Office of Naval Research (ONR) Immersive Sciences for Training, Education, Mission Rehearsal, and Operations | N00014 17 S F007

Frequently Asked Questions (FAQs)

1) What is this funding opportunity?

This is an Office of Naval Research (ONR) funding opportunity seeking white papers and full proposals for basic research under the program area "Immersive Sciences for Training, Education, Mission Rehearsal, and Operations."

2) What are the identifying details (Funding Opportunity Number and CFDA)?

The Funding Opportunity Number is N00014-17-S-F007 and the CFDA number is 12.300.

3) Which ONR organization is sponsoring the effort?

The opportunity is sponsored by ONR through its Expeditionary Maneuver Warfare and Combating Terrorism Science and Technology Department (Code 30).

4) Is ONR asking for white papers, full proposals, or both?

ONR is seeking both white papers and full proposals.

5) What is the main Navy and Marine Corps interest behind this program?

The practical, operational interest is to improve augmented reality (AR) and mixed reality in support of infantry training and real-world tasks, with a particular emphasis on small unit leaders such as squad leaders.

6) Is this opportunity aimed at delivering near-term fielded systems?

No. ONR is explicit that the effort is not primarily about delivering near-term fielded systems or product-like capability. It is focused on strengthening underlying science so future AR training and operational tools can be more effective, trustworthy, and scalable.

7) What are the core research challenge areas?

The opportunity is organized around three basic-research challenge areas: (1) automated generation of content and behaviors for AR and mixed reality, (2) measurement science for valid and objective measures of presence and immersion, and (3) human factors research to develop a taxonomy (and potentially broader theory) of visualization and interaction in AR.

8) What is the focus of Challenge Area 1 (automated content and behavior generation)?

This area focuses on reducing the time, cost, and specialized effort needed to create realistic 3D environments and populate them with relevant entities and plausible activity, with an emphasis on AR. The goal is to create tools and techniques that can extract and reconstruct usable 3D content from readily available sources, especially broadly accessible data such as crowd-sourced photos and videos found online.

9) What kinds of environment content does ONR want to see generated?

Desired outputs are not limited to static geometry. ONR cites interest in reconstructing terrain, roads, buildings, people, vehicles, and other environmental features needed to represent complex future operating environments, including dense urban and megacity settings.

10) Are improvements to existing methods (like photogrammetry) in scope?

Yes. ONR welcomes both entirely new approaches and meaningful improvements to existing methods such as photogrammetry.

11) Does Challenge Area 1 include behavior modeling?

ONR notes interest in technologies that can produce rough estimates of behavior patterns in an environment, while stopping short of full "pattern of life" modeling.

12) What is the focus of Challenge Area 2 (measurement science for presence and immersion)?

This area targets measurement techniques that provide valid, reliable, and objective measures of presence and immersion. ONR is highlighting a gap between common current practice (often subjective surveys or indirect proxies) and what is needed for rigorous research and training evaluation.

13) What limitations in current presence/immersion measurement does ONR point out?

ONR notes that many current approaches rely on subjective surveys or indirect proxies (behavioral or physiological measures) that may correlate with presence but do not directly quantify it.

14) What qualities should proposed presence/immersion measures have?

ONR emphasizes measures that are objective, sensitive, repeatable, and minimally invasive, enabling stakeholders to quantify presence relative to the real world or other baselines.

15) Does ONR want presence measurements linked to outcomes?

Yes. A key motivation is connecting presence to outcomes. ONR wants to understand how varying levels of presence influence training effectiveness and learning, and it implies interest in measures that support controlled comparison across systems, scenarios, and user populations.

16) What is the focus of Challenge Area 3 (human factors for AR visualization and interaction)?

This area is about developing a taxonomy (and potentially a broader theory) of visualization and interaction in AR. ONR observes that many AR interface prototypes exist (e.g., mid-air gestures, external controllers), but many have not been thoroughly evaluated through a human-factors lens.

17) What types of deliverables does ONR appear to be looking for in the human factors area?

Based on the description, the intent is to move beyond one-off demonstrations and produce structured classifications, experimentally supported design rules, and evaluation frameworks that help determine which visualization and interaction schemes work best, under what conditions, and for what tasks.

18) Who is eligible to apply as a prime applicant?

The FOA allows proposals from responsible sources in academia and industry. It specifically encourages participation from Historically Black Colleges and Universities (HBCUs) and Minority Institutions (MIs).

19) Is there a small business set-aside or other socio-economic set-aside?

No. The announcement states there is no set-aside for small businesses or other socio-economic categories under this opportunity.

20) Which organizations are not eligible to receive awards as prime recipients?

Federally Funded Research and Development Centers (FFRDCs), including Department of Energy national laboratories, are not eligible to receive awards as prime recipients. In addition, Navy laboratories, military universities and warfare centers, and other DoD or civilian government laboratories may not submit white papers or proposals directly.

21) Can federal laboratories or other government entities participate at all?

Yes. Those entities can participate through teaming arrangements with eligible prime applicants, provided the teaming structure is consistent with relevant sponsoring agreements and organizational constraints.

22) Are University Affiliated Research Centers (UARCs) eligible?

UARCs are generally eligible unless their DoD UARC contract terms prevent participation.

23) Does ONR encourage teaming and collaboration?

Yes. ONR encourages team proposals and signals an expectation of collaboration across the program ecosystem, including willingness to cooperate and exchange software, data, and other information with other contractors and ONR-selected system integrators as part of an integrated effort.

24) What does ONR say about sharing software, data, or information?

ONR indicates that, as part of an integrated effort, there is an expectation that performers will be willing to cooperate and exchange software, data, and other information with other contractors and ONR-selected system integrators.

25) Are there export control or ITAR considerations?

Yes. Export control compliance is flagged as a serious consideration. Applicants are responsible for ensuring compliance with International Traffic in Arms Regulations (ITAR) where applicable, and ONR notes that some DoD-funded developmental items may fall under the United States Munitions List (USML).

26) What should proposals say about ITAR restrictions?

Proposals are expected to address whether ITAR restrictions apply to the proposed work, including cases where research outputs could have both civilian and military applications.

27) What is the instrument type and activity category mentioned?

The instrument type is a grant, and it is listed under a science and technology research and development activity category.

28) What closing date is listed in the opportunity description?

The administrative details in the source listing include an original closing date of March 30, 2017.

29) Is the program explicitly more focused on AR, mixed reality, or both?

Both AR and mixed reality are included, but the first challenge area specifically emphasizes AR.

30) What kinds of data sources does ONR highlight for scalable 3D reconstruction?

ONR highlights "readily available sources" and especially broadly accessible data such as crowd-sourced photos and videos found online, in contrast to workflows dependent on niche skills or specialized hardware like LIDAR.