The Intelligence Layer for Autonomous Drones
NavDome™ enables drones to navigate complex environments while building spatial intelligence that improves with every flight.
Navigation with Memory
NavDome™ is being designed as an autonomy infrastructure layer that turns drone flight data into reusable spatial and operational knowledge. Instead of treating each mission as an isolated event, NavDome™ is built around the idea that every flight should improve the next.
Over time, this creates a continuously improving system of maps, environmental understanding, and mission-aware intelligence that can support more reliable autonomy across drone platforms and real-world operations.
Persistent Spatial Memory
Designed to capture and retain spatial knowledge from real-world missions so future flights can build on prior experience.
Compounding Operational Intelligence
Mission data can be enriched with environmental, semantic, and operational context to improve how autonomous systems navigate over time.
Platform Integration
Built with the goal of integrating across drone platforms, enabling NavDome™ to serve as an intelligence layer within broader autonomous systems.
Developing in one of the most demanding environments for drone navigation
Rather than designing autonomy systems in ideal laboratory conditions, NavDome is being shaped within one of the most demanding environments drones operate in—exterior building maintenance.
Developing NavDome within this environment forces the system to solve some of the hardest navigation challenges encountered in real-world operations, creating a foundation designed to perform reliably across a wide range of autonomous drone applications.
Exterior maintenance operations combine several of the most challenging conditions in drone navigation.
Close proximity flight
Most drone missions—such as surveying, mapping, agriculture, and cinematography—occur tens to hundreds of meters away from structures. Cleaning drones operate within centimeters to a few feet of vertical surfaces, often continuously. This leaves very little margin for positional drift.
GPS and sensors become unreliable near buildings
Large buildings introduce GPS multipath reflection, magnetic interference, and visual feature ambiguity. Glass facades in particular create difficult conditions for vision-based navigation systems.
Precise repeatable flight paths
Cleaning operations require highly repeatable paths across the same surfaces. While inspection drones can tolerate small deviations, cleaning drones must maintain stable alignment along facades for extended periods.
Unstable airflow near tall structures
Flying close to large vertical surfaces introduces wall effects, turbulence, and wind shear. Airflow around tall structures can create unpredictable updrafts and lateral gusts.
Changing weight and drag during flight
Cleaning drones often carry water systems, hoses, or variable loads that change the drone’s mass distribution and drag characteristics during flight, complicating control stability.
Little room for error
When operating close to structures, small localization errors can result in collisions—especially around facade features such as ledges, window frames, or architectural protrusions.
The Backbone of Autonomous Aerial Intelligence
NavDome™ is being built as a foundation for a future in which autonomous drones continuously learn from every mission, building the shared spatial intelligence required for safe, reliable, and scalable aerial autonomy.