|Artificial Intelligence in Cockpits for UAVs|
|Applied Vehicle Technology|
AI, big data, Certification Process, data fusion, flight control, path planning, UAS
Operational and logistics requirements in the ‘new defence’ are resulting in complex data analytics environments that hinder timely command and control decisions. Human performance limitations need to be addressed adequately and proactively in order to anticipate, adapt and act in machine-time rather than human-time scales.
In order to respond to some of these concerns, advances in Artificial Intelligence (AI) and Autonomous Air Systems need to be explored and exploited to improve the operational readiness of NATO. There is a need to formulate questions and quantify performance metrics on the ‘new defence’ requirements and devise strategies to adapt the topology in response to the paradigm shift in military conflicts.
The project proposes to explore AI enhanced Guidance, Navigation and Control (GNC) of Autonomous Air Systems to promote trust in autonomous decision making by exploring the underlying theory, mathematics, computational models, systems integration and field applications.
The objective of this activity is to create a shared understanding between experts of different technologies in order to improve level of autonomy of UAV through analysis, on board, of all data available.
• Cooperative and non-cooperative systems
• Guidance, Navigation and Control
• Path planning
• Data fusion and deep learning
• Sensor-craft design: integration of sensors in platforms
• Data acquisition, storage, and processing
• Big data, machine learning, data fusion and artificial intelligence
• Flight control and flight assistance technologies
• Human-machine interface
• Certification process