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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

AMO-EXPRESS-2.5: Crew Autonomy Onboard the International Space Station

NASA is committed to landing American astronauts, including the first woman and the next man, on the Moon by 2024. Currently, the crew cannot take on all functions performed by the ground today, so the future crews will need more automation to reduce the crew workload for future missions. Of significant importance for these missions is the balance between crew autonomy and vehicle automation. The Advanced Exploration Systems (AES) Autonomous Systems and Operations (ASO) Project has been investigating the ability to evaluate crew self-scheduling and activity monitoring for future space missions. The ASO project designed the Autonomous Mission and Operations- EXpedite the PRocessing of Experiments to Space Station Rack-2.5 (AMO-EXPRESS-2.5) payload to evaluate crew self-scheduling and activity monitoring. The AMO-EXPRESS-2.5 builds on the previous AMO-EXPRESS and AMO-EXPRESS-2.0 demonstrations on ISS. The AMO-EXPRESS-2.5 demonstration goals are to prove crew self-scheduling by planning through diagnosing systems expertise, failure detection, procedure recommendation and situational awareness. This paper will describe the development, test and execution results of the AMO-EXPRESS-2.5 demonstration, and will also outline the future planned development and operational efforts to enable autonomy for future deep space manned missions.

Brooke C. Allen↗
NASA NTRS2021

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE)

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗
NASA NTRS1988

Systems autonomy

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

Lum, Henry, Jr.↗
NASA NTRS2021

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Mission

NASA has partnered with Advanced Space to develop and build the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission which will serve as a pathfinder for Near Rectilinear Halo Orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) will be the intended orbit for the NASA’s Artemis Gateway lunar orbital platform. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for the Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The baseline for CAPSTONE is to fly a 12U cubesat developed, integrated, and tested by Tyvak Nanosatellite Systems carrying a payload communications system capable of cross-link ranging with the Lunar Reconnaissance Orbiter (LRO), a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA Launch Services Program, will be provided by a Rocket Lab launch vehicle utilizing their new Proton upper stage to deploy the CAPSTONE spacecraft into the lunar orbit. The CAPSTONE mission is targeting a launch no earlier than September 23, 2021. Upon launch, the spacecraft will traverse a highly efficient transfer taking approximately three months to enter a primary demonstration phase in an NRHO for six months followed by a twelve month technology enhancement operations phase. The CAPSTONE Project is lead by Advanced Space, LLC of Boulder Colorado. Spacecraft development and mission operations will be conducted by Tyvak Nanosatellite Systems of Irvine, California. Noted objectives for the CAPSTONE mission will be to demonstrate the accessibility of NHROs, validate key operational concepts in the NHRO environment, lay a foundation for commercial support of future lunar operations and accelerate the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology Program (SSTP), which is one of several programs in NASA’s Space Technology Mission Directorate. SSTP is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The launch for the CAPSTONE Mission is provided by Human Exploration & Operations Missions Directorate Advanced Exploration Systems Division. Coordination and Acquisition of the Launch is managed by NASA’s Launch Services Program. The CAPSTONE Mission and project status will be presented.

CAPSTONE↗
NASA NTRS2004

Development and Evaluation of an Airborne Separation Assurance System for Autonomous Aircraft Operations

NASA Langley Research Center is developing an Autonomous Operations Planner (AOP) that functions as an Airborne Separation Assurance System for autonomous flight operations. This development effort supports NASA s Distributed Air-Ground Traffic Management (DAG-TM) operational concept, designed to significantly increase capacity of the national airspace system, while maintaining safety. Autonomous aircraft pilots use the AOP to maintain traffic separation from other autonomous aircraft and managed aircraft flying under today's Instrument Flight Rules, while maintaining traffic flow management constraints assigned by Air Traffic Service Providers. AOP is designed to facilitate eventual implementation through careful modeling of its operational environment, interfaces with other aircraft systems and data links, and conformance with established flight deck conventions and human factors guidelines. AOP uses currently available or anticipated data exchanged over modeled Arinc 429 data buses and an Automatic Dependent Surveillance Broadcast 1090 MHz link. It provides pilots with conflict detection, prevention, and resolution functions and works with the Flight Management System to maintain assigned traffic flow management constraints. The AOP design has been enhanced over the course of several experiments conducted at NASA Langley and is being prepared for an upcoming Joint Air/Ground Simulation with NASA Ames Research Center.

Barhydt, Richard↗
NASA NTRS1989

Autonomous exploration system: Techniques for interpretation of multispectral data

An on-board autonomous exploration system that fuses data from multiple sensors, and makes decisions based on scientific goals is being developed using a series of artificial neural networks. Emphasis is placed on classifying minerals into broad geological categories by analyzing multispectral data from an imaging spectrometer. Artificial neural network architectures are being investigated for pattern matching and feature detection, information extraction, and decision making. As a first step, a stereogrammetry net extracts distance data from two gray scale stereo images. For each distance plane, the output is the probable mineral composition of the region, and a list of spectral features such as peaks, valleys, or plateaus, showing the characteristics of energy absorption and reflection. The classifier net is constructed using a grandmother cell architecture: an input layer of spectral data, an intermediate processor, and an output value. The feature detector is a three-layer feed-forward network that was developed to map input spectra to four geological classes, and will later be expanded to encompass more classes. Results from the classifier and feature detector nets will help to determine the relative importance of the region being examined with regard to current scientific goals of the system. This information is fed into a decision making neural net along with data from other sensors to decide on a plan of activity. A plan may be to examine the region at higher resolution, move closer, employ other sensors, or record an image and transmit it back to Earth.

Yates, Gigi↗
NASA NTRS2004

Autonomous navigation system based on GPS and magnetometer data

This invention is drawn to an autonomous navigation system using Global Positioning System (GPS) and magnetometers for low Earth orbit satellites. As a magnetometer is reliable and always provides information on spacecraft attitude, rate, and orbit, the magnetometer-GPS configuration solves GPS initialization problem, decreasing the convergence time for navigation estimate and improving the overall accuracy. Eventually the magnetometer-GPS configuration enables the system to avoid costly and inherently less reliable gyro for rate estimation. Being autonomous, this invention would provide for black-box spacecraft navigation, producing attitude, orbit, and rate estimates without any ground input with high accuracy and reliability.

Julie, Thienel K.↗
NASA NTRS1990

Physiology of motion sickness symptoms

Motion sickness research is reviewed with the emphasis placed on theories developed to explain its symptomatology. A general review of central nervous system, autonomic nervous system, and neuroendocrine system involvement in the syndrome. Particular attention is given to signs, symptoms, and physiological correlates, methodological issues, and directions for future research based on a dynamic interactive systems model.

Harm, Deborah L.↗
NASA NTRS2005

Experiences with a Requirements-Based Programming Approach to the Development of a NASA Autonomous Ground Control System

Requirements-to-Design-to-Code (R2D2C) is an approach to the engineering of computer-based systems that embodies the idea of requirements-based programming in system development. It goes further; however, in that the approach offers not only an underlying formalism, but full formal development from requirements capture through to the automatic generation of provably-correct code. As such, the approach has direct application to the development of systems requiring autonomic properties. We describe a prototype tool to support the method, and illustrate its applicability to the development of LOGOS, a NASA autonomous ground control system, which exhibits autonomic behavior. Finally, we briefly discuss other areas where the approach and prototype tool are being considered for application.

Hinchey, Michael G.↗
NASA NTRS1991

Intelligent vision system for autonomous vehicle operations

A complex optical system consisting of a 4f optical correlator with programmatic filters under the control of a digital on-board computer that operates at video rates for filter generation, storage, and management is described.

Scholl, Marija S.↗
NASA NTRS2004

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗
NASA NTRS2019

Integrated System for Autonomous and Adaptive Caretaking (ISAAC)

This presentation is an overview of the Integrated System for Autonomous and Adaptive Caretaking (ISAAC) project, funded by the STMD Game Changing Development program to develop autonomous caretaking capabilities for future human exploration spacecraft, especially during uncrewed phases.

Deans, Matt↗
NASA NTRSDate not supplied

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE): Pathfinder for Artemis Gateway

The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission was developed by NASA in collaboration with Advanced Space, LLC of Westminster, Colorado. This technology demonstration mission serves as a pathfinder for near rectilinear halo orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) is the intended orbit for NASA’s Artemis Gateway, a small, human-tended space station planned for lunar orbit. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and stationkeeping requirements for Gateway’s Power and Propulsion Element. Therefore, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. This presentation accompanies the paper of the same title.

Elwood F Agasid↗
NASA NTRS1983

Algorithm development for a spacecraft autonomous power system

Two algorithms were developed to demonstrate the implementation of autonomous functions in an existing spacecraft power system. The functions selected for autonomous operation include a typical performance monitoring function, battery state of charge, and a fault detection and response function represented by a battery state of charge below a preselected limit. The constraints imposed by the existing power system configuration are the available data in the telemetry stream and the existing commands and command structure. The areas requiring future development are the degree of battery characterization, the effects of hardware/software faults, and the verification of faults.

Bridgeforth, A. O.↗
NASA NTRS2007

Emerging Techniques for Vicarious Calibration of Visible Through Short Wave Infrared Remote Sensing Systems

Autonomous Visible to SWIR ground-based vicarious Cal/Val will be an essential Cal/Val component with such a large number of systems. Radiometrically calibrated spectroradiometers can improve confidence in current ground truth data through validation of radiometric modeling and validation or replacement of traditional sun photometer measurement. They also should enable significant reduction in deployed equipment such as equipment used in traditional sun photometer approaches. Simple, field-portable, white-light LED calibration source shows promise for visible range (420-750 nm). Prototype demonstrated <0.5% drift over 10-40 C temperature range. Additional complexity (more LEDs) will be necessary for extending spectral range into the NIR and SWIR. LED long lifetimes should produce at least several hundreds of hours or more of stability, minimizing the need for expensive calibrations and supporting long-duration field campaigns.

Ryan, Robert E.↗
NASA NTRS1987

Autonomous intelligent systems

NASA's Office of Aeronautics and Space Technology (OAST) has instituted a 'Systems Autonomy' technology development program aimed at the creation of increasingly sophisticated AI systems. Expert system production will in due course be followed by fully autonomous AI systems capable of the complex mission objectives of the Space Station, as well as of lunar and Martian exploration. AI systems must demonstrate the degree of their autonomy in a real-time operational environment, and then undergo mating to robotics technologies. OAST's Systems Autonomy Program and Robotics Program are discussed with a view to anticipated difficulties in their integration.

Lum, H.↗
NASA NTRS2003

An Autonomous Control System for an Intra-Vehicular Spacecraft Mobile Monitor Prototype

This paper presents an overview of an ongoing research and development effort at the NASA Ames Research Center to create an autonomous control system for an internal spacecraft autonomous mobile monitor. It primary functions are to provide crew support and perform intra- vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the mission roles and high-level functional requirements for an autonomous mobile monitor. The mobile monitor prototypes, of which two are operational and one is actively being designed, physical test facilities used to perform ground testing, including a 3D micro-gravity test facility, and simulators are briefly described. We provide an overview of the autonomy framework and describe each of its components, including those used for automated planning, goal-oriented task execution, diagnosis, and fault recovery. A sample mission test scenario is also described.

Dorais, Gregory A.↗