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At least 1,081 records · Page 60

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NASA NTRS1992

The planning coordinator: A design architecture for autonomous error recovery and on-line planning of intelligent tasks

Developing a robust, task level, error recovery and on-line planning architecture is an open research area. There is previously published work on both error recovery and on-line planning; however, none incorporates error recovery and on-line planning into one integrated platform. The integration of these two functionalities requires an architecture that possesses the following characteristics. The architecture must provide for the inclusion of new information without the destruction of existing information. The architecture must provide for the relating of pieces of information, old and new, to one another in a non-trivial rather than trivial manner (e.g., object one is related to object two under the following constraints, versus, yes, they are related; no, they are not related). Finally, the architecture must be not only a stand alone architecture, but also one that can be easily integrated as a supplement to some existing architecture. This thesis proposal addresses architectural development. Its intent is to integrate error recovery and on-line planning onto a single, integrated, multi-processor platform. This intelligent x-autonomous platform, called the Planning Coordinator, will be used initially to supplement existing x-autonomous systems and eventually replace them.

Farah, Jeffrey J.↗

NASA NTRS1993

Advanced Artificial Intelligence Technology Testbed

The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

Anken, Craig S.↗

NASA NTRS1993

Mixed data/goal driven intelligent real-time assessment and control

We describe work in progress to develop model-based systems for real-time assessment and control of complex systems. Intelligent real-time processing must balance accuracy and response-time requirements to maximize expected performance. We use brief (probability) and goal (utility) information to guide construction of an approximate system model on which we then apply approximate inference procedures to yield timely, effective assessments and control decisions.

Dambrosio, Bruce↗

NASA NTRS1993

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks.

Chien, Steve↗

NASA NTRS1992

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMAID)

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Rogers, James L.↗

NASA NTRS1992

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a heirarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

Erickson, J.↗

NASA NTRS1992

Discrete distributed strain sensing of intelligent structures

Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.

Anderson, Mark S.↗

NASA NTRS1993

An intercomparison of artificial intelligence approaches for polar scene identification

The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

Tovinkere, V. R.↗

NASA NTRS1993

System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation

Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

Nieten, Joseph↗

NASA NTRS1991

Approaches to the study of intelligence

A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.

Norman, Donald A.↗

NASA NTRS1989

Human-centered automation and AI - Ideas, insights, and issues from the Intelligent Cockpit Aids research effort

A development status evaluation is presented for the NASA-Langley Intelligent Cockpit Aids research program, which encompasses AI, human/machine interfaces, and conventional automation. Attention is being given to decision-aiding concepts for human-centered automation, with emphasis on inflight subsystem fault management, inflight mission replanning, and communications management. The cockpit envisioned is for advanced commercial transport aircraft.

Abbott, Kathy H.↗

NASA NTRS1988

RICIS research review of artificial intelligence and expert systems

The paper summarizes the research accomplishments of the past year for the artificial intelligence and expert systems areas. Most projects have been underway for only a short time; however, overall progress within the areas has been steady and worthwhile. Several projects have already attained their major objectives.

Feagin, Terry↗

NASA NTRS1990

Artificial intelligence and design: Opportunities, research problems and directions

The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions that are of intrinsic concern to AI. We present examples of current AI work on specific design tasks, and discuss new directions of research, both as extensions of current work and in the context of new design tasks where domain knowledge is either intractable or incomplete. The domains discussed include Digital Circuit Design, Mechanical Design of Rotational Transmissions, Design of Computer Architectures, Marine Design, Aircraft Design, and Design of Chemical Processes and Materials. Work in these domains is significant on technical grounds, and it is also important for economic and policy reasons.

Amarel, Saul↗

NASA NTRS1993

Distributed intelligent control and status networking

Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

Fortin, Andre↗

NASA NTRS1992

Electronic publishing and intelligent information retrieval

Europeans are now taking steps to homogenize policies and standardize procedures in electronic publishing (EP) in astronomy and space sciences. This arose from an open meeting organized in Oct. 1991 at Strasbourg Observatory (France) and another business meeting held late Mar. 1992 with the major publishers and journal editors in astronomy and space sciences. The ultimate aim of EP might be considered as the so-called 'intelligent information retrieval' (IIR) or better named 'advanced information retrieval' (AIR), taking advantage of the fact that the material to be published appears at some stage in a machine-readable form. It is obvious that the combination of desktop and electronic publishing with networking and new structuring of knowledge bases will profoundly reshape not only our ways of publishing, but also our procedures of communicating and retrieving information. It should be noted that a world-wide survey among astronomers and space scientists carried out before the October 1991 colloquium on the various packages and machines used, indicated that TEX-related packages were already in majoritarian use in our community. It has also been stressed at each meeting that the European developments should be carried out in collaboration with what is done in the US (STELLAR project, for instance). American scientists and journal editors actually attended both meetings mentioned above. The paper will offer a review of the status of electronic publishing in astronomy and its possible contribution to advanced information retrieval in this field. It will also report on recent meetings such as the 'Astronomy from Large Databases-2 (ALD-2)' conference dealing with the latest developments in networking, in data, information, and knowledge bases, as well as in the related methodologies.

Heck, A.↗

NASA NTRS1992

The application of artificial intelligence to astronomical scheduling problems

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike to other problem domains, and plans for the future evolution of the system.

Johnston, Mark D.↗

NASA NTRS1994

Design and control of active vision based mechanisms for intelligent robots

In this paper, we propose a design of an active vision system for intelligent robot application purposes. The system has the degrees of freedom of pan, tilt, vergence, camera height adjustment, and baseline adjustment with a hierarchical control system structure. Based on this vision system, we discuss two problems involved in the binocular gaze stabilization process: fixation point selection and vergence disparity extraction. A hierarchical approach to determining point of fixation from potential gaze targets using evaluation function representing human visual behavior to outside stimuli is suggested. We also characterize different visual tasks in two cameras for vergence control purposes, and a phase-based method based on binarized images to extract vergence disparity for vergence control is presented. A control algorithm for vergence control is discussed.

Wu, Liwei↗

NASA NTRS1994

Vehicle following controller design for autonomous intelligent vehicles

A new vehicle following controller is proposed for autonomous intelligent vehicles. The proposed vehicle following controller not only provides smooth transient maneuvers for unavoidable nonzero initial conditions but also guarantees the asymptotic platoon stability without the availability of feedforward information. Furthermore, the achieved asymptotic platoon stability is shown to be robust to sensor delays and an upper bound for the allowable sensor delays is also provided in this paper.

Chien, C. C.↗