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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

A systematic approach to the application of Automation, Robotics, and Machine Intelligence Systems /ARAMIS/ to future space projects

The potential applications of Automation, Robotics, and Machine Intelligence Systems (ARAMIS) to space projects are investigated, through a systematic method. In this method selected space projects are broken down into space project tasks, and 69 of these tasks are selected for study. Candidate ARAMIS options are defined for each task. The relative merits of these options are evaluated according to seven indices of performance. Logical sequences of ARAMIS development are also defined. Based on this data, promising applications of ARAMIS are

Smith, D. B. S.↗
NASA NTRS1991

A hierarchical distributed control model for coordinating intelligent systems

A hierarchical distributed control (HDC) model for coordinating cooperative problem-solving among intelligent systems is described. The model was implemented using SOCIAL, an innovative object-oriented tool for integrating heterogeneous, distributed software systems. SOCIAL embeds applications in 'wrapper' objects called Agents, which supply predefined capabilities for distributed communication, control, data specification, and translation. The HDC model is realized in SOCIAL as a 'Manager'Agent that coordinates interactions among application Agents. The HDC Manager: indexes the capabilities of application Agents; routes request messages to suitable server Agents; and stores results in a commonly accessible 'Bulletin-Board'. This centralized control model is illustrated in a fault diagnosis application for launch operations support of the Space Shuttle fleet at NASA, Kennedy Space Center.

Adler, Richard M.↗
NASA NTRS2002

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

Lin, Paul P.↗
NASA NTRS1987

Mixed-initiative control of intelligent systems

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data.

Borchardt, G. C.↗
NASA NTRS1982

Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Supplement, Appendix 4.3: Candidate ARAMIS Capabilities

Potential applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and to their related ground support functions, in the years 1985-2000, so that NASA may make informed decisions on which aspects of ARAMIS to develop. The study first identifies the specific tasks which will be required by future space projects. It then defines ARAMIS options which are candidates for those space project tasks, and evaluates the relative merits of these options. Finally, the study identifies promising applications of ARAMIS, and recommends specific areas for further research. The ARAMIS options defined and researched by the study group span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

Miller, R. H.↗
NASA NTRS1998

Field Guide for Designing Human Interaction with Intelligent Systems

The characteristics of this Field Guide approach address the problems of designing innovative software to support user tasks. The requirements for novel software are difficult to specify a priori, because there is not sufficient understanding of how the users' tasks should be supported, and there are not obvious pre-existing design solutions. When the design team is in unfamiliar territory, care must be taken to avoid rushing into detailed design, requirements specification, or implementation of the wrong product. The challenge is to get the right design and requirements in an efficient, cost-effective manner. This document's purpose is to describe the methods we are using to design human interactions with intelligent systems which support Space Shuttle flight controllers in the Mission Control Center at NASA/Johnson Space Center. Although these software systems usually have some intelligent features, the design challenges arise primarily from the innovation needed in the software design. While these methods are tailored to our specific context, they should be extensible, and helpful to designers of human interaction with other types of automated systems. We review the unique features of this context so that you can determine how to apply these methods to your project Throughout this Field Guide, goals of the design methods are discussed. This should help designers understand how a specific method might need to be adapted to the project at hand.

Malin, Jane T.↗
NASA NTRS1982

Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Application of ARAMIS capabilities to space project functional elements

Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities and their related ground support functions are studied, so that informed decisions can be made on which aspects of ARAMIS to develop. The specific tasks which will be required by future space project tasks are identified and the relative merits of these options are evaluated. The ARAMIS options defined and researched span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

Miller, R. H.↗
NASA NTRS2004

Demonstrating Robotic Autonomy in NASA's Intelligent Systems Project

This paper will provide an overview of NASA's investments in autonomy during the past five years within the Intelligent Systems Project, with particular attention paid to investments that have resulted in mission infusion of autonomy technology, in particular, into the recent Mars Exploration Rover (MER) mission. The content of the paper will be divided into two primary topic areas: a technical overview of the component technologies developed under the program, and a programmatic overview of the history and organization of the NASA IS project itself, with a focus on describing the program elements related to autonomy and intelligent robotics. The paper will also provide an overview of the September 2004 autonomy demonstrations, including a discussion of objectives, organization, and preliminary results (to the extent they are available before the submission deadline).

Morris, Robert↗
NASA NTRS2004

Intelligent Systems Technologies and Utilization of Earth Observation Data

The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

Ramapriyan, H. K.↗
NASA NTRS2004

Software for Intelligent System Health Management (ISHM)

The slide presentation is a briefing in four areas: overview of health management paradigms; overview of the ARC-Houston Software Engineering Technology Workshop held on April 20-22, 2004; identified technologies relevant to technical themes of intelligent system health management; and the author's thoughts on these topics.

Trevino, Luis C.↗
NASA NTRS1991

How to help intelligent systems with different uncertainty representations cooperate with each other

In order to solve a complicated problem one must use the knowledge from different domains. Therefore, if one wants to automatize the solution of these problems, one has to help the knowledge-based systems that correspond to these domains cooperate, that is, communicate facts and conclusions to each other in the process of decision making. One of the main obstacles to such cooperation is the fact that different intelligent systems use different methods of knowledge acquisition and different methods and formalisms for uncertainty representation. So an interface f is needed, 'translating' the values x, y, which represent uncertainty of the experts' knowledge in one system, into the values f(x), f(y) appropriate for another one. The problem of designing such an interface as a mathematical problem is formulated and solved. It is shown that the interface must be fractionally linear: f(x) = (ax + b)/(cx + d).

Kreinovich, Vladik YA.↗
NASA NTRS1987

Intelligent systems and robotics for an evolutionary Space Station

The Space Station will be a multipurpose space facility to acquire and exploit unique knowledge with a planned lifetime of greater than 20 years. It will include laboratories for science and manufacturing, provide a platform for earth and interplanetary observations, conduct satellite servicing, and serve as a transportation node for potential manned geosynchronous, lunar, and Mars missions. Environmental safety considerations and limited manpower resources require the extensive use of intelligent systems and flexible robotics on the Space Station. Design accommodations must be planned in advance to allow incorporation of these advancing technologies on the evolutionary Space Station.

Erickson, Jon D.↗
NASA NTRS1991

Autonomous power system intelligent diagnosis and control

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Ringer, Mark J.↗
NASA NTRS1991

Autonomous Power System intelligent diagnosis and control

The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution hardware. Knowledge-based software provides a robust method of control for highly complex space-based power systems that conventional methods do not allow. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis and control, the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space based power system. The operation of the Autonomous Power System as a whole is described and the responsibilities of the three elements - APEX, AIPS, and Brassboard - are characterized. A discussion of the methodologies used in each element is provided. Future plans are discussed for the growth of the Autonomous Power System.

Ringer, Mark J.↗
NASA NTRS1994

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

Intelligent Systems↗
NASA NTRS1988

Blindness in designing intelligent systems

New investigations of the foundations of artificial intelligence are challenging the hypothesis that problem solving is the cornerstone of intelligence. New distinctions among three domains of concern for humans--description, action, and commitment--have revealed that the design process for programmable machines, such as expert systems, is based on descriptions of actions and induces blindness to nonanalytic action and commitment. Design processes focusing in the domain of description are likely to yield programs like burearcracies: rigid, obtuse, impersonal, and unable to adapt to changing circumstances. Systems that learn from their past actions, and systems that organize information for interpretation by human experts, are more likely to be successful in areas where expert systems have failed.

Denning, Peter J.↗