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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Distributed Sensing and Computer Vision Methods for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.

Evan Kawamura↗
NASA NTRSDate not supplied

2040 Vision Study: NASA’s T3 Implementation Activities

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. As a result, NASA’s Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations) and discuss NASA’s TTT implementation activities, with special emphasis on recent accomplishments. The study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that marries two non-mutually exclusive paradigms – “design of the materials” (material scientist viewpoint) and “design with the materials” (structural analyst viewpoint) – into a concurrent transformational paradigm that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT’s hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United State's global competitiveness

Materials↗
DOE OSTI2015

Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a better performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.

acoustic↗
DOE OSTI2025

Monitoring installation of partially occluded subassemblies in modular construction factories using BIM, ray tracing, and computer vision

Modular and offsite construction methods are being increasingly adopted due to the advantages they offer in terms of project completion time, quality, and energy-efficiency. Despite these advantages, the current state of monitoring systems in modular construction factories highly relies on labor-intensive, subjective, and error-prone observational methods. A large body of research has aimed to automate the monitoring process using an array of sensors, such as IMUs and RFIDs, during the past two decades. Recently, computer vision-based methods have gained increasing interest as a non-intrusive technology to monitor the process inside modular construction factories. However, partial occlusion challenges have impeded their practical application on a large scale. This challenge is specifically important for monitoring the installation of subassemblies since they can obstruct the view of the monitoring camera, especially those that enable long-term monitoring like closed-circuit television (CCTV) fixed-view surveillance cameras. Here, this paper aims to address this challenge by proposing a novel computer vision-based method to monitor the installation of new subassemblies inside modular factories in highly occluded scenes. The proposed methodology identifies the subassemblies in the CCTV video footage using computer vision, analyzes the occlusions using BIM and ray casting techniques, and estimates the progress of assembly by comparing the BIM model with the detected subassemblies in the video. The proposed methodology was successfully validated on surveillance videos captured from a volumetric modular construction factory in the U.S., achieving 93% accuracy in identifying the installation of subassemblies. The results from this research show that the integration of BIM and computer vision is a promising method for monitoring the installation processes inside modular factories under severe occlusion.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

VSLAM and Vision-based Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft have many challenges in landing accurately and safely in urban, suburban, and rural environments. Localization in large and open rural environments could utilize GPS, but AAM aircraft in urban environments will encounter GPS degradation. Another challenge involves flight operation time, i.e., flying during the day or at night. There are different guidelines, landmarks, and landing light configurations at runways, heliports, and vertiports for daytime and nighttime applications. Tailoring feature detection methods for AAM approach and landing during the day and night pose different issues and challenges. It is easier to detect edges, lines, and other runway markers during the day than at night. Conversely, it is easier to see landing light configurations and patterns at nighttime than daytime. Consequently, utilizing the same feature detector for daytime and nighttime operations may not be feasible. This paper focuses on a vision-based precision approach and landing (PAL) by comparing ORB SLAM 2, a Vision Simultaneous Localization and Mapping (VSLAM) algorithm, and a novel EKF that combines onboard IMU measurements with coplanar pose from orthography and scaling with iterations (COPOSIT). Conducting unmanned aerial system (UAS) flight tests at NASA Armstrong Flight Research Center (AFRC) with landmarks and fiducials distributed around the landing zone provides a simulated AAM approach and landing data to test vision-based PAL methods to provide Alternative Position, Navigation, and Timing (APNT) solutions for AAM PAL applications. The novel vision-based PAL EKF with IMU and COPOSIT provides accurate state estimation when distributed landmarks and fiducials are in the field of view.

distributed sensing↗
NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗
DOE OSTI2019

Crowdsourced reliable labeling of safety-rule violations on images of complex construction scenes for advanced vision-based workplace safety

Construction workplace hazard detection requires engineers to analyze scenes manually against many safety rules, which is time-consuming, labor-intensive, and error-prone. Computer vision algorithms are yet to achieve reliable discrimination of anomalous and benign object relations underpinning safety violation detections. Recently developed deep learning-based computer vision algorithms need tens of thousands of images, including labels of the safety rules violated, in order to train deep-learning networks for acquiring spatiotemporal reasoning capacity in complex workplaces. Such training processes need human experts to label images and indicate whether the relationship between the worker, resource, and equipment in the scenes violate spatiotemporal arrangement rules for safe and productive operations. False alarms in those manual labels (labeling no-violation images as having violations) can significantly mislead the machine learning process and result in computer vision models that produce inaccurate hazard detections. Compared with false alarms, another type of mislabels, false negatives (labeling images having violations as “no violations”), seem to have fewer impacts on the reliability of the trained computer vision models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Event-related brain potentials reveal how multiple aspects of semantic processing unfold across parafoveal and foveal vision during sentence reading

Recent event–related brain potential (ERP) experiments have demonstrated parafoveal N400 expectancy and congruity effects, showing that semantic information can be accessed from words in parafoveal vision (a conclusion also supported by some eye–tracking work). At the same time, it is unclear how higher–order integrative aspects of language comprehension unfold across the visual field during reading. In the current study, we recorded ERPs in a parafoveal flanker paradigm, while readers were instructed to read passively for comprehension or to judge the plausibility of sentences in which target words varied in their semantic expectancy and congruity. We directly replicated prior work showing graded N400 effects for parafoveal viewing, which are then not duplicated when the target words are processed foveally. Critically, although N400 effects were not modulated by task goals, a posteriorly distributed late positive component thought to reflect semantic integration processes was observed to semantic incongruities only in the plausibility judgment task. Furthermore, this effect was observed at a considerable delay, appearing only after words had moved into foveal vision. Our findings thus suggest that semantic access can be initiated in parafoveal vision, whereas central foveal vision may be necessary to enact higher–order (and task–dependent) integrative processing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-D-16A-01: Medical Physics Workshop: Editorial Vision and Guidance On Writing and Reviewing Papers

On January 1, 2014, editorial leadership of Medical Physics passed from esteemed long-time Editor Bill Hendee to a collective editorial group composed of the three presenters listed above. In this presentation, we would like to outline our vision for the future of Medical Physics and review recent work-in-progress initiatives to implement this vision. Finally, we will close with guidance to authors on how to write a good Medical Physics paper. Vision for Medical Physics and current initiatives: Jeff Williamson, Editor-in-Chief We cannot improve on Dr. Hendee's succinct vision statement “to continue the Journal's tradition of publishing the very best science that propels our discipline forward and improves our contribution to patient care.” More concretely, the Journal should be s the preeminent forum for electronic exchange of cutting edge medical physics science. We seek to identify the best contributions in (a) high impact clinical physics innovations; (b) clinical translation and validation of basic science innovations; or (c) cutting edge basic science developments with potential for patient care improvements. Among the challenges and opportunities we face are: are electronic-only and open access publishing; trends towards more interactive, social-media based scientific communities; and diversification of the medical physics research, authorship, and readership domains, including clinical applications quite foreign to core ABR clinical competencies. To address these issues over the next 3 years, we have reduced the size of our Editorial Board and focused its efforts on improving the Journal's impact through 4 working groups (WGs): WG-1: Review process quality and selectivity Creation of 120 member Board of Associate Editors to improve review uniformity by placing Ms. management in fewer hands New reviewer guidelines and templates Answer: “what is the scope of medical physics research?” Recursive taxonomy for tagging review expertise and article contents WG-2 Improving reader experience Redesigning http://MedPhys.org to host interactive features and gateway to electronic issue archive Experimentation with interactive features beginning with “Point/Counterpoint” Data mining and Journal quality evaluation Find out who are audiences are Identify characteristics of high impact articles Measure effectiveness of innovations Outreach to related communities Special issues presenting high-impact work in designated subcommunities Addressing the needs of new research constituencies: engineers, biophysicists, clinicians Guidelines and templates for reviewers and associate editors: Shiva Das, Therapy Physics Editor We will discuss the Med. Phys. review process and a new initiative to create review templates that attempts to address current shortcomings. Template design is informed by the literature on of the review process effectiveness and practices of other journals. Its goals are to provide authors more constructive criticism to improve the manuscript; quantifying perceived importance and potential impact; and providing structured sections that prompt the reviewer to addresses important technical and editorial elements. While the template is recommended to be used, reviewers could alternatively enter their comments in the older free-form style. The expectations of the template are that it will enable consistently thorough, high quality reviews that accurately separate acceptable vs. substandard submissions but continue our tradition of helping authors to enhance papers with high potential. Ultimately, the goal is to reduce variability and subjectivity in the peer-review process, in turn leading to articles with higher research and clinical impact. We will also discuss interesting perspectives from several journals on aspects of the peer-review process such as public input via comments, influence of author-suggested reviewers, and bias in reviewer selection. Writing good scientific papers and responding to critiques: Mitch Goodsitt, Imaging Physics Editor The essential components of the abstract, introduction, methods, discussion and conclusion sections, as well as the desired writing style and style of the figures and tables will be reviewed. Publishable Medical Physics Ms. must include a clear and concise statement of the novelty and clinical and/or scientific importance of their work. Examples of novelty include: new technical solution to an important clinical problem; new generalizable knowledge; or first demonstration that an existing engineering solution solves a clinical problem. Authors must also include: sufficient background information and rationale; enough detail that the work can be reproduced by others; sufficient statistical analysis to refute or validate their hypothesis, how it compares to; is distinct from, and improves upon others' work; and the limitations of their study. When the authors receive critiques from the referees and associate editor, the authors should provide a detailed point-bypoint response to each comment. We now ask that the authors' rebuttal include the text of the original criticism, the authors' response, and the modified text along with the line numbers in the revised article. We also ask that the new text be highlighted in a different font color in the revised submission. These changes and others will be discussed. Their purpose is to facilitate the review process.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Regional Feedstock Partnership Summary Report: Enabling the Billion-Ton Vision

The U.S. Department of Energy (DOE) and the Sun Grant Initiative established the Regional Feedstock Partnership (referred to as the Partnership) to address information gaps associated with enabling the vision of a sustainable, reliable, billion-ton U.S. bioenergy industry by the year 2030 (i.e., the Billion-Ton Vision). Over the past 7 years (2008–2014), the Partnership has been successful at advancing the biomass feedstock production industry in the United States, with notable accomplishments. The Billion-Ton Study identifies the technical potential to expand domestic biomass production to offset up to 30% of U.S. petroleum consumption, while continuing to meet demands for food, feed, fiber, and export. This study verifies for the biofuels and chemical industries that a real and substantial resource base could justify the significant investment needed to develop robust conversion technologies and commercial-scale facilities. DOE and the Sun Grant Initiative established the Partnership to demonstrate and validate the underlying assumptions underpinning the Billion-Ton Vision to supply a sustainable and reliable source of lignocellulosic feedstock to a large-scale bioenergy industry. This report discusses the accomplishments of the Partnership, with references to accompanying scientific publications. These accomplishments include advances in sustainable feedstock production, feedstock yield, yield stability and stand persistence, energy crop commercialization readiness, information transfer, assessment of the economic impacts of achieving the Billion-Ton Vision, and the impact of feedstock species and environment conditions on feedstock quality characteristics.

09 BIOMASS FUELS↗
DOE OSTI2021

Nondestructive Assay Technical Infrastructure Program Mission and Vision

The Nondestructive Assay Program (NDAP) mission and vision is achieved by identifying and accomplishing a set of programmatic goals that correspond with eight broad technical program elements. The NDAP was created as a result of Defense Nuclear Facility Safety Board Recommendation 2007-1, entitled “Safety-Related In Situ Nondestructive Assay of Radioactive Materials,” which emphasized the need to improve in situ measurements of radioactive material at US Department of Energy (DOE) defense nuclear facilities. An NDAP five-year plan will define tasks to accomplish specific goals identified in the NDAP mission and vision. This mission and vision is applicable for eight technical program elements: Hardware/Software Development, Algorithm Development and Nuclear Data, Uncertainty Quantification, Nuclear Materials, Staffing, Personnel, And Training, Data Management, Requirement and Standards, and Information Preservation and Dissemination. An additional program element is technical support, which provides daily execution management support for the NDAP, site scope, and deliverable tracking via site task managers, along with technical advisement and support from the technical support group. The NDAP mission and vision provides attributes with specific goals for each program element, and some goals benefit multiple program elements. The goals and attributes defined herein are implemented via an NDAP five-year execution plan that defines site work scope, budget, and deliverables, all of which are updated annually. The NDAP is designed to benefit nondestructive assay (NDA) needs to support DOE nuclear criticality safety programs, ensuring that NDA technology is sufficiently capable of guaranteeing the safety of those who handle, store, process, or transport fissionable materials in the complex. Especially important for the NDAP is to maximize capabilities to identify, characterize, and manage in situ fissile material deposits in process equipment to ensure nuclear criticality safety at processing facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics

Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resources both for training and deployment. The problem is exacerbated as the amount and complexity of the data increases. Quantum-based vision transformer models could potentially alleviate this issue by reducing the training and operating time while maintaining the same predictive power. Although current quantum computers are not yet able to perform high-dimensional tasks, they do offer one of the most efficient solutions for the future. In this work, we construct several variations of a quantum hybrid vision transformer for a classification problem in high-energy physics (distinguishing photons and electrons in the electromagnetic calorimeter). We test them against classical vision transformer architectures. Our findings indicate that the hybrid models can achieve comparable performance to their classical analogs with a similar number of parameters.

Unlu, Eyup B. (ORCID:0000000266836463)↗
NASA NTRS1980

Design of a dynamic test platform for autonomous robot vision systems

The concept and design of a dynamic test platform for development and evluation of a robot vision system is discussed. The platform is to serve as a diagnostic and developmental tool for future work with the RPI Mars Rover's multi laser/multi detector vision system. The platform allows testing of the vision system while its attitude is varied, statically or periodically. The vision system is mounted on the test platform. It can then be subjected to a wide variety of simulated can thus be examined in a controlled, quantitative fashion. Defining and modeling Rover motions and designing the platform to emulate these motions are also discussed. Individual aspects of the design process are treated separately, as structural, driving linkages, and motors and transmissions.

Rich, G. C.↗
NASA NTRS1981

Visually induced self-motion sensation adapts rapidly to left-right reversal of vision

Three experiments were conducted using 15 adult volunteers with no overt oculomotor or vestibular disorders. In all experiments, left-right vision reversal was achieved using prism goggles, which permitted a binocular field of vision subtending approximately 45 deg horizontally and 28 deg vertically. In all experiments, circularvection (CV) was tested before and immediately after a period of exposure to reversed vision. After one to three hours of active movement while wearing vision-reversing goggles, 10 of 15 (stationary) human subjects viewing a moving stripe display experienced a self-rotation illusion in the same direction as seen stripe motion, rather than in the opposite (normal) direction, demonstrating that the central neural pathways that process visual self-rotation cues can undergo rapid adaptive modification.

Oman, C. M.↗
NASA NTRS1989

Helicopter flights with night-vision goggles: Human factors aspects

Night-vision goggles (NVGs) and, in particular, the advanced, helmet-mounted Aviators Night-Vision-Imaging System (ANVIS) allows helicopter pilots to perform low-level flight at night. It consists of light intensifier tubes which amplify low-intensity ambient illumination (star and moon light) and an optical system which together produce a bright image of the scene. However, these NVGs do not turn night into day, and, while they may often provide significant advantages over unaided night flight, they may also result in visual fatigue, high workload, and safety hazards. These problems reflect both system limitations and human-factors issues. A brief description of the technical characteristics of NVGs and of human night-vision capabilities is followed by a description and analysis of specific perceptual problems which occur with the use of NVGs in flight. Some of the issues addressed include: limitations imposed by a restricted field of view; problems related to binocular rivalry; the consequences of inappropriate focusing of the eye; the effects of ambient illumination levels and of various types of terrain on image quality; difficulties in distance and slope estimation; effects of dazzling; and visual fatigue and superimposed symbology. These issues are described and analyzed in terms of their possible consequences on helicopter pilot performance. The additional influence of individual differences among pilots is emphasized. Thermal imaging systems (forward looking infrared (FLIR)) are described briefly and compared to light intensifier systems (NVGs). Many of the phenomena which are described are not readily understood. More research is required to better understand the human-factors problems created by the use of NVGs and other night-vision aids, to enhance system design, and to improve training methods and simulation techniques.

Brickner, Michael S.↗
NASA NTRS1989

Knowledge-based machine vision systems for space station automation

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Ranganath, Heggere S.↗
NASA NTRS1992

Development of a machine vision guidance system for automated assembly of space structures

The topics are presented in viewgraph form and include: automated structural assembly robot vision; machine vision requirements; vision targets and hardware; reflective efficiency; target identification; pose estimation algorithms; triangle constraints; truss node with joint receptacle targets; end-effector mounted camera and light assembly; vision system results from optical bench tests; and future work.

Eric G Cooper↗
NASA NTRS1991

Three dimensional vision - Requirements and applications in a space environment

Various approaches to three-dimensional vision in space are reviewed with emphasis on the redundant 3D vision system designed for the Center for Intelligent Robotic Systems for Space Exploration. The system uses a controllable subset of five cameras, programmable structured light patterns, and sophisticated calibration routines. The design emphasizes real-time operation, human supervisory intervention, and the use of 3D vision to enhance the performance of cooperating robotic arms. Two methods of estimating the location of a point using 3D vision are discussed.

Noseworthy, J. R.↗