SBIR/STTR Research Award

Artic Small-Unmanned Aerial System Automatic Ground Control Point Processing for Terrain Modeling

Award identifier 3a02d1006bd16cd292580002275eb92ecd31b68163d1a6cd29a53f3776aa17c0Awarding agency Department of Defense · Army

Award amount

$203,689

Program and phase

STTR · Phase I

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
ESC AEROSPACE US, INC
Proposal award date
2025-03-04
Contract end date
2025-09-04
UEI
SUR9AK1VMNM1
Solicitation number
24.B
Topic code
A24B-T017

Research abstract

esc Aerospace and Photon-X have teamed to provide a unique, low SWaP-C vision system with incorporated artificial intelligence and machine learning (AI&ML) capability that enables data collection and orthomosaic creation in featureless environments.At the core of this capability is Photon-X’s patented 3D shape-based AI&ML Spatial Phase Imaging (SPI)technology. SPI provides an unmatched AI&ML capability to identify, classify, and track small “objects.” From aerial and ground targets at distances greater than 50 KM, to closeup inspection of small imperfections in surfaces, to ridges on a fingerprint, this innovative and unique sensor system is a perfect match of this topic application.The SPI software executes directly and measures the direct surface and its orientation. Each pixel on the array becomes a multi-vector tensor with X,Y,Z, Index, specular/diffuse, etc. which creates a rapid and efficient surface algorithm. What makes SPI different?SPI is a patented technology to extract a full 3D surface from a sensor with angular information at each pixel. Each super pixel determines the pixel orientation and then calculates the pixel-to-pixel surface flows. Both LiDAR and stereo optical vision sensors use a method to extract a “point-cloud” either based on reflected light or correspondence points. This makes these technologies less efficient and less accurate. Unlike a more traditional point-cloud visual representation, SPI goes directly to the surface and pixel relationships to one another. We have then developed algorithms to measure real-time “surface flow.” In doing so, we can easily identify any changes in pixel relationships/slopes of individual surfaces and edges on a surface/object. We can operate with real-time normals and corrected for lighting and specular diffuse surfaces such as snow fields and other “featureless” terrains.

Technology keywords

Not reported

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Agency intelligence

Department of Defense

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