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ICAO’s RPAS/3 Symposium
EMERGING TECHNOLOGIES – the balance between legacy and innovation
Three breakthrough technology domains paving the way for the of
future aviation
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RPAS require evolution of legacy technologies …
Category ExamplesFlight control Antennas, Speed control, Flight controller,
embedded computersNavigation GPS, altimeter, accelerometer, gyroscopes,
magnetic compass, airspeed, positioning / image recognition cameras, obstacle sensors
Mission specific equipment HD camera, thermal camera, LIDAR, temperature sensors, weather sensors
This could be seen as an incremental evolution of a legacy technology portfolio … but it means significant and continuous progress in SWaP
(Size, Weight and Power) , cost and performance !
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… but also maturation of some specific ones
▌Collision avoidance / warning : “Sense & Avoid”
▌Automatic take-off & Landing (ATOL)
▌Communication systems : create or improve connectivity (incl. satellite communication for BVLOS operation, fulfilling spectrum demand), high availability and QoS
▌ Security : anti-jamming, anti-intrusion, “Geo fencing”
▌RPAS delivery : safety, airworthiness, Air Traffic Integration
▌Mission management : Command & Control, on-board / off-board allocation, automated operations : move towards full autonomy for RPAS
Strong innovation focus required in technology, regulation, procedures
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However, there are some key breakthrough ahead
UAS are at the heart of the Digital Transformation, where value comes from data
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2 UAS provide an advanced vision of the future of manned aviation, and pave the way for its future
3 As a result, UTM cannot be a legacy ATM continuity, it must embed data-driven approach and will transform future ATM
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4 key digital technologies to enable critical digital decision chains
Connectivity & IoT Big Data Artificial Intelligence Cybersecurity
Data collection KnowledgeLearning & evolving
Security of data, communication, Application, services, system
Big Data and AI are strongly interconnected, as well as dependent on cybersecurity and IoT/connectivity
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AI processes information but can be based on models and/or on data
Ability to process information by artificial means:
▌PerceiveRich, complex and subtle information
▌ LearnWithin an environment
▌AbstractTo create meanings
▌ReasonTo plan and decide
Two approaches to AI
Deep Learning
Acceleration 2012 - 2017
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Some key challenges of deep learning based AI
▌ChallengesTrust & security !Frugal LearningCombination of real data, simulated and synthetic data Corpus balancingVulnerability of open neural network architectures
▌Hybrid AIExplainable AIAI system validation and certification
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Hybrid AI: combining model and data based AIA key differentiator leading to trustable, then certifiable AI
Reasoning engine
ExplainableAI
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Steps towards autonomy
Autonomy
2025 2030
ExtendedSurveillance
UrbanLogistic
Operations
UrbanMobility
AssistedCrew
ReducedCrew
(e.g. SPO)
2
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Drones control : Moving Towards High Levels of Automation2
Aviation can leverage its safety background to implement a sound roadmap (automation, autonomy)
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“Functional Health Monitoring”
Operation Domain :proved “safe”,
“deterministic”
System management /
supervision
Operation Domain :
considered “normal”
Resilience will need new capabilities in system management, where supervision will monitor and organize system stability and reconfiguration
2
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Drones Redefine Airspace Usage in both Civil & Military Domains3
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ECOsystem UTM Supports Safe & Secure UAS OperationsThales UTM offer focused on Authority Side of problem
(managing access to public asset à airspace)
3
Blending the world-class digital technologies acquired by Thales with market leading ATM knowledge to shape an advanced but workable solution for UTM
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Drone Air Traffic Integration requires counter-UAV technologies
AVEILLANT Gamekeeper ”Holographic” Radar
▌ Mounted on hillside looking over Monaco and coastal area
▌ 90 degree coverage
▌ Instrumented to 5 km
3
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Thank you !
