layout University Affiliated Research Center - UC Santa Cruz - NASA Ames Research Center

Information Sciences

Advanced information technology in support of NASA’s space exploration and aerospace missions

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.

Autonomy and Diagnostics

Integrated System Health Management (ISHM) is a key enabling technology for the success of the nation's space exploration vision. Many NASA enterprises have identified a critical need for ISHM techniques to provide autonomous (and in some cases automatic) operation of space systems. 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 space exploration missions. These techniques will be initially demonstrated on power distribution system test-beds being developed at Ames.

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Semantics-Based Information Management

This task is designed to infuse semantic technologies into NASA missions. Focal applications include the SemanticOrganizer information repository system, the SemanticIntegrator information integration system, the Mobile Agents exploration system and the Constellation Command, Control, Communications, and Information (C3I) Architecture. This task involves research and development in support of new capabilities, including:

  • Automatic creation of semantic nodes and links by analyzing text sources.
  • Automated methods of aligning overlapping but distinct ontologies.
  • Semantic integration of data stored within distributed data sources, including databases, web sources and remote services. 
  • Parsing, geospatial tracking and display of real-time, semantically-relevant events and activities.
  • Methods to facilitate the semantic interoperation of software systems. 

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Learning in Complex Systems

Many NASA missions involve designing, controlling, and/or optimizing complex, one-of-a-kind systems. This task will develop new and improved techniques for modeling, learning, controlling and diagnosing complex systems in service of the needs of NASA’s ESMD and ARMD research programs. Activities will focus on:

  • Distributed optimization techniques.
  • Methods for learning in dynamic/noisy environments.
  • Methods for achieving coordinated behavior in large distributed systems.

The technical challenge is to go beyond current control, optimization and multi-agent learning methods that generally assume reliable components, full communication among subsystems and a noise-free environment. Potential applications include airspace management and multi-rover/UAV coordination. 

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Engineering/Software Support for Aero-Acoustics

The design of advanced flight vehicles requires a growing spectrum of computational and experimental methods to optimize overall mission performance, improve safety and minimize developmental and operational costs. The project takes a multidisciplinary approach, drawing concepts and technologies from information technologies, aerospace design, materials engineering, and mathematical modeling. A specific goal of this task is research, data analysis, and reporting related to aerodynamic and acoustic wind tunnel studies. One component will be the development of improved capability to measure the flow properties in the Ames arcjet facility, supporting the Constellation Program and CEV/Orion Project in particular.

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Strategic and Tactical Activity Planning Tool Development

This task is developing automated speech recognition software as part of the uplink and activity planning functions used for the remote command and control of the Mars Exploration Rover (MER). The project will provide better-designed interfaces for planning and implementing MER activities, including development of a new uplink tool called SPIFe, which will also be applicable to other missions.

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Conversational Interfaces and Control

This task will conduct research and development supporting conversations between people and agents in collaborative tasks, focused on meeting the 2007 needs of NASA’s Exploration Technology Development programs, including “Human-Systems Interaction” and “Spacecraft and Vehicle Autonomy”. Under this initiative, technologies are being developed in areas such as speech recognition, language models and grammars, dialogue modeling, generation and speech synthesis. As demonstrated in prototype experiments, these technologies will serve a variety of NASA needs, including science data management, mission operations, and semi-autonomous robotic agents.

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Automated Design Using Evolvable Hardware

This project has two technical thrusts. The first is to develop radhard reconfigurable control software and hardware technologies, including reconfigurable fault-tolerant, FPGA-capable control technologies to support the high reliability, low power operation for long duration exposures in the space radiation environment. The second area uses advanced design and optimization algorithms to mitigate radiation and low-temperature induced failures in FPGA devices, custom analog integrated circuits and other electronics. The team will mature a suite of fault-mitigating technologies in support of CEV and lunar exploration missions.

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Time Series Analysis and Prognostics

This task will involve the performance of time series analysis and prognostics on data that represents the operation of complex engineering systems primarily as part of the Aeronautics Research Mission Directorate (ARMD) Integrated Vehicle Health Management (IVHM) program. This task will involve experimenting with known algorithms on such data and will also involve development of new algorithms. The new algorithms will likely first be tested on publicly-available benchmark datasets and then, after determining that the algorithms work properly, they will be tested on data from complex engineering systems.

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