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NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions.This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

synthetic data↗

NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗

NASA NTRS2014

Comparing MODIS C6 'Deep Blue' and 'Dark Target' Aerosol Data

The MODIS Collection 6 Atmospheres product suite includes refined versions of both 'Deep Blue' (DB) and 'Dark Target' (DT) aerosol algorithms, with the DB dataset now expanded to include coverage over vegetated land surfaces. This means that, over much of the global land surface, users will have both DB and DT data to choose from. A 'merged' dataset is also provided, primarily for visualization purposes, which takes retrievals from either or both algorithms based on regional and seasonal climatologies of normalized difference vegetation index (NDVI). This poster present some comparisons of these two C6 aerosol algorithms, focusing on AOD at 550 nm derived from MODIS Aqua measurements, with each other and with Aerosol Robotic Network (AERONET) data, with the intent to facilitate user decisions about the suitability of the two datasets for their desired applications.

MODIS Collection 6↗

NASA NTRSDate not supplied

Synthetic Data Generation for 3D Mesh Prediction and Spatial Reasoning During Multi-Agent Robotic Missions

In-space assembly operations require accurate reasoning over the pose, location, and structural organization of both the autonomous agents and assembly materials. In a full six-degree-of-freedom space, an accurate understanding of the full three-dimensional structure of the object of interest greatly enriches information for pose estimation and collision planning. Current methods of predicting pose estimation require a priori understanding of the shape of the object. Additionally, visual information in the space environment is impacted by variations in contrast and illumination. Using synthetic data allows us to rapidly generate large datasets with in varying environments and lighting conditions. This work details the generation of synthetic data used to explore the use of a region-based convolutional neural networks to detect objects of interest and predict a voxel-based three-dimensional mesh in order to understand their full three-dimensional shape. This mesh provides useful spatial information during in-space assembly operations without requiring either the complexity of maintaining models over the progress of building an object or observations from multiple angles. The generated meshes are then compared to that of ground truth in order to measure its performance.

James Ecker↗

NASA NTRS1994

Multimission Telemetry Visualization (MTV) system: A mission applications project from JPL's Multimedia Communications Laboratory

This paper describes the Multimission Telemetry Visualization (MTV) data acquisition/distribution system. MTV was developed by JPL's Multimedia Communications Laboratory (MCL) and designed to process and display digital, real-time, science and engineering data from JPL's Mission Control Center. The MTV system can be accessed using UNIX workstations and PC's over common datacom and telecom networks from worldwide locations. It is designed to lower data distribution costs while increasing data analysis functionality by integrating low-cost, off-the-shelf desktop hardware and software. MTV is expected to significantly lower the cost of real-time data display, processing, distribution, and allow for greater spacecraft safety and mission data access.

Koeberlein, Ernest, III↗

NASA NTRS1989

Optical pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Papers on optical pattern recognition are presented, covering topics such as the estimation of satellite pose and motion parameters using a neural net tracker, associative memory, optical implmentation of programmable neural networks, optoelectronic neural networks, dynamic autoassociative neural memory, heteroassociative memory, bilinear pattern recognition processors, optical processing of optical correlation plane data, and a synthetic discriminant function-based nonlinear optical correlator. Other topics include an interactive optical-digital image processor, geometric transformations for video compression and human teleoperator display, quasiconformal remapping for compensation of human visual field defects, hybrid vision for automated spacecraft landing, advanced symbolic and inference optical correlation filters, and a rotationally invariant holographic tracking system. Additional topics include the detection of rotational and scale-varying objects with a programmable joint transform correlator, a single spatial light modulator binary nonlinear optical correlator, optical joint transform correlation, linear phase coefficient composite filters, and binary phase-only filters.

Liu, Hua-Kuang↗

NASA NTRS1989

Visualization of fluid dynamics at NASA Ames

The hardware and software currently used for visualization of fluid dynamics at NASA Ames is described. The software includes programs to create scenes (for example particle traces representing the flow over an aircraft), programs to interactively view the scenes, and programs to control the creation of video tapes and 16mm movies. The hardware includes high performance graphics workstations, a high speed network, digital video equipment, and film recorders.

Watson, Val↗

NASA NTRS2015

RUMS - Realtime Visualization and Evaluation of Live, Virtual, Constructive Simulation Data

This paper describes the tools and display capabilities being developed to visualize aircraft flight and trajectory information that is produced during a distributed Live, Virtual, Constructive (LVC) simulation events involving a mix of manned and unmanned aircraft. This paper discusses the design approach and general software architecture of the Remote User Monitor Service (RUMS) application. The simulations and flight tests are conducted over a nationwide network with components communicating via software gateways that translate the messages and provide a location to access and collect data. The data collected is not only archived for post-processing and analysis, but also processed in real-time by RUMS, which allows dynamic viewing of the information via a web browser. This real-time dynamic viewing of the data allows test conductors and researchers to monitor the health of the distributed system and of the data being collected not only in situ where tests are conducted but also at remote locations.

distributed simulation↗

NASA NTRS2010

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗

NASA NTRS2015

Enhancing Interdisciplinary Human System Risk Research Through Modeling and Network Approaches

NASA's Human Research Program (HRP) supports research to reduce human health and performance risks inherent in future human space exploration missions. Understanding risk outcomes and contributing factors in an integrated manner allows HRP research to support development of efficient and effective mitigations from cross‐disciplinary perspectives, and to enable resilient human and engineered systems for spaceflight. The purpose of this work is to support scientific collaborations and research portfolio management by utilizing modeling for analysis and visualization of current and potential future interdisciplinary efforts.

Mindock, Jennifer↗

NASA NTRS1990

A catalog of selected compact radio sources for the construction of an extragalactic radio/optical reference frame (Argue et al. 1984): Documentation for the machine-readable version

This document describes the machine readable version of the Selected Compact Radio Source Catalog as it is currently being distributed from the international network of astronomical data centers. It is intended to enable users to read and process the computerized catalog. The catalog contains 233 strong, compact extragalactic radio sources having identified optical counterparts. The machine version contains the same data as the published catalog and includes source identifications, equatorial positions at J2000.0 and their mean errors, object classifications, visual magnitudes, redshift, 5-GHz flux densities, and comments.

Source record↗

NASA NTRS1995

Event-Based Study of the Effect of Execution Environments on Parallel Program Performance

In this paper we seek to demonstrate the importance of studying the effect of changes in execution environment parameters, on parallel applications executed on state-of-the-art multiprocessors. A comprehensive methodology for event-based analysis of program behavior is introduced. This methodology is used to study the performance significance of various system parameters such as processor speed, message-buffer size, buffer copy speed, network bandwidth, communication latency, interrupt overheads and other system parameters. With the help cf a few CFD examples, we illustrate the use of our technique in determining suitable parameter values of the execution environment for three applications. We also demonstrate how this approach can be used to predict performance across architectures and illustrate the use of visual and profile-like feedback to expose the effect of system parameters changes on the performance of specific applications module.

Sarukkai, Sekhar R.↗

NASA NTRS2017

Human Mars Mission Design - The Ultimate Systems Challenge

A human mission to Mars will occur at some time in the coming decades. When it does, it will be the end result of a complex network of interconnected design choices, systems analyses, technical optimizations, and non-technical compromises. This mission will extend the technologies, engineering design, and systems analyses to new limits, and may very well be the most complex undertaking in human history. It can be illustrated as a large menu, or as a large decision tree. Whatever the visualization tool, there are numerous design decisions required to assemble a human Mars mission, and many of these interconnect with one another. This paper examines these many decisions and further details a number of choices that are highly interwoven throughout the mission design. The large quantity of variables and their interconnectedness results in a highly complex systems challenge, and the paper illustrates how a change in one variable results in ripples (sometimes unintended) throughout many other facets of the design. The paper concludes with a discussion of some mission design variables that can be addressed first, and those that have already been addressed as a result of ongoing National Aeronautics and Space Administration (NASA) developments, or as a result of decisions outside the technical arena. It advocates the need for a 'reference design' that can be used as a point of comparison, and to illustrate the system-wide impacts as design variables change.

Connolly, John F.↗

NASA NTRS2017

Medical Optimization Network for Space Telemedicine Resources

INTRODUCTION: Long-duration missions beyond low Earth orbit introduce new constraints to the space medical system. Beyond the traditional limitations in mass, power, and volume, consideration must be given to other factors such as the inability to evacuate to Earth, communication delays, and limitations in clinical skillsets. As NASA develops the medical system for an exploration mission, it must have an ability to evaluate the trade space of what resources will be most important. The Medical Optimization Network for Space Telemedicine Resources (MONSTR) was developed over the past year for this reason, and is now a system for managing data pertaining to medical resources and their relative importance when addressing medical conditions. METHODS: The MONSTR web application with a Microsoft SQL database backend was developed and made accessible to Tableau v9.3 for analysis and visualization. The database was initially populated with a list of medical conditions of concern for an exploration mission taken from the Integrated Medical Model (IMM), a probabilistic model designed to quantify in-flight medical risk. A team of physicians working within the Exploration Medical Capability Element of NASA's Human Research Program compiled a list diagnostic and treatment medical resources required to address best- and worst-case scenarios of each medical condition using a terrestrial standard of care and entered this data into the system. This list included both tangible resources (e.g. medical equipment, medications) and intangible resources (e.g. clinical skills required to perform a procedure). The physician team then assigned criticality values to each instance of a resource, representing the importance of that resource to diagnosing or treating its associated condition(s). Medical condition probabilities of occurrence during a Mars mission were pulled from the IMM and imported into the MONSTR database for use within a resource criticality-weighting algorithm. DISCUSSION: The MONSTR tool is a novel approach to assess the relative value of individual resources needed for the diagnosis and treatment of medical conditions. Future work will add resources for prevention and long term care of these conditions. Once data collection is complete, MONSTR will provide the operational and research communities at NASA with information to support informed decisions regarding areas of research investment, future crew training, and medical supplies manifested as part of any exploration medical system.

Rubin, D.↗

NASA NTRS1990

Computation and parallel implementation for early vision

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.

Gualtieri, J. Anthony↗

NASA NTRS2002

Evolutionary Design of a Robotic Material Defect Detection System

During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.

Ballard, Gary↗

NASA NTRS2012

Small Aircraft Data Distribution System

The CARVE Small Aircraft Data Distribution System acquires the aircraft location and attitude data that is required by the various programs running on a distributed network. This system distributes the data it acquires to the data acquisition programs for inclusion in their data files. It uses UDP (User Datagram Protocol) to broadcast data over a LAN (Local Area Network) to any programs that might have a use for the data. The program is easily adaptable to acquire additional data and log that data to disk. The current version also drives displays using precision pitch and roll information to aid the pilot in maintaining a level-level attitude for radar/radiometer mapping beyond the degree available by flying visually or using a standard gyro-driven attitude indicator. The software is designed to acquire an array of data to help the mission manager make real-time decisions as to the effectiveness of the flight. This data is displayed for the mission manager and broadcast to the other experiments on the aircraft for inclusion in their data files. The program also drives real-time precision pitch and roll displays for the pilot and copilot to aid them in maintaining the desired attitude, when required, during data acquisition on mapping lines.

Chazanoff, Seth L.↗

NASA NTRS2006

NASA'S SERVIR Gulf of Mexico Project: The Gulf of Mexico Regional Collaborative (GoMRC)

The Gulf of Mexico Regional Collaborative (GoMRC) is a NASA-funded project that has as its goal to develop an integrated, working, prototype IT infrastructure for Earth science data, knowledge and models for the five Gulf U.S. states and Mexico, and to demonstrate its ability to help decision-makers better understand critical Gulf-scale issues. Within this preview, the mission of this project is to provide cross cutting solution network and rapid prototyping capability for the Gulf of Mexico region, in order to demonstrate substantial, collaborative, multi-agency research and transitional capabilities using unique NASA data sets and models to address regional problems. SERVIR Mesoamerica is seen as an excellent existing framework that can be used to integrate observational and GIs data bases, provide a sensor web interface, visualization and interactive analysis tools, archival functions, data dissemination and product generation within a Rapid Prototyping concept to assist decision-makers in better understanding Gulf-scale environmental issues.

Quattrochi, Dale A.↗