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NASA NTRS2008

PrismTech Data Distribution Service Java API Evaluation

My internship duties with Launch Control Systems required me to start performance testing of an Object Management Group's (OMG) Data Distribution Service (DDS) specification implementation by PrismTech Limited through the Java programming language application programming interface (API). DDS is a networking middleware for Real-Time Data Distribution. The performance testing involves latency, redundant publishers, extended duration, redundant failover, and read performance. Time constraints allowed only for a data throughput test. I have designed the testing applications to perform all performance tests when time is allowed. Performance evaluation data such as megabits per second and central processing unit (CPU) time consumption were not easily attainable through the Java programming language; they required new methods and classes created in the test applications. Evaluation of this product showed the rate that data can be sent across the network. Performance rates are better on Linux platforms than AIX and Sun platforms. Compared to previous C++ programming language API, the performance evaluation also shows the language differences for the implementation. The Java API of the DDS has a lower throughput performance than the C++ API.

Riggs, Cortney↗

NASA NTRS2011

A Tutorial on Interfacing the Object Management Group (OMG) Data Distribution Service (DDS) with LabView

This tutorial will explain the concepts and steps for interfacing a National Instruments LabView virtual instrument (VI) running on a Windows platform with another computer via the Object Management Group (OMG) Data Distribution Service (DDS) as implemented by the Twin Oaks Computing CoreDX. This paper is for educational purposes only and therefore, the referenced source code will be simplistic and void of all error checking. Implementation will be accomplished using the C programming language.

Smith, Kevin↗

NASA NTRS2002

Architecture Studies Done for High-Rate Duplex Direct Data Distribution (D4) Services

A study was sponsored to investigate a set of end-to-end system concepts for implementing a high-rate duplex direct data distribution (D4) space-to-ground communications link. The NASA Glenn Research Center is investigating these systems (both commercial and Government) as a possible method of providing a D4 communications service between NASA spacecraft in low Earth orbit and the respective principal investigators using or monitoring instruments aboard these spacecraft. Candidate commercial services were assessed regarding their near-term potential to provide a D4 type of service. The candidates included K-band and V-band geostationary orbit and nongeostationary orbit satellite relay services and direct downlink (D3) services. Internet protocol (IP) networking technologies were evaluated to enable the user-directed distribution and delivery of science data. Four realistic, near-future concepts were analyzed: 1) A duplex direct link (uplink plus downlink communication paths) between a low-Earth-orbit spacecraft and a principal-investigator-based autonomous Earth station; 2) A space-based relay using a future K-band nongeosynchronous-orbit system to handle both the uplink and downlink communication paths; 3) A hybrid link using both direct and relay services to achieve full duplex capability; 4) A dual-mode concept consisting of both a duplex direct link and a space relay duplex link operating independently. The concepts were analyzed in terms of contact time between the NASA spacecraft and the communications service and the achievable data throughput. Throughput estimates for the D4 systems were based on the infusion of advanced communications technology products (single and multibeam K-band phased-arrays and digital modems) being developed by Glenn. Cost estimates were also performed using extrapolated information from both terrestrial and current satellite communications providers. The throughput and cost estimates were used to compare the concepts.

Source record↗

NASA NTRS2018

Air Traffic Management-eXploration Testbed for Urban Air Mobility Research and Development

The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.

Testbed↗

NASA NTRS2018

Air Traffic Management-eXploration Testbed for Urban Air Mobility Research and Development

The presentation will describe the architecture, current capabilities and some future enhancements of the testbed that is being developed at the National Aeronautics and Space Administration (NASA) to enable benefit, impact, safety and cost assessments for accelerating the deployment of air traffic management concept and technologies in the national airspace system. The testbed will support analysis of operational feasibility of urban air mobility operations, a part of NASA's Air Traffic Management eXploration project, and provide the data needed by regulatory agencies charged with public safety. Introduction of concepts and technologies, especially new concepts and technologies, is difficult and often takes decades because of the inability to assess the operational impact of the interaction between the proposed concept and technology and operationally deployed systems in terms of system-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airlines and other operators. To overcome these limitations, the testbed is developing infrastructure to enable mathematical modeling, human-in-the-loop evaluations and testing with operational systems in a simulated environment. In addition to the difficulty of establishing communications between geographically distributed systems, downloading/installing software, and management of startup, error-handling and shutdown, a major impediment for conducting simulations and human-in-the-loop testing with operational systems is the tedious manual scenario generation process. Several of these difficulties have been addressed in the current state of the testbed. The testbed can be described in terms of the following elements- (1) web-based frontend and backend, (2) Testbed Builder, (3) Data Distribution Service, (4) Component Library, (5) Simulation Management, and (6) Scenario Generation. The web-based frontend and backend enable the user to interact with the testbed for tasks such as composing a simulation, running a simulation and retrieving output data. The Testbed Builder application launched from the web frontend is a graphical user interface for the user to drag-and-drop and connect predefined blocks for composing a simulation/scenario generation task. The Builder writes a set of instructions for Simulation Management based on the links between the blocks and the block properties such as the component (executable) associated with a particular block. Management of the distributed simulation is accomplished by Execution and Component Managers. Execution Manager interprets the instructions provided by the Builder to instruct the Component Managers to download components from the Component Library to specified computers and to start them up. Once started, the components communicate with each other by publishing messages and subscribing to messages that are delivered by the Data Distribution Service. The Scenario Generation capability can be used for creating traffic scenarios for Multi-Aircraft Control System, which has been used extensively at NASA for human-in-the-loop-based concept evaluations. The presentation will provide a testbed enabled example scenario of Multi-Aircraft Control System based simulation in which the urban air mobility pilot using the conflict detection and resolution system would interact with the air traffic controllers for resolving conflicts with other aircraft during terminal area operations.

Simulation↗

NASA NTRS1992

National Space Science Data Center data archive and distribution service (NDADS) automated retrieval mail system user's guide

The National Space Science Data Center (NSSDC) has developed an automated data retrieval request service utilizing our Data Archive and Distribution Service (NDADS) computer system. NDADS currently has selected project data written to optical disk platters with the disks residing in a robotic 'jukebox' near-line environment. This allows for rapid and automated access to the data with no staff intervention required. There are also automated help information and user services available that can be accessed. The request system permits an average-size data request to be completed within minutes of the request being sent to NSSDC. A mail message, in the format described in this document, retrieves the data and can send it to a remote site. Also listed in this document are the data currently available.

Perry, Charleen M.↗

NASA NTRS2000

Developing a distributed data dictionary service

This paper will explore the use of the Lightweight Directory Access Protocol (LDAP) using the ISO 11179 Data Dictionary Schema as a mechanism for standardizing the structure and communication links between data dictionaries.

datasets data dictionaries Lightweight Directory A↗

NASA NTRS2015

Towards an Open, Distributed Software Architecture for UxS Operations

To address the growing need to evaluate, test, and certify an ever expanding ecosystem of UxS platforms in preparation of cultural integration, NASA Langley Research Center's Autonomy Incubator (AI) has taken on the challenge of developing a software framework in which UxS platforms developed by third parties can be integrated into a single system which provides evaluation and testing, mission planning and operation, and out-of-the-box autonomy and data fusion capabilities. This software framework, named AEON (Autonomous Entity Operations Network), has two main goals. The first goal is the development of a cross-platform, extensible, onboard software system that provides autonomy at the mission execution and course-planning level, a highly configurable data fusion framework sensitive to the platform's available sensor hardware, and plug-and-play compatibility with a wide array of computer systems, sensors, software, and controls hardware. The second goal is the development of a ground control system that acts as a test-bed for integration of the proposed heterogeneous fleet, and allows for complex mission planning, tracking, and debugging capabilities. The ground control system should also be highly extensible and allow plug-and-play interoperability with third party software systems. In order to achieve these goals, this paper proposes an open, distributed software architecture which utilizes at its core the Data Distribution Service (DDS) standards, established by the Object Management Group (OMG), for inter-process communication and data flow. The design decisions proposed herein leverage the advantages of existing robotics software architectures and the DDS standards to develop software that is scalable, high-performance, fault tolerant, modular, and readily interoperable with external platforms and software.

Cross, Charles D.↗

NASA NTRS2011

RAPID and DDS

This talk gives an overview of the the Robot Applications Programmers Interface Delegate (RAPID) as well as the distributed systems middleware Data Distribution Service (DDS). DDS is an open software standard, RAPID is cleared for open-source release under NOSA. RAPID specifies data-structures and semantics for high-level telemetry published by NASA robotic software. These data-structures are supported by multiple robotic platforms at Johnson Space Center (JSC), Jet Propulsion Laboratory (JPL) and Ames Research Center (ARC), providing high-level interoperability between those platforms. DDS is used as the middleware for data transfer. The feature set of the middleware heavily influences the design decision made in the RAPID specification. So it is appropriate to discuss both in this introductory talk.

Utz, Hans Heinrich↗

NASA NTRS2020

Distributed Spacecraft Autonomy (DSA): Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC)measurements. DSA will be demonstrated on board the NASA Ames Starling mission a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets.The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasma sphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input data set for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software,aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements,which define the range of observability for the satellites, as well as exploitative measurements,which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions.As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown.Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middle ware provides reliable delivery, routing, and topic subscription features over User Data gram Protocol (UDP).Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarms calability from 2 satellites to 100 satellites is shown.

Fugate, Jason↗

NASA NTRSDate not supplied

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗

NASA NTRS2009

CCSDS Spacecraft Monitor and Control Mission Operations Interoperability Prototype

We are entering a new era in space exploration. Reduced operating budgets require innovative solutions to leverage existing systems to implement the capabilities of future missions. Custom solutions to fulfill mission objectives are no longer viable. Can NASA adopt international standards to reduce costs and increase interoperability with other space agencies? Can legacy systems be leveraged in a service oriented architecture (SOA) to further reduce operations costs? The Operations Technology Facility (OTF) at the Johnson Space Center (JSC) is collaborating with Deutsches Zentrum fur Luft- und Raumfahrt (DLR) to answer these very questions. The Mission Operations and Information Management Services Area (MOIMS) Spacecraft Monitor and Control (SM&C) Working Group within the Consultative Committee for Space Data Systems (CCSDS) is developing the Mission Operations standards to address this problem space. The set of proposed standards presents a service oriented architecture to increase the level of interoperability among space agencies. The OTF and DLR are developing independent implementations of the standards as part of an interoperability prototype. This prototype will address three key components: validation of the SM&C Mission Operations protocol, exploration of the Object Management Group (OMG) Data Distribution Service (DDS), and the incorporation of legacy systems in a SOA. The OTF will implement the service providers described in the SM&C Mission Operation standards to create a portal for interaction with a spacecraft simulator. DLR will implement the service consumers to perform the monitor and control of the spacecraft. The specifications insulate the applications from the underlying transport layer. We will gain experience with a DDS transport layer as we delegate responsibility to the middleware and explore transport bridges to connect disparate middleware products. A SOA facilitates the reuse of software components. The prototype will leverage the capabilities of existing legacy systems. Various custom applications and middleware solutions will be combined into one system providing the illusion of a set of homogenous services. This paper will document our journey as we implement the interoperability prototype. The team consists of software engineers with experience on the current command, telemetry and messaging systems that support the International Space Station (ISS) and Space Shuttle programs. Emphasis will be on the objectives, results and potential cost saving benefits.

Lucord, Steve↗

NASA NTRSDate not supplied

Rapid Spacecraft Payload Development: In-Orbit Demonstration of Flight Software Reuse, Scalability, and Dependability

As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.

computer programming↗

NASA NTRS2010

Seagrass Health Modeling and Prediction with NASA Science Data

Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.

Robinson, Harold D.↗

NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗

NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗

NASA NTRSDate not supplied

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

Benjamin N Kelley↗

NASA NTRSDate not supplied

Atmospheric Infrared Sounder Version 7 Near-Real-Time Product and Imagery Released by NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of data processing, archive, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. The GES DISC provides service to both AIRS routine and Near Real-Time (NRT) products. The AIRS NRT products are an important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). In collaboration with AIRS Project, the GES DISC has just released products from the Version 7 algorithm. The new version algorithm provides significant improvements over the previous version. The most substantial advances are: improved consistency between day and night water vapor; improved total column ozone and temperature; improved infrared-only (IR-only) retrievals, especially in high latitude regions; an improved Stochastic Cloud Clearing Neural Network used as a first guess at the initial value in the iterative retrieval process; and removal of ambiguity in surface classification in the IR-only retrieval algorithm. In addition, the GES DISC produces AIRS NRT imagery. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The data products used to generate this imagery include atmospheric temperature, humidity, precipitation, cloud, Dust Score, CO, and SO2. In this presentation, we will demonstrate visualization of the AIRS NRT imagery from the new Version 7, and demonstrate some improvements over the previous version. Progress on improving the AIRS NRT imagery, a collaboration project with the AIRS Applications Development Team at NASA Jet Propulsion Laboratory (JPL), will also be presented.

Feng Ding↗