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At least 1,171 records · Page 65

Architectures for intelligent machines

The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.

Saridis, George N.↗

NASA/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program 1992

Since 1964, the National Aeronautics and Space Administration (NASA) has supported a program of summer faculty fellowships for engineering and science educators. In a series of collaborations between NASA research and development centers and nearby universities, engineering faculty members spend 10 weeks working with professional peers on research. The Summer Faculty Program Committee of the American Society for Engineering Education supervises the programs. Objectives of the program are (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of participants' institutions; and (4) to contribute to the research objectives of the NASA center.

Spencer, John H.↗

Neural network training by integration of adjoint systems of equations forward in time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Toomarian, Nikzad↗

Automation of closed environments in space for human comfort and safety

This report culminates the work accomplished during a three year design project on the automation of an Environmental Control and Life Support System (ECLSS) suitable for space travel and colonization. The system would provide a comfortable living environment in space that is fully functional with limited human supervision. A completely automated ECLSS would increase astronaut productivity while contributing to their safety and comfort. The first section of this report, section 1.0, briefly explains the project, its goals, and the scheduling used by the team in meeting these goals. Section 2.0 presents an in-depth look at each of the component subsystems. Each subsection describes the mathematical modeling and computer simulation used to represent that portion of the system. The individual models have been integrated into a complete computer simulation of the CO2 removal process. In section 3.0, the two simulation control schemes are described. The classical control approach uses traditional methods to control the mechanical equipment. The expert control system uses fuzzy logic and artificial intelligence to control the system. By integrating the two control systems with the mathematical computer simulation, the effectiveness of the two schemes can be compared. The results are then used as proof of concept in considering new control schemes for the entire ECLSS. Section 4.0 covers the results and trends observed when the model was subjected to different test situations. These results provide insight into the operating procedures of the model and the different control schemes. The appendix, section 5.0, contains summaries of lectures presented during the past year, homework assignments, and the completed source code used for the computer simulation and control system.

Source record↗

Automatically calibrating admittances in KATE's autonomous launch operations model

This report documents a 1000-line Symbolics LISP program that automatically calibrates all 15 fluid admittances in KATE's Autonomous Launch Operations (ALO) model. (KATE is Kennedy Space Center's Knowledge-based Autonomous Test Engineer, a diagnosis and repair expert system created for use on the Space Shuttle's various fluid flow systems.) As a new KATE application, the calibrator described here breaks new ground for KSC's Artificial Intelligence Lab by allowing KATE to both control and measure the hardware she supervises. By automating a formerly manual process, the calibrator: (1) saves the ALO model builder untold amounts of labor; (2) enables quick repairs after workmen accidently adjust ALO's hand valves; and (3) frees the modeler to pursue new KATE applications that previously were too complicated. Also reported are suggestions for enhancing the program: (1) to calibrate ALO's TV cameras, pumps, and sensor tolerances; and (2) to calibrate devices in other KATE models, such as the shuttle's LOX and Environment Control System (ECS).

Morgan, Steve↗

Adaptive control with an expert system based supervisory level

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Sullivan, Gerald A.↗

An autonomous rendezvous and docking system using cruise missile technologies

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery.

Jones, Ruel Edwin↗

The role of smart systems in rendezvous, close proximity operations and docking maneuvers

Various missions scenarios (Space Station logistics, LEO and GEO services, and SEI operation) will involve flexibility in mission management. This means operations will be one or a combination of the following: autonomous, supervised autonomous, and machine aided manual control. Smart Systems will likely play a significant role in making these missions successful from a safety/reliability perspective and less costly from an operations perspective. This does not imply that Smart Systems need to be super sophisticated. On the contrary, Smart Systems have been described as automated intelligence that if a person had done it wrong, it would be considered stupid. The first part of this paper will describe the types of Smart System techniques involved in AR and CC, their specifications, duties, and interactions. Next will be a discussion of the work performed under the auspice of the ALS Program to further Expert Systems applications imbedded in the control process, NASA/JSC CRAD, and other related IRAD projects. This will include issues pertaining to the following: integration, speed, knowledge encapsulation, and cooperative systems. Finally, a brief description will be offered to outline the major obstacles for the acceptance of Smart Systems in critical applications.

Szatkowski, Gerard P.↗

Employing lighting techniques during on-orbit operations

As a result of past space missions and evaluations, many procedures have been established and shown to be prudent applications for use in present and future space environment scenarios. However, recent procedures to employ the use of robotics to assist crewmembers in performing tasks which require viewing remote and obstructed locations have led to a need to pursue alternative methods to assist in these operations. One of those techniques which is under development entails incorporating the use of suitable lighting aids/techniques with a closed circuit television (CCTV) camera/monitor system to supervise the robotics operations. The capability to provide adequate lighting during grappling, deploying, docking and berthing operations under all on-orbit illumination conditions is essential to a successful mission. Using automated devices such as the Remote Manipulator System (RMS) to dock and berth a vehicle during payload retrieval, under nighttime, earthshine, solar, or artificial illumination conditions can become a cumbersome task without first incorporating lighting techniques that provide the proper target illumination, orientation, and alignment cues. Studies indicate that the use of visual aids such as the CCTV with a pretested and properly oriented lighting system can decrease the time necessary to accomplish grappling tasks. Evaluations have been and continue to be performed to assess the various on-orbit conditions in order to predict and determine the appropriate lighting techniques and viewing angles necessary to assist crewmembers in payload operations.

Wheelwright, Charles D.↗

Multi-layered reasoning by means of conceptual fuzzy sets

The real world consists of a very large number of instances of events and continuous numeric values. On the other hand, people represent and process their knowledge in terms of abstracted concepts derived from generalization of these instances and numeric values. Logic based paradigms for knowledge representation use symbolic processing both for concept representation and inference. Their underlying assumption is that a concept can be defined precisely. However, as this assumption hardly holds for natural concepts, it follows that symbolic processing cannot deal with such concepts. Thus symbolic processing has essential problems from a practical point of view of applications in the real world. In contrast, fuzzy set theory can be viewed as a stronger and more practical notation than formal, logic based theories because it supports both symbolic processing and numeric processing, connecting the logic based world and the real world. In this paper, we propose multi-layered reasoning by using conceptual fuzzy sets (CFS). The general characteristics of CFS are discussed along with upper layer supervision and context dependent processing.

Takagi, Tomohiro↗

Fuzzy control of an unmanned helicopter

This paper discusses an application of fuzzy control to an unmanned helicopter. The authors design a fuzzy controller to achieve semi-autonomous flight of a helicopter by giving macroscopic flight commands from the ground. The fuzzy controller proposed in this study consists of two layers: the upper layer for navigation supervising the lower layer and the lower layer for ordinary rule based control. The performance of the fuzzy controller is evaluated in experiments where an industrial helicopter Yamaha R-50 is used. At present an operator can wirelessly control the helicopter through a flight computer with eight commands such as 'hover', 'fly forward', 'turn left', 'stop', etc.

Sugeno, M.↗

Petri net controllers for distributed robotic systems

Petri nets are a well established modelling technique for analyzing parallel systems. When coupled with an event-driven operating system, Petri nets can provide an effective means for integrating and controlling the functions of distributed robotic applications. Recent work has shown that Petri net graphs can also serve as remarkably intuitive operator interfaces. In this paper, the advantages of using Petri nets as high-level controllers to coordinate robotic functions are outlined, the considerations for designing Petri net controllers are discussed, and simple Petri net structures for implementing an interface for operator supervision are presented. A detailed example is presented which illustrates these concepts for a sensor-based assembly application.

Lefebvre, D. R.↗

Improving performance through concept formation and conceptual clustering

Research from June 1989 through October 1992 focussed on concept formation, clustering, and supervised learning for purposes of improving the efficiency of problem-solving, planning, and diagnosis. These projects resulted in two dissertations on clustering, explanation-based learning, and means-ends planning, and publications in conferences and workshops, several book chapters, and journals; a complete Bibliography of NASA Ames supported publications is included. The following topics are studied: clustering of explanations and problem-solving experiences; clustering and means-end planning; and diagnosis of space shuttle and space station operating modes.

Fisher, Douglas H.↗

Tree Classification Software

This paper introduces the IND Tree Package to prospective users. IND does supervised learning using classification trees. This learning task is a basic tool used in the development of diagnosis, monitoring and expert systems. The IND Tree Package was developed as part of a NASA project to semi-automate the development of data analysis and modelling algorithms using artificial intelligence techniques. The IND Tree Package integrates features from CART and C4 with newer Bayesian and minimum encoding methods for growing classification trees and graphs. The IND Tree Package also provides an experimental control suite on top. The newer features give improved probability estimates often required in diagnostic and screening tasks. The package comes with a manual, Unix 'man' entries, and a guide to tree methods and research. The IND Tree Package is implemented in C under Unix and was beta-tested at university and commercial research laboratories in the United States.

Buntine, Wray↗

Development of an expert data reduction assistant

We propose the development of an expert system tool for the management and reduction of complex data sets. The proposed work is an extension of a successful prototype system for the calibration of CCD images developed by Dr. Johnston in 1987. The reduction of complex multi-parameter data sets presents severe challenges to a scientist. Not only must a particular data analysis system be mastered, (e.g. IRAF/SDAS/MIDAS), large amounts of data can require many days of tedious work and supervision by the scientist for even the most straightforward reductions. The proposed Expert Data Reduction Assistant will help the scientist overcome these obstacles by developing a reduction plan based on the data at hand and producing a script for the reduction of the data in a target common language.

Miller, Glenn E.↗

The probabilistic neural network architecture for high speed classification of remotely sensed imagery

In this paper we discuss a neural network architecture (the Probabilistic Neural Net or the PNN) that, to the best of our knowledge, has not previously been applied to remotely sensed data. The PNN is a supervised non-parametric classification algorithm as opposed to the Gaussian maximum likelihood classifier (GMLC). The PNN works by fitting a Gaussian kernel to each training point. The width of the Gaussian is controlled by a tuning parameter called the window width. If very small widths are used, the method is equivalent to the nearest neighbor method. For large windows, the PNN behaves like the GMLC. The basic implementation of the PNN requires no training time at all. In this respect it is far better than the commonly used backpropagation neural network which can be shown to take O(N6) time for training where N is the dimensionality of the input vector. In addition the PNN can be implemented in a feed forward mode in hardware. The disadvantage of the PNN is that it requires all the training data to be stored. Some solutions to this problem are discussed in the paper. Finally, we discuss the accuracy of the PNN with respect to the GMLC and the backpropagation neural network (BPNN). The PNN is shown to be better than GMLC and not as good as the BPNN with regards to classification accuracy.

Chettri, Samir R.↗

Composite materials for the extravehicular mobility unit

The extravehicular mobility unit (EMU), commonly known as the astronaut space suit assembly (SSA) and primary life support system (PLSS), has evolved through the years to incorporate new and innovative materials in order to meet the demands of the space environment. The space shuttle program which is seeing an increasing level of extravehicular activity (EVA), also called space walks, along with interest in an EMU for Lunar-Mars missions means even more demanding conditions are being placed on the suit and PLSS. The project for this NASA-ASEE Summer Program was to investigate new materials for these applications. The focus was to emphasize the use of composite materials for every component of the EMU to enhance the properties while reducing the total weight of the EMU. To accomplish this, development of new materials called fullerene reinforced materials (FRM's) was initiated. Fullerenes are carbon molecules which when added to a material significantly reduce the weight of that material. The Faculty Fellow worked directly on the development of the fullerene reinforced materials. A chamber for fullerene production was designed and assembled and first generation samples were processed. He also supervised with the JSC Colleague, a study of composite materials for the EMU conducted by the student participant in the NASA-ASEE Program, Hector Tello a Rice University graduate student, and by a NASA Aerospace Technologist (Materials Engineer) Evelyne Orndoff, in the Systems Engineering Analysis Office (EC7), also a Rice University graduate student. Hector Tello conducted a study on beryllium and Be alloys and initiated a study of carbon and glass reinforced composites for space applications. Evelyne Orndoff compiled an inventory of the materials on the SSA. Ms. Orndoff also reviewed SSA material requirements and cited aspects of the SSA design where composite materials might be further considered. Hector Tello spent part of his time investigating the solar radiation sensitivity of anodic coatings. This project was directed toward the effects of ultra-violet radiation on high emissivity anodic coatings. The work of both Evelyne Orndoff and Hector Tello is of interest to the Engineering Directorate at NASA/JSC and is also directed toward their research as Rice University graduate students.

Barrera, Enrique V.↗

The Center of Excellence for Hypersonics Training and Research at the University of Texas at Austin

Over the period of this grant (1986-92), 23 graduate students were supported by the Center and received education and training in hypersonics through MS and Ph.D. programs. An additional 8 Ph.D. candidates and 2 MS candidates, with their own fellowship support, were attracted to The University of Texas and were recruited into the hypersonics program because of the Center. Their research, supervised by the 10 faculty involved in the Center, resulted in approximately 50 publications and presentations in journals and at national and international technical conferences. To provide broad-based training, a new hypersonics curriculum was created, enabling students to take 8 core classes in theoretical, computational, and experimental hypersonics, and other option classes over a two to four semester period. The Center also developed an active continuing education program. The Hypersonics Short Course was taught 3 times, twice in the USA and once in Europe. Approximately 300 persons were attracted to hear lectures by more than 25 of the leading experts in the field. In addition, a hypersonic aerodynamics short course was offered through AIAA, as well as short courses on computational fluid dynamics (CFD) and advanced CFD. The existence of the Center also enabled faculty to leverage a substantial volume of additional funds from other agencies, for research and graduate student training. Overall, this was a highly successful and highly visible program.

Dolling, David S.↗