SBIR/STTR Research Award

Non-Emitting Autonomous ISR Mission Capability With AI Object Identification Onboard Unmanned Aerial System

Award identifier bca69a43a3078061886992b3d0a6276faee749e9047ffdff4d4af6e3e554d953Awarding agency Department of Defense · Air Force

Award amount

$1,249,988

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
Flyby Robotics
Proposal award date
2025-05-22
Contract end date
2027-02-22
UEI
V4W9XEKCVL18
Solicitation number
X25.5
Topic code
AFX255-DPCSO2

Research abstract

Special Operations Forces rely on unmanned systems to conduct battlefield intelligence, surveillance and reconnaissance missions without endangering the lives of servicemen. But today’s unmanned systems require operators to emit frequencies from a ground station in order to initiate missions — a dangerous liability that, in the age of electronic warfare, can allow the adversary to easily geolocate and target the warfighter. To mitigate this risk, operators need an unmanned system capable of initiating and executing stealth ISR mission sets without connecting to a ground station. To best support ISR operations, this unmanned system must have AI/ML capabilities permitting autonomous flight as well as AI-powered object identification.Flyby Robotics is the developer of the F-11D, a massively ML-capable Group 2 UAS built around a NVIDIA Jetson Orin GPU with 100 trillion operations per second (TOPS) of processing power. This ML capability supports an APNT (alternative positioning, navigation and timing) GPS navigation feature, among others. Built with a modular, open-architecture design, the F-11D supports Multi-Mission Set Battlefield Sustainment, facilitating rapid battlefield innovation to adapt to emerging threats and evolving adversary tactics.Within the next 21 months, Flyby Robotics will deliver a fully autonomous, non-emissive ISR capability on the F-11D to the U.S. Air Force. Operators will pre-load an area of operations (AO) geofence and target identification parameters—such as enemy armored vehicles—via ethernet or USB. Once deployed, the F-11D will use onboard machine learning (ML) capabilities to interpret user gestures for launch, eliminating the need for active ground station control. The drone will then execute a serpentine waypoint patrol, scanning the AO for targets of interest. Upon mission completion, the F-11D will autonomously return, land, and provide operators with an on-map visualization of identified threats, such as the location of enemy tanks. This technology will allow U.S. forces to maintain operational effectiveness in GPS- and comms-denied environments while reducing exposure to enemy detection and engagement.

Technology keywords

Not reported

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Agency intelligence

Department of Defense

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