SBIR/STTR Research Award

RAPID: Realistic Assessment of Performance in Devices

Award identifier b8fc0672135494d1948a34b00f1aebae06472664e378b63e971f29bd0bed3e12Awarding agency Department of Defense · Air Force

Award amount

$150,000

Program and phase

SBIR · Phase I

Award year

2012

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
APTIMA INC
Proposal award date
2011-12-29
Contract end date
Not reported
UEI
K1GCPNNZKEN7
Solicitation number
2011.2
Topic code
AF112-023

Research abstract

ABSTRACT: As the Air Force responds to high demands for Remotely Piloted Aircraft (RPA) operations, devices and strategies for effectively training Pilots and Sensor Operators are likely to increase in importance. While simulation-based training is available, little is known regarding the training effectiveness trade-offs of devices, environments, and/or methods. Current tools and processes for evaluating effectiveness lack the flexibility and automation required for providing quick, clear, and useful training guidance in light of technological improvements and changes to key missions. Thus, a Realistic Assessment of Performance in Devices (RAPID) Tool, an automated, data-driven, model-based decision support tool that is continually refined and validated, is required to provide training developers and acquisitions professionals clear recommendations on how to effectively train RPA operators. The RAPID Tool will leverage, enhance, and integrate proven technologies to accelerate automation of processes and models to produce a single source that will comprehensively analyze the effectiveness of existing and future RPA training solutions (e.g., devices, environments, and methods). When fully implemented, the RAPID Tool"s data-driven, automated, and continually refined models will support environment/device trade-off analyses, recommend blending learning strategies, and enable rapid assessment and characterization of training devices and tools in relation to desired training outcomes. BENEFIT: The results of our Phase I and II activities will be the RAPID Tool, an automated and adaptable tool that facilitates rapid, data driven analyses of the effectiveness of training environments and devices in relation to RPA training objectives. Specifically, the RAPID Tool will facilitate and house the automatic processing of objective performance data to continually refine and validate its underlying model of the relationships of relevant training environment characteristics and devices to training objectives. In support of training developers, the RAPID Tool will provide recommended training strategies for achieving desired outcomes effectively and efficiently leveraging a variety of training environments, tools, and devices as applicable. To acquisition professionals, the RAPID Tool will provide a data driven analysis of the training effectiveness trade-offs of current and future devices, including consideration of non-traditional fidelity variables that are important in RPA training environments. While we will develop a tool customized to meet the needs and challenges of Air Force RPA operations, our approach is designed to be generalizable and applicable to other DoD agencies and commercial organizations who share some common challenges with the Air Force: (1) high demand for achieving training objectives in environments besides live missions (e.g. high consequences for errors); (2) uncertainty regarding which training devices, environments, and methods effectively train which training objectives; and (3) limited resources to achieve operational training objectives.

Technology keywords

Not reported

Awards with the same topic code

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Research funding history

520 SBIR/STTR records share this UEI (1997–2025). Reported award amounts total $208,057,185. Reported amounts are not federal obligations.

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

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Transportation, Department of Energy, Department of Homeland Security

Agency intelligence

Department of Defense

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