Opportunity Information: Apply for 13 SN 0005

  • The Office of Naval Research in the science and technology and other research and development sector is offering a public funding opportunity titled "Special Program Announcement for 2013 Basic Research Challenges in the Science of Autonomy" and is now available to receive applicants.
  • Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 12.300 Basic and Applied Scientific Research.
  • This funding opportunity was created on Mar 11, 2013 and posted on Dec 6, 2012.
  • Applicants must submit their applications by Mar 25, 2013. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
  • The funding agency has allocated a total of $5,200,000.00 to eligible and selected applicants.
  • Each selected applicant is eligible to receive up to $150,000.00 in funding.
  • The number of recipients for this funding is limited to 10 candidate(s).
  • Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.
Apply for 13 SN 0005

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Opportunity Summary:

The Office of Naval Research (ONR) announced this Special Program Announcement as a discretionary funding opportunity to support 6.1 basic research in the science of autonomy, with an emphasis on foundational, cross-disciplinary problems that matter for naval operations. The core idea is to advance the underlying science that enables autonomous systems to perceive, decide, learn, and operate effectively across multiple domains, including air, sea, undersea, and ground platforms. Rather than focusing on near-term product development, the announcement is aimed at fundamental research challenges that cut across scientific and engineering disciplines and that can unlock new capabilities for the Navy over the long run.

The program identifies five specific research thrusts. The first is "Understanding satisficing in human, animal, and engineered autonomous systems for fast decision making with limited data." This thrust is about how real-world decision makers (including biological and engineered ones) make good-enough choices quickly when information is incomplete, time is limited, and collecting more data is costly or impossible. The intent is to uncover principles, models, and algorithms that allow autonomous systems to behave robustly under uncertainty, using limited observations while still producing effective decisions.

The second thrust is "Cognitively compatible semantic and visual representation of autonomous system perceptual data for effective human/machine collaboration." Here the focus is on how autonomous systems represent what they sense (for example, sensor feeds, detections, tracks, and scene interpretations) in ways that align with human cognition. The goal is better human-machine teaming: systems that can communicate what they perceive and intend in forms that are meaningful to operators, support trust and transparency, and reduce cognitive burden. This includes both semantic representations (meaningful labels, relations, and concepts) and visual representations (displays and visualizations) that help humans understand and collaborate with autonomous platforms.

The third thrust is "Mental simulation as a unifying framework for perception, cognition and control in autonomous systems and dexterous robots." This area emphasizes internal modeling and simulation as a mechanism for intelligent behavior. It points to autonomy that can predict outcomes, imagine future states, evaluate alternative actions, and link perception with planning and control. The mention of dexterous robots highlights manipulation and fine motor control, where the ability to internally simulate object interactions and motion can be central to reliable performance in complex environments.

The fourth thrust is "Structured machine learning for scene understanding." This thrust targets learning methods that exploit structure in the world, such as spatial relationships, hierarchies, constraints, geometry, and context. The intent is scene understanding that goes beyond detecting isolated objects and instead reasons about how elements relate, what is happening, and what those relationships imply for navigation, mission execution, and safety. Structured learning approaches can help with generalization, data efficiency, and interpretability, all of which are important for autonomy in operational settings.

The fifth thrust is "Integrated autonomy for long duration operations." This area is about autonomy that can persist over long time horizons with minimal intervention, which is especially relevant for naval missions that may require extended endurance, remote operations, limited communications, and resilience to changing conditions. Integrated autonomy implies bringing together perception, decision making, learning, system health management, and mission adaptation so the platform can remain effective for long periods despite uncertainty, wear, environmental variability, and shifting objectives.

From an administrative and funding perspective, the opportunity is identified as Funding Opportunity Number 13 SN 0005 under CFDA 12.300 (Basic and Applied Scientific Research). ONR anticipated making about 10 awards, with total estimated funding of $5,200,000. Individual awards were expected to fall roughly between $100,000 (floor) and $150,000 (ceiling). The announcement states there is no cost sharing or matching requirement, and eligibility is described as unrestricted, meaning it is broadly open to different types of applicant entities as long as they meet any conditions described in the full announcement.

Key dates included an initial posting on December 6, 2012, with creation information recorded March 11, 2013. The original closing date was April 8, 2013, but the current closing date listed is March 25, 2013, with an archive date of May 8, 2013. The funding instruments referenced include grants and procurement contracts, indicating ONR could support work through different award mechanisms depending on the nature of the proposed effort and contracting approach. For applicants needing help accessing the full announcement, the listed point of contact was Contracting Officer Lynnette Desorcie at 703-696-4324, with an email address provided in the announcement, and ONR also pointed applicants to a link compiling ONR BAAs and related opportunities for further details.

Frequently Asked Questions (FAQs)

1) What is this funding opportunity?

This is a Special Program Announcement from the Office of Naval Research (ONR) offering discretionary funding to support 6.1 basic research in the science of autonomy, with an emphasis on foundational, cross-disciplinary problems relevant to naval operations.

2) What does "6.1 basic research" mean in the context of this announcement?

In this announcement, 6.1 refers to basic research. The stated intent is to advance underlying scientific principles and approaches that enable autonomy, rather than focusing on near-term product development.

3) What is the main goal of the program?

The program aims to advance the underlying science that enables autonomous systems to perceive, decide, learn, and operate effectively across multiple domains (air, sea, undersea, and ground), in ways that matter for naval operations over the long run.

4) Is this opportunity focused on building deployable products or prototypes?

No. The announcement emphasizes fundamental research challenges and specifically notes that it is not focused on near-term product development.

5) What research areas (thrusts) does ONR identify in this announcement?

The announcement identifies five research thrusts:

  • Understanding satisficing in human, animal, and engineered autonomous systems for fast decision making with limited data
  • Cognitively compatible semantic and visual representation of autonomous system perceptual data for effective human/machine collaboration
  • Mental simulation as a unifying framework for perception, cognition and control in autonomous systems and dexterous robots
  • Structured machine learning for scene understanding
  • Integrated autonomy for long duration operations

6) What does the "satisficing" thrust focus on?

This thrust focuses on how real-world decision makers (human, animal, and engineered) make good-enough decisions quickly when data are limited, time is constrained, and collecting more information is costly or not possible. The stated intent is to uncover principles, models, and algorithms enabling robust autonomous behavior under uncertainty using limited observations.

7) What does "cognitively compatible semantic and visual representation" mean here?

This thrust focuses on representing autonomous system perceptual data (such as sensor feeds, detections, tracks, and scene interpretations) in ways that align with human cognition. The goal is better human-machine collaboration through meaningful semantic representations (labels, relations, concepts) and visual representations (displays, visualizations) that support trust, transparency, and reduced cognitive burden.

8) What is meant by "mental simulation" as a framework for autonomy and dexterous robots?

This thrust emphasizes internal modeling and simulation as a mechanism for intelligent behavior, including predicting outcomes, imagining future states, evaluating alternative actions, and linking perception with planning and control. The mention of dexterous robots highlights manipulation and fine motor control where simulating object interactions and motion can be central to reliable performance.

9) What is "structured machine learning for scene understanding" in this program?

This thrust targets learning methods that exploit structure in the world, including spatial relationships, hierarchies, constraints, geometry, and context. The intent is to support scene understanding that reasons about relationships and activity (not just isolated object detection), with relevance to navigation, mission execution, and safety. The announcement notes structured approaches can improve generalization, data efficiency, and interpretability.

10) What does "integrated autonomy for long duration operations" cover?

This thrust focuses on autonomy that can persist over long time horizons with minimal intervention, relevant to missions requiring extended endurance, remote operations, limited communications, and resilience to changing conditions. "Integrated autonomy" is described as bringing together perception, decision making, learning, system health management, and mission adaptation so platforms remain effective over long periods despite uncertainty and variability.

11) What operational domains are referenced as relevant to this autonomy research?

The announcement explicitly references autonomous systems operating across multiple domains, including air, sea, undersea, and ground platforms.

12) What is the Funding Opportunity Number and CFDA number for this announcement?

The opportunity is identified as Funding Opportunity Number 13 SN 0005 under CFDA 12.300 (Basic and Applied Scientific Research).

13) How many awards does ONR expect to make?

ONR anticipated making about 10 awards under this announcement.

14) What is the estimated total funding for the program?

The total estimated funding amount listed is $5,200,000.

15) What is the expected size of individual awards?

Individual awards were expected to range from roughly $100,000 (floor) to $150,000 (ceiling).

16) Is cost sharing or matching required?

No. The announcement states there is no cost sharing or matching requirement.

17) Who is eligible to apply?

Eligibility is described as unrestricted, meaning it is broadly open to different types of applicant entities, as long as they meet any conditions described in the full announcement.

18) What types of funding instruments may ONR use for awards?

The announcement references grants and procurement contracts as funding instruments, indicating ONR could support work through different award mechanisms depending on the proposed effort and contracting approach.

19) What are the key dates listed for this opportunity?

  • Initial posting date: December 6, 2012
  • Creation information recorded: March 11, 2013
  • Original closing date: April 8, 2013
  • Current closing date listed: March 25, 2013
  • Archive date: May 8, 2013

20) The announcement shows different closing dates. Which one applies?

Based on the information provided, the original closing date was April 8, 2013, but the current closing date listed is March 25, 2013. Applicants would need to rely on the current closing date shown in the listing and confirm details in the full announcement.

21) Who is the point of contact for help accessing the full announcement?

The listed point of contact is Contracting Officer Lynnette Desorcie at 703-696-4324. An email address is also provided in the announcement.

22) Is there a place ONR points applicants to for related opportunities or more details?

Yes. ONR pointed applicants to a link compiling ONR BAAs and related opportunities for further details.

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