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At least 1,405 records · Page 78

Service Oriented Robotic Architecture for Space Robotics: Design, Testing, and Lessons Learned

This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at the NASA Ames Research Center. SORA relies on proven software engineering methods and technologies applied to space robotics. Based on a Service Oriented Architecture and robust middleware, SORA encompasses on-board robot control and a full suite of software tools necessary for remotely operated exploration missions. SORA has been eld tested in numerous scenarios of robotic lunar and planetary exploration. The experiments conducted by IRG with SORA exercise a large set of the constraints encountered in space applications: remote robotic assets, ight relevant science instruments, distributed operations, high network latencies and unreliable or intermittent communication links. In this paper, we present the results of these eld tests in regard to the developed architecture, and discuss its bene ts and limitations.

service oriented architecture↗

Concept of Operations for Interval Management Arrivals and Approach

This paper presents the concept of operations for interval management operations to be deployed in the US National Airspace System (NAS) by the Federal Aviation Administration (FAA) Interval Management Program. The arrivals and approach operations are explored in detail including the primary operation and variations. The use of interval management operations is described that begin in en route airspace and continue to a termination point inside the arrival terminal area in the highly automated terminal environment that includes other arrival management tools such as arrival metering, Ground-based Interval Management - Spacing (GIM-S), and Terminal Sequencing and Spacing (TSAS). The roles of Air Traffic and Pilots and the ground automation tools that are used by Air Traffic Controllers to enable the operations are explored.

Hicok, Daniel S.↗

Telemetry Anomaly Detection System using Machine Learning to Streamline Mission Operations

Spacecraft housekeeping telemetry is monitored at flight control centers by the operations engineers using tools that can perform limit checking or simple trend analysis. Recent developments in machine learning techniques for anomaly detection enables the implementation of more sophisticated systems that aim to augment current state-of-theart mission tools to provide valuable decision support for the spacecraft operators, assisting in anomaly detection and potentially saving console time for the engineers. We will show some results of the implementation of an anomaly detection tool for the NASA Mars Science Laboratory mission.

Weber, Romann↗

LiveCheckHSI: a Hardware/Software Co-verification Tool for Hyperspectral Imaging Systems with Embedded System-on-Chip Instrument Avionics

The emergent technology of system-on-chip (SoC) devices promises lighter, smaller, cheaper, and more capable and reliable space electronic systems that could help to unveil some of the most treasured secrets in our universe. This technology is an improvement over the technology that is currently used in space applications, which lags behind state-of-the-art commercial-off-the-shelf (COTS) equipment by several generations. SoC technology integrates all computational power required by next-generation space exploration science instruments onto a single chip. This paper describes hardware/software co-verification tools for the Xilinx Zynq-based control and data handling system that have been developed at the Jet Propulsion Laboratory (JPL) for visible-infrared imaging spectrometers. The system acquires and compresses images in real-time, in addition to programming the spectrometer (frame rate, exposure time), focus step motor, and heaters and reporting telemetry.

Dolman, David↗

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗

Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal

On July 30th 2020, the Mars 2020 mission successfully launched out of Cape Canaveral, Florida, passed through the Earth’s shadow, and began its short cruise to Mars. Less than seven months later, the Perseverance rover touched down safely in Jezero Crater to begin its ambitious mission that includes looking for signs of ancient life and collecting samples for future return to Earth. Getting to the successful landing, or “Tango Delta Nominal,” could not have been achieved without also considering the off-nominal. One of the teams supporting this ambitious mission is the fault protection (FP) team. This team is tasked with assessing the various failures, or faults, that could prevent mission success and with ensuring that the autonomous behaviors built into the software and hardware can detect faults and recover the vehicle to a safe state. As part of its charter, the FP team designed a test campaign to provide confidence in the system’s robustness to off-nominal scenarios across all of Mars 2020’s mission phases. The greatest challenge associated with designing such a validation campaign was reducing the infinite number of anomalous scenarios into a finite test suite. In addition, the tests needed to be executed efficiently in order to utilize the team’s limited test venue access, but still needed to maintain a level of rigor that guaranteed confidence in the test outcomes. Given that each test scenario generated massive amounts of data, the team also developed methods for quickly ascertaining whether the autonomous fault protection behaviors maintained vehicle safety in the presence of an anomaly. This paper summarizes the processes that the Mars 2020 fault protection team employed to execute its off-nominal validation campaign. It captures both the methods of generating a suite of off-nominal tests, as well as reducing it to a subset that can be realistically executed within schedule and resource constraints. It also describes the various processes and philosophies that the team utilized to execute the tests efficiently, including creating a standardized procedure template, keeping the test cases modular so that they could be easily interchanged, and capturing common fault injections in a change-controlled database. Finally, it will describe the tools and processes for assessing the test data, focusing in particular on a tool that evaluated vehicle state using “secondary” sources of data to validate that the software had truly configured the spacecraft to the expected safe state.

Morantz, Chaz↗

Autonomous Navigation of a Lunar Relay Using GNSS and Other Measurements

Many of the highest priority destinations at the Moon lack a continuous view of Earth, such as the lunar poles or lunar far side. Exploration of these sites will require spacecraft in cislunar space to relay communications and provide position, navigation, and timing (PNT) services. Accurate knowledge of relay position, velocity, and time is essential to these services. This paper describes a concept for a PNT Instrument being developed for the Lunar Communications Relay and Navigation Systems (LCRNS) Project. The instrument is intended as a payload that would enable autonomous, on-board, real-time navigation and timing using Global Navigation Satellite System (GNSS), optical navigation, and one-way measurements from Earth-based ground stations. Hardware-in-the-loop simulations using flight software are used to realistically characterize performance on hardware platforms with a path to flight. These results provide preliminary validation of the proposed PNT Instrument, demonstrate the benefits of augmenting GNSS with other measurements, and serve as an insightful reference for the design of future lunar missions, including those that will operate within the LunaNet framework of standards. This instrument concept relies on several technologies developed at NASA Goddard Space Flight Center (GSFC). For GNSS observables, the instrument relies on the high-altitude NavCube 3 mini (NC3m) GNSS receiver specifically designed for cislunar applications. The autoNGC system, which consists of flight software and a hardware platform, is responsible for fusing the observables using its extended Kalman filter, the Goddard Enhanced Onboard Navigation System (GEONS). Optical navigation observables are processed within autoNGC (“autonomous Navigation, Guidance, and Control”) using the Goddard Image Analysis & Navigation Tool (GIANT) which is also responsible for simulating high-fidelity images for test and analysis. In addition to describing the PNT Instrument and its components, the paper will present predicted performance based on simulation results. As a baseline, it will present GNSS-only hardware-in-the loop results using a NC3m test unit to process Spirent-simulated GPS signals in a potential lunar relay trajectory: a 12-hour elliptical frozen lunar orbit (ELFO). GEONS then processes the GPS pseudorange and time differenced carrier phase measurements to estimate and propagate the relay state (position, velocity, and time). These results extend previously published work that showed preliminary ELFO performance. Previous work has shown the importance of other measurement types, so additional simulations are performed which augment GNSS with ground station observables and several methods of optical navigation, including celestial navigation, limb-finding (e.g., observations of the lunar horizon), and terrain relative navigation (TRN). TRN involves correlating simulated predicted images of the lunar surface with actual imagery; misalignments of landmarks identified in each image are translated into relay state updates. TRN is valuable as a measurement of the relay’s state relative to the Moon, especially during GNSS outages or after maneuvers. One-way Pseudorange and Doppler measurements from Earth-based ground stations are also simulated. The full set of observables is processed using autoNGC. These simulations make use of autoNGC and NC3m test units, a lab atomic clock, and a pulse-per-second (PPS) generation and distribution system. This combination of subsystems, and the hardware platforms used in this analysis, represents a PNT Instrument that could be flown on a lunar relay. Results from the hardware-in-the-loop simulations presented in this paper provide a preliminary assessment of the achievable navigation performance of this instrument concept. PNT Instrument performance is compared to the GPS-only performance, and a discussion is provided on the apparent merits and challenges of each measurement type.

Ben Ashman↗

Towards Sustainable Aviation With Efficient Airspace Operations

In November 2021, the Federal Aviation Administration published the United States Aviation Climate Action Plan to accelerate innovation across the U.S. aviation ecosystem. In response, NASA has established the Sustainable Flight National Partnership to engage with industry, academia, and other agencies to accomplish net-zero carbon emissions by 2050. As part of the SFNP Mission, NASA is conducting a series of real world operational demonstrations in the current National Airspace System with a focus on delivering real world sustainability benefits. This paper presents the current work and future plan for the SFNP Ops Demo Series and describes the cloud based infrastructure used for virtual deployment of decision support tools to flight operators and Air Traffic Controllers to help improve operational efficiency of the National Airspace System. Validation results are shared along with the key sustainability benefits such as jet fuel savings and reduction in CO2 emissions. The operational efficiency metrics such as delay savings are also reported.

Sustainable Flight National Partnership↗

Earth-Independent Medical Operations (EIMO) Concept of Operations

In contrast to the current crew health paradigm for low-Earth orbit and Lunar missions, which depends on real-time communication with Mission Control, deep-space exploration missions will require a significant shift in medical operations. This shift is driven by the constraints of operating at a considerable distance from Earth, such as resource limitations—lack of resupply, restricted mass, power, volume, and data—as well as communication delays and the inability to evacuate back to Earth during emergencies. To move toward a more self-reliant medical model, a strategy is needed to gradually increase space-based crew autonomy and reduce risks to mission success in the challenging environment of deep space. This transformative change, known as "Earth-Independent Medical Operations" (EIMO), explores the gradual transfer of medical care and decision-making from Earth-based support to space-based systems. The goal of this transition is to enhance astronaut health and performance while minimizing mission risks. EIMO requires the development of a medical system that integrates seamlessly with mission planning, vehicle and spacesuit design, and data architecture. This integration is crucial for building a robust medical infrastructure that not only safeguards astronaut well-being but also ensures overall mission success. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has revised the EIMO model-based Concept of Operations (ConOps) which outlines an initial vision for EIMO. The ConOps, which is built on the stakeholders’ need, system goals, and objectives (NGOs), presents an array of in-mission scenarios that span a wide range of medical conditions demonstrating the system’s capabilities from basic to complex events. Developed by a multidisciplinary team of systems engineers, scientists, and clinicians within ExMC, the ConOps revision includes two new scenarios(Barotrauma and Self-Medical Management and Behavioral Health and Chronic Medical Care), and implementation of findings from EIMO technical interchange meetings that focused on data and training. The envisioned EIMO Medical System (MS) operates as a system of systems, gathering data from various sources such as reference databases, real-time wearable sensors, point-of-care diagnostics, and environmental controls. The MS also incorporates advanced training tools to support autonomous medical care, assisting the Crew Medical Officer (CMO) during medical events where Ground Support is either unavailable or communication-delayed beyond practicality. Furthermore, MS functions and capabilities were decomposed from the scenarios to establish foundational requirements for EIMO and traced to the NASA Spaceflight Human-System Standard(NASA-STD-3001, Volumes 1 and 2). These traces were performed to gain insights on the alignment of EIMO requirements with the NASA standard. This work serves as an initial recommendation to increase crew autonomy gradually and safely for Mars missions and future deep-space exploration.

medical system↗

A Novel Fiber-Bragg-Grating-Based Unique Identifier for Use in Tags and Seals

Tags and seals are important tools used in safeguards regimes for the control of nuclear materials. Vital to a successful tag or seal is the ability to securely, uniquely, and positively distinguish it from others of the same kind. This allows one to validate that items entered into an inspection regime to which the tag or seal is affixed are as claimed. We are developing a new type of unique identifier (UID) for such applications that is based on fiber-Bragg grating (FBG) technology. The index of refraction of the core glass of a fiber optic can be locally and permanently altered if sensitized fibers are exposed to intense ultraviolet light. This can be used to create index modulations with a regular periodicity comparable to the wavelengths of light with which the fiber is used. If broadband illumination is sent down the fiber, any light that is in resonance with the modulations will be reflected back to the input end of the fiber where it can be detected. The shape of the returned spectrum can be set by the modulation pattern written into the fiber’s core. We take advantage of these properties to create a compact UID that contains several FBGs potted into a monolithic body. By connecting the UID to an optical interrogator, the complex spectral return can be uniquely identified with a short measurement, providing a robust identification. As a device based on narrowband spectral returns, FBGs are inherently radiation tolerant, making them ideal for use with nuclear materials. Further, they can be read out remotely via a long fiber optic or locally via brief connection to a portable optical interrogator. Because the spectral signature of FBGs is sensitive to external mechanical perturbations, we are exploring the ability to reversibly alter the signature obtained from the UID by applying controlled mechanical forces with a simple device. Such a “key” will allow different stakeholders to obtain their own unique signature from the device, providing a new level of surety to safeguards inspections.

Ziock, Klaus-Peter↗

MY EXES and EDM for Automated Remediation Data Quality Assessments - 19053

MY Electronic data exchange and Evaluation System (EXES) is a new web-based technology providing external admin access and full control to the Web-based EXES tool developed by GD for EPA for automated environmental remediation data quality assessments. EXES replaces most manual assessment processes, reducing remediation data review time and costs and ensuring that data are of known and documented quality. This tool is available from EPA to federal agencies and remediation firms and has successfully been used to support over 190 site investigations, 105 Remedial investigations and over 20 compliance monitoring efforts. The new MY EXES functionality has been developed for project managers and decision makers to setup projects, track receipt of environmental remediation monitoring data, assess data quality, and manage data. It is designed to be flexible and configurable to meet any government agency's data review and data management needs. It is accessible 24/7 through a secure portal. MY EXES efficiently evaluates analytical data regardless of the underlying method and data reporting requirements. It is a centralized project and data assessment tool that is scalable, flexible and configurable; improving data quality while reducing cost through the following: - Provides users with the ability to create a project and to specify the analytical methods corresponding to the data that will be submitted for that project. A project can be modified and managed anytime during the project's life cycle. - Allows users to manage a library of analytical methods that can be made available for association to their projects. - Users can specify the automated tests and assessment that needs to be performed on the analytical data deliverables based on specific requirements in the project's Quality Assurance Project Plan (QAPP). - Users specify: - The format of the incoming data deliverables from the laboratory; - The type and level of review services to be performed; - The assessment deliverables to be generated - output spreadsheets and reports; - Project owner sets up system access and permissions for members of the project team. - A faster (600%) and less expensive (85%) process than the traditional data usability/validation. The EXES Data Manager application (EDM) provides a centralized data repository to view and retrieve generated reports, spreadsheets, and other data deliverables as defined by the client, eliminating the need for data transfer between project team members. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Robotic Non-destructive Test of Concrete Structures with GPR, Impact Echo and 3D Vision - 19540

Structural members come across with various internal defects that cannot be evaluated visually. Instead, hand-held nondestructive sensors are used to detect such defects. In many situations, the hand-held NDT is not possible in high-risk structures because of limited access or safety issues. Therefore, Robotic NDT plays major role in assessing such structures. Robot Operating Systems (ROS) is a powerful open source tool, which is used to program and control robots and other devices enabling one to use sensors, devices and new functionalities such as autonomous navigation, visual perception. For the research presented, ROS is used to program the Sawyer robot arm manufactured by Rethink Robotics. The control system for the robot ensures the ability to adapt to different weights of integrated measuring devices and measured force applied against the wall with a wheeled measuring device while making a remote sweep. Twelve reinforced concrete (RC) beams built with characterized defects are evaluated with the robotic arm integrated with the measuring devices. The RC beams are characterized by voids, corrosion and debonding problems of rebars. The Impact Echo and Ground Penetrating Radar (GPR) devices attached to the robot arm are used to measure the material properties of the concrete beams. The robot arm ensures consistency and uniformity of measurement even in obscure locations. Infrared cameras are used to obtain 3D images of the surfaces of the concrete structures. Roughness is analyzed using computer vision techniques prior to the use of other sensors that are in touch with the surfaces. The computer vision is also used to handle the images collected from GPR sensor. Hand-held NDE is also performed to verify the results obtained by robotic examination. (authors)

42 ENGINEERING↗

Software reliability through fault-avoidance and fault-tolerance

Strategies and tools for the testing, risk assessment and risk control of dependable software-based systems were developed. Part of this project consists of studies to enable the transfer of technology to industry, for example the risk management techniques for safety-concious systems. Theoretical investigations of Boolean and Relational Operator (BRO) testing strategy were conducted for condition-based testing. The Basic Graph Generation and Analysis tool (BGG) was extended to fully incorporate several variants of the BRO metric. Single- and multi-phase risk, coverage and time-based models are being developed to provide additional theoretical and empirical basis for estimation of the reliability and availability of large, highly dependable software. A model for software process and risk management was developed. The use of cause-effect graphing for software specification and validation was investigated. Lastly, advanced software fault-tolerance models were studied to provide alternatives and improvements in situations where simple software fault-tolerance strategies break down.

Vouk, Mladen A.↗

Invasive Species Forecasting System: A Decision Support Tool for the U.S. Geological Survey: FY 2005 Benchmarking Report v.1.6

The National Institute of Invasive Species Science (NIISS), through collaboration with NASA's Goddard Space Flight Center (GSFC), recently began incorporating NASA observations and predictive modeling tools to fulfill its mission. These enhancements, labeled collectively as the Invasive Species Forecasting System (ISFS), are now in place in the NIISS in their initial state (V1.0). The ISFS is the primary decision support tool of the NIISS for the management and control of invasive species on Department of Interior and adjacent lands. The ISFS is the backbone for a unique information services line-of-business for the NIISS, and it provides the means for delivering advanced decision support capabilities to a wide range of management applications. This report describes the operational characteristics of the ISFS, a decision support tool of the United States Geological Survey (USGS). Recent enhancements to the performance of the ISFS, attained through the integration of observations, models, and systems engineering from the NASA are benchmarked; i.e., described quantitatively and evaluated in relation to the performance of the USGS system before incorporation of the NASA enhancements. This report benchmarks Version 1.0 of the ISFS.

Stohlgren, Tom↗

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

Advanced aerodynamics and active controls for a next generation transport

In aerodynamics, the use of new and flexible tools for the design of supercritical wings is discussed. Trends in the design and performance of highlift devices are outlined. In the field of active controls, the determination of suitable configurations with regard to flying qualities is described, particularly related to results from a piloted simulation.

Taylor, A. B.↗

Aspects of model-based rocket engine condition monitoring and control

A rigorous propulsion system modelling method suitable for control and condition monitoring purposes is developed. Previously developed control oriented methods yielding nominal models for gaseous medium propulsion systems are extended to include both nominal and anomalous models for liquid mediums in the following two ways. First, thermodynamic and fluid dynamic properties for liquids such as liquid hydrogen are incorporated into the governing equations. Second, anomalous conditions are captured in ways compatible with existing system theoretic design tools so that anomalous models can be constructed. Control and condition monitoring based methods are seen as an improvement over some existing modelling methods because such methods typically do not rigorously lead to low order models nor do they provide a means for capturing anomalous conditions. Applications to the nominal SSME HPFP and degraded HPFP serve to illustrate the approach.

Karr, Gerald R.↗

Reliability of Fault Tolerant Control Systems

This paper reports Part I of a two part effort, that is intended to delineate the relationship between reliability and fault tolerant control in a quantitative manner. Reliability analysis of fault-tolerant control systems is performed using Markov models. Reliability properties, peculiar to fault-tolerant control systems are emphasized. As a consequence, coverage of failures through redundancy management can be severely limited. It is shown that in the early life of a syi1ein composed of highly reliable subsystems, the reliability of the overall system is affine with respect to coverage, and inadequate coverage induces dominant single point failures. The utility of some existing software tools for assessing the reliability of fault tolerant control systems is also discussed. Coverage modeling is attempted in Part II in a way that captures its dependence on the control performance and on the diagnostic resolution.

Wu, N. Eva↗