SBIR/STTR Research Award

SBIR Phase II: Reconstructing Consistently Detailed City-Scale Environments From Incomplete 2D and 3D Data

Award identifier eb160143f6ee7a6f8df059c70cf1b8a060246b818c8b9013baa8112068ccbaf1Awarding agency National Science Foundation

Award amount

$1,300,000

Program and phase

SBIR · Phase II

Award year

2019

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Geopipe, Inc.
Proposal award date
2019-05-15
Contract end date
2021-04-30
UEI
RVJDFJJLV3U7
Solicitation number
Not reported
Topic code
IT

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the ability to more completely understand the real world through a perfect virtual copy. This SBIR Phase II project makes it possible to create virtual reproductions of real cities that not only show how the world looks, but reproduce every object and every detail perfectly, allowing users to interact with it. These virtual copies make it possible to quickly and effectively train soldiers and first responders, train autonomous ground and flying vehicles, place new construction into a dense city, simulate the effects of catastrophic weather, and explore imaginary scenarios through games. Billions of dollars are already spent mapping and 3D modeling the real world for these and many other applications, but these virtual cities are created through painstaking manual methods that can take months to years, or lack necessary information about what is in the world. This SBIR Phase II project will make it possible to rapidly and automatically create detailed 3D copies of any area of the real world. This Small Business Innovation Research (SBIR) Phase II project will advance the state of the art in reconstructing highly detailed 3D models of the world for diverse commercial applications. This project introduces new methods for turning raw multimodal sensor data into semantic information describing the world and immersive, interactive-ready 3D models. It will remove the time, money, and manual effort necessary to create accurate 3D models of real world areas today, by using computer intelligence instead of human effort to parse sensor data like photographs and laser scans. The resulting 3D models and underlying semantic information describing the world will be used directly in game engines and simulation software, in analysis tools, in rendering software, and beyond. This research will build on the associated Phase I project, first improving the detail that can be identified and reproduced in virtual copies of the real world, then showing readiness for commercialization with paying customers. The result of the project will be a market-ready product for an initial market segment, capable of accurately reproducing real cities in 3D models that customers can readily use, as well as traction that demonstrates customer need for the product. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

3 SBIR/STTR records share this UEI (2017–2020). Reported award amounts total $1,574,009. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Science Foundation, Department of Defense

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.