Information Sciences

Archived Tasks

The UARC oversees a broad range of Information Sciences research tasks (summarized below), with an emphasis on cross-disciplinary investigations. Current research focus areas include:

Software Engineering and Synthesis
Autonomous Systems and Robotics
Collaborative Information and Data Systems
Human-Centered Computing
Human Factors
Neuro-engineering Technologies
Knowledge Discovery and Data Mining
High-Performance and Distributed Computing
Advanced Networking

It is anticipated that the UARC’s work in this area will expand, as ARC leads in the development of advanced information technology, computer science, and computing technologies.

Archived Tasks :

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Evolvable Systems for Automated Spacecraft Design (ESASD)

Integrated System Health Management (ISHM)

Spoken Dialogue Systems for NASA Applications

Advanced Reasoning Systems for ISHM

HPC Institute for Advanced Rotorcraft Modeling and Simulation (HI-ARMS)

Bioengineering Branch Research and Development

Current Tasks

Evolvable Systems for Automated Spacecraft Design (ESASD)

This project supports the first Exploration Systems cycle of innovation within the Software, Intelligent Systems, and Modeling (SISM) Element Program, and also the Advanced Space Technology Program (ASTP). This task develops, tests, validates and delivers advanced automated hardware design, optimization, and reconfiguration algorithms to address unique requirements for sustainable human and robotic exploration missions, thereby enabling NASA spacecraft to achieve dramatic improvements in performance, robustness, cost, and environment adaptability. As stated in an article titled “Machines found catching up to human intelligence” in the Perspective section of the Taiwan News on November 25, 2005:

“The AI software examined millions of potential antenna designs before settling on a final one," said Jason Lohn, the lead scientist on the project at NASA's Ames Research Center in Mountain View, California. "Through a process patterned after Darwin's survival of the fittest, the strongest designs survive and the less capable do not."

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Integrated System Health Management (ISHM)

Many NASA enterprises have identified a critical need for Integrated System Health Management (ISHM) techniques to provide autonomous (and in some cases automatic) operation of space systems. ISHM is a key enabling technology for the success of the nation's space exploration vision. Within NASA, Ames leads the way in developing model-based diagnosis and recovery techniques that support ISHM. The Autonomy and Diagnostics task focuses on extending these existing techniques as well as developing new techniques that support the ISHM needs of ESMD space exploration missions.

The overall research vision focuses on the use of stochastic and hybrid (discrete + continuous, qualitative + quantitative) models describing the structural, transitional, and behavioral properties of devices, sub-systems, systems, and “systems of systems.” In addition, the project incorporates research into modeling rigorous statistical methods (e.g., Bayesian reasoning) for uncertainty management. These models will be used to detect when off-nominal conditions occur; to isolate and identify faults responsible for the off-nominal conditions; and then to synthesize recovery actions to ensure crew safety and maximize mission goal achievement in the presence of the identified faults. These techniques will be initially demonstrated on power distribution system test-beds being developed at Ames.

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Data Mining

This project covers various approaches to searching, characterizing, interpolating within, and reasoning about, very large datasets. These datasets are often multivariate, being made up of multiple observations that are temporally or spatially related. Examples of such datasets include:

Images and other data from various NASA missions observing Earth, other planets, and interplanetary space.
Text data.
Simulation data.

Standard problems in the field include:

Intelligent compression: If the data can be fully or partially explained by some physical behavior, or if the data vary in a predictable way, it may be possible to achieve very high rates of compression. This saves storage and time in handling large datasets.
Interpolation: Developing approximation techniques to provide data at arbitrary locations.
Sampling: Determining the “best” locations for obtaining additional data.

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IMAGEBot:

The overall goal of the IMAGEBot project is development of a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system. By providing agent-based automation not only of ecological forecasting, but also of the post-processing on model outputs needed to visualize the results, this project seeks to facilitate rapid data exploration and “what-if” analyses. These types of capabilities will be essential to fully achieve the promise of a Sensor Web, in which huge volumes of real-time data are used to support activities ranging from basic science to monitoring and tracking severe weather and critical events.

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REGULUS:

The main goal of the REGULUS project is to develop enabling technology to make language modeling accessible to domain experts who are not familiar with computational linguistics. This will involve the creation of extensive documentation, tutorial materials, and implemented examples. Work will be carried out in collaboration with other NASA groups that wish to acquire expertise in the development of spoken language interfaces, so that development can be tailored to their needs.

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Spoken Dialog Images

It has become clear that spoken dialogue systems are a key technology for current and future NASA projects. These have the promise of enabling humans to easily interact with complex diagnostic and control systems, which will greatly multiply astronaut effectiveness. The Spoken Dialog Systems task supports the development of spoken language interfaces to robotic planners and execution modules; conversational interfaces to planetary exploration missions (Mobile Agents); conversational control of Advanced EVA suits; and conversations between teams of agents and humans.

There have been numerous press releases associated with the successful testing onboard the International Space Station on June 27, 2005, of Clarissa, developed as part of the Spoken Dialog Systems task. This advanced spoken-dialog system reads the steps of a procedure to an astronaut; answers questions; and responds to spoken commands.

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Spoken Dialogue Systems for NASA Applications

Spoken dialogue systems have emerged as a key technology for NASA’s present and future projects. They have the promise of allowing humans to easily interact with complex diagnostic and control systems, thereby multiplying astronaut effectiveness.

The Research in Advanced Language Interfaces and Speech Technology group (RIALIST) focuses on spoken dialogue interfaces to semi-autonomous agents and complex systems. RIALIST makes use of established speech and language technology (such as the Nuance recognizer and the SRI Gemini and Open Agent Architecture) and also pursues new research and development in areas such as dialogue management and specialized language models. Technologies for spoken dialogue interfaces will be developed in areas such as speech recognition, language models and grammars, dialogue modeling, generation, and speech synthesis, and applied to a variety of NASA missions and applications.

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Advanced Reasoning Systems for ISHM

The task will support the development and deployment of novel real-time reasoning systems for fault detection and isolation in the Advanced Diagnostics and Prognostics Testbed (ADAPT) laboratory of NASA Ames Research Center. The task will measure and evaluate system performance—including real-time responses, footprint, and fault coverage—based on the ADAPT framework. The task will also explore other potential applications of advanced reasoning tools and technologies in the context of deployed complex health management systems. Finally, the task will investigate other deployment opportunities and platforms for these reasoning tools, including other NASA ground or flight testbeds and flight vehicles.

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HPC Institute for Advanced Rotorcraft Modeling and Simulation (HI-ARMS)

The goal of HI-ARMS is to transform the current “analysis-test” paradigm in the U.S. rotorcraft industry and government laboratories into one built around High Performance Computing (HPC). HI-ARMS will enable domestic manufacturers of rotary-winged aircraft to create effective designs (or upgrades) of rotorcraft systems while minimizing development cost and risk. It will also enable the Department of Defense to accurately predict mission capability, improve the effectiveness of vehicle test programs and effectively conduct rotorcraft source selection processes.

This UARC task will provide technical expertise in the areas of turbulence modeling, Detached Eddy Simulation, low-Mach number preconditioning and the numerical accuracy and parallel/scalable efficiency of algorithms employed and developed in near-body and off-body software products.

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Bioengineering Branch Research and Development

The Ames Bioengineering Branch is responsible for the development and analysis of advanced life support technologies and systems for use in space as well as applications of these technologies to problems on Earth. The scope of the branch activities includes development of technologies for air revitalization, water purification, solid waste processing, protective systems technology for individuals, systems analysis and software tools associated with these technologies, as well as bionanotechnology development. The branch staff includes expertise in the appropriate physical/chemical and biological disciplines who are assembled into teams that address each of these areas.

This task will include the investigation of novel physical, chemical and biological processes for the design and development of life support technologies for applications in space. The effects of performance parameter variations, subsystem interactions and functional tradeoffs will be evaluated during development of life support and protective systems technologies. The results of these studies will provide input for evaluating alternate approaches as well as aiding in the design and development of the integrated life support and protective systems required for human missions supporting the Vision for Space Exploration. In addition, analytical simulation and experimentation will be used to evaluate new concepts, analyze proposed modifications, define gaps in required capabilities, and develop new bionanotechnology processes.

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Research Areas: