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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 217 records · Page 12
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NASA NTRS2006

The NASA Space Communications Data Networking Architecture

The NASA Space Communications Architecture Working Group (SCAWG) has recently been developing an integrated agency-wide space communications architecture in order to provide the necessary communication and navigation capabilities to support NASA's new Exploration and Science Programs. A critical element of the space communications architecture is the end-to-end Data Networking Architecture, which must provide a wide range of services required for missions ranging from planetary rovers to human spaceflight, and from sub-orbital space to deep space. Requirements for a higher degree of user autonomy and interoperability between a variety of elements must be accommodated within an architecture that necessarily features minimum operational complexity. The architecture must also be scalable and evolvable to meet mission needs for the next 25 years. This paper will describe the recommended NASA Data Networking Architecture, present some of the rationale for the recommendations, and will illustrate an application of the architecture to example NASA missions.

Israel, David J.↗
NASA NTRS2018

Artificial Intelligence - The Future of Space Communications

Presentation focus on the Cognitive Communications Project Overview. The project aims to develop cognitive communications technologies to increase mission science return and improve resource efficiencies. Another key aspect of the project is understanding the fundamental aspects of cognitive technology and developing artificial intelligence to advance the future of space communications. This involves the use of machine learning algorithms in the next generation architecture for space communications in the effort to increase efficiency, autonomy and increased performance of the space communication and navigations next generation architecture.

Briones, Janette C.↗
NASA NTRS2023

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA's Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA's primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA's Starling 1.0 satellites.

Caleb Ashmore Adams↗
NASA NTRS2005

Monitoring Floods with NASA's ST6 Autonomous Sciencecraft Experiment: Implications on Planetary Exploration

NASA's New Millennium Program (NMP) Autonomous Sciencecraft Experiment (ASE) [1-3] has been successfully demonstrated in Earth-orbit. NASA has identified the development of an autonomously operating spacecraft as a necessity for an expanded program of missions exploring the Solar System. The versatile ASE spacecraft command and control, image formation, and science processing software was uploaded to the Earth Observer 1 (EO-1) spacecraft in early 2004 and has been undergoing onboard testing since May 2004 for the near real-time detection of surface modification related to transient geological and hydrological processes such as volcanism [4], ice formation and retreat [5], and flooding [6]. Space autonomy technology developed as part of ASE creates the new capability to autonomously detect, assess, react to, and monitor dynamic events such as flooding. Part of the challenge has been the difficulty to observe flooding in real time at sufficient temporal resolutions; more importantly, it is the large spatial extent of most drainage networks coupled with the size of the data sets necessary to be downlinked from satellites that make it difficult to monitor flooding from space. Below is a description of the algorithms (referred to as ASE Flood water Classifiers) used in tandem with the Hyperion spectrometer instrument on EO-1 to identify flooding and some of the test results.

Ip, Felipe↗
NASA NTRS2016

WindBots: A Concept for Persistent In-Situ Science Explorers for Gas Giants

This report summarizes the study of a mission concept to Jupiter with one or multiple Wind Robots able to operate in the Jovian atmosphere, above and below the clouds - down to 10 bar, for long durations and using energy obtained from local sources. This concept would be a step towards persistent exploration of gas giants by robots performing in-situ atmospheric science, powered by locally harvested energy. The Wind Robots, referred in this report as WindBots (WBs), would ride the planetary winds and transform aeolian energy into kinetic energy of flight, and electrical energy for on-board equipment. Small shape adjustments modify the aerodynamic characteristics of their surfaces, allowing for changes in direction and a high movement autonomy. Specifically, we sought solutions to increase survivability to strong/turbulent winds, and mobility and autonomy compared to passive balloons.

WindBots↗
NASA NTRS2022

Starling Animation

NASA’s Starling mission is advancing the readiness of various technologies for cooperative groups of spacecraft – also known as distributed missions, clusters, or swarms. Starling will demonstrate technologies to enable multipoint science data collection by several small spacecraft flying in swarms. The six-month mission will use four CubeSats in low-Earth orbit to test four technologies that let spacecraft operate in a synchronized manner without resources from the ground. The technologies will advance the following capabilities. • Network Communication • Cluster Flight Control • Relative navigation • Distributed Spacecraft Autonomy The Starling mission will test whether the technologies work as expected, what their limitations are, and what developments are still needed for CubeSat swarms to be successful. This animation illustrates Starling mission operations, offering an overview of each technology being demonstrated.

Howard N Cannon↗
NASA NTRS1998

Rovers for Mars Polar Exploration

Mobility is a generic capability needed for Mars exploration. Requirements for mobility range from those to get observations of individual rocks all the way to getting high resolution observations of regional areas. Table 1 shows the required-range of mobility to achieve various tasks. The Pathfinder mission and field experiments simulating rover missions [1, 2, 3, 4, 5] provide guidance as to rover capabilities that can reasonably be expected in the next decade. Rover mobility can be accomplished in a variety of ways, the most common being wheels or tracks and legged-walkers. Wheeled vehicles can traverse over rocks smaller than 1/2 wheel diameter, and with path planning to avoid larger rocks, can traverse terrains comparable to those seen on Mars in the Viking and Pathfinder landing sites. Slopes of 45 deg can be easily negotiated by wheeled rovers. Walking vehicles can negotiate even more complex terrain but requires computation capability to select each leg placement. Extremely complex terrain was traversed by the Nomad II walker which descended into (and most of the way out of) an active volcanic caldera (Mount Spur, AK) in 1995, although a slope failure eventually resulted in broken legs. The traverse range of a rover is limited by its science objectives, performance capabilities, and operational lifetime. The speed of rover traverse is a relative minor factor. With a different communication system, and no stops for science experiments, Sojourner could probably have traveled a kilometer. But, achieving land speed records is not a major objective of a science mission. Achieving science objectives requires targeting particular objects and studying them in detail, and the associated operational requirements will likely limit rover traverse range significantly. Traversing from target to target requires relatively few command cycles provided the traverse is over a short enough distance that it can be adequately planned. An operational goal of 100 m traverse per command cycle, arriving at a predetermined target, seems achievable. Investigating science targets requiring manipulator or instrument placement and sample collection will likely take several command cycles per target. Mission simulations [6] have demonstrated that traverse dI stances of 100-300 m, with detailed investigation of 5-10 targets take 50-100 command cycles, not unlike the Pathfinder experience in spite of the use of larger, faster, more capable rovers. Significant advances in rover autonomy will be needed to improve this Situation and it is not clear how much improvement will be brought to flight programs in the next decade. Dust accumulation on solar panels degrades power over time and, without dust removal, rover operational lifetimes may be limited to 90 sols.

Stoker, Carol↗
NASA NTRS2003

Rover Technology Development and Infusion for the 2009 Mars Science Laboratory Mission

After the 2003 Mars Exploration Rovers (MER) Mission, NASA plans to send a larger, longer life Mobile Science Laboratory (MSL) in 2009. This rover is planned to last 500 days, travel ten kilometers, and demonstrate autonomous capabilities that reduce the number of communication cycles now needed to achieve successful completion of activities on the surface.

spacecraft autonomy planetary robotics technology ↗
NASA NTRS1978

A review of satellite time-transfer technology: Accomplishments and future applications

The research accomplishments by NASA in meeting the needs of the space program for precise time in satellite tracking are presented. As a major user of precise time signals for clock synchronization of NASA's worldwide satellite tracking networks, the agency provides much of the necessary impetus for the development of stable frequency sources and time synchronization technology. The precision time required for both satellite tracking and space science experiments has increased at a rate of about one order of magnitude per decade from 1 millisecond in the 1950's to 100 microseconds during the Apollo era in the 1960's to 10 microseconds in the 1970's. For the Tracking and Data Relay Satellite System, satellite timing requirements will be extended to 1 microsecond and below. These requirements are needed for spacecraft autonomy and data packeting.

Cooper, R. S.↗
NASA NTRS2005

Sensor Webs: Autonomous Rapid Response to Monitor Transient Science Events

To better understand how physical phenomena, such as volcanic eruptions, evolve over time, multiple sensor observations over the duration of the event are required. Using sensor web approaches that integrate original detections by in-situ sensors and global-coverage, lower-resolution, on-orbit assets with automated rapid response observations from high resolution sensors, more observations of significant events can be made with increased temporal, spatial, and spectral resolution. This paper describes experiments using Earth Observing 1 (EO-1) along with other space and ground assets to implement progressive mission autonomy to identify, locate and image with high resolution instruments phenomena such as wildfires, volcanoes, floods and ice breakup. The software that plans, schedules and controls the various satellite assets are used to form ad hoc constellations which enable collaborative autonomous image collections triggered by transient phenomena. This software is both flight and ground based and works in concert to run all of the required assets cohesively and includes software that is model-based, artificial intelligence software.

Mandl, Dan↗
NASA NTRS2009

Robotics Algorithms Provide Nutritional Guidelines

On July 5, 1997, a small robot emerged from its lander like an insect from an egg, crawling out onto the rocky surface of Mars. About the size of a child s wagon, NASA s Sojourner robot was the first successful rover mission to the Red Planet. For 83 sols (Martian days, typically about 40 minutes longer than Earth days), Sojourner - largely remote controlled by NASA operators on Earth - transmitted photos and data unlike any previously collected. Sojourner was perhaps the crowning achievement of the NASA Space Telerobotics Program, an Agency initiative designed to push the limits of robotics in space. Telerobotics - devices that merge the autonomy of robotics with the direct human control of teleoperators - was already a part of NASA s efforts; probes like the Viking landers that preceded Sojourner on Mars, for example, were telerobotic applications. The Space Telerobotics Program, a collaboration between Ames Research Center, Johnson Space Center, Jet Propulsion Laboratory (JPL), and multiple universities, focused on developing remote-controlled robotics for three main purposes: on-orbit assembly and servicing, science payload tending, and planetary surface robotics. The overarching goal was to create robots that could be guided to build structures in space, monitor scientific experiments, and, like Sojourner, scout distant planets in advance of human explorers. While telerobotics remains a significant aspect of NASA s efforts, as evidenced by the currently operating Spirit and Opportunity Mars rovers, the Hubble Space Telescope, and many others - the Space Telerobotics Program was dissolved and redistributed within the Agency the same year as Sojourner s success. The program produced a host of remarkable technologies and surprising inspirations, including one that is changing the way people eat

Source record↗
NASA NTRS2018

Starling1 - Mission Technologies Overview

The Starling series of demonstration missions will test technologies required to achieve affordable, distributed spacecraft ("swarm") missions that: are scalable to at least 100 spacecraft for applications that include synchronized multipoint measurements; involve closely coordinated ensembles of two or more spacecraft operating as a single unit for interferometric, synthetic aperture, or similar sensor architectures; or use autonomous or semi-autonomous operation of multiple spacecraft functioning as a unit to achieve science or other mission objectives with low-cost small spacecraft.Starling1 will focus on developing technologies that enable scalability and deep space application. The mission goals include the demonstration of a Mobile Ad-hoc NETwork (MANET) through an in-space communication experiment, vision based relative navigation through the Starling Formation-flying Optical eXperiment (StarFOX), and demonstration of autonomous spacecraft reconfiguration using technologies developed by the Distributed System Autonomy (DSA) project.

Cannon, Howard↗
NASA NTRS1997

(abstract) Mars Balloon Trajectory Model for Mars Geoscience Aerobot Development

The Mars Geoscience Aerobot (MGA) is a proposed Mars aerobot (robotic aerovehicle) mission featuring advanced capabilities for surface imagimg and atmospheric science. Development of the MGA mission has been catalyzed by science objectives that include surface geology and atmospheric measurements. The MGA consists of a superpressure balloon that is reflective on top and white on the bottom to avoid condensation CO&sub2; frost during the night. The MGA also features a

balloons↗
NASA NTRS1979

A review of satellite time transfer technology - Accomplishments and future applications

A brief review of the research accomplishments by NASA in meeting the needs of the space program for precise time in satellite tracking is presented. As a major user of precise time signals for clock synchronization of NASA's worldwide satellite tracking networks, the agency provided much of the necessary impetus for the development of stable frequency sources and time synchronization technology. The precision in time required for both satellite tracking and space science experiments has increased at a rate of about 1 order of magnitude per decade from 1 ms in the 1950's to 100 microsec during the Apollo era in the 1960's to 10 microsec in the 1970's. In the 1980's, when the Tracking and Data Relay Satellite System (TDRSS) comes into operation, satellite timing requirements will be extended to 1 microsec and below. These requirements are needed for spacecraft autonomy and data packeting which are now in active planning stages.

Cooper, R. S.↗
NASA NTRS2017

What Machines Need to Learn to Support Human Problem-Solving

In the development of intelligent systems that interact with humans, there is often confusion between how the system functions with respect to the humans it interacts with and how it interfaces with those humans. The former is a much deeper challenge than the latter it requires a system-level understanding of evolving human roles as well as an understanding of what humans need to know (and when) in order to perform their tasks. This talk will focus on some of the challenges in getting this right as well as on the type of research and development that results in successful human-autonomy teaming. Brief Bio: Dr. Alonso Vera is Chief of the Human Systems Integration Division at NASA Ames Research Center. His expertise is in human-computer interaction, information systems, artificial intelligence, and computational human performance modeling. He has led the design, development and deployment of mission software systems across NASA robotic and human space flight missions, including Mars Exploration Rovers, Phoenix Mars Lander, ISS, Constellation, and Exploration Systems. Dr. Vera received a Bachelor of Science with First Class Honors from McGill University in 1985 and a Ph.D. from Cornell University in 1991. He went on to a Post-Doctoral Fellowship in the School of Computer Science at Carnegie Mellon University from 1990-93.

intelligent systems↗