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NASA NTRS2019

Quantum Technologies for UAS (QTech)

Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.

Quantum Computing↗
NASA NTRS2018

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗
NASA NTRS2017

Beyond Point Design: General Pattern to Specific Implementations

Elsewhere we have discussed a number of problems typical of highly automated systems and proposed tenets for addressing these problems based on Human-Autonomy Teaming (HAT)[1]. We have examined these principles in the context of aviation [2,3]. Here we discuss the generality of these tenets by examining how they might be applied to photography and automotive navigation. While these domains are very different, we find application of our HAT tenets provides a number of opportunities for improving interaction between human operators and automation. We then illustrate how the generalities found across aviation, photography and navigation can be captured in a design pattern.

Lachter, Joel Benjamin↗
NASA NTRS2017

The Underpinnings of Workload in Unmanned Vehicle Systems

This paper identifies and characterizes factors that contribute to operator workload in unmanned vehicle systems. Our objective is to provide a basis for developing models of workload for use in design and operation of complex human-machine systems. In 1986, Hart developed a foundational conceptual model of workload, which formed the basis for arguably the most widely used workload measurement technique—the NASA Task Load Index. Since that time, however, there have been many advances in models and factor identification as well as workload control measures. Additionally, there is a need to further inventory and describe factors that contribute to human workload in light of technological advances, including automation and autonomy. Thus, we propose a conceptual framework for the workload construct and present a taxonomy of factors that can contribute to operator workload. These factors, referred to as workload drivers, are associated with a variety of system elements including the environment, task, equipment and operator. In addition, we discuss how workload moderators, such as automation and interface design, can be manipulated in order to influence operator workload. We contend that workload drivers, workload moderators, and the interactions among drivers and moderators all need to be accounted for when building complex, human-machine systems.

Hooey, Becky L.↗
NASA NTRS2019

Standardizing Microprocessor and GPU Radiation Test Approaches

Microprocessor, Graphics Processing Units (GPUs) and DDRx memory devices have emerged as promising next-generation technologies that enables both high performance processing and acceleration of complex algorithms for the latest challenges in human spaceflight, autonomous vehicles and artificial intelligence (AI). The feature sets of these devices offer exponential increases to throughput, calculation capability and system autonomy when compared to legacy flight systems. NASA's Electronic Part and Packaging (NEPP) Program has conducted an investigation into the radiation susceptibility of leading edge devices and process technologies by establishing standardized test approaches. Unlike most discrete devices, these require state of the art test systems to induce specific hardware activity similar to application software, thus allowing the characterization of failure modes within the system. To best characterize the tested part, NEPP eliminates variables that may impact device performance under radiation. Simplification of remaining system-level variables leads to an improved understanding of complex computational devices and their intended applications. The failure modes and error signatures that are recorded during testing are used to determine radiation sensitivity of the semiconductor process and the microcode architecture of the design. This presentation will discuss the test methodology that NASA Electronic Parts and Packaging (NEPP) is working to establish for its microprocessor, GPU and DDRx memory test programs to provide guidance on these devices and their underlying technology, in regards to their potential usage in future space flight systems.

GPU↗
NASA NTRS2019

Astrobiology Survey of a Lava Cave at Lava Beds National Monument by a Rover Carrying a Remote Sensing Instrument Payload

We report here on a survey of a lava tube cave by a rover that is instrumented for astrobiology missions. The NASA Ames testbed rover, CaveR, was deployed in Valentine Cave in Lava Beds National Monument (N. CA, USA) during August of 2018. The rover carried an instrument package consisting of Near Infrared and Visible Spectrometer System (NIRVSS) a point spectrometer operating in 1590-3400 nm range, sensitive to H2O and -OH bearing minerals, pyroxenes, and carbonates (Roush, et al 2018); the bore sighted Drill Operations Camera (DOC), a monochrome imager illuminated by LEDs at 410, 540, 640, 740, 905 and 940 nm; a Realsense ™ depth sensor system for 3D model generation; and a high resolution DSLR stereo camera. The payload was mounted on a tiltable instrument platform attached to the left side of the rover. The rover was driven manually in the cave by field operators, following instructions from a remote science operations team, and simulating a mission concept with science-guided autonomy. A simulated mission took place for 3 days with a team of 3 scientists selecting targets and interpreting data from the payload. To begin the mission, the rover drove along one wall of the cave imaging continuously with the Realsense in 20 m cave segments, three total. At the start of each day, the images from a 20m segment and a panorama stitched from them were provided to the science team to examine. The science team used these data to prioritize specific points along the cave wall for the collection of NIRVSS, DOC, and DSLR data. The objective of the data collection was to identify and study putative biological and mineralogical features in the cave. The data were delivered in xGDS, a customized mapping, planning, and data base management software developed at NASA Ames (Lee, et al 2013). Once the targets for further observations were selected, a plan for collecting the observations (positions in the cave and pointing for each requested observation) was constructed using xGDS and delivered to a rover team to execute the science data collection plan. Acquired data were delivered back to the science team for analysis. Preliminary results from the experiment illustrate the utility of the system (rover plus payload) to study the cave geology and mineralogy and its potential for identifying biomineral features.

Wong, Uland↗
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 NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗
NASA NTRS2019

NASA Electrified Aircraft Propulsion Efforts

NASA's broad investments in Electrified Aircraft Propulsion (EAP) are reviewed in this paper. NASA investments are guided by an assessment of potential market impacts, technical key performance parameters, and technology readiness attained through a combination of studies, enabling fundamental research, and flight research. NASA has determined that the impact of EAP varies by market and NASA is considering three markets: national/international, on-demand mobility, and short haul regional air transport. Flight research is underway to demonstrate integrated solutions and inform standards and certification processes. This paper focuses on the vehicle related activities, however there are related NASA activities in air space management and vehicle autonomy activities as well as a breakthrough technology project called the Convergent Aeronautics Solutions Project. A key finding is that sufficient technical advances in key areas have been made which indicate EAP is a viable technology for aircraft. Significant progress has been made to reduce EAP adoption barriers and further work is needed to transition the technology to a commercial product and improve the technology so it is applicable to large transonic aircraft. This paper will review the activities of the Hybrid Gas Electric Subproject of the Advanced Air Transport Technology Project, the Revolutionary Vertical Lift Technology Project, and the X-57 Flight Demonstration Project, and discuss the potential EAP benefits for commercial and military applications.

Jansen, Ralph H.↗
NASA NTRS2019

Lunar Navigation Beacon Network Using Global Navigation Satellite System Receivers

With the increasing traffic in the lunar regime as part of NASA efforts to return humans to the moon. In order to support these missions, new capabilities are needed to support autonomous navigation and inter-asset communication. Additionally, with maturation and flight demonstration of increasingly capable small satellites, there is an opportunity to embed technology into a small spacecraft as part of companion missions. This paper addresses one such architecture, taking advantage of a lunar lander vehicle to host a companion spacecraft to build out lunar navigation and communication capability. The backbone of this spacecraft is the Navigator GPS receiver. This hardware has continually broken records on high altitude GPS coverage and has the potential to support autonomous navigation at lunar distances. This research proposes a large cubesat built around this technology and catching a ride to the moon via a lander mission. The concept of operations includes the spacecraft deploying prior to the lunar sphere of influence and maneuvering to enter into a lunar orbit. With the Navigator receiver, this spacecraft is capable of a large amount of autonomy, with a limited need for ground-based orbit determination. This spacecraft will fly alongside the lander, acting as a navigation reference during cruise, descent, and post-landing for mission validation. To assess this mission scenario, three aspects are covered in detail herein: the feasibility and mission requirements for entering into a lunar orbit given deployment along a lander surface-bound trajectory, the performance capability of the receiver along this transfer trajectory and in lunar orbit, and the ability to support navigation of the lander itself. These three areas are discussed in detail, providing results that support feasibility of the mission and determination of initial requirements.

Anzalone, Evan J.↗
NASA NTRS2019

Autonomous Operating System (AOS)

The Autonomy Operating System (AOS) is a software system that enables core capabilities for the autonomous operations for an unmanned aircraft. It is based on the NASA cFS system and provides a higher-level layer of infrastructure and applications for the execution of flight plans, natural-language communication with Air Traffic Control, Diagnostics, Prognostics, and contingency planning.

Lowry, Michael R.↗
NASA NTRS2014

Advanced Inspection System: Integrating Robotic Configurations & Controls

The Advanced Inspection System (AIS) promotes the ability to perform field inspections and repairs remotely by operator command. The robotic system is required to be a fully autonomous operation, managed by computer execution of scripts with limited user control. AIS is a complex yet intriguing challenge in which various goals must be reached to achieve complete autonomy. The first steps to building such a system require human computer interactions and computer simulations for testing and verification. Such applications include the use of a wireless video game controller via Bluetooth Technology and the use of Leap Motion, a gesture based motion controller which can be used to manipulate robotic arm movements. Utilizing the Robotic Operating System (ROS) environment, these applications, in accordance to developing a 3D simulation of the system, will provide a foundational test bed for AIS development.

Wlodarczyk, Stephan J.↗
NASA NTRS2016

Onboard Data Analysis for the Planetary Instrument for X-Ray Lithography

Imaging spectrometers are invaluable instruments for robotic science exploration, enabling quantitative maps of physical and chemical properties at high spatial resolution. This is particularly valuable in remote missions to other planetary bodies like Mars. The PIXL instrument on the Mars 2020 rover will deploy an arm-mounted X-Ray fluorescence spectrometer to map chemical composition at sub-millimeter scales. Its high resolution places dramatic new demands on instrument placement accuracy and measurement time. We address these challenges using novel on board data analysis strategies inspired by FRC science autonomy research.

Thompson, David R.↗
NASA NTRS2019

Cognitive Communications for NASA Space Systems

The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset scheduling. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗
NASA NTRS2016

Progress on Modular Unmanned Aircraft Technology

Modular unmanned aerial systems (UAS) are a new development in UAS architecture that holds promise for reusable, reconfigurable hosts for science and autonomy payloads. Modularity of airframe subcomponents lowers costs, facilitates rapid field repair, permits holistic optimization, and enables mass-customization of bespoke platforms customizing the aircraft around a given payload or payloads. Without modular UAS, sensors and instruments often must be designed to fit in a non-modifiable airframe. This talk will present how the nexus of modularity, rapid prototyping and design reuse opens up new tradeoffs, and discuss the envisioned benefits, price paid, and enhanced missions made possible by this new approach to aircraft development.

Dahlgren, Robert P.↗
NASA NTRS2020

NASA’s Human Landing System: The Strategy for the 2024 Mission and Future Sustainability

In response to the 2018 White House Space Policy Directive- sustainable lunar exploration, and to the Vice President’s March 2019 direction to do so by 2024, NASA is working to establish humanity's presence on and around the Moon by: 1) sending payloads to its surface, 2) assembling the Gateway outpost in orbit and 3) demonstrating the first human lunar landings since 1972. NASA’s Artemis program is implementing a multi-faceted and coordinated agency-wide approach with a focus on the lunar South Pole. The Artemis missions will demonstrate new technologies, capabilities and business approaches needed for future exploration, including Mars. Assessing options to accelerate development of required systems, NASA is utilizing public-private engagements through the Human Exploration and Operations (HEO) Mission Directorate’s NextSTEP Broad Agency Announcements. The design, development and demonstration of the Human Landing System (HLS) is expected to be led by commercial partners. Utilizing efforts across mission directorates, the Artemis effort will benefit from programs from the Science Mission Directorate (SMD) and Space Technology Mission Directorate (STMD). SMD’s Commercial Lunar Payload Services (CLPS) initiative will procure commercial robotic lunar delivery services and the development of science instruments and technology demonstration payloads. The Space Technology Mission Directorate (STMD) portfolio of technology advancements relative to HLS include lunar lander components and technologies for pointing, navigation and tracking, fuel storage and transfer, autonomy and mobility, communications, propulsion and power. In addition to describing the objectives and requirements of the 2024 Artemis mission, this paper will present NASA’s approach to accessing the lunar surface with an affordable human-rated landing system, current status and the role o a sustainable lunar presence.

Chavers, Greg↗
NASA NTRS2019

Communication Bandwidth Considerations for Exploration Medical Care During Space Missions

Destinations beyond low Earth orbit, especially Mars, have several important constraints, including limited resupply, limited to no possibility of medical evacuation, and delayed communication with ground support teams. Therefore, medical care is driven towards greater autonomy and necessitates a medical system that supports this paradigm, including the potential for high medical data transfer rates in order to share medical information and coordinate care with the ground in an intermittent fashion as communication allows. The medical data transfer needs for a Martian exploration mission were estimated by defining two medical scenarios that would require high data rate communications between the spacecraft and Earth. One medical scenario involves a case of hydronephrosis (outflow obstruction of the kidney) that evolves into pyelonephritis (kidney infection), then urosepsis (systemic infection originating from the kidney), due to obstruction by a kidney stone. A second medical scenario involved the death of a crewmember’s child back on Earth that requires behavioral health care. For each of these scenarios, a data communications timeline was created following the medical care described by the scenario. From these timelines, total medical data transfers and burst transmission rates were estimated. Total data transferred from the vehicle-to-ground were estimated to be 94 gigabytes (GB) and 835 GB for the hydronephrosis and behavioral health scenarios, respectively. Data burst rates were estimated to be 7.7 megabytes per second (MB/s) and 15 MB/s for the hydronephrosis and behavioral health scenarios, respectively. Even though any crewed Mars mission should be capable of functioning autonomously, as long as the possibility of communication between Earth and Mars exists, Earth-based subject matter experts will be relied upon to augment mission medical capability. Therefore, setting an upper boundary limit for medical communication rates can help factor medical system needs into total vehicle communication requirements.

Krihak, Michael↗
NASA NTRS2019

Medical System Concept of Operations for Mars Exploration Mission-11: Exploration Medical Capability (ExMC) Element - Human Research Program

NASA’s exploration missions to Mars will have durations of 2-3 years and will take humans farther away from Earth than ever before. This will result in a paradigm shift for mission planning, spacecraft design, human systems integration, and in-flight medical care. Constraints on real-time communication, resupply, and medical evacuation are major architectural drivers. These constraints require medical system development to be tightly integrated with mission and vehicle design to provide crew autonomy and enable mission success. This concept of operations provides a common vision of medical care for developing a medical system for Mars exploration missions. It documents an overview of the stakeholder needs and goals of a medical system and provides examples of the types of activities the system will be used for during the mission. Development of the concept of operations considers mission variables such as distance from Earth, duration of mission, time to definitive medical care, communication protocols between crewmembers and ground support, personnel capabilities and skill sets, medical hardware and software, and medical data management. The information provided in this document informs the ExMC Systems Engineering effort to define the functions to be provided by the medical system. In addition, this concept of operations will inform the subsequent systems engineering process of developing technical requirements, system architectures, interfaces, and verification and validation approaches for the medical system. This document supports the closure of ExMC Gap Med01: We do not have a concept of operations for medical care during exploration missions, corresponding to the ExMC-managed human system risk: Risk of Adverse Health Outcomes & Decrements in Performance due to Inflight Medical Conditions. This document is applicable to the ExMC Element Systems Engineering process and may be used for collaboration within the Human Research Program.

Urbina, Michelle↗