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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Dosimetry of heavy ions by use of CCD detectors

The design and the atomic composition of Charge Coupled Devices (CCD's) make them unique for investigations of single energetic particle events. As detector system for ionizing particles they detect single particles with local resolution and near real time particle tracking. In combination with its properties as optical sensor, particle transversals of single particles are to be correlated to any objects attached to the light sensitive surface of the sensor by simple imaging of their shadow and subsequent image analysis of both, optical image and particle effects, observed in affected pixels. With biological objects it is possible for the first time to investigate effects of single heavy ions in tissue or extinguished organs of metabolizing (i.e. moving) systems with a local resolution better than 15 microns. Calibration data for particle detection in CCD's are presented for low energetic protons and heavy ions.

Schott, J. U.↗
NASA NTRS2008

Object Recognition using Feature- and Color-Based Methods

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Duong, Tuan↗
NASA NTRS2016

Hexapod Robot

The project I am working on at NASA-Johnson Space Center in Houston, TX is a hexapod robot. This project was started by various engineers at the Trick Lab. The goal of this project is to have the hexapod track a yellow ball or possibly another object from left to right and up/down. The purpose is to have it track an object like a real creature. The project will consist of using software and hardware. This project started with a hexapod robot which uses a senor bar to track a yellow ball but with a limited field of vision. The sensor bar acts as the robots "head." Two servos will be added to the hexapod to create flexion and extension of the head. The neck and head servos will have to be programmed to be added to the original memory map of the existing servos. I will be using preexisting code. The main programming language that will be used to add to the preexisting code is C++. The trick modeling and simulation software will also be used in the process to improve its tracking and movement. This project will use a trial and error approach, basically seeing what works and what does not. The first step is to initially understand how the hexapod works. To get a general understanding of how the hexapod maneuvers and plan on how to had a neck and head servo which works with the rest of the body. The second step would be configuring the head and neck servos with the leg servos. During this step, limits will be programmed specifically for the each servo. By doing this, the servo is limited to how far it can rotate both clockwise and counterclockwise and this is to prevent hardware damage. The hexapod will have two modes in which it works in. The first mode will be if the sensor bar does not detect an object. If the object it is programmed to look for is not in its view it will automatically scan from left to right 3 times then up and down once. The second mode will be if the sensor bar does detect the object. In this mode the hexapod will track the object from left to right or up and down. The hexapod will eventually be able to track the object moving its head and body in sync with on another and being able to rotate its body at 360 degrees. This is the plans and possible end results for the hexapod robot I will be working on during my summer internship at NASA Johnson Space Center. Since working on the hexapod project I have gained an increase interest in robotics. I enjoy the process of critical thinking. Also will working on this project I was challenged in a way that made more passionate to strive even more to become an engineer. I've learned that asking questions is an important part of the learning process. Also I learn that much more is accomplished when teamwork is applied.

Begody, Ericka↗
NASA NTRS1982

Software simulations of the detection of rapidly moving asteroids by a charge-coupled device

A rendezvous of an unmanned probe to an earth-approaching asteroid has been given a high priority in the planning of interplanetary missions for the 1990s. Even without a space mission, much could be learned about the history of asteroids and comet nuclei if more information were available concerning asteroids with orbits which cross or approach the orbit of earth. It is estimated that the total number of earth-crossers accessible to ground-based survey telescopes should be approximately 1000. However, in connection with the small size and rapid angular motion expected of many of these objects an average of only one object is discovered per year. Attention is given to the development of the software necessary to distinguish such rapidly moving asteroids from stars and noise in continuously scanned CCD exposures of the night sky. Model and input parameters are considered along with detector sensitivity, aspects of minimum detectable displacement, and the point-spread function of the CCD.

Mcmillan, R. S.↗
NASA NTRS1993

Multiple-camera/motion stereoscopy for range estimation in helicopter flight

Aiding the pilot to improve safety and reduce pilot workload by detecting obstacles and planning obstacle-free flight paths during low-altitude helicopter flight is desirable. Computer vision techniques provide an attractive method of obstacle detection and range estimation for objects within a large field of view ahead of the helicopter. Previous research has had considerable success by using an image sequence from a single moving camera to solving this problem. The major limitations of single camera approaches are that no range information can be obtained near the instantaneous direction of motion or in the absence of motion. These limitations can be overcome through the use of multiple cameras. This paper presents a hybrid motion/stereo algorithm which allows range refinement through recursive range estimation while avoiding loss of range information in the direction of travel. A feature-based approach is used to track objects between image frames. An extended Kalman filter combines knowledge of the camera motion and measurements of a feature's image location to recursively estimate the feature's range and to predict its location in future images. Performance of the algorithm will be illustrated using an image sequence, motion information, and independent range measurements from a low-altitude helicopter flight experiment.

Smith, Phillip N.↗
NASA NTRS2003

Dual beam optical interferometer

A dual beam interferometer device is disclosed that enables moving an optics module in a direction, which changes the path lengths of two beams of light. The two beams reflect off a surface of an object and generate different speckle patterns detected by an element, such as a camera. The camera detects a characteristic of the surface.

Gutierrez, Roman C.↗
NASA NTRSDate not supplied

Enhancing the Sensitivity of Redox Detection in Search-for-Life Missions Using Chemical Vapor Deposition (CVD) Graphene Electrodes

The primary objective for this effort is to fabricate and characterize redox-active molecules using CVD graphene as working electrodes using standard "on-chip" lithographic techniques. We then plan to move away from “on-chip” graphene electrodes and study methods for CVD graphene transfer that can also accommodate in-space manufacturing (ISM), enabling the use of this technology for crewed mission operations of the future.

graphene↗
NASA NTRS2020

Polarization Sensing in Digital Holographic Microscopy

Digital holographic microscopy is well suited to the search for microbial species due in part to its intrinsic stability, volumetric imaging capability, and sensitivity to very dilute samples. This is all done with a system having no moving parts, making it additionally attractive for flight instrumentation. Our devices have been field tested on several occasions, and have demonstrated robustness to extreme conditions. When bacteria are alive and moving, they are easy to detect. However, some measurements are subtler. Can we distinguish between a live yet nonmotile species and a mineral, for instance? To provide another method of discrimination, we have added the ability to measure object polarization. This will allow us to characterize the sample by polarization state without any sacrifice in the spatial or temporal resolution (< 1um at 15 Hz). This snapshot polarization sensing is a new method for characterizing the sample under test. In this paper, we will describe the instrument design, the laboratory tests, and demonstrate its performance with live bacteria and crystalline samples.

Wallace, James↗
NASA NTRS1975

Servo-controlled intravital microscope system

A microscope system is described for viewing an area of a living body tissue that is rapidly moving, by maintaining the same area in the field-of-view and in focus. A focus sensing portion of the system includes two video cameras at which the viewed image is projected, one camera being slightly in front of the image plane and the other slightly behind it. A focus sensing circuit for each camera differentiates certain high frequency components of the video signal and then detects them and passes them through a low pass filter, to provide dc focus signal whose magnitudes represent the degree of focus. An error signal equal to the difference between the focus signals, drives a servo that moves the microscope objective so that an in-focus view is delivered to an image viewing/recording camera.

Mansour, M. N.↗
NASA NTRS1986

Satellite debris - Recent measurements

More frequent reports concerning orbital debris damage to spacecraft have prompted the design, development and testing of equipment and techniques for the observation of moving objects by passive optical means. A consolidation is presently made of hundreds of hours of space debris observation, quantifying the numbers of small bodies in space relative to the actively watched artificial satellite population and estimating the numbers of detectable objects from near-earth orbit to geostationary orbit distances. The debris reported constitutes 11 times the tracked population in near-earth orbit and between 25 and 50 percent of the deep space population.

Taff, L. G.↗
NASA NTRS1996

CCD Detects Two Images In Quick Succession

Prototype special-purpose charge-coupled device (CCD) designed to detect two 1,024 x 1,024-pixel images in rapid succession. Readout performed slowly to minimize noise. CCD operated in synchronism with pulsed laser, stroboscope, or other pulsed source of light to form pairs of images of rapidly moving objects.

Janesick, James R.↗
NASA NTRS2009

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗
NASA NTRS2019

A Robust Vision-Based Algorithm for Detecting and Classifying Small Orbital Debris Using On-Board Optical Cameras

This study develops a vision-based detection and classification algorithm to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. The algorithm operates in near real time and is robust under difficult tasks in moving objects classification such as multiple moving objects, objects with various movement trajectories and speeds, very small or faint objects, and substantial background motion. The performance of the algorithm is optimized and validated using space image data available through simulated environments generated using NASA Marshall Space Flight Centers Dynamic Star Field Simulator of on-board optical sensors and cameras.

Zamani, Yasin↗
NASA NTRS2019

Machine Learning for the Zwicky Transient Facility

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective.

Ashish Mahabal↗
NASA NTRS2004

NASA's Terrestrial Planet Finder Missions

NASA has decided to move forward with two complementary Terrestrial Planet Finder (TPF) missions, a visible coronagraph and an infrared formation flying interferometer. These missions are major missions in the NASA Office of Space Science Origins Theme. The primary science objectives of the TPF missions are to search for, detect, and characterize planets and planetary systems beyond our own Solar System, including specifically Earth-like planets.

Terrestrial Planet Finder (TPF)↗
NASA NTRSDate not supplied

Constraining Alteration Processes Along the Siccar Point Unconformity in Gale Crater: Results from the Sample Analysis at Mars Instrument

A driving factor for sending the Mars Science Laboratory, Curiosity rover to Gale Crater was the orbital detection of clay minerals in the Glen Torridon (GT) region suggesting a past aqueous environment was habitable and could contain organic evidence of past microbiology. The objective of the Curiosity’s Sample Analysis at Mars (SAM)instrument was to detect organic evidence of past microbiology and volatile bearing mineralogy that would inform if past geochemical conditions would have supported microbiology in the GT region. The Siccar Point unconformity occurs between the underlying GT mudstone and the overlying Stimsons and stone of the Green heugh Pediment has evidence of enhanced alteration in the mudstone just below the contact suggestive of aqueous processes favorable for microbial activity. The origin of the altered material includes subaerial weathering, alteration from fluids moving along unconformity, upward fluid percolation from the mudstone or downward fluid percolation from the Pediment 1,2,3,4,5The objectives of this work were to 1) Utilize the S AM-EGA results to characterize the geochemistry and mineralogy above and below the Siccar Point unconformity through analysis of drilled samples in the3 GT mudstones and an overlying pediment sandstone. and 2) Utilize SAM-EGA results to constrain alteration scenario(s) below the unconformity.

B Sutter↗
NASA NTRS2004

Segmenting Images for a Better Diagnosis

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Source record↗
NASA NTRS2019

NIAC Phase I Final Report: On-Orbit, Collision-Free Mapping of Small Orbital Debris

Sub-centimeter orbital debris is currently undetectable using ground-based radar and optical methods. However, the pits in Space Shuttle windows produced by paint chips (e.g. the 3.8mm diameter pit produced by a 0.2mm paint chip on STS-7) demonstrate that small debris can cause serious damage to spacecraft. Recent analytical, computational and experimental work has shown that charged objects moving quickly through a plasma will cause the formation of solitons in the plasma density. Due to their exposure to the solar wind plasma environment, even the smallest space debris will be charged. Depending on the debris size, charge and velocity, the plasma signature of the solitons may be detected by simple instrumentation on spacecraft. We will describe the amplitude and velocity of solitons that may be produced by mm-cm scale orbital debris in LEO. We will discuss the feasibility of mapping sub-cm orbital debris using a fleet of CubeSats equipped with Langmuir probes. The time and fleet size required to map the debris will also be described. Plasma soliton detection would be the first collision-free method of mapping the small debris population.

Orbital Debris↗