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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

LANDO: Developing Autonomous Surface Operations for Planetary Surfaces

The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative (ECI) selected for funding by the Space Technology Mission Directorate (STMD) beginning in fiscal year 2022. Over the two-year project duration, the LANDO project will deliver a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that has been validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface, sized for a Commercial Lunar Payload Services (CLPS) mission). Specific to the LANDO project, the autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous surface construction (ASC) operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the On-orbit Servicing, Assembly and Manufacturing (OSAM) National Initiative. In this paper, an overview of the LANDO ECI project is presented.

autonomy↗
NASA NTRSDate not supplied

LANDO: Developing autonomous surface operations for planetary surfaces

The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative (ECI) selected for funding by the Space Technology Mission Directorate (STMD) beginning in fiscal year 2022. Over the two-year project duration, the LANDO project will deliver a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that has been validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface, sized for a Commercial Lunar Payload Services (CLPS) mission). Specific to the LANDO project, the autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous surface construction (ASC) operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the On-orbit Servicing, Assembly and Manufacturing (OSAM) National Initiative. In this paper, an overview of the LANDO ECI project is presented.

autonomy↗
NASA NTRS2017

Remotely Piloted Aircraft Systems Panel (RPASP) Working Paper: Autonomy and Automation

A significant level of debate and confusion has surrounded the meaning of the terms "autonomy" and "automation". Automation is a multi-dimensional concept, and we propose that RPAS automation should be described with reference to the specific system and task that has been automated, the context in which the automation functions, and other relevant dimensions. In this paper, we present a definition of "automation". We recommend that autonomy and autonomous operations are out of the scope of the RPAS panel. WG7 proposes to develop, in consultation with other workgroups, a taxonomy of "Levels of Automation" for RPAS.

Autonomy↗
NASA NTRS2018

Overview of MSFC Additive Electronics Capabilities

Focus: Marshall seeks to support the Agency in the development of next generation printed electronics technologies for living and working in space, with emphasis on enhanced electronics manufacturing processes and capabilities development on the ground and in-space. Near-Term: Human Habitation Elements and Life Support Systems - pursuing integrated flexible wearable air, water, vital monitoring solutions for next generation printed technologies; Complete startup printing technology demonstrations which prove basic processes and establish ISM (In-Space Manufacturing) infrastructure needed for future applications including metals based manufacturing. Medium Term: Target low-cost research and demonstration activities that support multi-material additive manufacturing, more sophisticated parts production, printed electronics and ISM; Maturation and flight demonstration of printed propulsion system components, with emphasis on infusion into small-spacecraft-based missions. Long-Term: Evolve systems capabilities to be supportive of destination (lunar or Mars) resources and requirements, increase autonomy in systems and utilize in-situ resources towards manufacturing; Support development of self-replicable systems and their infusion into future spacecraft and missions.

MacLeod, Todd C.↗
NASA NTRS2018

Leverage Points for System Health Management of Autonomous Systems

Systems Health Management (SHM) is one of three basic functionalities that constitute an autonomous capability of a system. The other two functionalities are Planning & Scheduling, and Task Execution. In an autonomous system, variable autonomy is often distinct from variable authority to sense, decide, and act. There are quantifiable Levels of Autonomy that can be achieved by tuning different portions of the Observe-Orient-Decide-Act loop to provide flexibility and control. This approach is tabulated for multiple domains such as spacecraft and aerial vehicles. Examining SHM through a Systems Thinking lens helps us understand its stocks and flows, loops, and delays. Systems thinking, and modeling, is a useful way to understand change and complexity of systems of many types. There are certain archetypes that underlie well-known autonomy architectures. And there often are leverage points - best places to intervene in a system - that can resolve or mitigate some fundamental challenges in the design and deployment of autonomous systems. I identify these levers and present the ones that have been successfully used in NASA missions.

Systems Thinking↗
NASA NTRS1988

High level intelligent control of telerobotics systems

A high level robot command language is proposed for the autonomous mode of an advanced telerobotics system and a predictive display mechanism for the teleoperational model. It is believed that any such system will involve some mixture of these two modes, since, although artificial intelligence can facilitate significant autonomy, a system that can resort to teleoperation will always have the advantage. The high level command language will allow humans to give the robot instructions in a very natural manner. The robot will then analyze these instructions to infer meaning so that is can translate the task into lower level executable primitives. If, however, the robot is unable to perform the task autonomously, it will switch to the teleoperational mode. The time delay between control movement and actual robot movement has always been a problem in teleoperations. The remote operator may not actually see (via a monitor) the results of high actions for several seconds. A computer generated predictive display system is proposed whereby the operator can see a real-time model of the robot's environment and the delayed video picture on the monitor at the same time.

Mckee, James↗
NASA NTRS1999

An Overview of Future NASA Missions, Concepts, and Technologies Related to Imaging of the World's Land Areas

In the near term NASA is entering into the peak activity period of the Earth Observing System (EOS). The EOS AM-1 /"Terra" spacecraft is nearing launch and operation to be followed soon by the New Millennium Program (NMP) Earth Observing (EO-1) mission. Other missions related to land imaging and studies include EOS PM-1 mission, the Earth System Sciences Program (ESSP) Vegetation Canopy Lidar (VCL) mission, the EOS/IceSat mission. These missions involve clear advances in technologies and observational capability including improvements in multispectral imaging and other observing strategies, for example, "formation flying". Plans are underway to define the next era of EOS missions, commonly called "EOS Follow-on" or EOS II. The programmatic planning includes concepts that represent advances over the present Landsat-7 mission that concomitantly recognize the advances being made in land imaging within the private sector. The National Polar Orbiting Environmental Satellite Series (NPOESS) Preparatory Project (NPP) is an effort that will help to transition EOS medium resolution (herein meaning spatial resolutions near 500 meters), multispectral measurement capabilities such as represented by the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) into the NPOESS operational series of satellites. Developments in Synthetic Aperture Radar (SAR) and passive microwave land observing capabilities are also proceeding. Beyond these efforts the Earth Science Enterprise Technology Strategy is embarking efforts to advance technologies in several basic areas: instruments, flight systems and operational capability, and information systems. In the case of instruments architectures will be examined that offer significant reductions in mass, volume, power and observational flexibility. For flight systems and operational capability, formation flying including calibration and data fusion, systems operation autonomy, and mechanical and electronic innovations that can reduce spacecraft and subsystem resource requirements. The efforts in information systems will include better approaches for linking multiple data sets, extracting and visualizing information, and improvements in collecting, compressing, transmitting, processing, distributing and archiving data from multiple platforms. Overall concepts such as sensor webs, constellations of observing systems, and rapid and tailored data availability and delivery to multiple users comprise and notions Earth Science Vision for the future.

Salomonson, Vincent V.↗
NASA NTRS2019

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗
NASA NTRS1997

Infusion of Autonomy Technology into Space Missions: DS1 Lessons Learned

The impact of infusing breakthrough autonomy technology into a flight project was a big surprise. Valuable technical and cultural lessons, many of general applicability when intorducing system-level autonomy, have been learned by infusing the Remote Agent (RA) into NASA's Deep Space 1 (DS1) Spacecraft.

Autonomy↗
NASA NTRS2010

Verification and Validation of Flight-Critical Systems

For the first time in many years, the NASA budget presented to congress calls for a focused effort on the verification and validation (V&V) of complex systems. This is mostly motivated by the results of the VVFCS (V&V of Flight-Critical Systems) study, which should materialize as a a concrete effort under the Aviation Safety program. This talk will present the results of the study, from requirements coming out of discussions with the FAA and the Joint Planning and Development Office (JPDO) to technical plan addressing the issue, and its proposed current and future V&V research agenda, which will be addressed by NASA Ames, Langley, and Dryden as well as external partners through NASA Research Announcements (NRA) calls. This agenda calls for pushing V&V earlier in the life cycle and take advantage of formal methods to increase safety and reduce cost of V&V. I will present the on-going research work (especially the four main technical areas: Safety Assurance, Distributed Systems, Authority and Autonomy, and Software-Intensive Systems), possible extensions, and how VVFCS plans on grounding the research in realistic examples, including an intended V&V test-bench based on an Integrated Modular Avionics (IMA) architecture and hosted by Dryden.

Brat, Guillaume↗
NASA NTRS2016

Traveler: Trustworthy Autonomy

This presentation discusses the FAA belief that this research may hold the key to enabling safe autonomous operation of vehicles.

complex systems↗
NASA NTRS2001

Mission data system and the future of autonomy at Jet Propulsion Laboratory

Planetary missions require significant levels of autonomy, due to the critical, one-time-only, nature of many mission objectives, and to the long delay times for human intervention. These missions also operate in highly uncertain environments, such as planetary atmospheres or surfaces. Mission Data Systems (MDS) is a project to construct a reusable software architecture for planetary missions, based on identifying the states of the mission.

MDS autonomy↗
NASA NTRS1996

The Planetary Data System Distributed Inventory System

The advent of the World Wide Web (Web) and the ability to easily put data repositories on-line has resulted in a proliferation of digital libraries. The heterogeneity of the underlying systems, the autonomy of the individual sites, and distributed nature of the technology has made both interoperability across the sites and the search for resources within a site major research topics. This article will describe a system that addresses both issues using standard Web protocols and meta-data labels to implement an inventory of on-line resources across a group of sites. The success of this system is strongly dependent on the existence of and adherence to a standards architecture that guides the management of meta-data within participating sites.

Hughes, J. Steven↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗