Engineering PapersSearch

Engineering topics

Lau, Sonie

Publications and source records attributed to Lau, Sonie.

At least 19 records

Subauditory Speech Recognition based on EMG/EPG Signals

Sub-vocal electromyogram/electro palatogram (EMG/EPG) signal classification is demonstrated as a method for silent speech recognition. Recorded electrode signals from the larynx and sublingual areas below the jaw are noise filtered and transformed into features using complex dual quad tree wavelet transforms. Feature sets for six sub-vocally pronounced words are trained using a trust region scaled conjugate gradient neural network. Real time signals for previously unseen patterns are classified into categories suitable for primitive control of graphic objects. Feature construction, recognition accuracy and an approach for extension of the technique to a variety of real world application areas are presented.

Jorgensen, Charles

Linear and Order Statistics Combiners for Pattern Classification

Several researchers have experimentally shown that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple classifiers. This chapter provides an analytical framework to quantify the improvements in classification results due to combining. The results apply to both linear combiners and order statistics combiners. We first show that to a first order approximation, the error rate obtained over and above the Bayes error rate, is directly proportional to the variance of the actual decision boundaries around the Bayes optimum boundary. Combining classifiers in output space reduces this variance, and hence reduces the 'added' error. If N unbiased classifiers are combined by simple averaging. the added error rate can be reduced by a factor of N if the individual errors in approximating the decision boundaries are uncorrelated. Expressions are then derived for linear combiners which are biased or correlated, and the effect of output correlations on ensemble performance is quantified. For order statistics based non-linear combiners, we derive expressions that indicate how much the median, the maximum and in general the i-th order statistic can improve classifier performance. The analysis presented here facilitates the understanding of the relationships among error rates, classifier boundary distributions, and combining in output space. Experimental results on several public domain data sets are provided to illustrate the benefits of combining and to support the analytical results.

Tumer, Kagan

Medium Fidelity Simulation of Oxygen Tank Venting

The item to he cleared is a medium-fidelity software simulation model of a vented cryogenic tank. Such tanks are commonly used to transport cryogenic liquids such as liquid oxygen via truck, and have appeared on liquid-fueled rockets for decades. This simulation model works with the HCC simulation system that was developed by Xerox PARC and NASA Ames Research Center. HCC has been previously cleared for distribution. When used with the HCC software, the model generates simulated readings for the tank pressure and temperature as the simulated cryogenic liquid boils off and is vented. Failures (such as a broken vent valve) can be injected into the simulation to produce readings corresponding to the failure. Release of this simulation will allow researchers to test their software diagnosis systems by attempting to diagnose the simulated failure from the simulated readings. This model does not contain any encryption software nor can it perform any control tasks that might be export controlled.

Sweet, Adam

Mars Rovers: Past, Present, and Future

This viewgraph presentation provides information on the exploration of Mars through the use of rover vehicles. Mars is considered an interesting planet because it is the most like Earth of all known planets, and it may have or have had water on or below its surface. There are many different engineering design challenges for roving vehicles intended for Mars. These include: communications time delay, narrow communications bandwidth, extreme temperatures, rough and rocky terrain, the lack of a global positioning system, and dust. The Sojourner Rover specifications are provided including wheel diameter and instruments. There are prototypes being tested at NASA's Ames Research Center of the next generation Mars rovers.

Bualat, Maria

Roughness Perception of Haptically Displayed Fractal Surfaces

Surface profiles were generated by a fractal algorithm and haptically rendered on a force feedback joystick, Subjects were asked to use the joystick to explore pairs of surfaces and report to the experimenter which of the surfaces they felt was rougher. Surfaces were characterized by their root mean square (RMS) amplitude and their fractal dimension. The most important factor affecting the perceived roughness of the fractal surfaces was the RMS amplitude of the surface. When comparing surfaces of fractal dimension 1.2-1.35 it was found that the fractal dimension was negatively correlated with perceived roughness.

Costa, Michael A.

On-Line Fringe Tracking and Prediction at IOTA

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data; and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize on-line the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

Wilson, Edward

Model Based Autonomy for Robust Mars Operations

Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

Kurien, James A.

An Introduction to Markov Modeling: Concepts and Uses

Kharkov modeling is a modeling technique that is widely useful for dependability analysis of complex fault tolerant systems. It is very flexible in the type of systems and system behavior it can model. It is not, however, the most appropriate modeling technique for every modeling situation. The first task in obtaining a reliability or availability estimate for a system is selecting which modeling technique is most appropriate to the situation at hand. A person performing a dependability analysis must confront the question: is Kharkov modeling most appropriate to the system under consideration, or should another technique be used instead? The need to answer this gives rise to other more basic questions regarding Kharkov modeling: what are the capabilities and limitations of Kharkov modeling as a modeling technique? How does it relate to other modeling techniques? What kind of system behavior can it model? What kinds of software tools are available for performing dependability analyses with Kharkov modeling techniques? These questions and others will be addressed in this tutorial.

Boyd, Mark A.

Basis Selection for Wavelet Regression

A wavelet basis selection procedure is presented for wavelet regression. Both the basis and the threshold are selected using cross-validation. The method includes the capability of incorporating prior knowledge on the smoothness (or shape of the basis functions) into the basis selection procedure. The results of the method are demonstrated on sampled functions widely used in the wavelet regression literature. The results of the method are contrasted with other published methods.

Wheeler, Kevin R.

Markov Tracking for Agent Coordination

Partially observable Markov decision processes (POMDPs) axe an attractive representation for representing agent behavior, since they capture uncertainty in both the agent's state and its actions. However, finding an optimal policy for POMDPs in general is computationally difficult. In this paper we present Markov Tracking, a restricted problem of coordinating actions with an agent or process represented as a POMDP Because the actions coordinate with the agent rather than influence its behavior, the optimal solution to this problem can be computed locally and quickly. We also demonstrate the use of the technique on sequential POMDPs, which can be used to model a behavior that follows a linear, acyclic trajectory through a series of states. By imposing a "windowing" restriction that restricts the number of possible alternatives considered at any moment to a fixed size, a coordinating action can be calculated in constant time, making this amenable to coordination with complex agents.

Washington, Richard

A Hybrid Procedural/Deductive Executive for Autonomous Spacecraft

The New Millennium Remote Agent (NMRA) will be the first AI system to control an actual spacecraft. The spacecraft domain places a strong premium on autonomy and requires dynamic recoveries and robust concurrent execution, all in the presence of tight real-time deadlines, changing goals, scarce resource constraints, and a wide variety of possible failures. To achieve this level of execution robustness, we have integrated a procedural executive based on generic procedures with a deductive model-based executive. A procedural executive provides sophisticated control constructs such as loops, parallel activity, locks, and synchronization which are used for robust schedule execution, hierarchical task decomposition, and routine configuration management. A deductive executive provides algorithms for sophisticated state inference and optimal failure recover), planning. The integrated executive enables designers to code knowledge via a combination of procedures and declarative models, yielding a rich modeling capability suitable to the challenges of real spacecraft control. The interface between the two executives ensures both that recovery sequences are smoothly merged into high-level schedule execution and that a high degree of reactivity is retained to effectively handle additional failures during recovery.

Pell, Barney

Using Decision Procedures to Build Domain-Specific Deductive Synthesis Systems

This paper describes a class of decision procedures that we have found useful for efficient, domain-specific deductive synthesis. These procedures are called closure-based ground literal satisfiability procedures. We argue that this is a large and interesting class of procedures and show how to interface these procedures to a theorem prover for efficient deductive synthesis. Finally, we describe some results we have observed from our implementation. Amphion/NAIF is a domain-specific, high-assurance software synthesis system. It takes an abstract specification of a problem in solar system mechanics, such as 'when will a signal sent from the Cassini spacecraft to Earth be blocked by the planet Saturn?', and automatically synthesizes a FORTRAN program to solve it.

VanBaalen, Jeffrey

Testing Planetary Rovers: Technologies, Perspectives, and Lessons Learned

Rovers are a vital component of NASA's strategy for manned and unmanned exploration of space. For the past five years, the Intelligent Mechanisms Group at the NASA Ames Research Center has conducted a vigorous program of field testing of rovers from both technology and science team productivity perspective. In this talk, I will give an overview of the the last two years of the test program, focusing on tests conducted in the Painted Desert of Arizona, the Atacama desert in Chile, and on IMG participation in the Mars Pathfinder mission. An overview of autonomy, manipulation, and user interface technologies developed in response to these missions will be presented, and lesson's learned in these missions and their impact on future flight missions will be presented. I will close with some perspectives on how the testing program has affected current rover systems.

Thomas, Hans

Explaining Synthesized Software

Motivated by NASA's need for high-assurance software, NASA Ames' Amphion project has developed a generic program generation system based on deductive synthesis. Amphion has a number of advantages, such as the ability to develop a new synthesis system simply by writing a declarative domain theory. However, as a practical matter, the validation of the domain theory for such a system is problematic because the link between generated programs and the domain theory is complex. As a result, when generated programs do not behave as expected, it is difficult to isolate the cause, whether it be an incorrect problem specification or an error in the domain theory. This paper describes a tool we are developing that provides formal traceability between specifications and generated code for deductive synthesis systems. It is based on extensive instrumentation of the refutation-based theorem prover used to synthesize programs. It takes augmented proof structures and abstracts them to provide explanations of the relation between a specification, a domain theory, and synthesized code. In generating these explanations, the tool exploits the structure of Amphion domain theories, so the end user is not confronted with the intricacies of raw proof traces. This tool is crucial for the validation of domain theories as well as being important in everyday use of the code synthesis system. It plays an important role in validation because when generated programs exhibit incorrect behavior, it provides the links that can be traced to identify errors in specifications or domain theory. It plays an important role in the everyday use of the synthesis system by explaining to users what parts of a specification or of the domain theory contribute to what pieces of a generated program. Comments are inserted into the synthesized code that document these explanations.

VanBaalen, Jeffrey

Leap Before You Look: Information Gathering In the PUCCINI Planner

Most of the work in planning with incomplete information takes a "look before you leap" perspective: Actions must be guaranteed to have their intended effects before they can be executed. We argue that this approach is impossible to follow in many real-world domains. The agent may not have enough information to ensure that an action will have a given effect in advance of executing it. This paper describes PUCCINI, a partial order planner used to control the Internet Softbot (Etzioni & Weld 1994). PUCCINI takes a different approach to coping with incomplete information: "Leap before you look!" PUCCINI doesn't require actions to be known to have the desired effects before execution. However, it still maintains soundness, by requiring the effects to be verified eventually. We discuss how this is achieved using a simple generalization of causal links.

Golden, Keith

Multilayer Volume Holographic Optical Memory

We demonstrate a scheme for volume holographic storage based on the features of shift selectivity of a speckle reference wave hologram. The proposed recording method allows more efficient use of the recording medium and increases the storage density in comparison with spherical or plane-wave reference beams. Experimental results of multiple hologram storage and replay in a photorefractive crystal of iron-doped lithium niobate are presented. The mechanism of lateral and longitudinal shift selectivity are described theoretically and shown to agree with experimental measurements.

Markov, Vladimir

Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

Patterson-Hine, Ann

Making the Impossible Possible: Strategies for Fast POMDP Monitoring

Systems modeled as partially observable Markov decision processes (POMDPs) can be tracked quickly with three restrictions: all actions are grouped together, the out-degree of each system state is bounded by a constant, and the number of non-zero elements in the belief state is bounded by a (different) constant. With these restrictions, the tracking algorithm operates in constant time and linear space. The first restriction assumes that the action itself is unobservable. The second restriction defines a subclass of POMDPs that covers however a wide range of problems. The third restriction is an approximation technique that can lead to a potentially vexing problem: an observation may be received that has probability according to the restricted belief state. This problem of impossibility will cause the belief state to collapse. In this paper we discuss the tradeoffs between the constant bound on the belief state and the quality of the solution. We concentrate on strategies for overcoming the impossibility problem and demonstrate initial experimental results that indicate promising directions.

Washington, Richard