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NASA NTRSDate not supplied

Demonstration of Rapid Development Through Containerization: OSE-SAT

Modern advancements in spacecraft technology have enabled engineers to develop radically smaller and lighter spacecraft, which has drastically reduced the cost of putting spacecraft into space. Despite these advancements and the shrinking cost to get spacecraft into space, space exploration is still prohibitively expensive. So much so that many space missions prefer to err on the side of caution than take on additional risk by trying newer, unproven technologies. This risk-averse mission design, while very reasonable from a program management point of view, significantly impacts engineers’ ability to solve newer, more complicated problems and limits scientists’ ability to develop more complex experiments that rely on newer technology. Often these new technologies remain stuck at lower technology readiness levels for many years due to the space community's reluctance to take on the additional risks of proving out unproven technology. The Distributed Spacecraft Autonomy (DSA) team at NASA Ames Research Center is developing a containerized solution to enable the rapid development of newer space technologies and accelerate their adoption into space missions. The Opportunistic Software Experiments for Spacecraft Autonomy Testbeds (OSE-SAT) is an on-orbit test bed that aims to reduce the amount of risk associated with newer, unproven space technologies by containerizing each experiment in its own isolated environment and providing a safe, robust, and controlled interface to access spacecraft host resources that is monitored in real time by thoroughly tested Trusted Container developed by DSA. This paper will describe DSA’s implementation of OSE-SAT and discuss the benefits, as well as challenges, of on-orbit containerization.

Aaron J Woodard↗

NASA NTRS2014

NASA Wearable Technology CLUSTER 2013-2014 Report

Wearable technology has the potential to revolutionize the way humans interact with one another, with information, and with the electronic systems that surround them. This change can already be seen in the dramatic increase in the availability and use of wearable health and activity monitors. These devices continuously monitor the wearer using on-‐body sensors and wireless communication. They provide feedback that can be used to improve physical health and performance. Smart watches and head mounted displays are also receiving a great deal of commercial attention, providing immediate access to information via graphical displays, as well as additional sensing features. For the purposes of the Wearable Technology CLUSTER, wearable technology is broadly defined as any electronic sensing, human interfaces, computing, or communication that is mounted on the body. Current commercially available wearable devices primarily house electronics in rigid packaging to provide protection from flexing, moisture, and other contaminants. NASA mentors are interested in this approach, but are also interested in direct integration of electronics into clothing to enable more comfortable systems. For human spaceflight, wearable technology holds a great deal of promise for significantly improving safety, efficiency, autonomy, and research capacity for the crew in space and support personnel on the ground. Specific capabilities of interest include: Continuous biomedical monitoring for research and detection of health problems. Environmental monitoring for individual exposure assessments and alarms. Activity monitoring for responsive robotics and environments. Multi-modal caution and warning using tactile, auditory, and visual alarms. Wireless, hands-free, on-demand voice communication. Mobile, on-demand access to space vehicle and robotic displays and controls. Many technical challenges must be overcome to realize these wearable technology applications. For example, to make a wearable device that is both functional and comfortable for long duration wear, developers must strive to reduce electronic mass and volume while also addressing constraints imposed by the body attachment method. Depending on the application, the device must be placed in a location that the user can see and reach, and that provides the appropriate access to air and the wearer's skin. Limited power is available from body-‐worn batteries and heat must be managed to prevent discomfort. If the clothing is to be washed, there are additional durability and washability hurdles that traditional electronics are not designed to address. Finally, each specific capability has unique technical challenges that will likely require unique solutions. In addition to the technical challenges, development of wearable devices is made more difficult by the diversity of skills required and the historic lack of collaboration across domains. Wearable technology development requires expertise in textiles engineering, apparel design, software and computer engineering, electronic design and manufacturing, human factors engineering, and application-‐specific fields such as acoustics, medical devices, and sensing. Knowledge from each of these domains must be integrated to create functional and comfortable devices. For this reason, the diversity of knowledge and experience represented in the Wearable Technology is critical to overcoming the fundamental challenges in the field.

Simon, Cory↗

NASA NTRS2014

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations↗

NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗

NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

machine learning↗

NASA NTRS2018

Remote Sensing of Venusian Seismic Activity with a Small Spacecraft, the VAMOS Mission Concept

The Venusian atmosphere creates inhospitable temperature and pressure conditions for the surface of Venus, Earth’s twin planet, making in-situ measurements of any appreciable length difficult, expensive, and risky to obtain. Yet, because of the apparent youthfulness of Venus’ surface features, long-duration seismic observations are in high demand in order to determine and understand the dynamic processes taking place in lieu of plate tectonics. The Venus Airglow Measurements and Orbiter for Seismicity (VAMOS) mission concept would make use of the dense Venusian atmosphere as a medium to conduct seismic vibrations from the surface to the ionosphere. Here, the resulting atmospheric gravity waves and acoustic waves can be observed in the form of perturbations in airglow emissions, the basic principles for which have been demonstrated at Earth following a tsunami and at Venus with the European Venus Express’s Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) instrument. In addition, these observations would enable VAMOS to determine the crustal structure and ionospheric variability of Venus without approaching the surface or atmosphere themselves. Equipped with an instrument of modest size and mass, the baseline VAMOS spacecraft is designed to fit within a SmallSat form factor and travel to Venus predominantly under its own power. VAMOS would enter into an orbit uniquely suited for the longduration, full-disk staring observations required for seismic readings. VAMOS’ journey would be enabled by modern solar electric propulsion technology and SmallSat avionics, which allow the spacecraft to reach Venus and autonomously filter observation data on board to detect Venus-quake events. Currently, trade studies are being conducted to determine mission architecture robustness to launch and rideshare opportunities. Key spacecraft challenges for VAMOS, just as with many SmallSat-based mission concepts, include thermal and power management, onboard processing capabilities, telecommunications throughput, and propulsion technology. The VAMOS mission concept is being studied at JPL as part of the NASA Planetary Science Deep Space SmallSat Studies (PSDS3) program, which will not only produce a viable and exciting mission concept for a Venus SmallSat, but will have the opportunity to examine many issues facing the development of SmallSats for planetary exploration. These include SmallSat solar electric propulsion, autonomy, telecommunications, and resource management that can be applied to various inner solar system mission architectures.

Helbert, Jörn↗

NASA NTRS2019

Prognostics As-A-Service: A Scalable Cloud Architecture for Prognostics

Comprehensive aircraft system health-state awareness is critical for maintaining safe, efficient growth in global operations, enabling higher levels of autonomy, and facilitating new forms of aviation. Maintainers, vehicle operators, air traffic controllers, dispatchers, pilots, autonomous systems, and other decision-makers must have reliable real-time knowledge of the vehicle health, the health of its critical composite systems, predictions of how health changes with time, and forecasts of how its capabilities change with health degradation to preserve safety and efficiency. Providing this information in a reliable manner in computationally constrained environments and across a wide range of vehicles and systems continues to be a challenge. This challenge can be partially resolved through cloud computing, where the execution of prognostic and diagnostic algorithms is performed on a network of remote servers hosted on the internet. NASA is developing a cloud computing service, Prognostics As-A-Service (PaaS), that explores the feasibility and challenges of cloud-enhanced prognostics. Though such a system has broad applicability, this research effort is focused on aviation applications.

Prognostics↗

NASA NTRSDate not supplied

Lunar Base Construction Planning

Previous lunar missions and campaigns have been restricted to using robotic landers and lunar orbiting satellites as well as sortie type of operations using astronaut crews(NASA Apollo program).Now, the next phase of lunar exploration has begun under NASA’s Artemis program and there has been an international response where other nations such as China, Russia, India, Canada, Japan and theEuropean Union of nations, have all expressed interest in either collaborating or competing with NASA on theMoon. This next phase has an overarching goal of achieving a permanent human presence on theMoon via sustainable methods. A lunar base with human occupancy will require infrastructure to provide shelter, utilities, landing/launch pads, roads, communications, power and all the other necessities to sustain human life and protect equipment.Since human biology is not well suited for surviving in the lunar environment, there will be many forms of automated equipment, autonomy and robotic helpers that will minimize the amount of Extra-Vehicular Activity(EVA) required by the crew. This will mean that the radiation dosage received by the crew will stay within acceptable and safe career doses. Radiation shielding via the use of regolith can also mitigate radiation dangers.The required infrastructure must be constructed, but the mass and logistics of bringing all the construction materials from Earth are prohibitive, which makes the necessary construction difficult to achieve.In-Situ Resource Utilization (ISRU) aims to solve this challenge by sourcing construction materials locally or “in-situ”. This means that their transportation can be completely eliminated, resulting in large cost savings by avoiding the launch out of Earth’s deep gravity well and subsequent trans lunar injection, lunar orbit capture and landing. This paper will give ahistorical review and current status of lunar construction planning and a high level introduction to the required infrastructure and construction equipment that will be required to robotically build a lunar base using in-situ resources.It will also organize these tasks into logical groupings so that technology development and implementation can be pursued within a framework that can be referenced by all involved.

Lunar↗

NASA NTRS2011

Haptic-Multimodal Flight Control System Update

The rapidly advancing capabilities of autonomous aircraft suggest a future where many of the responsibilities of today s pilot transition to the vehicle, transforming the pilot s job into something akin to driving a car or simply being a passenger. Notionally, this transition will reduce the specialized skills, training, and attention required of the human user while improving safety and performance. However, our experience with highly automated aircraft highlights many challenges to this transition including: lack of automation resilience; adverse human-automation interaction under stress; and the difficulty of developing certification standards and methods of compliance for complex systems performing critical functions traditionally performed by the pilot (e.g., sense and avoid vs. see and avoid). Recognizing these opportunities and realities, researchers at NASA Langley are developing a haptic-multimodal flight control (HFC) system concept that can serve as a bridge between today s state of the art aircraft that are highly automated but have little autonomy and can only be operated safely by highly trained experts (i.e., pilots) to a future in which non-experts (e.g., drivers) can safely and reliably use autonomous aircraft to perform a variety of missions. This paper reviews the motivation and theoretical basis of the HFC system, describes its current state of development, and presents results from two pilot-in-the-loop simulation studies. These preliminary studies suggest the HFC reshapes human-automation interaction in a way well-suited to revolutionary ease-of-use.

Goodrich, Kenneth H.↗

NASA NTRS2015

Certification Considerations for Adaptive Systems

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Bhattacharyya, Siddhartha↗

NASA NTRSDate not supplied

Lunar Base Construction Overview

Previous lunar missions and campaigns have been restricted to using robotic landers and lunar orbiting satellites as well as sortie type of operations using astronaut crews (NASA Apollo program). Now, the next phase of lunar exploration has begun under NASA’s Artemis program and there has been an international response where other nations such as China, Russia, India, Canada, Japan and the European Union of nations, have all expressed interest in either collaborating or competing with NASA on the Moon. This next phase has an over arching goal of achieving a permanent human presence on the Moon via sustainable methods. A lunar base with human occupancy will require infrastructure to provide shelter, utilities, landing/launch pads, roads, communications, power and all the other necessities to sustain human life and protect equipment. Since human biology is not well suited for surviving in the lunar environment, there will be many forms of automated equipment, autonomy and robotic helpers that will minimize the amount of Extra-Vehicular Activity (EVA) required by the crew. This will mean that the radiation dosage received by the crew will stay within acceptable and safe career doses. Radiation shielding via the use of regolith can also mitigate radiation dangers. The required infrastructure must be constructed, but the mass and logistics of bringing all the construction materials from Earth are prohibitive, which makes the necessary construction difficult to achieve. In-Situ Resource Utilization (ISRU) aims to solve this challenge by sourcing construction materials locally or “in-situ”. This means that their transportation can be completely eliminated, resulting in large cost savings by avoiding the launch out of Earth’s deep gravity well and subsequent trans lunar injection, lunar orbit capture and landing. This paper will give an overview of the required construction tasks and related equipment that will be required to robotically build a lunar base using in-situ resources. It will also organize these tasks into logical groupings so that technology development and implementation can be pursued within a framework that can be referenced by all involved.

Lunar Base↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

NASA NTRSDate not supplied

AmesDT: Digital Twin and Autonomy Validation Environment

A simulation of NASA Ames Research Center was developed to provide a common testbed for multiple areas of research within the Intelligent Systems Division, primarily related to verification and validation of autonomous technologies, machine learning, and digital twin systems. AmesSim corresponds a physical rover that is capable of navigation in the real-world environment; in this way, the same experiments can be run in both settings, with the same software and hardware stacks in the loop. The simulation is built in Unreal Engine 4 and uses the AirSim plugin for API convenience. Several custom modifications allow deterministic, faster-than-realtime execution, which enables consistent testing of on-line algorithms and large-scale data collection. This paper describes the architecture and capabilities of the simulation and discusses development challenge.

simulation↗

NASA NTRS2021

Strategies for the Design and Operation of Resilient Extraterrestrial Habitats

An Earth-independent permanent extraterrestrial habitat system must function as intended under continuous disruptive conditions, and with significantly limited Earth support and extended uncrewed periods. Designing for the demands that extreme environments such as wild temperature fluctuations, galactic cosmic rays, destructive dust, meteoroid impacts (direct or indirect), vibrations, and solar particle events, will place on long-term deep space habitats represents one of the greatest challenges in this endeavor. This context necessitates that we establish the know-how and technologies to build habitat systems that are resilient. Resilience is not simply robustness or redundancy: it is a system property that accounts for both anticipated and unanticipated disruptions via the design choices and maintenance processes and adapts to them in operation. We currently lack the frameworks and technologies needed to achieve a high level of resilience in a habitat system. The Resilient ExtraTerrestrial Habitats Institute (RETHi) has the mission of leveraging existing novel technologies to provide situational awareness and autonomy to enable the design of habitats that are able to adapt, absorb and rapidly recover from expected and unexpected disruptions. We are establishing both fully virtual and coupled physical-virtual simulation capabilities that will enable us to explore a wide range of potential deep space SmartHab configurations and operating modes.

Space habitats↗

NASA NTRS2021

Strategies for the Design and Operation of Resilient Extraterrestrial Habitats

An Earth-independent permanent extraterrestrial habitat system must function as intended under continuous disruptive conditions, and with significantly limited Earth support and extended uncrewed periods. Designing for the demands that extreme environments such as wild temperature fluctuations, galactic cosmic rays, destructive dust, meteoroid impacts (direct or indirect), vibrations, and solar particle events, will place on long-term deep space habitats represents one of the greatest challenges in this endeavor. This context necessitates that we establish the know-how and technologies to build habitat systems that are resilient. Resilience is not simply robustness or redundancy: it is a system property that accounts for both anticipated and unanticipated disruptions via the design choices and maintenance processes, and adapts to them in operation. We currently lack the frameworks and technologies needed to achieve a high level of resilience in a habitat system. The Resilient Extra Terrestrial Habitats Institute (RETHi) has the mission of leveraging existing novel technologies to provide situational awareness and autonomy to enable the design of habitats that are able to adapt, absorb and rapidly recover from expected and unexpected disruptions. We are establishing both fully virtual and coupled physical-virtual simulation capabilities that will enable us to explore a wide range of potential deep space Smart Hab configurations and operating modes.

Space habitats↗

NASA NTRS2002

The Personal Satellite Assistant: An Internal Spacecraft Autonomous Mobile Monitor

This paper presents an overview of the research and development effort at the NASA Ames Research Center to create an internal spacecraft autonomous mobile monitor capable of performing intra-vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the capabilities, mission roles, rationale, high-level functional requirements, and design challenges for an autonomous mobile monitor. The rapid prototyping design methodology used, in which five prototypes of increasing fidelity are designed, is described as well as the status of these prototypes, of which two are operational and being tested, and one is actively being designed. The physical test facilities used to perform ground testing are briefly described, including a micro-gravity test facility that permits a prototype to propel itself in 3 dimensions with 6 degrees-of-freedom as if it were in an micro-gravity environment. We also describe an overview of the autonomy framework and its components including the software simulators used in the development process. Sample mission test scenarios are also described. The paper concludes with a discussion of future and related work followed by the summary.

Dorais, Gregory A.↗

NASA NTRSDate not supplied

A Strategy for Advancing Earth Independent Medical Operations

Exploration medical operations to the Moon and Mars present unprecedented challenges for providing in-mission medical care. The greater distance from Earth is the primary hazard that drives the need for a medical operations paradigm shift from low earth orbit mission. Increasingly complex long duration and long distance missions will have resource constraints (ex: mass, power, volume, data), a paucity of resupply or evacuation opportunities, and disruptions in real-time communications. In order to advance a more autonomous medical approach, a multi-faceted strategy will need to optimize all aspects of human health and performance in space. This strategy will include: increasing onboard medical autonomy through the development of novel crew health and performance systems; decision support capabilities to augment astronauts’ abilities in preventing, diagnosing, and treating medical conditions; creating new procedures and training tools for skill maintenance and just-in-time training; and enabling rapid crew access to data from all on-board systems, leading to better-informed, real-time, autonomous decisions. Collectively, this approach can be referred to as “Earth Independent Medical Operations” (EIMO). The Exploration Medical Capability Element of NASA’s Human Research Program has undertaken a longitudinal planning process to consensus around EIMO. Technical interchange meetings will occur with key constituents in late 2022 and again in early 2023 to define EIMO in practical terms and identify key elements of an EIMO system, with greater conceptual articulation and dissemination planned for the second half of 2023. We will share insights into the strategy for internal and external consensus building around EIMO, with a particular focus on the approach to partner stakeholders within NASA as well as commercial agencies.

Jay Lemery↗

NASA NTRS2017

Safe Autonomous Flight Environment (SAFE50) for the Notional Last 50 ft of Operation of 55 lb Class of UAS

The most difficult phase of small Unmanned Aerial System (sUAS) deployment is autonomous operations below the notional 50 ft in urban landscapes. Understanding the feasibility of safely flying sUAS autonomously below 50 ft is a game changer for many civilian applications. This paper outlines three areas of research currently underway which address key challenges for flight in the urban landscape. These are: (1) Off-line and On-board wind estimation and accommodation; (2) Real-time trajectory planning via characterization of obstacles using a LIDAR; (3) On-board information fusion for real-time decision-making and safe trajectory generation.

Autonomy↗