-long research project on a vision-based runway landing guidance system based on Artificial Intelligence / Machine Learning / Neural Networks are presented in this report. An in-depth presentation of the system is provided, followed by an analysis of its performance on flight tests and through the W-shaped process for learning assurance.
Format:

PDF
Funding:

692M15-20-H-00002
Collection(s):

FAA Technical Library
Main Document Checksum:

[+]

urn:sha256:8a0bad19e81f9b2ec9d825f56ad013a23ef54568fbc124c372390a442b6f205a
Download URL:

https://rosap.ntl.bts.gov/view/dot/62210/dot_62210_DS1.pdf
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Neural Network Based Runway Landing Guidance for General Aviation Autoland

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