Stefano Cecchi
Modeling of a machine learning-based virtual copilot for helicopters.
Rel. Elisa Capello, Gianluca Parnisari. Politecnico di Torino, Master of science program in Aerospace Engineering, 2024
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Abstract
The aviation industry has always searched for new solutions to make air transport safer and more efficient. As technology develops rapidly, different needs and challenges occur. In this sense, Artificial Intelligence (AI) has opened new horizons. Exploring present and future possible AI contributions, this thesis aims to develop an onboard AI suitable for helicopter pilot co-handling to reduce pilot workload. Drawing insights from flight manuals and previous studies, it becomes evident that helicopter pilots encounter numerous critical phases during flight. It was chosen to investigate three critical use cases: predicting Vortex Ring State (VRS), detecting engine malfunctions, and aiding pilots during autorotation scenarios.
Each of these cases presents unique challenges in aviation safety and operational efficiency
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