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Topics addressed include: collision-free motion planning of multiple robot arms; two-dimensional object recognition; and pictorial databases (storage and sharing of the representations of three-dimensional objects).
Lockheed, the Hubble Space Telescope mission operations contractor, is currently engaged in a project to develop a distributed architecture of communicating expert systems to support vehicle operations. This architecture, called Telemetry Analysis for Lockheed Operated Spacecraft (TALOS), has potentially wide applicability to spacecraft operations. The architecture mirrors the organization of the human experts within an operations control center. The prototype analyzes telemetry from a history tape to determine the state of the vehicle with respect to on-board safemode events. The prototype is currently being expanded along two fronts. One consists of expert systems modules which perform deeper level diagnostics and which operate in an off-line mode. The other is a high speed front-end expert system which will monitor real time telemetry for anomalies and spacecraft status and send activation and initialization messages to the off-line modules when an anomaly is detected.
A knowledge based system to assist process engineers in evaluating the processability and moldability of poly-isocyanurate (PIR) formulations for the thermal protection system of the Space Shuttle external tank (ET) is discussed. The Reaction Injection Molding- Process Development Advisor (RIM-PDA) is a coupled system which takes advantage of both symbolic and numeric processing techniques. This system will aid the process engineer in identifying a startup set of mold schedules and in refining the mold schedules to remedy specific process problems diagnosed by the system.
A generalized technique for the numerical solution of any given class of problems is presented. The technique requires the analytic (or numerical) solution of every applicable equation for all variables that appear in the problem. Conditional blocks are employed to rapidly expand the set of known variables from a minimum of input. The method is illustrated via the use of the Hohmann transfer problem from orbital mechanics.
The ultimate goal of this research is to build an improved model-based selection and classification system for the United States Air Force. Researchers are developing innovative approaches to ability testing. The Learning Abilities Measurement Program (LAMP) examines individual differences in learning abilities, seeking answers to the questions of why some people learn more and better than others and whether there are basic cognitive processes applicable across tasks and domains that are predictive of successful performance (or whether there are more complex problem solving behaviors involved).
Adaptive Tactical Navigation (ATN) is a laboratory prototype of a knowledge based system to provide navigation system management and decision aiding in the next generation of tactical aircraft. ATN's purpose is to manage a set of multimode navigation equipment, dynamically selecting the best equipment to use in accordance with mission goals and phase, threat environment, equipment malfunction status, and battle damage. ATN encompasses functions as diverse as sensor data interpretation, diagnosis, and planning. Real time issues that were identified in ATN and the approaches used to address them are addressed. Functional requirements and a global architecture for the ATN system are described. Decision making with time constraints are discussed. Two subproblems are identified; making decisions with incomplete information and with limited resources. Approaches used in ATN to address real time performance are described and simulation results are discussed.
The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.
This report, an addendum to the six month report submitted to NASA Langley Research Center in December 1987, covers research performed by the Fiber and Electro-Optics Research Center (FEORC) at Virginia Tech for the NASA Langley Research Center, Grant NAG1-780, for the period from December 1987 to June 1988. This final report discusses the research performed in the following four areas as described in the proposal: Fabrication of Sensor Fibers Optimized for Embedding in Advanced Composites; Fabrication of Sensor Fiber with In-Line Splices and Evaluation via OTR methods; Modal Domain Optical Fiber Sensor Analysis; and Acoustic Fiber Waveguide Implementation.
Lockheed, the Hubble Space Telescope Mission Operations Contractor, is currently engaged in a project to develop a distributed architecture of communicating expert systems to support vehicle operations. This architecture, named Telemetry Analysis Logic for Operating Spacecraft (TALOS), has the potential for wide applicability in spacecraft operations. The architecture mirrors the organization of the human experts within an operations control center.
The principal objective is to develop methods for assessing the likelihood of wind shear encounter, for deciding what flight path to pursue, and for using the aircraft's full potential for combating wind shear. This study requires the definition of both deterministic and statistical techniques for fusing internal and external information, for making go/no-go decisions, and for generating commands to the aircraft's cockpit displays and autopilot for both manually controlled and automatic flight. The program has begun with the development of a real-time expert system for pilot aiding that is based on the results of the FAA Windshear Training Aids Program. A two-volume manual that presents an overview, pilot guide, training program, and substantiating data provides guidelines for this initial development. The Expert System to Avoid Wind Shear (ESAWS) currently contains over 140 rules and is coded in the LISP programming language for implementation on a Symbolics 3670 LISP machine.
Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.
This report is concerned with the application of software quality and evaluation measures to AI software and, more broadly, with the question of quality assurance for AI software. Considered are not only the metrics that attempt to measure some aspect of software quality, but also the methodologies and techniques (such as systematic testing) that attempt to improve some dimension of quality, without necessarily quantifying the extent of the improvement. The report is divided into three parts Part 1 reviews existing software quality measures, i.e., those that have been developed for, and applied to, conventional software. Part 2 considers the characteristics of AI software, the applicability and potential utility of measures and techniques identified in the first part, and reviews those few methods developed specifically for AI software. Part 3 presents an assessment and recommendations for the further exploration of this important area.
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Since interstellar travel is not economically possible on the time scale of a human lifetime, communication with extraterrestrials can be achieved only by sending some form of energy or matter across space; photons (electromagnetic waves) are best. Of particular interest to SETI is the region from about 1,000-60,000 MHz known as the free-space microwave window. During the course of NASA's Cyclops program, it was pointed out that the hydrogen and hydroxyl lines bounded a band in which there were no other known lines. The threatened loss of the microwave window to earth-based services is discussed.
The application of AI technology may have significant potential payoff for rotorcraft. In the near term, the status of the technology will limit its applicability to decision aids rather than total automation. The specific application areas are categorized into onboard and nonflight aids. The onboard applications include: fault monitoring, diagnosis, and reconfiguration; mission and tactics planning; situation assessment; navigation aids, especially in nap-of-the-earth flight; and adaptive man-machine interfaces. The nonflight applications include training and maintenance diagnostics.
NASA's Office of Aeronautics and Space Technology (OAST) has instituted a 'Systems Autonomy' technology development program aimed at the creation of increasingly sophisticated AI systems. Expert system production will in due course be followed by fully autonomous AI systems capable of the complex mission objectives of the Space Station, as well as of lunar and Martian exploration. AI systems must demonstrate the degree of their autonomy in a real-time operational environment, and then undergo mating to robotics technologies. OAST's Systems Autonomy Program and Robotics Program are discussed with a view to anticipated difficulties in their integration.
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Significant research products which have emerged from the core program of NASA's Office of Aeronautics and Space Technology (OAST) are discussed. The Space Station Thermal Control System, the Space Shuttle Integrated Communications Officer Station, the Launch Processing System, the Expert Scheduling System for Pioneer Venus Spacecraft, a Bayesian classification system, and a spaceborne multiprocessor system are included. The technology trends which led to these results are discussed and future developments in technology are forecasted.