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

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.
NVG-CSL NVG-QM
Simulated clear star light scene injected into night vision goggles Simulated quarter moon scene injected into night vision goggles

Advanced Geospatial Metadata for Simulation

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.

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:
  • Acquisition Planning
  • Procurement Cost, Schedule, and Budgetary analysis
  • Training and Readiness (T&R) analysis
  • Training Front-end, and Training Capability Gap analysis
  • Cost-Benefit analysis, and Business Case Analysis (BCA)
  • Modeling and Simulation test and evaluation support
  • Independent Verification and Validation (IV&V)
  • 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.

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.
Nanosat formation_path_and_orientation
Satellite formation flyer: NASA's envisioned ST5 Nanosat Constellation Trailblazer. 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.