Search NASA⌕ Search

SEARCH · Search NASA

Results for “Computational Intelligence”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Human interaction with an intelligent computer in multi-task situations

A general formulation of human decision making in multiple task situations is presented. It includes a description of the state, event, and action space in which the multiple task supervisor operates. A specific application to a failure detection and correction situation is discussed and results of a simulation experiment presented. Issues considered include static vs. dynamic allocation of responsibility and competitive vs. cooperative intelligence.

Rouse, W. B.↗
NASA NTRS1980

Decision making and problem solving with computer assistance

In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

Kraiss, F.↗
NASA NTRS1979

Artificial intelligence programming languages for computer aided manufacturing

Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

Rieger, C.↗
NASA NTRS1974

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Yakimovsky, Y.↗
NASA NTRS1981

The enchanted loom

The evolution of intelligence began with the movement of Crossopterygian fish onto land. The eventual appearance of large dinosaurs eliminated all but the smallest of mammalian creatures, with the survivors forced to move only nocturnally, when enhanced olfactory and aural faculties were favored and involved a larger grey matter/body mass ratio than possessed by the dinosaurs. Additionally, the mammals made comparisons between the inputs of various senses, implying the presence of significant memory capacity and an ability to abstract survival information. More complex behavior occurred with the advent of tree dwellers (forward-looking eyes), hands, color vision, and the ability to grip and manipulate objects. An extra pound of brain evolved in the human skull in less than a million years. The neural processes that can lead to an action by a creature with a brain are mimicked by the basic AND and OR gates in computers, which are rapidly approaching the circuit density of the human brain. It is suggested that humans will eventually produce computers of higher intelligence than people possess, and computer spacecraft, alive in an electronic sense, will travel outward to explore the universe.

Jastrow, R.↗
NASA NTRS1972

A TDM link with channel coding and digital voice.

The features of a TDM (time-division multiplexed) link model are described. A PCM telemetry sequence was coded for error correction and multiplexed with a digitized voice channel. An all-digital implementation of a variable-slope delta modulation algorithm was used to digitize the voice channel. The results of extensive testing are reported. The measured coding gain and the system performance over a Gaussian channel are compared with theoretical predictions and computer simulations. Word intelligibility scores are reported as a measure of voice channel performance.

Jones, M. W.↗
NASA NTRS1982

Distribution of man-machine controls in space teleoperation

The distribution of control between man and machine is dependent on the tasks, available technology, human performance characteristics and control goals. This dependency has very specific projections on systems designed for teleoperation in space. This paper gives a brief outline of the space-related issues and presents the results of advanced teleoperator research and development at the Jet Propulsion Laboratory (JPL). The research and development work includes smart sensors, flexible computer controls and intelligent man-machine interface devices in the area of visual displays and kinesthetic man-machine coupling in remote control of manipulators. Some of the development results have been tested at the Johnson Space Center (JSC) using the simulated full-scale Shuttle Remote Manipulator System (RMS). The research and development work for advanced space teleoperation is far from complete and poses many interdisciplinary challenges.

Bejczy, A. K.↗
NASA NTRS1974

Numerical computation of echograms in a room: Application to determination of intelligibility

Echogram recordings are used to estimate the acoustic quality of a room. Using two methods based on geometric acoustics, echograms are computed for rooms of irregular shape. The image method and the ray method have been applied to a heptahedral room as well as a conference hall. The results obtained, which have been verified experimentally, permit an estimate of the intelligibility coefficient.

Santon, F.↗
NASA NTRS1964

Artificial intelligence

Artificial intelligence - system for instructing computer and programming language for manipulating symbolic expressions

ARTIFICIAL INTELLIGENCE↗
NASA NTRS1974

An orientable, stabilized balloon-borne gondola for around-the-world flights

A system capable of pointing a balloon-borne telescope at selected celestial objects to an accuracy of approximately 10 arc minutes for an extended period (weeks to months) without reliance on telemetry is described. A unique combination of a sun/star tracker, an on-board computer, and a gyrocompass is utilized for navigation, source acquisition and tracking, and data compression and recording. The possibilities for intelligent activities by the computer are also discussed.

Ricker, G. R.↗
NASA NTRS1975

Topics in programmable automation

Topics explored in the development of integrated programmable automation systems include: numerically controlled and computer controlled machining; machine intelligence and the emulation of human-like capabilities; large scale semiconductor integration technology applications; and sensor technology for asynchronous local computation without burdening the executive minicomputer which controls the whole system. The role and development of training aids, and the potential application of these aids to augmented teleoperator systems are discussed.

Rosen, C. A.↗
NASA NTRS1980

Upgrading the free flying rendezvous and docking simulator and the orbital servicer system

Recommendations are made for upgrading two teleoperator/robotics test and simulation systems based upon a review of latest technology advances in the involved disciplines. A second generation Free Flying Mobility Unit is recommended which adds a sixth degree of freedom and incorporates other improvements which greatly expand the center's capability to perform evaluation tests and demonstrations of advanced systems concepts for rendezvous and docking in support of the Teleoperator Maneuvering System (TMS) Program. The Orbital Servicer System provides the capability for testing and demonstrating concepts for on orbit servicing of compatibly designed satellites/payloads. The TMS is to be the transporting vehicle for the servicer. The manipulator arm of the Orbital service System is presently computer controlled in the trajectory portion of the module transfer operation. The ultimate objective is to fully automte its operation requiring additional capabilities in sensors, artificial intelligence, image analysis, communications, computer programming, pattern recognition, kinematics, and manipulator design. It is recommended that the Electronics and Control Laboratory move to acquire the basic competencies in robotics necessary to achieve full automation.

Eastman, R. M.↗
NASA NTRS1982

Automation technology for aerospace power management

The growing size and complexity of spacecraft power systems coupled with limited space/ground communications necessitate increasingly automated onboard control systems. Research in computer science, particularly artificial intelligence has developed methods and techniques for constructing man-machine systems with problem-solving expertise in limited domains which may contribute to the automation of power systems. Since these systems perform tasks which are typically performed by human experts they have become known as Expert Systems. A review of the current state of the art in expert systems technology is presented, and potential applications in power systems management are considered. It is concluded that expert systems appear to have significant potential for improving the productivity of operations personnel in aerospace applications, and in automating the control of many aerospace systems.

Larsen, R. L.↗
NASA NTRS1990

Artificial Intelligence for Multi-Mission Planetary Operations

A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

David J Atkinson↗
NASA NTRS1982

A floating-point/multiple-precision processor for airborne applications

A compact input output (I/O) numerical processor capable of performing floating-point, multiple precision and other arithmetic functions at execution times which are at least 100 times faster than comparable software emulation is described. The I/O device is a microcomputer system containing a 16 bit microprocessor, a numerical coprocessor with eight 80 bit registers running at a 5 MHz clock rate, 18K random access memory (RAM) and 16K electrically programmable read only memory (EPROM). The processor acts as an intelligent slave to the host computer and can be programmed in high order languages such as FORTRAN and PL/M-86.

Yee, R.↗
NASA NTRS2026

Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗