The unparalleled scale of the PURT Facility enables cutting edge research in autonomy

NASA University Leadership Initiative: Secure and Safe Assured Autonomy (S2A2)

Diagram showing wind correction paths for drone flights

This project involves model checking, formal verification of autopilot software, and reachable set calculations. These can ensure flight mission safety by acccounting for uncertainties like wind. These methods can also prove the liveness property for several flight missions with multiple vehicles.

Technology Innovation Institute (TII)

In these projects, we're looking for ways to keep autonomous drones secure from cyberattack. We're mathematically analyzing vulnerabilities in urban UAS applications and developing ways to reliably detect and mitigate these attacks. We are also identifying methods to identify and map how GPS signals can reflect and cause multipath errors within an urban environment, creating a time-based trajectory based on satellite positions.

Cyber-Physical Security in a Smart City

Comparison of a camera-based drone navigation network and a ground-based radar station.

External vision-based UAS monitoring system

  • External vision-based UAS monitoring system
  • A network of auto-calibrated vision sensors with tracking accuracy within 0.5m
  • Leverages motion detection and machine learning to track non-cooperative targets
  • Delivery UAS cyberattack detection (GPS spoofing, hijacking)
  • Safety redundancy in urban navigation scenarios

Illustration showing GPS signal bouncing off a skyscraper and sending a bad location signal to a drone

GNSS emulation with multipath error

  • An open source solution to create more realistic urban GNSS properties for SITL and HITL simulation
  • Provide accurate testing environment for UAS safe urban navigation algorithm validation
  • Mapping GNSS multipath error of any city in simulation