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At least 577 records · Page 32

Guidance for human interface with artificial intelligence systems

The beginning of a research effort to collect and integrate existing research findings about how to combine computer power and people is discussed, including problems and pitfalls as well as desirable features. The goal of the research is to develop guidance for the design of human interfaces with intelligent systems. Fault management tasks in NASA domains are the focus of the investigation. Research is being conducted to support the development of guidance for designers that will enable them to make human interface considerations into account during the creation of intelligent systems.

Potter, Scott S.↗

Applications of artificial intelligence to mission planning

The following subject areas are covered: object-oriented programming task; rule-based programming task; algorithms for resource allocation; connecting a Symbolics to a VAX; FORTRAN from Lisp; trees and forest task; software data structure conversion; software functionality modifications and enhancements; portability of resource allocation to a TI MicroExplorer; frontier of feasibility software system; and conclusions.

Ford, Donnie R.↗

Validation of an expert system intended for research in distributed artificial intelligence

The expert system discussed in this paper is designed to function as a testbed for research on cooperating expert systems. Cooperating expert systems are members of an organization which dictates the manner in which the expert systems will interact when solving a problem. The Blackbox Expert described in this paper has been constructed using the C Language Integrated Production System (CLIPS), C++, and X windowing environment. CLIPS is embedded in a C++ program which provides objects that are used to maintain the state of the Blackbox puzzle. These objects are accessed by CLIPS rules through user-defined functions calls. The performance of the Blackbox Expert is validated by experimentation. A group of people are asked to solve a set of test cases for the Blackbox puzzle. A metric has been devised which evaluates the 'correctness' of a solution proposed for a test case of Blackbox. Using this metric and the solutions proposed by the humans, each person receives a rating for their ability to solve the Blackbox puzzle. The Blackbox Expert solves the same set of test cases and is assigned a rating for its ability. Then the rating obtained by the Blackbox Expert is compared with the ratings of the people, thus establishing the skill level of our expert system.

Grossner, C.↗

Artificial intelligence approach to planning the robotic assembly of large tetrahedral truss structures

An assembly planner for tetrahedral truss structures is presented. To overcome the difficulties due to the large number of parts, the planner exploits the simplicity and uniformity of the shapes of the parts and the regularity of their interconnection. The planning automation is based on the computational formalism known as production system. The global data base consists of a hexagonal grid representation of the truss structure. This representation captures the regularity of tetrahedral truss structures and their multiple hierarchies. It maps into quadratic grids and can be implemented in a computer by using a two-dimensional array data structure. By maintaining the multiple hierarchies explicitly in the model, the choice of a particular hierarchy is only made when needed, thus allowing a more informed decision. Furthermore, testing the preconditions of the production rules is simple because the patterned way in which the struts are interconnected is incorporated into the topology of the hexagonal grid. A directed graph representation of assembly sequences allows the use of both graph search and backtracking control strategies.

Homemdemello, Luiz S.↗

Applying artificial intelligence to the control of space telescopes (extended abstract)

The field of astronomy has recently benefited from the availability of space telescopes. The Hubble Space Telescope (HST), for instance, despite its problems, provides a unique and valuable view of the universe. However, unlike HST, a telescope need not be in low Earth orbit to escape our thickening atmosphere: it is currently technologically feasible to put a telescope on the moon, and there are excellent reasons for doing this. Either in low Earth orbit or on the moon, a space telescope represents an expensive and sought-after resource. Thus, the planning, scheduling, and control of these telescopes is an important problem that must be seriously studied.

Drummond, Mark↗

Space Shuttle processing - A case study in artificial intelligence

A scheduling system incorporating AI is described and applied to the automated processing of the Space Shuttle. The unique problem of addressing the temporal, resource, and orbiter-configuration requirements of shuttle processing is described with comparisons to traditional project management for manufacturing processes. The present scheduling system is developed to handle the late inputs and complex programs that characterize shuttle processing by incorporating fixed preemptive scheduling, constraint-based simulated annealing, and the characteristics of an 'anytime' algorithm. The Space-Shuttle processing environment is modeled with 500 activities broken down into 4000 subtasks and with 1600 temporal constraints, 8000 resource constraints, and 3900 state requirements. The algorithm is shown to scale to very large problems and maintain anytime characteristics suggesting that an automated scheduling process is achievable and potentially cost-effective.

Mollikarimi, Cindy↗

An application of artificial intelligence to automatic telescopes

Automatic Photoelectric Telescopes (APT's) allow an astronomer to be removed form the telescope site in both time and space. APT's 'execute' an observation program (a set of observation requests) expressed in an ASCII-based language (ATIS) and collect observation results expressed in this same language. The observation program is currently constructed by a Principal Astronomer from the requests of multiple users; the execution is currently controlled by a simple heuristic dispatch scheduler. Research aimed at improving the use of APT's is being carried out by the Entropy Reduction Engine (ERE) project at NASA Ames. The overall goal of the ERE project is the study and construction of systems that integrate planning, scheduling, and control. This paper discusses the application of some ERE technical results to the improvement of both the scheduling and the operation of APT's.

Swanson, Keith↗

Artificial intelligence for geologic mapping with imaging spectrometers

This project was a three year study at the Center for the Study of Earth from Space (CSES) within the Cooperative Institute for Research in Environmental Science (CIRES) at the University of Colorado, Boulder. The goal of this research was to develop an expert system to allow automated identification of geologic materials based on their spectral characteristics in imaging spectrometer data such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This requirement was dictated by the volume of data produced by imaging spectrometers, which prohibits manual analysis. The research described is based on the development of automated techniques for analysis of imaging spectrometer data that emulate the analytical processes used by a human observer. The research tested the feasibility of such an approach, implemented an operational system, and tested the validity of the results for selected imaging spectrometer data sets.

Kruse, F. A.↗

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

Rubaai, Ahmed↗

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

A laboratory implementation of a fuzzy logic-tracking controller using a low cost Motorola MC68HC11E9 microprocessor is described in this report. The objective is to design the most optimal yet practical controller that can be implemented and marketed, and which gives respectable performance, even when the system loads, inertia and parameters are varying. A distinguishing feature of this work is the by-product goal of developing a marketable, simple, functional and low cost controller. Additionally, real-time nonlinearities are not ignored, and a mathematical model is not required. A number of components have been designed, built and tested individually, and in various combinations of hardware and software segments. These components have been integrated with a brushless motor to constitute the drive system. A microprocessor-based FLC is incorporated to provide robust speed and position control. Design objectives that are difficult to express mathematically can be easily incorporated in a fuzzy logic-based controller by linguistic information (in the form of fuzzy IF-THEN rules). The theory and design are tested in the laboratory using a hardware setup. Several test cases have been conducted to confirm the effectiveness of the proposed controller. The results indicate excellent tracking performance for both speed and position trajectories. For the purpose of comparison, a bang-bang controller has been tested. The fuzzy logic controller performs significantly better than the traditional bang-bang controller. The bang-bang controller has been shown to be relatively inaccurate and lacking in robustness. Description of the implementation hardware system is also given.

Rubaai, Ahmed↗

An Artificial Intelligence Classification Tool and Its Application to Gamma-Ray Bursts

Despite being the most energetic phenomenon in the known universe, the astrophysics of gamma-ray bursts (GRBs) has still proven difficult to understand. It has only been within the past five years that the GRB distance scale has been firmly established, on the basis of a few dozen bursts with x-ray, optical, and radio afterglows. The afterglows indicate source redshifts of z=1 to z=5, total energy outputs of roughly 10(exp 52) ergs, and energy confined to the far x-ray to near gamma-ray regime of the electromagnetic spectrum. The multi-wavelength afterglow observations have thus far provided more insight on the nature of the GRB mechanism than the GRB observations; far more papers have been written about the few observed gamma-ray burst afterglows in the past few years than about the thousands of detected gamma-ray bursts. One reason the GRB central engine is still so poorly understood is that GRBs have complex, overlapping characteristics that do not appear to be produced by one homogeneous process. At least two subclasses have been found on the basis of duration, spectral hardness, and fluence (time integrated flux); Class 1 bursts are softer, longer, and brighter than Class 2 bursts (with two second durations indicating a rough division). A third GRB subclass, overlapping the other two, has been identified using statistical clustering techniques; Class 3 bursts are intermediate between Class 1 and Class 2 bursts in brightness and duration, but are softer than Class 1 bursts. We are developing a tool to aid scientists in the study of GRB properties. In the process of developing this tool, we are building a large gamma-ray burst classification database. We are also scientifically analyzing some GRB data as we develop the tool. Tool development thus proceeds in tandem with the dataset for which it is being designed. The tool invokes a modified KDD (Knowledge Discovery in Databases) process, which is described as follows.

Hakkila, Jon↗

Autonomous operations through onboard artificial intelligence

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Sciencecraft Experiment ASE TechSat 21↗

Using Artificial Intelligence to Inform Pilots of Weather

An automated system to assist a General Aviation (GA) pilot in improving situational awareness of weather in flight is now undergoing development. This development is prompted by the observation that most fatal GA accidents are attributable to loss of weather awareness. Loss of weather awareness, in turn, has been attributed to the difficulty of interpreting traditional preflight weather briefings and the difficulty of both obtaining and interpreting traditional in-flight weather briefings. The developmental automated system not only improves weather awareness but also substantially reduces the time a pilot must spend in acquiring and maintaining weather awareness.

Spirkovska, Lilly↗