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A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological visio systems.
The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.
JPL has achieved the first autonomous cross-country robotic traverses to use stereo vision, with all computing onboard the vehicle. This paper describes the stereo vision system, including the underlying statistical model and the details of the implementation. It is argued that the overall approach provides a unifying paradigm for practical domain-independent stereo ranging.
2014 NASA published the outcome of the 2030 CFD (Computational Fluid Dynamics) Vision study: “CFD Vision 2030: A path to Revolutionary Computational Aerosciences” . 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 (Multidisciplinary Design Analysis and Optimization) and HPC (High Performance Computing) hardware. The study also proposed four conceptual ideas of Grand Challenge problems that would build on and benefit from advances outlined in the roadmap. The proposed challenges were meant to foster more detailed descriptions of grand challenge problems for specific disciplines. One of the proposed challenges was in the gas turbine propulsion area, focusing on transient full engine simulations. The current paper addresses detailed technical aspects of that challenge, and proposes a plan to approach it in a gradual manner, which includes high fidelity modeling of components, component coupling, and targeted experimental campaigns relying on common research models.
Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.
Viewgraphs on extravehicular activity/manned systems are presented. Objectives of crewstation design include (1) development of human-computer interface technology and graphical presentations, including multi-dimensional visual and aural displays; (2) provide a technology base for autonomous vision and other perceptual systems, virtual workstation technology, and computational vision systems; and (3) develop databases and models of human strength, motion, and body positions in microgravity environments. Extravehicular technology is addressed.
Artificial intelligence concepts are applied to robotics. Artificial neural networks, expert systems and laser imaging techniques for autonomous space robots are being studied. A computer graphics laser range finder simulator developed by Wu has been used by Weiland and Norwood to study use of artificial neural networks for path planning and obstacle avoidance. Interest is expressed in applications of CLIPS, NETS, and Fuzzy Control. These applications are applied to robot navigation.
There were two major sections of the project for the Office of Human Resources (OHR). The first section was to conduct a planning study to analyze software use with the goal of recommending software purchases and determining whether the need exists for a file server. The second section was analysis and distribution planning for retirement planning computer program entitled VISION provided by NASA Headquarters. The software planning study was developed to help OHR analyze the current administrative desktop computing environment and make decisions regarding software acquisition and implementation. There were three major areas addressed by the study: current environment new software requirements, and strategies regarding the implementation of a server in the Office. To gather data on current environment, employees were surveyed and an inventory of computers were produced. The surveys were compiled and analyzed by the ASEE fellow with interpretation help by OHR staff. New software requirements represented a compilation and analysis of the surveyed requests of OHR personnel. Finally, the information on the use of a server represents research done by the ASEE fellow and analysis of survey data to determine software requirements for a server. This included selection of a methodology to estimate the number of copies of each software program required given current use and estimated growth. The report presents the results of the computing survey, a description of the current computing environment, recommenations for changes in the computing environment, current software needs, management advantages of using a server, and management considerations in the implementation of a server. In addition, detailed specifications were presented for the hardware and software recommendations to offer a complete picture to OHR management. The retirement planning computer program available to NASA employees will aid in long-range retirement planning. The intended audience is the NASA civil service employee with several years until retirement. The employee enters current salary and savings information as well as goals concerning salary at retirement, assumptions on inflation, and the return on investments. The program produces a picture of the employee's retirement income from all sources based on the assumptions entered. A session showing features of the program was conducted for key personnel at the Center. After analysis, it was decided to offer the program through the Learning Center starting in August 1994.
Flight-control and navigation systems inspired by the structure and function of the visual system and brain of insects have been proposed for a class of developmental miniature robotic aircraft called "biomorphic flyers" described earlier in "Development of Biomorphic Flyers" (NPO-30554), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 54. These form a subset of biomorphic explorers, which, as reported in several articles in past issues of NASA Tech Briefs ["Biomorphic Explorers" (NPO-20142), Vol. 22, No. 9 (September 1998), page 71; "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), Vol. 27, No. 5 (May 2003), page 54; and "Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), Vol. 28, No. 5 (May 2004), page 36], are proposed small robots, equipped with microsensors and communication systems, that would incorporate crucial functions of mobility, adaptability, and even cooperative behavior. These functions are inherent to biological organisms but are challenging frontiers for technical systems. Biomorphic flyers could be used on Earth or remote planets to explore otherwise difficult or impossible to reach sites. An example of an exploratory task of search/surveillance functions currently being tested is to obtain high-resolution aerial imagery, using a variety of miniaturized electronic cameras. The control functions to be implemented by the systems in development include holding altitude, avoiding hazards, following terrain, navigation by reference to recognizable terrain features, stabilization of flight, and smooth landing. Flying insects perform these and other functions remarkably well, even though insect brains contains fewer than 10(exp -4) as many neurons as does the human brain. Although most insects have immobile, fixed-focus eyes and lack stereoscopy (and hence cannot perceive depth directly), they utilize a number of ingenious strategies for perceiving, and navigating in, three dimensions. Despite their lack of stereoscopy, insects infer distances to potential obstacles and other objects from image motion cues that result from their own motions in the environment. The concept of motion of texture in images as a source of motion cues is denoted generally as the concept of optic or optical flow. Computationally, a strategy based on optical flow is simpler than is stereoscopy for avoiding hazards and following terrain. Hence, this strategy offers the potential to design vision-based control computing subsystems that would be more compact, would weigh less, and would demand less power than would subsystems of equivalent capability based on a conventional stereoscopic approach.
Vision-based measurement methods were used to measure bubble sizes in this sonoluminescence experiment. Bubble imaging was accomplished by placing the bubble between a bright light source and a microscope-CCD camera system. A collimated light-emitting diode was operated in a pulsed model with an adjustable time delay with respect to the piezo-electric transducer drive signal. The light-emitting diode produced a bubble shadowgraph consisting of a multiple exposure made by numerous light pulses imaged onto a charge-couple device camera. Each image was transferred from the camera to a computer-controlled machine vision system via a frame grabber. The frame grabber was equipped with on-board memory to accomodate sequential image buffering while images were transferred to the host processor and analyzed. This configuration allowed the host computer to perform diameter measurements, centroid position measurements and shape estimation in "real-time" as the next image was being acquired. Bubble size measurement accuracy with an uncertainty of 3 microns was achieved using standard lenses and machine vision algorithms. Bubble centroid position accuracy was also within the 3 micron tolerance of the vision system. This uncertainty estimation accounted for the optical spatial resolution, digitization errors and the edge detection algorithm accuracy. The vision algorithms include camera calibration, thresholding, edge detection, edge position determination, distance between two edges computations and centroid position computations.
The scope of the current work is to develop practical sensing implementations for robots operating in complex, partially unstructured environments. A focus in this work is to develop object models and estimation techniques which are specific to requirements of robot locomotion, approach and avoidance, and grasp and manipulation. Such problems have to date received limited attention in either computer or human vision - in essence, asking not only how perception is in general modeled, but also what is the functional purpose of its underlying representations. As in the past, researchers are drawing on ideas from both the psychological and machine vision literature. Of particular interest is the development 3-D shape and motion estimates for complex objects when given only partial and uncertain information and when such information is incrementally accrued over time. Current studies consider the use of surface motion, contour, and texture information, with the longer range goal of developing a fused sensing strategy based on these sources and others.
Outline: NASA Motivation; CFD Vision 2030 Study Summary - The Vision - Roadmap - Validation Experiments - CFD 2030 Activities Since Report Release; T3 Technical Challenges Supporting CFD Vision 2030 - Revolutionary Computational Aerosciences (RCA) [Aerodynamics - Aerothermodynamics - Aerostructures - Aeroacoustics - Propulsion Integration] - Multidisciplinary Design, Analysis, and Optimization (MDAO) - Combustion Modeling - Innovative Measurements (Proposed); Implementation Plan, Going Forward; Summary.
This compilation of papers in this book represents approximately half of the works discussed at the MS&T 2010 symposium entitled Tools, Models, Databases, and Simulation Tools Developed and Needed to Realize the Vision of Integrated Computational Materials Engineering at Materials Science & Technology wherein five sessions comprised of 33 presentations was organized. The goal of the symposium was two fold To provide a forum in which current state-of-the-art methods for ICME (e.g., information informatics, experimentation, and modeling) could be openly discussed and critiqued by not only materials scientist but also structural engineers/researchers, component designers, industrial leaders and government program managers. To leave the symposium and in particular the panel discussion with a clear idea of the gaps and barriers (both technical, cultural and economical) that must be addressed in order for ICME to fully succeed. The organizers felt that these goals were met, as particularly evident by the standing room only attendance during a lively panel discussion session at the end of the Symposium. However it is the firm belief of the editors of this book that this symposium was merely a start in the right direction, and that subsequent conferences/symposium (e.g., First World Congress on Integrated Computational Materials Engineering to be held July 10-14, 2011 at Seven Springs Mountain Resort in Pennsylvania) must work hard to ensure that a truly diverse, multidisciplinary, community of researchers and practitioners are present and have ample opportunity for interaction. This will ensure that a proper balance between push and pull disciplines and technologies is maintained so that this emerging focus area, Integrated Computational Materials Engineering (ICME), has the greatest potential for success and impact on "system-level" payoffs. Similarly, a pro-active approach is required to reform historical modes of operation in industry, government and the academic sectors so as to facilitate multidisciplinary collaboration and to clearly articulate the vision and scope of ICME.
Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.
A computer-operated binocular vision testing device was developed as one part of a system designed for NASA to evaluate the visual function of astronauts during spaceflight. This particular device, called the Mark 3 Haploscope, employs semi-automated psychophysical test procedures to measure visual acuity, stereopsis, phoria, fixation disparity, refractive state and accommodation/convergence relationships. Test procedures are self-administered and can be used repeatedly without subject memorization. The Haploscope was designed as one module of the complete NASA Vision Testing System. However, it is capable of stand-alone operation. Moreover, the compactness and portability of the Haploscope make possible its use in a broad variety of testing environments.
A computer-controlled binocular vision testing device has been developed as one part of a system designed for NASA to test the vision of astronauts during spaceflight. The device, called the Mark III Haploscope, utilizes semi-automated psychophysical test procedures to measure visual acuity, stereopsis, phorias, fixation disparity and accommodation/convergence relationships. All tests are self-administered, yield quantitative data and may be used repeatedly without subject memorization. Future applications of this programmable, compact device include its use as a clinical instrument to perform routine eye examinations or vision screening, and as a research tool to examine the effects of environment or work-cycle upon visual function.
The papers, abstracts, and presentations were presented at a three day workshop focused on sensor modeling and simulation, and image enhancement, processing, and fusion. The technical sessions emphasized how sensor technology can be used to create visual imagery adequate for aircraft control and operations. Participants from industry, government, and academic laboratories contributed to panels on Sensor Systems, Sensor Modeling, Sensor Fusion, Image Processing (Computer and Human Vision), and Image Evaluation and Metrics.
Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of providing a fault-tolerant environment and achieving significant computational capabilities for high-performance computing applications. However, the task of manually managing and configuring a cluster quickly becomes daunting as the cluster grows in size. Autonomic computing, with its vision to provide self-management, can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Autonomic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management and its evolution to include reflex reactions via pulse monitoring.