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NASA NTRS2019

Designing the User Experience for Earth Observation Data Services in the Cloud

NASA's Earth Observation (EO) inventory is projected to grow by an order of magnitude over the next 5-6 years. The current mode for working with EO data of downloading the data to a local machine (laptop, desktop or server) will be difficult to sustain for these upcoming volumes. Therefore, NASA is in the process of developing a capability to host large volume data in commercial cloud, with an eye toward encouraging data analysis in the cloud. However, in order for the user community to take advantage of this new mode of data interaction, the user experience must be redesigned. Cloud-hosted data brings new challenges, such as managing the costs of data egress and working with data in Web Object Storage instead of a Posix filesystem. However, it also brings new opportunities. Scaling data transformation processes may permit more synchronous data services with near-immediate response vs. cumbersome ordering systems with latencies of hours or days. Data co-location in the cloud can facilitate data integration and fusion. Highly scalable filesystems and databases in the cloud support data reorganization to facilitate analysis at scale. In the course of NASA's reimagining of the User Experience for EO data usage relies on end user input gathered through surveys, workshops and meetings (such as this). At the same time, we have embarked on a course of pedagogy and capacity building to help the user community evolve to cloud-based analysis.

Lynnes, Christopher↗

NASA NTRS2019

Nasa GeneLab Computomics Reveal Horizontal Gene Transfer on International Space Station Environmental Metagenomes

Prokaryotic lifeforms can be observed to demonstrate many keen adaptive advantages, perhaps facilitated by a nature simplistic relative to divergent domains of life. In particular, decompartmentalized gene expression facilitates adaptation by allowing free exchange of genetic material, albeit at the cost of increased susceptibility to genetic damage. Thus, these lifeforms must compensate by embracing diverse investment strategies in an attempt to “brute force” the evolvability equation through precipitous genesis, lean metabolic efficiency, and sheer population. This prokaryotic archetype also enables symbiotic relationships with secondary mobile genetic elements known as plasmids, which have been shown to drive evolution on rapid temporal scales through processes such as conjugation and transformation. This study attempts to decipher whether these mechanisms of horizontal gene transfer (HGT) are major factors in determining prokaryote fitness within a unique isolated environment, the International Space Station (ISS). The ISS Microbial Tracking (MT) project has generated a wealth of data concerning the successive reigns of microbial genera that appear to thrive amidst harsh conditions for life. Despite relatively higher doses of ionizing radiation as compared to Earth, complications associated with microgravity, and the anti-microbial mélange deployed, microbial life still persists in this environment. The NASA GeneLab serves as a data repository and analysis platform to enable researchers to access space flight factor related data. With the use of GeneLab’s modern computational suites (computomics), phylogenetic and functional genomic investigations of HGT events were conducted on the data generated from the MT-1 project. The putative data concerning the plasmid population (plasmidome) of the ISS was algorithmically derived and compared to those of habitats with similar environmental dynamics- such as living quarters and hospitals- to investigate whether these HGT elements may play crucial role(s) in shaping the microbiome of this closed habitat that serves as the only inhabited structure in space.

Bense, Nicholas↗

NASA NTRS2019

Early Prototype Development of the Passive Orbital Nutrient Delivery System (PONDS)

Long-duration space missions will eventually require a fresh food supply to supplement crew diets, which means growing crops in space. The Passive Orbital Nutrient Delivery System (PONDS) is a new plant growth approach that contains both an area for a contained substrate and a reservoir for water and/or plant nutrient solutions. Ground studies have shown that the system facilitates both reliable water delivery to seeds for germination (e.g., while avoiding overwatering), and transport of water from the reservoir for improved plant growth while providing nutrients and oxygen to the root zone. In ground prototypes a capillary mat wicking material passively links the water/nutrient solution reservoir to a removable rooting module containing a substrate adapted to support plant growth. Oxygen permeable membranes are incorporated into both the reservoir walls and the rooting modules, bringing in oxygen from outside of the system into the reservoir and then into the rooting modules where the plant roots proliferate. Water is delivered from the reservoir to the substrate contained within the rooting module through the use of wicking material inserted into the plant growth substrate both from the bottom and from the sides of the rooting module. The capillary mat material is intrinsically hydrophilic and continuously wicks water to the substrate throughout the plant growth interval. The system is therefore self-watering in terms of supplying water to the root zone encompassed within the rooting module on demand. At the top, a hydrophilic phenolic foam plug surrounds the wick in the seed insertion zone, and both contains the substrate within the rooting module, and facilitates removal of excess moisture from the capillary mat wick before it can encompass seeds prior to germination. This work is supported by NASA’s Space Life and Physical Sciences and Research Applications Division (SLPSRAD).

Levine, Howard G.↗

NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗

NASA NTRSDate not supplied

Sparse Linear Algebra Toolkit for Computational Aerodynamics

Finding solutions to sparse linear systems of equations is an essential step in Computational Engineering applications of interest to NASA. Linear systems of equations are composed and solved in almost every computational engineering application. The characteristics of linear systems vary greatly from one application to another. Accordingly, there are a wide variety of methods for the solution of linear systems of equations. The operations and methods prepared by the authors are focused on linear systems of interest to NASA, primarily those associated with Computational Fluid Dynamics (CFD), Aeroelasticity, and Aeroacoustics. The Sparse Linear Algebra Toolkit (SLAT) is a coordinated collection of software featuring operations, methods, and data structures that are useful when solving sparse linear systems of equations on modern computer architectures. The implemented operations and methods are designed and tuned for parallelism in shared memory, in distributed memory, and across the hybrid combination of distributed-shared memory. The toolkit includes novel methods and implementations for modern architectures and facilitates development of new approaches for meeting NASA’s evolving computational engineering challenges using evolving computer architectures that are not available in vendor libraries. In this paper, significant features and interfaces within SLAT are presented and verified for simulations performed with NASA’s CFD solver, FUN3D. The runtime and scaling performance of the Generalized Minimum Residual (GMRES) method implemented in SLAT is analyzed for the linear subproblems within the solution of turbulent Navier-Stokes equations employed in the simulation of high-lift configurations. Prior to this work, the SPARSKIT GMRES implementation was the only Krylov subspace method available within FUN3D. A strong scaling study shows the SLAT GMRES implementation facilitates accurate Reynolds-averaged Navier-Stokes CFD solutions between 15% and 56% faster than the SPARSKIT GMRES implementation.

Stephen L Wood↗

NASA NTRS2020

TURBOMAT-FR: Turbomachinery Aeroelastic Forced Response Analysis Automation Using MATLAB®: PART 1

The primary aim of this effort is to develop a software tool named “Turbomachinery Aeroelastic Analysis Tool for Forced Response (TURBOMAT-FR)” using MATLAB® (The MathWorks, Inc.) scripts. The tool will aid in performing routine forced response analysis of turbomachinery fan blades with the aid of the modal summation method (MSUM). The MSUM approach requires a modal solution consisting of modal displacements, modal frequencies, and modal stresses. The MATLAB® scripts facilitate easy extraction of the required quantities from the computational fluid dynamics (CFD) and MSC Nastran (Hexagon AB) solution files. These quantities are subsequently utilized by the MSUM approach to perform a complete forced response analysis.The MATLAB® scripts in TURBOMAT-FR are utilized in postprocessing of the MSC Nastran finite element analysis outputs in three types of solutions or steps, namely (1) stresses and displacements from static and steady response solution, (2) unsteady stresses and displacements from direct forced response solution, and (3) modal solution containing modal displacements and modal stresses. In step (4), separate MATLAB® scripts are also developed to read the processed outputs in step (3) and perform forced response analysis using MSUM. The TURBOMAT-FR MATLAB® scripts mentioned previously are presented in two reports designated “Part 1” and “Part 2”. The current report, Part 1, presents the scripts needed to accomplish steps (1) and (2), noted previously. This will be exclusively useful for performing only the static and steady response analysis and the forced response analysis using the direct forced response solution approach. Part 2 contains the TURBOMAT-FR MATLAB® scripts needed to accomplish steps (3) and (4). The MATLAB® scripts given in Part 2 facilitate the calculation of unsteady stresses using MSUM and provide an automated procedure associated with aeroelastic forced response analysis with different pressure files for the same structural model. The unsteady stresses calculated using MSUM in Part 2 can be compared with those presented in Part 1. A cantilevered blade-alone model subjected to a realistic pressure loading to a boundary was used for static and unsteady direct forced response analysis to demonstrate the effectiveness of the TURBOMATFR MATLAB® scripts.

MATLAB-Scripts↗

NASA NTRS2020

TURBOMAT-FR: Turbomachinery Aeroelastic Forced Response Analysis Automation Using MATLAB® Part 2

The primary aim of this effort is to develop a software tool named “Turbomachinery Aeroelastic Analysis Tool for Forced Response (TURBOMAT-FR)” using MATLAB® (The MathWorks, Inc.) scripts. The tool will aid in performing routine forced response analysis of turbomachinery fan blades with the aid of the modal summation method (MSUM). The MSUM approach requires a modal solution consisting of modal displacements, frequencies, and stresses. The MATLAB® scripts facilitate easy extraction of the required quantities from the computational fluid dynamics (CFD) and MSC Nastran (Hexagon AB) solution files. These quantities are subsequently utilized by the MSUM approach to perform a complete forced response analysis using the MATLAB® scripts. The MATLAB® scripts in TURBOMAT-FR are utilized in postprocessing of the MSC Nastran finite element analysis outputs in three types of solutions or steps, namely (1) stresses and displacements from static or steady response solution, (2) unsteady stresses and displacements from direct forced response solution, and (3) modal solution containing modal displacements and modal stresses. In step (4), separate MATLAB® scripts are also developed to read the processed outputs in step (3) and perform forced response analysis using MSUM. It should be noted that the direct forced response solution from step (2) will provide for a comparison with those obtained from the MSUM approach in steps (3) and (4). The TURBOMAT-FR MATLAB® scripts mentioned previously are presented in two reports designated Parts 1 and 2. Part 1 presents the scripts needed to accomplish steps (1) and (2). The current report, Part 2, presents the scripts needed to accomplish steps (3) and (4), noted previously. The TURBOMAT-FR MATLAB® scripts provided here in Part 2 facilitate the calculation of unsteady stresses using MSUM and provide an automated procedure associated with aeroelastic forced response analysis with different pressure files. The unsteady stresses calculated using MSUM can be compared with those presented in Part 1. A cantilevered blade-alone model subjected to a realistic pressure loading to a boundary was used for static and unsteady direct forced response analysis to demonstrate the effectiveness of the TURBOMATFR MATLAB® scripts.

T S R Reddy↗

NASA NTRSDate not supplied

Urban Air Mobility National Campaign Test Series

The Urban Air Mobility (UAM) National Campaign test series is designed to promote public confidence in UAM safety, facilitate community-wide learning while capturing the public’s imagination, and give prospective vehicle manufacturers and operators, and prospective airspace service providers, insights into the evolving regulatory and operational environment. The National Campaign is also intended to support requirements and system development for Urban Air Mobility through integrated demonstrations of candidate vehicles and airspace in operational scenarios critical to scalable commercialization. The NASA National Campaign series will facilitate bringing together vehicle and airspace service providers to demonstrate industry’s concept and technology maturity levels with respect to vehicle performance, safety assurance, and airspace interoperability solutions for civil use.

Urban Air Mobility↗

NASA NTRS2020

Recommended Laboratory and Field Studies ahead of Future Mercury Exploration

Data from Mariner 10, MESSENGER, and ground-based telescopic observations have facilitated great advancements towards understanding the geochemistry, geology, internal structure, and space environment (exosphere/magnetosphere) of Mercury. Future exploration efforts by BepiColombo, landed science, and sample return will revolutionize our understanding of this planet. However, to enhance the scientific return of past, present, and future data collection at Mercury, it is imperative that laboratory and field-based studies be conducted over the next decade. This white paper gives examples of laboratory and field studies, including instrument testing, which should take place over the next decade to facilitate the interpretation of data and preparation of future missions to the inner-most planet. By no means are the topics in this paper exhaustive, but rather are meant to demonstrate the immense amount of work that needs to be completed ahead of, or in conjunction with, current and future exploration efforts of Mercury. This work would amplify the benefits from additional data obtained from the planet’s surface to the fullest extent possible, and to aid in decision making of future instrument payloads. We have chosen to focus our inputs here on geochemistry, geology, and space environment related efforts, but we emphasize that extensive research in the areas of geophysics and other geosciences-related disciplines will benefit from additional studies.

Kathleen E. Vander Kaaden↗

NASA NTRSDate not supplied

Developing a Medical System Foundation for Level of Care IV: Short-Duration Lunar Orbit

The Human Research Program (HRP) Exploration Medical Capability (ExMC) element has developed a Medical System Foundation for Level of Care IV, as defined by NASA’s space flight human-system standards, for short-duration lunar orbit missions by employing a systems engineering approach using model-based systems engineering tools. This Foundation includes a concept of operations, medical system architecture, associated functional and non-functional requirements and rationales, and medical conditions, capabilities, and resources. Collectively, these serve as a starting point (“Foundation”) for a medical system that meets the Level of Care IV requirement. The Foundation also includes traces to the current versions of NASA standards documents and lower (e.g., sub-system) and higher (e.g., vehicle system) level requirements. Stakeholders can use the Foundation to analyze the traces between medical capabilities, medical conditions, medical resources, and requirements; identify medical system interfaces with other vehicle systems/subsystems; and as a basis for performing trades on risks vs. medical system mass and volume allocation. To facilitate communication of the Foundation to stakeholders who do not have access to the modeling tools used, an HTML representation of the Foundation was created. This discussion will focus on the processes through which the Medical System Foundation was developed, how the Foundation builds a bridge between the medical and engineering domains and facilitates communication between these communities, and how these processes can be applied more broadly to a crew health and performance system and other system domains.

S. Lumpkins↗

NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗

NASA NTRS2021

CubeSat Technology Past and Present: Current State-Of-The-Art Survey

A cube satellite (CubeSat) is an evolving and emerging technology that gives a novice or advanced researcher relatively affordable access to space research experiments and applications. The initial CubeSat standard was created in 1999 by California Polytechnic State University, San Luis Obispo and Stanford University’s Space Systems Development Lab to facilitate direct access to space for university students. This initial CubeSat standard has now been adopted by hundreds of organizations worldwide and includes not only universities, educational institutions, but private firms and government organizations. Dozens of CubeSats have been launched since 2003 and have come from more than 29 states in the United States. The CubeSat standard facilitates frequent and affordable access to space with launch opportunities available on most launch vehicles. CubeSats are a class of research spacecraft called nanosatellites and are built to standard CubeSat Units or U dimensions of 10 by 10 by 10 cm and are formally classified as 1U, 2U, 3U, or 6U in size. Most CubeSats are deployed from a Poly-Picosatellite Orbital Deployer called a P-POD. Partnerships among NASA, U.S. industry, and educational institutions are being formed to build upon existing successful CubeSat initiatives with a goal to expand and include launching 50 small satellites from 50 states within the next several years. An extensive and detailed literature review that includes over 830 citations has been conducted to provide a comprehensive resource on both NASA and non-NASA CubeSat experiments and applications that can serve as a guide for background information on CubeSats as well as a valuable resource of lessons learned from CubeSats that have been launched in the past. CubeSats are currently being launched from all over the world on different launch vehicle platforms. Some organizations providing launch opportunities are California Polytechnic State University (http://www.cubesat.org/contactus), ISISPACE Group (https://www.isispace.nl/), Nanoracks (http://nanoracks.com/), Spaceflight Industries, Inc. (http://spaceflight.com/), TriSept Corporation (https://trisept.com/), and Tyvak Nano-Satellite Systems, Inc. (https://www.tyvak.com/).

Cubesat↗

NASA NTRS2017

Precision Asteroid Astrometry

Among the methods used to guide spacecraft to their destinations, Optical Navigation (OpNav) remains an effective option. OpNav makes use of star fields and small body ephemerides to precisely locate spacecraft. To facilitate accurate OpNav, the small body ephemerides must be constantly updated; asteroid orbits accumulate errors each year of a few milliarcseconds. Through extended exposures, taken with strategic offsets, a least-squares solution can be found that determines updated ephemeris data. This updated data can also be used by occultation astronomers to gain further information about the small bodies, including their size and shape. Using the 24-inch telescope at the Caltech Table Mountain Observatory (TMO), we capture two or more 180 second exposures of each target. These images, combined with a file for the predicted background star field and two reference files, are then processed through a series of scripts and programs. Starting with a prediction file and two to five exposures of the asteroid, the data is processed. This original data is about 32MB per observation. Once the data are reduced to only Right Ascension and Declination for each target, the data are ready for delivery. This consists of text only, and for each target takes about 80 bytes; this resulting data reduction is about five orders of magnitude. This method produces observed positions that are refined by about 12 milliarcseconds, a refinement that is accomplished almost nowhere else. The occultation observations that are facilitated by the ephemerides being refined also produce results that are not possible in any other way from ground-based observations.

Dial, Jason↗

NASA NTRS2021

Anion-Assisted Delivery of Multivalent Cations to Inert Electrodes

To understand and control key electrochemical processes - metal plating, corrosion, intercalation, etc. requires molecular-scale details of the active species at electrochemical interfaces and their mechanisms for de-solvation from the electrolyte. Using free energy sampling techniques we reveal the interfacial speciation of divalent cations in ether-based electrolytes and mechanisms for their delivery to an inert graphene electrode interface. Surprisingly, we find that anion solvophobicity drives a high population of anion-containing species to the interface that facilitate the delivery of divalent cations, even to negatively charged electrodes. Our simulations indicate that cation desolvation is greatly facilitated by cation-anion coupling. We propose anion solvophobicity as a molecular-level descriptor for rational design of electrolytes with increased efficiency for electrochemical processes limited by multivalent cation desolvation.

Electrochemical interfaces↗

NASA NTRSDate not supplied

Reports of Resilient Performance: Investigating Operators' Descriptions of Safety-producing Behaviors in the Aviation Safety Reporting System

While many existing taxonomies and frameworks provide a common vocabulary for describing how human operators fail in the context of sociotechnical systems, at present, there is no common vocabulary to describe how humans succeed. Such a framework would facilitate systematically collecting and analyzing data on how human performance can produce safety, not just how it can reduce safety. One potentially rich source of currently available information for exploring desired performance is the reports submitted to NASA’s Aviation Safety Reporting System (ASRS). These de-identified, confidential, and voluntary narrative reports are submitted by pilots, controllers, ground operators, and others within aviation operations. While these reports are primarily submitted to describe safety risks, incidents, and problems, they also often describe how those risks were mitigated, and provide a window into aspects of everyday work in aviation. These reports can be searched in a variety of ways. This paper describes methods for systematically examining ASRS narratives to understand how operators talk about their own resilient behaviors during adverse safety conditions and events. Guided by Erik Hollnagel’s Resilience Assessment Grid framework (i.e., anticipate, monitor, respond, learn), various approaches and tools for such inquiries are described. The approach, process, challenges, and suggestions to building an operator-based description of resilient performance are discussed, and tools to facilitate data analysis to maximize learning from these reports are described.

ASRS narratives↗

NASA NTRS2021

Automated UAS Measurements of Reflectance and Solar Induced Florescence (SIF) for Assessment of the Dynamics in Photosynthetic Function, Application for Maize (Zea Mays L.) in Greenbelt, Maryland, US

To enable monitoring of the parameters governing photosynthesis at the temporal frequency relevant to their dynamics and at a spatial scale that allows practical assessment and management there is a strong need for advancement in the UAS remote sensing methods and instruments. Currently, no single sensor can provide data at the desired high temporal, spectral and spatial resolutions. Our field measurements obtained using the integrated UAS Piccolo system during the summers of 2017 and 2018 demonstrate that science quality reflectance and solar induced fluorescence (SIF) data can be retrieved with high temporal frequency using small Unmanned Aerial Systems (UAS). The implemented approach facilitates consistent data comparisons in space and time and facilitates their integration with other spectral satellite and airborne data.

Petya Campbell↗

NASA NTRSDate not supplied

Recommendations to Advance Space Trusted Autonomy

The interagency Space Science and Technology Partnership Forum was established in2015 to identify synergistic efforts and technologies across the U.S. government. While the various space agencies of the U.S. government have distinctly different visions for future operational space systems, all share important foundational common needs. These needs, combined with the maturation of autonomous technology and the prospect of leveraging autonomous systems to address those needs, have led each agency to consider how and when to to implement increasing levels of autonomy in their space systems, and how to determine the trustworthiness of an autonomous system. The Partnership facilitated dialogue among the partners, collected and analyzed data on current and desired future levels of capability, and identified gaps to motivate three recommendations that can be addressed within the Partnership community. These recommendations address the need for more robust documenting and socializing of anomalies in space system operations; the need to expand communication and trust within the community of developers, operators, and end users; and the need for a safe development and testing environment for maturing and demonstrating future autonomous space systems. These recommendations will facilitate both near-term programmatic actions and long-term steps for implementing enduring progress towards enabling space trusted autonomy.

Christopher A Jones↗

NASA NTRSDate not supplied

Enabling a Voice Management System for Space Applications, Design and Software Development

Sustainable missions, beyond low Earth orbit, will require autonomous capabilities in order to achieve NASA’s Artemis program objectives. Correspondingly, the crew must have a means to efficiently interact with these autonomous systems; this can be facilitated via voice and speech communications. Voice-based controls enable the user to access autonomous systems hands-free/eyes-free, allowing the user to better focus on critical tasks. The goal of this project was to explore the knowledge and technology needed to successfully design effective voice interfaces for autonomous systems. The main objective was to understand how a crew member, through voice interaction, could most efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project leveraged prior research conducted by the University of Michigan’s Bioastronautics and Life Support System (BLiSS) team as part of a NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The X-Hab 2020 work from the BliSS Team resulted in an intuitive graphical user interface/user experience that was built on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2021 project leveraged this technology and incorporated a voice-based assistant and NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the background noise environment of spacecraft was assessed, and a relatable personality for the autonomous system to facilitate human-like conversations was created. This work’s success was largely due to the diverse team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The differing perspectives fostered elaborate discussions, resulting in the conception of three main interactions: (1) User-System, (2) NPAS-System, and (3) Environment-System. The system developed, i.e. the VUI, had to be unique, efficient, and intuitive; thus, the team crafted a personality for the system to enable human-like conversation. User surveys sent to students and young professionals were used to help determine these personality traits by capturing perspectives and expectations of the “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS system for quick and reliable information transfer. Results of this research include (1) a working prototype user interface, that is compatible with NASA’s NPAS system; (2) software that demonstrates the ability to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate, i.e. be heard, in a noisy environment. The technologies chosen for this project’s demonstrations included the following: Raspberry Pi, RASA, Mozilla Deep Speech, Coqui, RTX Voice and Adobe XD. This work has laid the foundation for the development of VUI’s used for autonomy, and is intended to provide guidance for future VUI development.

Tara Vega↗