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At least 253 records · Page 14

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NASA NTRS1987

Orbital navigation, docking and obstacle avoidance as a form of three dimensional model-based image understanding

Range imagery from a laser scanner can be used to provide sufficient information for docking and obstacle avoidance procedures to be performed automatically. Three dimensional model-based computer vision algorithms in development can perform these tasks even with targets which may not be cooperative (that is, objects without special targets or markers to provide unambiguous location points). Roll, pitch and yaw of the vehicle can be taken into account as image scanning takes place, so that these can be corrected when the image is converted from egocentric to world coordinates. Other attributes of the sensor, such as the registered reflectence and texture channels, provide additional data sources for algorithm robustness. Temporal fusion of sensor immages can take place in the work coordinate domain, allowing for the building of complex maps in three dimensional space.

Beyer, J.↗

NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗

NASA NTRSDate not supplied

Predicting Cognitive States Using Machine Learning Fusion Paradigms to Reduce Model Uncertainty

The development of a synergetic system between humans and technology is a challenge that the scientific community has been facing for many years. Our aeronautic research aims to enhance this synergy between humans and machines through predictive human performance modeling for systems to mitigate high-risk situations. By being able to predict and anticipate human states, the crew monitoring system should be able to adjust and support the pilot for aviation safety. Our work focusing on attention-related human performance-limiting states (AHPLS) that impact a pilot’s performance and introduce high-risk catastrophic situations [1]. For example, AHPLS has been cited as a causal factor in more than 50% of all loss control in flight and thus contributes significantly toward commercial aviation fatalities [1, 2]. Cognitive state and its physiological fingerprint can be valuable information for this detecting AHPLS, but human cognitive state detection is still a major limitation for these crew monitoring systems.

machine learning↗

NASA NTRS2003

Update on Integrated Optical Design Analyzer

Updated information on the Integrated Optical Design Analyzer (IODA) computer program has become available. IODA was described in Software for Multidisciplinary Concurrent Optical Design (MFS-31452), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 8a. To recapitulate: IODA facilitates multidisciplinary concurrent engineering of highly precise optical instruments. The architecture of IODA was developed by reviewing design processes and software in an effort to automate design procedures. IODA significantly reduces design iteration cycle time and eliminates many potential sources of error. IODA integrates the modeling efforts of a team of experts in different disciplines (e.g., optics, structural analysis, and heat transfer) working at different locations and provides seamless fusion of data among thermal, structural, and optical models used to design an instrument. IODA is compatible with data files generated by the NASTRAN structural-analysis program and the Code V (Registered Trademark) optical-analysis program, and can be used to couple analyses performed by these two programs. IODA supports multiple-load-case analysis for quickly accomplishing trade studies. IODA can also model the transient response of an instrument under the influence of dynamic loads and disturbances.

Moore, James D., Jr.↗

NASA NTRS2001

GPS/Magnetometer Based Satellite Navigation and Attitude Determination

In recent years algorithms were developed for orbit, attitude and angular-rate determination of Low Earth Orbiting (LEO) satellites. Those algorithms rely on measurements of magnetometers, which are standard, relatively inexpensive, sensors that are normally installed on every LEO satellite. Although magnetometers alone are sufficient for obtaining the desired information, the convergence of the algorithms to the correct values of the satellite orbital parameters, position, attitude and angular velocity is very slow. The addition of sun sensors reduces the convergence time considerably. However, for many LEO satellites the sun data is not available during portions of the orbit when the spacecraft (SC) is in the earth shadow. It is here where the GPS space vehicles (SV) can provide valuable support. This is clearly demonstrated in the present paper. Although GPS measurements alone can be used to obtain SC position, velocity, attitude and angular-rate, the use of magnetometers improve the results due to the synergistic effect of sensor fusion. Moreover, it is possible to obtain these results with less than three SVs. In this paper we introduce an estimation algorithm, which is a combination of an Extended Kalman Filter (EKF) and a Pseudo Linear Kalman Filter (PSELIKA).

Deutschmann, Julie↗

NASA NTRS2005

Real-time Enhanced Vision System

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

Hines, Glenn D.↗

NASA NTRS1999

Orthologs, paralogs and genome comparisons

During the past decade, ancient gene duplications were recognized as one of the main forces in the generation of diverse gene families and the creation of new functional capabilities. New tools developed to search data banks for homologous sequences, and an increased availability of reliable three-dimensional structural information led to the recognition that proteins with diverse functions can belong to the same superfamily. Analyses of the evolution of these superfamilies promises to provide insights into early evolution but are complicated by several important evolutionary processes. Horizontal transfer of genes can lead to a vertical spread of innovations among organisms, therefore finding a certain property in some descendants of an ancestor does not guarantee that it was present in that ancestor. Complete or partial gene conversion between duplicated genes can yield phylogenetic trees with several, apparently independent gene duplications, suggesting an often surprising parallelism in the evolution of independent lineages. Additionally, the breakup of domains within a protein and the fusion of domains into multifunctional proteins makes the delineation of superfamilies a task that remains difficult to automate.

Non-NASA Center↗

NASA NTRS2008

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗

NASA NTRS2015

Magnetospheric Multiscale Overview and Science Objectives

Magnetospheric Multiscale (MMS), a NASA four-spacecraft constellation mission launched on March 12, 2015, will investigate magnetic reconnection in the boundary regions of the Earth's magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. The most important goal of MMS is to conduct a definitive experiment to determine what causes magnetic field lines to reconnect in a collisionless plasma. The significance of the MMS results will extend far beyond the Earth's magnetosphere because reconnection is known to occur in interplanetary space and in the solar corona where it is responsible for solar flares and the disconnection events known as coronal mass ejections. Active research is also being conducted on reconnection in the laboratory and specifically in magnetic-confinement fusion devices in which it is a limiting factor in achieving and maintaining electron temperatures high enough to initiate fusion. Finally, reconnection is proposed as the cause of numerous phenomena throughout the universe such as comet-tail disconnection events, magnetar flares, supernova ejections, and dynamics of neutron-star accretion disks. The MMS mission design is focused on answering specific questions about reconnection at the Earth's magnetosphere. The prime focus of the mission is on determining the kinetic processes occurring in the electron diffusion region that are responsible for reconnection and that determine how it is initiated; but the mission will also place that physics into the context of the broad spectrum of physical processes associated with reconnection. Connections to other disciplines such as solar physics, astrophysics, and laboratory plasma physics are expected to be made through theory and modeling as informed by the MMS results.

Space plasma physics↗

NASA NTRS1997

Neural Network Based Sensory Fusion for Landmark Detection

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Kumbla, Kishan -K.↗

NASA NTRS1998

ELIPS: Toward a Sensor Fusion Processor on a Chip

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an "intelligent" processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

Daud, Taher↗

NASA NTRS2001

Magnetized Target Fusion Driven by Plasma Liners

For practical applications of magnetized target fusion, standoff drivers to deliver the imploding momentum flux to the target plasma remotely are required. Quasi-spherically converging plasma jets have been proposed as standoff drivers for this purpose. The concept involves the dynamic formation of a quasi-spherical plasma liner by the merging of plasma jets, and the use of the liner so formed to compress a spheromak or a field reversed configuration (FRC). Theoretical analysis and computer modeling of the concept are presented. It is shown that, with the appropriate choice of the flow parameters in the liner and the target, the impact between the liner and the target plasma can be made to be shockless in the liner or to generate at most a very weak shock in the liner. Additional information is contained in the original extended abstract.

Thio, Y. C. Francis↗

NASA NTRS1999

Model system for plant cell biology: GFP imaging in living onion epidermal cells

The ability to visualize organelle localization and dynamics is very useful in studying cellular physiological events. Until recently, this has been accomplished using a variety of staining methods. However, staining can give inaccurate information due to nonspecific staining, diffusion of the stain or through toxic effects. The ability to target green fluorescent protein (GFP) to various organelles allows for specific labeling of organelles in vivo. The disadvantages of GFP thus far have been the time and money involved in developing stable transformants or maintaining cell cultures for transient expression. In this paper, we present a rapid transient expression system using onion epidermal peels. We have localized GFP to various cellular compartments (including the cell wall) to illustrate the utility of this method and to visualize dynamics of these compartments. The onion epidermis has large, living, transparent cells in a monolayer, making them ideal for visualizing GFP. This method is easy and inexpensive, and it allows for testing of new GFP fusion proteins in a living tissue to determine deleterious effects and the ability to express before stable transformants are attempted.

NASA Discipline Plant Biology↗

NASA NTRS1991

Method and apparatus for sensor fusion

Method and apparatus for fusion of data from optical and radar sensors by error minimization procedure is presented. The method was applied to the problem of shape reconstruction of an unknown surface at a distance. The method involves deriving an incomplete surface model from an optical sensor. The unknown characteristics of the surface are represented by some parameter. The correct value of the parameter is computed by iteratively generating theoretical predictions of the radar cross sections (RCS) of the surface, comparing the predicted and the observed values for the RCS, and improving the surface model from results of the comparison. Theoretical RCS may be computed from the surface model in several ways. One RCS prediction technique is the method of moments. The method of moments can be applied to an unknown surface only if some shape information is available from an independent source. The optical image provides the independent information.

Krishen, Kumar↗

NASA NTRS1991

Reliable fusion of control and sensing in intelligent machines

Although robotics research has produced a wealth of sophisticated control and sensing algorithms, very little research has been aimed at reliably combining these control and sensing strategies so that a specific task can be executed. To improve the reliability of robotic systems, analytic techniques are developed for calculating the probability that a particular combination of control and sensing algorithms will satisfy the required specifications. The probability can then be used to assess the reliability of the design. An entropy formulation is first used to quickly eliminate designs not capable of meeting the specifications. Next, a framework for analyzing reliability based on the first order second moment methods of structural engineering is proposed. To ensure performance over an interval of time, lower bounds on the reliability of meeting a set of quadratic specifications with a Gaussian discrete time invariant control system are derived. A case study analyzing visual positioning in robotic system is considered. The reliability of meeting timing and positioning specifications in the presence of camera pixel truncation, forward and inverse kinematic errors, and Gaussian joint measurement noise is determined. This information is used to select a visual sensing strategy, a kinematic algorithm, and a discrete compensator capable of accomplishing the desired task. Simulation results using PUMA 560 kinematic and dynamic characteristics are presented.

Mcinroy, John E.↗

NASA NTRS1992

Helium mining on the Moon: Site selection and evaluation

The feasibility of recovering helium (He) from the Moon as a source of fusion energy on Earth is currently being studied at the University of Wisconsin. Part of this study is selection and evaluation of potential sites for lunar He mining. Selection and evaluation of potential mining sites are based on four salient findings by various investigators of lunar samples: (1) Regoliths from areas underlain by highland materials contain less than 20 wppm He; (2) Certain maria regoliths contain less than 20 wppm He, but other contain 25 to 49 wppm; (3) The He content of a mare regolith is a function of its composition; regoliths rich in Ti are relatively rich in He; and (4) He is concentrated in the less than 100-micron size fractions of regoliths. The first three findings suggest that maria are the most promising mining sites, specifically, those that have high-Ti regoliths. Information on the regional distribution and extent of high-Ti regoliths comes mainly from two sources: direct sampling by various Apollo and Luna missions, and remote sensing by gamma-ray spectroscopy and Earth-based measurements of lunar spectral reflectance. Sampling provides essential control on calibration and interpretation of data from remote sensing. These data indicate that Mare Tranquillitatis is the principal area of high-Ti regolith of the eastern nearside, but large areas of high-Ti regolith are indicated in the Imbrium and Procellarum regions. Recovery of significant amounts of He-3 will require mining billions of tonnes of regolith. Large individual areas suitable for mining must therefore be delineated. The concentration of He in the finer size fractions and considerations of ease of mining mean that mining areas must be as free as possible of sizable craters and blocks of rock. Pending additional lunar missions, information regarding these features must be obtained from lunar photographs, photogeologic maps, and radar surveys. The present study is decidedly preliminary; available information is much to limited to permit even a close approach to final evaluations. As a prelude to recovery of He from the Moon, systematic exploration and sampling of high-Ti regoliths should therefore have a high priority in future lunar missions.

Cameron, Eugene N.↗

NASA NTRS1972

Ion and laser microprobes applied to the measurement of corrosion produced hydrogen on a microscopic scale.

Use of an ion microprobe and a laser microprobe to measure concentrations of corrosion-produced hydrogen on a microscopic scale. Hydrogen concentrations of several thousand ppm were measured by both analytical techniques below corroded and fracture surfaces of hot salt stress corroded titanium alloy specimens. This extremely high concentration compares with only about 100 ppm hydrogen determined by standard vacuum fusion chemical analyses of bulk samples. Both the ion and laser microprobes were used to measure hydrogen concentration profiles in stepped intervals to substantial depths below the original corroded and fracture surfaces. For the ion microprobe, the area of local analysis was 22 microns in diameter and for the laser microprobe, the area of local analysis was about 300 microns in diameter. The segregation of hydrogen below fracture surfaces supports a previously proposed theory that corrosion-produced hydrogen is responsible for hot salt stress corrosion embrittlement and cracking of titanium alloys. These advanced analytical techniques suggest great potential for many areas of stress corrosion and hydrogen embrittlement research, quality control, and field inspection of corrosion problems. For example, it appears possible that a contour map of hydrogen distribution at notch roots and crack tips could be quantitatively determined. Such information would be useful in substantiating current theories of stress corrosion and hydrogen embrittlement.

Gray, H. R.↗

NASA NTRS2001

Micro Navigator

Miniature high-performance low-mass space avionics systems are desired for planned future outer planetary exploration missions (i.e. Europa Orbiter/Lander, Pluto-Kuiper Express). The spacecraft fuel and mass requirements enabling orbit insertion is the driving requirement. The Micro Navigator is an integrated autonomous Guidance, Navigation & Control (GN&C)micro-system that would provide the critical avionics function for navigation, pointing, and precision landing. The Micro Navigator hardware and software allow fusion of data from multiple sensors to provide a single integrated vehicle state vector necessary for six degrees of freedom GN&C. The benefits of this MicroNavigator include: 1) The Micro Navigator employs MEMS devices that promise orders of magnitude reductions in mass power and volume of inertial sensors (accelerometers and gyroscopes), celestial sensing devices (startracker, sun sensor), and computing element; 2) The highly integrated nature of the unit will reduce the cost of flight missions. a) The advanced miniaturization technologies employed by the Micro Navigator lend themselves to mass production, and therefore will reduce production cost of spacecraft. b) The integral approach simplifies interface issues associated with discrete components and reduces cost associated with integration and test of multiple components; and 3) The integration of sensors and processing elements into a single unit will allow the Micro Navigator to encapsulate attitude information and determination functions into a single object. This is particularly beneficial for object-oriented software architectures that are used in advanced spacecraft. Additional information is contained in the original extended abstract.

Blaes, B. R.↗