AI Framework for Multimodal Scene Construction and Data Generation

Name: AI Framework for Multimodal Scene Construction and Data Generation
Creator: Department of Defense
Published: 2026-03-02T23:14:22.351474+00:00
Keywords: SBIR

Department of DefenseUSAF

AI Overview

The DoD seeks an AI framework generating high-fidelity, multimodal synthetic scenes for training autonomous systems and AI/ML models in realistic environments. The solution must integrate geospatial data with RF and EO/IR sensor simulations, ensuring spatial-temporal consistency and compatibility with existing tools like FLITES and Xpatch.

This summary is AI-generated from the official solicitation.

Key Details

Agency

Department of Defense

Funding Amount

—

Release Date

March 2, 2026

Due Date

June 3, 2026 (Closed)

Official Description

The DoD requires large-scale, high-fidelity background scenes to advance autonomous systems and Artificial Intelligence and Machine Learning (AI/ML) capabilities. These scenes are critical for providing realistic, context-rich environments that enable AI/ML and/or autonomous systems to learn, adapt, and perform effectively in real-world, dynamic conditions. A critical component of this effort is the ability to generate dynamic, high-fidelity background scenes that realistically model operational...

Change History

Opportunity RemovedJun 3, 2026 at 4:01 PM

AI Framework for Multimodal Scene Construction and Data Generation

Opportunity DAF26BZ01-DV005 no longer available

Q&A UpdatedMay 16, 2026 at 5:27 PM

AI Framework for Multimodal Scene Construction and Data Generation

# Q&A Changes Summary **New Answers Provided:** - **Q1 (AI Weather):** Clarified that weather-focused proposals are "Highly unlikely" to be responsive. - **Q2 (Feedback Loop):** Changed from pending to "To be discussed upon award." - **Q3 (Pass/Fail Criteria):** Clarified criteria exist "if available." - **Q4 (Phase 2 Prototype):** Added specifics—ROI should be large areas; no priority location list; end users include researchers, analysts, and planners. - **Q5 (Semantic Vocabulary):** No preferred vocabulary. - **Q6 (AI Models & Material Properties):** Clarified applicants should build own proxy models; government will provide material properties and standards where appropriate; flexibility on geospatial architecture (OpenUSD, OGC CDB, glTF, or novel approaches acceptable). **Key Clarifications:** Scope is broad (large areas, multiple end users); applicants bear responsibility for AI model development; government providing some material properties; flexible technical approach encouraged.

Q&A UpdatedMay 14, 2026 at 5:46 PM

AI Framework for Multimodal Scene Construction and Data Generation

Added 5 new Q&As: Q1 clarifies weather/atmospheric modeling as responsive scope; Q2-Q4 address feedback loops, pass/fail criteria, and end-user identification; Q5 requests semantic-class vocabulary guidance. Original Q2-Q4 renumbered as Q7-Q9 with identical answers. No substantive answer changes to existing questions.

Q&A UpdatedMay 12, 2026 at 7:39 PM

AI Framework for Multimodal Scene Construction and Data Generation

Added 1 new Q&A (Q1) with 3 detailed questions addressing: (1) whether AFRL provides baseline AI models/datasets or applicants must build their own; (2) availability of standardized material properties library for RF/thermal physics mapping; (3) AFRL's preference on geospatial data format standards (OpenUSD, OGC CDB, glTF, or novel schema).

Q&A UpdatedMay 9, 2026 at 10:22 PM

AI Framework for Multimodal Scene Construction and Data Generation

All three Q&As received answers. Key clarifications: (Q1) Linux deployment (containers or on-prem); (Q2) Details deferred to post-award kickoff, but confirms thermal imaging required, RF data both types needed, latest FLITES/Xpatch versions, converter acceptable, standardized format available, CUI/ITAR compliant solutions acceptable, development on applicant infrastructure; (Q3) Focus on scene fidelity, generation speed, and multimodal capability.

Q&A UpdatedMay 7, 2026 at 4:43 PM

AI Framework for Multimodal Scene Construction and Data Generation

**Summary of Q&A Changes:** Added new Q1 asking about software delivery format (container, standalone application, or other) and target computer system specifications. Original Q1 and Q2 renumbered to Q2 and Q3 respectively. No answers provided yet to any questions.

Q&A UpdatedMay 6, 2026 at 4:40 PM

AI Framework for Multimodal Scene Construction and Data Generation

**What Changed:** Replaced 1 broad question with 7 detailed technical questions covering: (1) data sourcing responsibilities, (2) thermal imaging requirements, (3) RF training data interpretation, (4) tool version compatibility, (5) scene file format handling, (6) standardized format preferences, and (7) security/infrastructure deployment. Original Q2 about gaps in prior efforts moved to end.

Q&A UpdatedMay 6, 2026 at 3:03 PM

AI Framework for Multimodal Scene Construction and Data Generation

# Summary This content seeks clarification on existing gaps in a capability area by asking applicants to identify what prior funded efforts have not yet achieved and what this new funding opportunity should address.

Status ChangedMay 6, 2026 at 1:47 PM