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At least 325 records · Page 18
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NASA NTRS2003

Terrain Portrayal for Head-Down Displays Flight Test

The Synthetic Vision Systems General Aviation (SVS-GA) element of NASA's Aviation Safety Program is developing technology to eliminate low visibility induced General Aviation (GA) accidents through the application of synthetic vision techniques. SVS displays present computer generated 3-dimensional imagery of the surrounding terrain to greatly enhance pilot's situation awareness (SA), reducing or eliminating Controlled Flight into Terrain (CFIT), as well as Low-Visibility Loss of Control (LVLOC) accidents. In addition to substantial safety benefits, SVS displays have many potential operational benefits that can lead to flight in instrument meteorological conditions (IMC) resembling those conducted in visual meteorological conditions (VMC). Potential benefits could include lower landing minimums, more approach options, reduced training time, etc. SVS conducted research will develop display concepts providing the pilot with an unobstructed view of the outside terrain, regardless of weather conditions and time of day. A critical component of SVS displays is the appropriate presentation of terrain to the pilot. The relationship between the realism of the terrain presentation and resulting enhancements of pilot SA and pilot performance has been largely undefined. Comprised of coordinated simulation and flight test efforts, the terrain portrayal for head-down displays (TP-HDD) test series examined the effects of two primary elements of terrain portrayal: variations of digital elevation model (DEM) resolution and terrain texturing. Variations in DEM resolution ranged from sparsely spaced (30 arc-sec/2,953ft) to very closely spaced data (1 arc-sec/98 ft). Variations in texture involved three primary methods: constant color, elevation-based generic, and photo-realistic, along with a secondary depth cue enhancer in the form of a fishnet grid overlay. The TP-HDD test series was designed to provide comprehensive data to enable design trades to optimize all SVS applications, as well as develop requirements and recommendations to facilitate the implementation and certification of SVS displays. The TP-HDD flight experiment utilized the NASA LaRC Cessna 206 Stationaire and evaluated eight terrain portrayal concepts in an effort to confirm and extend results from the previously conducted TP-HDD simulation experiment. A total of 15 evaluation pilots, of various qualifications, accumulated over 75 hours of dedicated research flight time at Newport News (PHF) and Roanoke (ROA), VA, airports from August through October, 2002. This report will present results from the portion of testing conducted at Roanoke, VA.

Hughes, Monica F.↗
NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory’s considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm’s performance and ability to process ‘flight-like’ imagery formats with a ‘flight-like’ trajectory, positioning ourselves to easily process flight data from the upcoming ‘ISS Selfie’ activity and then compare the algorithm’s quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system.Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗
NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory's considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm's performance and ability to process 'flight-like' imagery formats with a 'flight-like' trajectory, positioning ourselves to easily process flight data from the upcoming 'ISS Selfie' activity and then compare the algorithm's quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system. Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗
NASA NTRS2004

Compact Microscope Imaging System with Intelligent Controls

The figure presents selected views of a compact microscope imaging system (CMIS) that includes a miniature video microscope, a Cartesian robot (a computer- controlled three-dimensional translation stage), and machine-vision and control subsystems. The CMIS was built from commercial off-the-shelf instrumentation, computer hardware and software, and custom machine-vision software. The machine-vision and control subsystems include adaptive neural networks that afford a measure of artificial intelligence. The CMIS can perform several automated tasks with accuracy and repeatability . tasks that, heretofore, have required the full attention of human technicians using relatively bulky conventional microscopes. In addition, the automation and control capabilities of the system inherently include a capability for remote control. Unlike human technicians, the CMIS is not at risk of becoming fatigued or distracted: theoretically, it can perform continuously at the level of the best human technicians. In its capabilities for remote control and for relieving human technicians of tedious routine tasks, the CMIS is expected to be especially useful in biomedical research, materials science, inspection of parts on industrial production lines, and space science. The CMIS can automatically focus on and scan a microscope sample, find areas of interest, record the resulting images, and analyze images from multiple samples simultaneously. Automatic focusing is an iterative process: The translation stage is used to move the microscope along its optical axis in a succession of coarse, medium, and fine steps. A fast Fourier transform (FFT) of the image is computed at each step, and the FFT is analyzed for its spatial-frequency content. The microscope position that results in the greatest dispersal of FFT content toward high spatial frequencies (indicating that the image shows the greatest amount of detail) is deemed to be the focal position.

McDowell, Mark↗
NASA NTRS2007

The "Biologically-Inspired Computing" Column

Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.

Hinchey, Mike↗
NASA NTRS1991

Medical informatics and telemedicine: A vision

The goal of medical informatics is to improve care. This requires the commitment and harmonious collaboration between the computer scientists and clinicians and an integrated database. The vision described is how medical information systems are going to impact the way medical care is delivered in the future.

Clemmer, Terry P.↗
NASA NTRS1994

An architecture for real-time vision processing

To study the feasibility of developing an architecture for real time vision processing, a task queue server and parallel algorithms for two vision operations were designed and implemented on an i860-based Mercury Computing System 860VS array processor. The proposed architecture treats each vision function as a task or set of tasks which may be recursively divided into subtasks and processed by multiple processors coordinated by a task queue server accessible by all processors. Each idle processor subsequently fetches a task and associated data from the task queue server for processing and posts the result to shared memory for later use. Load balancing can be carried out within the processing system without the requirement for a centralized controller. The author concludes that real time vision processing cannot be achieved without both sequential and parallel vision algorithms and a good parallel vision architecture.

Chien, Chiun-Hong↗
NASA NTRS1995

Help for the Visually Impaired

The Low Vision Enhancement System (LVES) is a video headset that offers people with low vision a view of their surroundings equivalent to the image on a five-foot television screen four feet from the viewer. It will not make the blind see but for many people with low vision, it eases everyday activities such as reading, watching TV and shopping. LVES was developed over almost a decade of cooperation between Stennis Space Center, the Wilmer Eye Institute of the Johns Hopkins Medical Institutions, the Department of Veteran Affairs, and Visionics Corporation. With the aid of Stennis scientists, Wilmer researchers used NASA technology for computer processing of satellite images and head-mounted vision enhancement systems originally intended for the space station. The unit consists of a head-mounted video display, three video cameras, and a control unit for the cameras. The cameras feed images to the video display in the headset.

Source record↗
NASA NTRS1993

Quality metrics for sensor images

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Ahumada, AL↗
NASA NTRS2000

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

Johnston, William E.↗
NASA NTRSDate not supplied

Vision 2030 Aircraft Propulsion Grand Challenge Problem: Full-engine CFD Simulations with High Geometric Fidelity and Physics Accuracy

In 2014 NASA published the outcome of the 2030 CFD Vision study: “CFD Vision 2030: A path to Revolutionary Computational Aerosciences” (Slotnick et al., 2014). The study provided a comprehensive review of the state of the art of CFD in 2014 for aerospace applications including, but not limited to, numerical algorithms, physics models, MDAO and HPC hardware. The study also proposed four conceptual ideas of Grand Challenge problems that would benefit from advances outlined in the roadmap including “off-design turbofan engine transient simulation”. The proposed challenges served as a starting point for more detailed problem descriptions that would benefit from advances in simulation. The objective of this paper is to build upon the NASA 2030 CFD Vision study and provide a detailed overview of what needs to take place to enable accurate and efficient simulation of flow through an aircraft engine at off-design condition for transient operation . Execution of the proposed roadmap would significantly advance aircraft engine development by reducing program cost, reducing program development timelines and enabling design objectives associated with Specific Fuel Consumption (SFC), noise, weight and durability.

compressor↗
NASA NTRS2016

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Toward CFD Vision 2030

Unstructured grid adaptation is a powerful tool to control discretization error for Computational Fluid Dynamics (CFD). It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provides a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity continue to be significant bottlenecks in the CFD work flow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to diffuse grid adaptation technology into production CFD work flows.

Park, Michael A.↗
NASA NTRS1993

Near real-time stereo vision system

The apparatus for a near real-time stereo vision system for use with a robotic vehicle is described. The system is comprised of two cameras mounted on three-axis rotation platforms, image-processing boards, a CPU, and specialized stereo vision algorithms. Bandpass-filtered image pyramids are computed, stereo matching is performed by least-squares correlation, and confidence ranges are estimated by means of Bayes' theorem. In particular, Laplacian image pyramids are built and disparity maps are produced from the 60 x 64 level of the pyramids at rates of up to 2 seconds per image pair. The first autonomous cross-country robotic traverses (of up to 100 meters) have been achieved using the stereo vision system of the present invention with all computing done onboard the vehicle. The overall approach disclosed herein provides a unifying paradigm for practical domain-independent stereo ranging.

Anderson, Charles H.↗
NASA NTRS1988

Lunar stone saw

This project addresses the problem of cutting lunar stones into blocks to be used to construct shelters to protect personnel and equipment from harmful solar radiation. This plant will manufacture 6 in x 1 ft x 2 ft blocks and will be located near the south pole to allow it to be in the shade at all times. This design uses a computer controlled robot, a boulder handler that uses hydraulics for movement, a computer system that used 3-D vision to determine the size of boulders, a polycrystalline diamond tipped saw blade that utilizes radiation for cooling, and a solar tower to collect solar energy. Only two electric motors are used in this plant because of the heavy weight of electric motors and the problem of cooling them. These two motors will be cooled by thermoelectric cooling. All other motors and actuators are to be hydraulic. The architectural design for the building as well as the conceptual design of the machines for cutting the blocks are described.

Clark, Tom↗
NASA NTRS1992

Supercomputers Of The Future

Report evaluates supercomputer needs of five key disciplines: turbulence physics, aerodynamics, aerothermodynamics, chemistry, and mathematical modeling of human vision. Predicts these fields will require computer speed greater than 10(Sup 18) floating-point operations per second (FLOP's) and memory capacity greater than 10(Sup 15) words. Also, new parallel computer architectures and new structured numerical methods will make necessary speed and capacity available.

Peterson, Victor L.↗
NASA NTRS1991

Recent advances in the development and transfer of machine vision technologies for space

Recent work concerned with real-time machine vision is briefly reviewed. This work includes methodologies and techniques for optimal illumination, shape-from-shading of general (non-Lambertian) 3D surfaces, laser vision devices and technology, high level vision, sensor fusion, real-time computing, artificial neural network design and use, and motion estimation. Two new methods that are currently being developed for object recognition in clutter and for 3D attitude tracking based on line correspondence are discussed.

Defigueiredo, Rui J. P.↗
NASA NTRS1988

A New Tool for Quality Control

Diffracto, Ltd. is now offering a new product inspection system that allows detection of minute flaws previously difficult or impossible to observe. Called D-Sight, it represents a revolutionary technique for inspection of flat or curved surfaces to find such imperfections as dings, dents and waviness. System amplifies defects, making them highly visible to simplify decision making as to corrective measures or to identify areas that need further study. CVA 3000 employs a camera, high intensity lamps and a special reflective screen to produce a D- Sight image of light reflected from a surface. Image is captured and stored in a computerized vision system then analyzed by a computer program. A live image of surface is projected onto a video display and compared with a stored master image to identify imperfections. Localized defects measuring less than 1/1000 of an inch are readily detected.

Source record↗
NASA NTRS1991

Optical correlator techniques applied to robotic vision

Vision processing is one of the most computationally intensive tasks required of an autonomous robot. The data flow from a single typical imaging sensor is roughly 60 Mbits/sec, which can easily overload current on-board processors. Optical correlator-based processing can be used to perform many of the functions required of a general robotic vision system, such as object recognition, tracking, and orientation determination, and can perform these functions fast enough to keep pace with the incoming sensor data. We describe a hybrid digital electronic/analog optical robotic vision processing system developed at Ames Research Center to test concepts and algorithms for autonomous construction, inspection, and maintenance of space-based habitats. We discuss the system architecture design and implementation, its performance characteristics, and our future plans. In particular, we compare the performance of the system to a more conventional all digital electronic system developed concurrently. The hybrid system consistently outperforms the digital electronic one in both speed and robustness.

Hine, Butler P., III↗