Artificial Intelligence (AI) Powered Adaptive Flight Controller for Novel Unmanned Aerial Vehicle (UAV) with Commercial and Humanitarian Applications

The project entails research into machine learning techniques to control unmanned aerial vehicles (UAVs) with complex flight characteristics for surveillance and cargo transportation applications. In addition, it advances networked UAV fleet control and optimization methodologies to improve the potential of UAV fleets to perform coordinated tasks efficiently and reliably.

Faculty Supervisor:

Davide Spinello

Student:

Nathaniel Mailhot

Partner:

Romaeris Corporation

Discipline:

Engineering - mechanical

Sector:

Aerospace and defense

University:

Program:

Accelerate

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