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| Physics-Based Sensor Simulations |
| The development of modular, reuasable, physics-based synthetic environments and
sensor simulations represents the cutting edge of future training system
capability. RSC is actively engaged with USN/USMC, USAF, and USA in the
specification, development, and integration of these technologies. |
| Sensor-in-the-Loop
Simulations |
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RSC is a leading researcher in simulation-based sensor stimulation of
electro-optical sensors for training system applications. By producing
physics-based characterizations of commercial display systems, we have
implemented closed-loop simulations with greatly enhanced accuracy and realism.
The images below were collected from actual sensor video viewing an
RSC-developed synthetic scene. For available Virtual Terrain Board products see
VTB Price List.
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| Simulated clear star light scene injected into
night vision goggles |
Simulated quarter moon scene injected into night
vision goggles |
| Advanced Geospatial Metadata for
Simulation |
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Simulation systems for training and mission rehearsal rely on up-to-date and
relevant datasets (scene images and other data types) for immediate processing
into flyable runtime databases. Today's simulation requirements necessitate the
management of multi-Terabytes raw multi-spectral remote sensing data, refined
images, vector data, and cultural features. This data represents substantial
investment in data procurement by the Federal Government. Geospatial metadata,
the information that accompany the dataset, is critical in managing an
organization's internal investment in geospatial data. Under contracts from USN
and USAF, RSC is at the cutting edge of developing and deploying advanced
geospatial metadata standards intended for the simulation community. The
metadata is relevant to determine data discovery, data quality and fitness for
use, image lineage, access, and transfer.
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| Technology Transition |
RSC provides transfer of R&D results to advanced technology demonstrations
for the commercial and defense sectors. This includes RDT&E program
management support to the Department of Defense in the following areas:
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Acquisition Planning
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Procurement Cost, Schedule, and Budgetary analysis
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Training and Readiness (T&R) analysis
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Training Front-end, and Training Capability Gap analysis
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Cost-Benefit analysis, and Business Case Analysis (BCA)
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Modeling and Simulation test and evaluation support
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Independent Verification and Validation (IV&V)
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Risk Analysis
RSCs technology transition engagements include: the Office of Naval Research,
DARPA, Naval Research Lab, Air Force Research Laboratory (AFRL) Mesa, Army
Research Lab (ARL), and the Simulation Laboratories at NAWC AD, Patuxent River,
Maryland.
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| Control of Vehicle Formations |
| A vehicle formation is a set of spatially distributed, autonomous vehicles,
often called 'autonomous agents', whose dynamic states are coupled through a
common control law. RSC, together with its partners in the academia, is working
on innovative control concepts for such formations. The decentralized and
cooperative formation control law combines results from dynamical system
theory, control theory, and algebraic graph theory. This research area is of
interest in several areas. For example, NASA identified formation flying
technologies for multiple spacecraft as a critical part of for many of NASA's
21st century missions. Teams of autonomous robots are of interest in both the
civilian and defense sector.
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| Satellite formation flyer: NASA's
envisioned ST5 Nanosat Constellation Trailblazer. |
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A formation tracks its assigned trajectory and changes
orientation (simulation) |
| Intelligent Control |
| In many control applications the context varies during operation, where
'context' refers to parameters inherent to the plant, the environment, or both.
Fixed controllers, including 'robust' designs, are often insufficient with such
uncertainties present in plant and/or environment. The real-time adjustment of
controller parameters and/or controller structure, based on
measurements/observations, is an attractive control concept, generally referred
to as 'intelligent control'. Two such areas are adaptive control and learning
control, each with its own methods of controller adjustment. RSC staff is
engaged in R&D of intelligent control theory, applications, and associated
computational tools.
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