SBIR/STTR Research Award

Synthetic Data Generation For Autonomous On-Orbit Docking AI/ML Solutions

Award identifier aade16e3a186e96a56c7db26ba354b1696e6f7831b3bcc35798c1c9f8ee34c87Awarding agency Department of Defense · Air Force

Award amount

$249,820

Program and phase

STTR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
LEXSET.AI INC
Proposal award date
2022-08-11
Contract end date
2023-01-11
UEI
CJLFZ2FMV7P9
Solicitation number
X21.S
Topic code
AF21S-TCSO1

Research abstract

Explore Space Ops requirements to create a training data solution to enable Computer Vision algorithms that support systems for autonomous docking with objects on orbit and debris remediation. Lexset’s platform employs cutting edge technologies from simulation and computer graphics to enable rapid configurations of complex domains, and enables the user to make instant changes to a specific dataset to train CV algorithms. The company is seeking to adapt their ‘earthbound’ generation platform to space applications. This will include exploring how to integrate a physics engine that simulates movement of objects in space onto their existing platform

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

7 SBIR/STTR records share this UEI (2022–2025). Reported award amounts total $5,224,225. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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