Artificial Intelligence is advancing data-driven approaches to sensor fusion and state estimation, as well as downstream decision-making, but its role in Positioning, Navigation and Timing (PNT) remains unresolved.
This event will explore how modern AI techniques, including deep learning, probabilistic modelling, and emerging foundation models, are being applied to core PNT challenges such as signal processing, multi-sensor fusion, and navigation in GNSS-denied or degraded environments (e.g. indoor settings, urban canyons, or contested RF conditions).
Bringing together experts from academia, industry, and startups, the session will critically examine:
- The integration of AI with traditional model-based navigation frameworks
- Robustness, explainability, and uncertainty quantification in safety-critical systems
- The use of learned representations for spatial awareness and localisation
- Whether concepts such as ‘foundation models’ can be effectively applied to navigation problems.
Attend to:
- Gain insights into how AI is being applied to modern navigation systems
- Hear perspectives from leading researchers and industry innovators
- Explore real-world PNT challenges and emerging opportunities
- Understand the current limits and future potential and risks of AI in navigation
- Network with the UK’s PNT and spatial AI community
Who Should Attend?
This event is ideal for professionals and researchers working in:
- Navigation and positioning technologies
- AI and machine learning
- Autonomous systems and robotics
- Telecommunications and spatial data
- Standards, policy, and innovation
Event Fees:
Employees of Cambridge Wireless member organisations can attend for free
Members of the Royal Insitute of Navigation can attend this event for free, to claim your free delegate place please email Clare Kettle.
Tickets for non-members are £50 plus VAT.
