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Some of the parallel computational strategies are reviewed, and their adequacy assessed for a given architecture and a given problem. The performance of both extreme parallel hardware technologies on real-life structural problems is also reported.
This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.
This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.
The functional performance of the Galileo spacecraft's attitude and articulation control subsystem is evaluated. The tests are performed utilizing the simulation program developed on an IBM 370 system known as the Functional Simulation (FUNSIM). FUNSIM is an entirely software-based simulation which uses the actual flight software in HAL/S and simulated spacecraft dynamics in FORTRAN language. A description of how the test cases were selected to verify that the algorithms perform functionally correctly, and a summary of the problems encountered are included in the paper. The benefits of having an alternative test bed such as FUNSIM to the real-time simulation test beds which utilize the spacecraft hardware components in discovering the problems are described. A sample test case which shows that the desired tasks were performed functionally correctly is included in the paper. The commands in this test are selected to start the dual-spin spacecraft initially in launch mode and lead it all the way to inertial mode. Major attitude control algorithms such as rotor and platform attitude estimators, clock and core platform attitude estimators, clock and core platform controllers, and the command turn and burn are examined.
Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.
The use of satellite proper time as integration variable and space time correlation handling were examined for means to reduce computational requirements. Implementation architectures were discussed with emphasis on minimization of computer configuration hardware requirements. Selected benchmark experiment results are presented to size processor requirements for achieving GPS-NAVSTAR navigation accuracies in both the user and control segments.
Hardware and software were developed to implement the hybrid digital control of two Jet A-1 fueled Mach 0.3 burners from startup to completion of a preset number of hot corrosion flame durability cycle tests of materials at 1652 F. This was accomplished by use of a basic language programmable microcomputer and data aquisition and control unit connected together by the IEEE-488 Bus. The absolute specimen temperature was controlled to + or - 3 F by use of digital adjustment of the fuel flow using a P-I-D (Proportional-Integral-Derivative) control algorithm. The specimen temperature was within + or - 2 F of the set point more than 90 percent of the time. Pressure control was achieved by digital adjustment of the combustion air flow using a proportional control algorithm. The burner pressure was controlled at 1.0 + or - 0.02 psig. Logic schemes were incorporated into the system to protect the test specimen from abnormal test conditions in the event of a hardware of software malfunction.
The task of establishing a film calibration scheme for magnitude studies of Skylab photographic images of Comet Kohoutek is examined. Since the data are recorded in terms of film density and have to be used in terms of exposure, the conversion from density to exposure is critical. In this film calibration scheme, the hardware deals with the data sources, recording medium, and data conversion to a computer compatible program, whereas the software deals with signal to noise enhancement, stepwedge calibration curve and leads to modeling of the film characteristic curves. A mathematical model of the characteristic curve is obtained using a modified version of Efroymson's (1960) stepwise multiple linear regression algorithm, which gives log exposure as a function of density. The difference in the calibration curves from pre- and postflight exposures is well accounted for in the model as a result of sensitive statistical tests. The characteristic curve modeling program requires about 4K of core and is executed in about 3 min.
Operating procedures for this redundant system are described. A test plan is developed with two objectives. First, performance of the hardware and software delivered is demonstrated. Second, applicability of multiple IMU systems to the space shuttle mission is shown through detailed experiments with FDI algorithms and other multiple IMU software: gyrocompassing, calibration, and navigation. Gimbal flip is examined in light of its possible detrimental effects on FDI and navigation. For Vol. 3, see N74-10296.
The Ocean Topography Experiment satellite will carry a modular Attitude Determination and Control Subsystem (ADCS) which contains all equipment required for attitude determination, stabilization, and control, as well as hydrazine thruster firing control, during all mission phases. Attention is presently given to the ADCS's architecture, constituent hardware components, performance requirements, and predicted on-orbit performance compliance, with emphasis on the design and analysis of the Normal Mission Mode control algorithm furnishing the primary scientific data-acquisition operational mode. This mode's attitude determination and control of on-orbit performance is predicted to better than 43 arcsec.
Astrometric measurements made with the Mark III stellar interferometer on five nights in August-September 1988 yielded average formal 1-sigma errors for 12 FK5 stars of 6 mas in declination and 10 mas in right ascension. This improvement in precision over previously reported measurements with this instrument made in 1986 is attributable to several factors: a second 12 m baseline; oriented E-S, was added to the instrument to improve the determination of right ascension; two-color analysis was included in the data-reduction process, along with a new central-fringe identification algorithm using three spectral channels, in order to reduce atmospheric errors; thermal control was greatly improved; and changes were made to observational procedures and hardware to monitor variations in the delay offset due to residual thermal drifts. Approximately half of the new positions are within 50 mas of their FK5 positions. However, an extended series of measurements are needed to ascertain the accuracy that can be achieved by interferometry.
Since the 1960's, NASA has performed numerous rendezvous and docking missions. The common element of all US rendezvous and docking is that the spacecraft has always been piloted by astronauts. Only the Russian Space Program has developed and demonstrated an autonomous capability. The Demonstration of Autonomous Rendezvous Technology (DART) project currently funded under NASA's Space Launch Initiative (SLI) Cycle I, provides a key step in establishing an autonomous rendezvous capability for the United States. DART's objective is to demonstrate, in space, the hardware and software necessary for autonomous rendezvous. Orbital Sciences Corporation intends to integrate an Advanced Video Guidance Sensor and Autonomous Rendezvous and Proximity Operations algorithms into a Pegasus upper stage in order to demonstrate the capability to autonomously rendezvous with a target currently in orbit. The DART mission will occur in April 2004. The launch site will be Vandenburg AFB and the launch vehicle will be a Pegasus XL equipped with a Hydrazine Auxiliary Propulsion System 4th stage. All mission objectives will be completed within a 24 hour period. The paper provides a summary of mission objectives, mission overview and a discussion on the design features of the chase and target vehicles.
A SINDA subroutine has been developed to predict the power generated by a Thermo-Electric Cooler (TEC). A TEC can be described analytically by relations between four parameters: cold side temperature, hot side temperature, parasitic heat load, and electrical power. The subroutine requires the user to input the hot side and cold side temperatures, the corresponding parasitic heat load, and coefficients describing the vendor performance curves. The subroutine then utilizes an iterative solution scheme and vendor TEC performance curves for specific hardware to determine the current (and consequently the TEC power) that satisfies these requirements. This paper provides an in-depth discussion of the algorithm employed in the subroutine, implementation of the subroutine in the HST Wide Field Camera 3 thermal model, and the evaluation of the subroutine performance against actual test/correlation data.
A computer-implemented system and method of intra-oral analysis for measuring plaque removal is disclosed. The system includes hardware for real-time image acquisition and software to store the acquired images on a patient-by-patient basis. The system implements algorithms to segment teeth of interest from surrounding gum, and uses a real-time image-based morphing procedure to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The system integrates these components into a single software suite with an easy-to-use graphical user interface (GUI) that allows users to do an end-to-end run of a patient record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image.
A simple algorithm for optimizing and focusing lens designs is presented. The goal of the algorithm is to simultaneously create the best and most uniform image quality over the field of view. Rather than relatively weighting multiple field points, only the image quality from the worst field point is considered. When optimizing a lens design, iterations are made to make this worst field point better until such a time as a different field point becomes worse. The same technique is used to determine focus position. The algorithm works with all the various image quality metrics. It works with both symmetrical and asymmetrical systems. It works with theoretical models and real hardware.
AVIRIS data represent a new and important approach for the retrieval of atmospheric and surface parameters from optical remote sensing data. Not only as a test for future space systems, but also as an operational airborne remote sensing system, the development of algorithms to retrieve information from AVIRIS data is an important step to these new approaches and capabilities. Many things have been learned since AVIRIS became operational, and the successive technical improvements in the hardware and the more sophisticated calibration techniques employed have increased the quality of the data to the point of almost meeting optimum user requirements. However, the potential capabilities of imaging spectrometry over the standard multispectral techniques have still not been fully demonstrated. Reasons for this are the technical difficulties in handling the data, the critical aspect of calibration for advanced retrieval methods, and the lack of proper models with which to invert the measured AVIRIS radiances in all the spectral channels. To achieve the potential of imaging spectrometry, these issues must be addressed. In this paper, an algorithm to retrieve information about both atmospheric and surface parameters from AVIRIS data, by using model inversion techniques, is described. Emphasis is put on the derivation of the model itself as well as proper inversion techniques, robust to noise in the data and an inadequate ability of the model to describe natural variability in the data. The problem of non-linear effects is addressed, as it has been demonstrated to be a major source of error in the numerical values retrieved by more simple, linear-based approaches. Non-linear effects are especially critical for the retrieval of surface parameters where both scattering and absorption effects are coupled, as well as in the cases of significant multiple-scattering contributions. However, sophisticated modeling approaches can handle such non-linear effects, which are especially important over vegetated surfaces. All the data used in this study were acquired during the 1991 Multisensor Airborne Campaign (MAC-Europe), as part of the European Field Experiment on a Desertification-threatened Area (EFEDA), carried out in Spain in June-July 1991.
On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. At JPL, a novel, adaptive and predictive technique for lossless compression of hyperspectral data, named the Fast Lossless (FL) algorithm, was recently developed. This technique uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. Because of its outstanding performance and suitability for real-time onboard hardware implementation, the FL compressor is being formalized as the emerging CCSDS Standard for Lossless Multispectral & Hyperspectral image compression. The FL compressor is well-suited for parallel hardware implementation. A GPU hardware implementation was developed for FL targeting the current state-of-the-art GPUs from NVIDIA(Trademark). The GPU implementation on a NVIDIA(Trademark) GeForce(Trademark) GTX 580 achieves a throughput performance of 583.08 Mbits/sec (44.85 MSamples/sec) and an acceleration of at least 6 times a software implementation running on a 3.47 GHz single core Intel(Trademark) Xeon(Trademark) processor. This paper describes the design and implementation of the FL algorithm on the GPU. The massively parallel implementation will provide in the future a fast and practical real-time solution for airborne and space applications.
Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.