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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Ground Operations Autonomous Control and Integrated Health Management

The Ground Operations Autonomous Control and Integrated Health Management plays a key role for future ground operations at NASA. The software that is integrated into this system is called G2 2011 Gensym. The purpose of this report is to describe the Ground Operations Autonomous Control and Integrated Health Management with the use of the G2 Gensym software and the G2 NASA toolkit for Integrated System Health Management (ISHM) which is a Computer Software Configuration Item (CSCI). The decision rationale for the use of the G2 platform is to develop a modular capability for ISHM and AC. Toolkit modules include knowledge bases that are generic and can be applied in any application domain module. That way, there's a maximization of reusability, maintainability, and systematic evolution, portability, and scalability. Engine modules are generic, while application modules represent the domain model of a specific application. Furthermore, the NASA toolkit, developed since 2006 (a set of modules), makes it possible to create application domain models quickly, using pre-defined objects that include sensors and components libraries for typical fluid, electrical, and mechanical systems.

Computer Programs↗
NASA NTRSDate not supplied

AssistTaxi: A Comprehensive Dataset for Taxiway Analysis and Autonomous Operations

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. This poster presents AssistTaxi, which is a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Additionally, the dataset serves as a valuable resource for validating and enhancing existing algorithms as well as facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique.

Data Collection↗
NASA NTRS2016

Autonomous Operations System: Development and Application

Autonomous control systems provides the ability of self-governance beyond the conventional control system. As the complexity of mechanical and electrical systems increases, there develops a natural drive for developing robust control systems to manage complicated operations. By closing the bridge between conventional automated systems to knowledge based self-awareness systems, nominal control of operations can evolve into relying on safe critical mitigation processes to support any off-nominal behavior. Current research and development efforts lead by the Autonomous Propellant Loading (APL) group at NASA Kennedy Space Center aims to improve cryogenic propellant transfer operations by developing an automated control and health monitoring system. As an integrated systems, the center aims to produce an Autonomous Operations System (AOS) capable of integrating health management operations with automated control to produce a fully autonomous system.

Autonomous Control Systems↗
NASA NTRS2015

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Allen, B. Danette↗
NASA NTRS2016

Autonomous Operations Mission Development Suite

This is a presentation related to the development of Autonomous Operations Systems at NASA Kennedy Space Center. It covers a high level description of the work of FY14, FY15, FY16 for the AES IGODU and APL projects.

Ground Support Equipment↗
NASA NTRS2011

Recent Developments in the Design, Capabilities and Autonomous Operations of a Lightweight Surface Manipulation System and Test-bed

The first generation of a versatile high performance device for performing payload handling and assembly operations on planetary surfaces, the Lightweight Surface Manipulation System (LSMS), has been designed and built. Over the course of its development, conventional crane type payload handling configurations and operations have been successfully demonstrated and the range of motion, types of operations and the versatility greatly expanded. This enhanced set of 1st generation LSMS hardware is now serving as a laboratory test-bed allowing the continuing development of end effectors, operational techniques and remotely controlled and automated operations. This paper describes the most recent LSMS and test-bed development activities, that have focused on two major efforts. The first effort was to complete a preliminary design of the 2nd generation LSMS that has the capability for limited mobility and can reposition itself between lander decks, mobility chassis, and fixed base locations. A major portion of this effort involved conducting a study to establish the feasibility of, and define, the specifications for a lightweight cable-drive waist joint. The second effort was to continue expanding the versatility and autonomy of large planetary surface manipulators using the 1st generation LSMS as a test-bed. This has been accomplished by increasing manipulator capabilities and efficiencies through both design changes and tool and end effector development. A software development effort has expanded the operational capabilities of the LSMS test-bed to include; autonomous operations based on stored paths, use of a vision system for target acquisition and tracking, and remote command and control over a communications bridge.

Dorsey, John T.↗
NASA NTRSDate not supplied

MBSE Execution of Scalable Autonomous Operations for a High Density Vertiplex

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) and NASA SE processes were executed via MBSE using MagicDraw. Since the adoption of MBSE and utilization of MagicDraw, the systems engineering team has made tremendous strides in each pillar of MBSE including, requirements, behavior, and structure. Scalable Autonomous Operations (SAO) was a stage in the development of the High Density Vertiplex focusing on the autonomous terminal operations of a vertiport with sUAS aircraft. MBSE served the systems engineering team to document and verify the physical architecture and capture a logical architecture of SAO for distribution to the AAM community. This paper will detail methodologies that were created to successfully execute NASA SE processes via MBSE in the SAO stage as well as highlight challenges and lessons learned.

Demetrios Katsaduros↗
NASA NTRS2012

Onboard Processing and Autonomous Operations on the IPEX Cubesat

IPEX is a 1u Cubesat sponsored by NASA Earth Science Technology Office (ESTO), the goals or which are: (1) Flight validate high performance flight computing, (2) Flight validate onboard instrument data processing product generation software, (3) flight validate autonomous operations for instrument processing, (4) enhance NASA outreach and university ties.

Hyperspectral Infrared Imager (HyspIRI)↗
NASA NTRSDate not supplied

Autonomous Operations: Expectations vs. Reality (at NASA)

- Future deep-space exploration drives need for autonomy - Communication time delay between Earth and deep-space system precludes Earth-based remote-control - Autonomy is: - Acting separately from others (Webster’s Dictionary) - Able to independently choose how to act to achieve goals - Autonomy is a relative term: Autonomous from whom? for what purpose? and when? - Autonomous Operations is: - Automatically controlled operation of a system that replaces human effort - Able to perform a pre-specified set of instructions on its own - Automation is a tool that enables and supports autonomy

Autonomous Operation↗
NASA NTRS2012

Autonomous Operations Planner: A Flexible Platform for Research in Flight-Deck Support for Airborne Self-Separation

The Autonomous Operations Planner (AOP), developed by NASA, is a flexible and powerful prototype of a flight-deck automation system to support self-separation of aircraft. The AOP incorporates a variety of algorithms to detect and resolve conflicts between the trajectories of its own aircraft and traffic aircraft while meeting route constraints such as required times of arrival and avoiding airspace hazards such as convective weather and restricted airspace. This integrated suite of algorithms provides flight crew support for strategic and tactical conflict resolutions and conflict-free trajectory planning while en route. The AOP has supported an extensive set of experiments covering various conditions and variations on the self-separation concept, yielding insight into the system s design and resolving various challenges encountered in the exploration of the concept. The design of the AOP will enable it to continue to evolve and support experimentation as the self-separation concept is refined.

Karr, David A.↗
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 NTRSDate not supplied

The Anatomy of Software Changes and Bugs in Autonomous Operating System

Cyberphysical systems with autonomous functions are complex pieces of software, consisting of many components, some of which implement autonomous functionality and some may use AI or machine learning algorithms. Software bugs in an autonomous system are of particular concern, as they can have catastrophic consequences. However, detailed studies based on empirical data are rare and therefore these bugs are not well understood. This paper aims to contribute towards filling that gap by investigating the software changes and bugs in Autonomy Operating System (AOS) for Unmanned Aircraft Systems (UAS), which consist of 26 components containing about 103,000 lines of code and having a total of 772 bugfixes. Based on the data extracted from the code repository and semi-structured interviews with the developers of AOS, we explore the differences among autonomous software components, components developed using Model-based Software Engineering, and reuse with respect to change proneness, fault proneness, distribution of bugfixes among AOS components and files of these components, and characteristics of bugs of different AOS components. Our results show that the autonomous components were significantly more change prone (measured in number of commits and code churn) and fault prone (measured in bugfixes per KLoC) than non-autonomous components. The distribution of the locations of bugfixes was skewed, both at component and file level (i.e., a small number of components / files contained the majority of bugs). These evidence-based findings provide important insights to researchers and practitioners alike and can be used to efficiently improve the quality and reliability of autonomous systems.

Katerina Goseva-Popstojanova↗
NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) subproject aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-TheLoop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and MultiAircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

Advanced Air Mobility↗
NASA NTRS2018

The Europa Lander Mission: A Space Exploration Challenge for Autonomous Operations

NASA has proposed a Europa Lander Mission, with a notional launch date in the 2024-2025 timeframe. Key features of the mission are: Take 5 samples from 10 cm under the Europa surface; Mission duration is expected to be 20 (Earth) days; Data will be telemetered data back to Earth via a dedicated Carrier Relay Orbiter (CRO) spacecraft. Some information about the Europa surface is available from Cassini, indicating the presence of mountains, ridges, and other complex features, and simulations of planet-wide lighting can be performed, but this information is available only at 6m per pixel resolution (Galileo imagery). While surface temperatures are exceedingly cold (average of 114 degrees Kelvin, or minus 160 degrees Centigrade at the equator), this need not translate to solid (and hard) ice. The possible presence of small grain features (snow-like), penitentes (inverse-icicles), plumes, and other complex terrain features, will complicate operations. The time delay for such a mission is 30-60 minutes. The CRO is in view of the Lander for roughly 8 hours, and is in view of Earth for roughly 10 hours, meaning significant autonomy will be needed. A compelling case can be made for the use of aggressive autonomous operations of the *entire* mission. In this talk we will describe the Europa mission and its objectives, as well as similar Icy Worlds missions of the future. We will then describe the autonomy challenges of such a mission, using examples of similar missions and specific autonomy technologies that have been used in the past to address these challenges. We will make the case that despite some technologies that may be suitable, Europa lander presents a unique, and unaddressed, challenge for autonomy.

Plan Execution↗
NASA NTRSDate not supplied

Airspace Performance Observations of Scalable Autonomous Operations in a High Density Vertiplex Simulation

The National Aeronautics and Space Administration’s (NASA’s) High Density Vertiplex (HDV) sub- project aims to develop and demonstrate progressive automation technologies that contribute to the Advanced Air Mobility (AAM) concept. Using Human-and-Hardware-In-The- Loop (HHITL) techniques, HDV demonstrates initial vertiport automation services at vertiports with increased air traffic volume in both simulated and live test environments. In 2023, the Scalable Autonomous Operations (SAO) simulation was conducted in which prototype vertiport, airspace, and ground control station technologies were assessed on technical performance. During the SAO simulation, an observational study captured an initial impression of the HDV airspace performance, potential disruptions to the airspace, and highlighted some capability and procedural gaps. Observations took place in two parts. In the first part, five scenario use cases (Nominal, Missed Approach, Speed Change, Divert, and Multi- Aircraft Divert) were conducted with three human operator roles (Vertiport Manager, Fleet Manager, and Ground Control Station Operator). Researchers collected metrics on throughput, closest point of approach, and airborne delay. In the second part of the study, the Missed Approach scenario was observed under three traffic density levels (20, 40, and 60 operations per hour) to challenge the automation to correctly identify slots in the vertiport arrival schedule. The results showed that the automation successfully found a slot for the Missed Approach vehicle in the 20 operations per hour condition, after some delay it found one in the 40 condition, and it did not find one in the 60 condition. The observations of technical and human performance throughout the five scenario use cases and the Missed Approach case study indicated that for HDV to increase traffic density and maintain or increase throughput, airspace monitoring services should be able to detect and resolve conflicts between aircraft. Furthermore, the roles and responsibilities of human operators need additional definition when it comes to responding to vehicle conflicts.

advanced air mobility↗
NASA NTRS2016

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.↗
NASA NTRS2014

Advancing Autonomous Operations for Deep Space Vehicles

Starting in Jan 2012, the Advanced Exploration Systems (AES) Autonomous Mission Operations (AMO) Project began to investigate the ability to create and execute "single button" crew initiated autonomous activities [1]. NASA Marshall Space Flight Center (MSFC) designed and built a fluid transfer hardware test-bed to use as a sub-system target for the investigations of intelligent procedures that would command and control a fluid transfer test-bed, would perform self-monitoring during fluid transfers, detect anomalies and faults, isolate the fault and recover the procedures function that was being executed, all without operator intervention. In addition to the development of intelligent procedures, the team is also exploring various methods for autonomous activity execution where a planned timeline of activities are executed autonomously and also the initial analysis of crew procedure development. This paper will detail the development of intelligent procedures for the NASA MSFC Autonomous Fluid Transfer System (AFTS) as well as the autonomous plan execution capabilities being investigated. Manned deep space missions, with extreme communication delays with Earth based assets, presents significant challenges for what the on-board procedure content will encompass as well as the planned execution of the procedures.

Haddock, Angie T.↗