SEARCH · Search NASA

Results for “Earth Vision”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS2008

Tactile Robotic Topographical Mapping Without Force or Contact Sensors

A method of topographical mapping of a local solid surface within the range of motion of a robot arm is based on detection of contact between the surface and the end effector (the fixture or tool at the tip of the robot arm). The method was conceived to enable mapping of local terrain by an exploratory robot on a remote planet, without need to incorporate delicate contact switches, force sensors, a vision system, or other additional, costly hardware. The method could also be used on Earth for determining the size and shape of an unknown surface in the vicinity of a robot, perhaps in an unanticipated situation in which other means of mapping (e.g., stereoscopic imaging or laser scanning with triangulation) are not available. The method uses control software modified to utilize the inherent capability of the robotic control system to measure the joint positions, the rates of change of the joint positions, and the electrical current demanded by the robotic arm joint actuators. The system utilizes these coordinate data and the known robot-arm kinematics to compute the position and velocity of the end effector, move the end effector along a specified trajectory, place the end effector at a specified location, and measure the electrical currents in the joint actuators. Since the joint actuator current is approximately proportional to the actuator forces and torques, a sudden rise in joint current, combined with a slowing of the joint, is a possible indication of actuator stall and surface contact. Hence, even though the robotic arm is not equipped with contact sensors, it is possible to sense contact (albeit with reduced sensitivity) as the end effector becomes stalled against a surface that one seeks to measure.

Burke, Kevin↗

NASA NTRS2018

Cold Stowage: An ISS Project

NASA's vision for humans pursuing deep space flight involves the collection of science in low earth orbit aboard the International Space Station (ISS). As a service to the science community, Johnson Space Center (JSC) has developed hardware and processes to preserve collected science on the ISS and transfer it safely back to the Principal Investigators. This hardware includes an array of freezers, refrigerators, and incubators. The Cold Stowage team is part of the International Space Station (ISS) program. JSC manages the operation, support and integration tasks provided by Jacobs Technology and the University of Alabama Birmingham (UAB). Cold Stowage provides controlled environments to meet temperature requirements during ascent, on-orbit operations and return, in relation to International Space Station Payload Science.

Hartley, Garen↗

NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗

DOE OSTI2021

How AI Predicts the Untrained and Unseen

Focus Area: Model predictability improvements (Primary); Data optimization (secondary); Data complexity insights (secondary). The Scientific Challenge: If we believe that a future under extreme conditions will look very differently from today, we can likely agree that ML/AI models trained on past and present datasets will not be adequate to make reliable predictions into the future. This is true for water cycling, as well as biogeochemistry and other Earth system components and behaviors. Additionally, ML/AI models are inherently non-physical. Despite the flourishing success of ML/AI in many applications, such as computer vision, natural language process, and gaming, even the most sophisticated AI models don’t understand the very basic physical laws. Therefore, a natural question is: Can we trust ML/AI based predictions of Earth system behaviors that are fundamentally driven by physical laws? So, are physics models with meticulous process representation a better choice? Not exactly. Physical models, when firmly rooted in first principles, work great at predicting behaviors of systems with a well-defined set of boundary conditions and variables. However, as a complex system, the number of parameters and the degree of complexity and dynamics in processes, coupling, and scale dependent emergent behaviors make the Earth system behaviors very challenging to predict with physical models composed of deterministic laws. In addition, due to the lack of fundamental understandings, physical models often implement empirical correlations derived from observations with biases from locality of data generation. Because correlation is not necessarily causation or comply with first principles, scaling of model predictions beyond locality is often invalid. Beyond the limitation of models, physics or AI, our knowledge of the Earth system is limited by the lack of observational technologies and resources. Insufficient data density, dimensionality and diversity only offer a sliced (or projected) view of the Earth system, e.g. Plato’s Cave analogy, limiting our capability to better understand and represent fundamental processes in models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

SPICES: Spectro-Polarimetric Imaging and Characterization of Exoplanetary Systems - From Planetary Disks To Nearby Super Earths

SPICES (Spectro-Polarimetric Imaging and Characterization of Exoplanetary Systems) is a five-year M-class mission proposed to ESA Cosmic Vision. Its purpose is to image and characterize long-period extrasolar planets and circumstellar disks in the visible (450-900 nm) at a spectral resolution of about 40 using both spectroscopy and polarimetry. By 2020/2022, present and near-term instruments will have found several tens of planets that SPICES will be able to observe and study in detail. Equipped with a 1.5 m telescope, SPICES can preferentially access exoplanets located at several AUs (0.5-10 AU) from nearby stars (less than 25 pc) with masses ranging from a few Jupiter masses to Super Earths (approximately 2 Earth radii, approximately 10 mass compared to Earth) as well as circumstellar disks as faint as a few times the zodiacal light in the Solar System.

Boccaletti, Anthony↗

NASA NTRS2024

Artificial Intelligence Medical Support for Long-Duration Space Missions

We envision an artificial intelligence (AI) based system that will provide support and recommendations to the crew medical officer (CMO) and ground flight surgeon during long-duration space missions. Such a system would be pretrained on the knowledgebase of clinical knowledge on Earth, minimizing the amount of Earth data that needs to be transferred into space. Then during deployment, the system would be constantly refined through active learning from diverse streams of data from sensors in the spacecraft, data collected daily from individual astronauts, and human-in-the-loop feedback from the crew. The model could be interrogated for predictions and recommendations on personalized crew health based on the overall status of the spacecraft, medicinal stores, and status of other crew members. Adaptation techniques would be used to incorporate spaceflight data that have very different distributions from the training data due to the extreme environment. Edge computing and the most advanced neuromorphic processing would enable computation in scenarios with low power and bandwidth, while dimensionality reduction would be employed to ensure that the input data streams from spaceflight are as small as possible. In order to realize this long-term vision, several hardware and software aspects need to be developed and assembled. First, models pretrained on Earth biomedical data would need to be evaluated for predictive accuracy, and the best one selected. That model would need to be adapted to learn from diverse, sparse, and inconsistently measured data streams, as well as human-in-the-loop feedback. A data integration, standardization, and dimensionality reduction methodology would need to be developed to handle all data types and feed them into the model. Once the software and data infrastructure is developed, it would need to be integrated with small footprint compute processors and tested in high-radiation, high-vibration, unregulated temperature situations. As a short-term goal, we recommend to focus on the development of the data and model software structure. Several large language models (LLM) already exist that have been trained on Earth biomedical and clinical knowledgebases, including BioMedLLM, Med-PaLM, SPOKE LLM, and Foresight. These models need to be evaluated for accuracy and the best one chosen for a proof-of-concept structure, while maintaining awareness of the accelerating AI field and incorporating any newly improved model architectures as needed. Then, we recommend to develop a database of synthetic data types to mimic the diverse data streams that are expected in a long-duration space mission. This should include environmental and microbial data from the spacecraft, non-invasive data from wearables and point-of-care devices employed by astronauts, and more invasive molecular and physiological monitoring of clinical and biomarker data from astronauts. The data standardization methodology should be developed, and these data streams used to refine the clinical LLM. Several scenarios should be developed that could plausibly come up in a long-duration space mission, and changes or aberrations introduced to the data at specific times to mimic these scenarios. Then, question and answer tasks should be designed to interrogate the model for predictions and recommendations, with acceptable answers already identified.

Artificial Intelligence↗

NASA NTRSDate not supplied

How Autonomous Intelligent Systems Can Facilitate Earth-independent Medical Care: Going Beyond Telepresence

During the last decade, teleoperated robotic systems have extended humans’ sensorimotor competence to digitally fly beyond the physical barrier of distance and scale and thus transmit sensorimotor skills of the human through direct communication. Telepresence capabilities have enabled tele-physical remote access at small scales thanks to telerobotic mediums. Although the concept was initially motivated by space applications, such technologies quickly have expanded into the medical domain and resulted in teleoperated medical robots, including telerobotic surgical systems (such as the da Vinci surgical system). Effective telepresence fundamentally depends on an agile, reliable, and secure communication medium that can transmit real-time information between the operator and a remote device. However, direct telepresence may not be achievable for long-duration exploration spaceflight missions. Thus, autonomous systems and local intelligence represent potential solutions to the aforementioned issues. One example solution employs demonstration systems which enable learning from the pre-captured inputs of a skilled human operator. These will be computationally modeled and later probabilistically replicated toward the completion of remote physical tasks when direct telepresence is not viable - such as under communication blackout conditions. In other words, trained autonomous systems (e.g., robots) can perform remote operations that mimic the physical performance of experts during remote operations/training. Beyond learning the physics of the task, autonomous agents can also be used to conduct algorithmic decision-making that mimics the higher-level cognition of the expert. Thus, using an autonomous system, pre-trained cognitive and manipulation-based skills can be leveraged (acquired during pre-mission events) to produce digital twins of an intelligent operator. Such systems can be used for the real-time conduction of intricate tasks in complex and unstructured environments. Such systems will operationalize “cognitive digital twins” and can expand the reach of human cognition and manipulation through the power of data-driven learning from demonstration algorithms. This system category will be discussed as a fully autonomous operation in this talk. In addition to the above, we will also propose and discuss the possibility of partial-automation using remote intelligence and remote sensing. In contrast to full automation, partial automation can close the loop through a local operator equipped with augmented sensory awareness through wearable systems. Such technologies will allow the local operator to conduct delicate tasks while being guided using sensory augmentation and being monitored to gauge her/his level of cognitive focus and performance. The difference with the previous category is that a remote human will conduct the task. Further, rather than making a digital twin of human cognition, we will augment the control inputs of the local human to match those of the skilled expert operator who is not accessible in real-time. Going beyond classic telepresence and thus approaching intelligent telepresence, our vision is that autonomous agents will eventually enable the safe, consistent and efficient delivery of complex, remote and smart medical care during space exploration across operators in an Earth-independent fashion. We will discuss our collective vision from NASA and MERIIT@NYU lab in this talk.

Telepresence↗

NASA NTRS2005

Future Visions for Scientific Human Exploration

Today, humans explore deep-space locations such as Mars, asteroids, and beyond, vicariously here on Earth, with noteworthy success. However, to achieve the revolutionary breakthroughs that have punctuated the history of science since the dawn of the Space Age has always required humans as "the discoverers," as Daniel Boorstin contends in this book of the same name. During Apollo 17, human explorers on the lunar surface discovered the "genesis rock," orange glass, and humans in space revamped the optically crippled Hubble Space Telescope to enable some of the greatest astronomical discoveries of all time. Science-driven human exploration is about developing the opportunities for such events, perhaps associated with challenging problems such as whether we can identify life beyond Earth within the universe. At issue, however, is how to safely insert humans and the spaceflight systems required to allow humans to operate as they do best in the hostile environment of deep space. The first issue is minimizing the problems associated with human adaptation to the most challenging aspects of deep space space radiation and microgravity (or non-Earth gravity). One solution path is to develop technologies that allow for minimization of the exposure time of people to deep space, as was accomplished in Apollo. For a mission to the planet Mars, this might entail new technological solutions for in-space propulsion that would make possible time-minimized transfers to and from Mars. The problem of rapid, reliable in-space transportation is challenged by the celestial mechanics of moving in space and the so-called "rocket equation." To travel to Mars from Earth in less than the time fuel-minimizing trajectories allow (i.e., Hohmann transfers) requires an exponential increase in the amount of fuel. Thus, month-long transits would require a mass of fuel as large as the dry mass of the ISS, assuming the existence of continuous acceleration engines. This raises the largest technological stumbling block to moving humans on site as deep-space explorers, delivering the masses required for human spaceflight systems to LEO or other Earth orbital vantage points using the existing or projected fleet of Earth-to-orbit (ETO) launch vehicles. Without a return to Saturn V-class boosters or an alternate path, one cannot imagine emplacing the masses that would be required for any deep-space voyage without a prohibitive number of Shuttle-class launches. One futurist solution might involve mass launch systems that could be used to move the consumables, including fuel, water, food, and building materials, to LEO in pieces rather than launching integrated systems. This approach would necessitate the development of robotic assembly and fuel-storage systems in Earth orbit, but could provide for a natural separation of low-value cargo (e.g., fuel, water).

Garvin, James↗

NASA NTRS2014

Landsat-8: Science and Product Vision for Terrestrial Global Change Research

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012-2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived 'higher-level' Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Landsat↗

NASA NTRS2002

Engines for the Cosmos

Galactic forces spiral across the cosmos fueled by nuclear fission and fusion and atoms in plasmatic states with throes of constraints of gravitational forces and magnetic fields, In their wanderings these galaxies spew light, radiation, atomic and subatomic particles throughout the universe. Throughout the ages of man visions of journeying through the stars have been wondered. If humans and human devices from Earth are to go beyond the Moon and journey into deep space, it must be accomplished with like forces of the cosmos such as electrical fields, magnetic fields, ions, electrons and energies generated from the manipulation of subatomic and atomic particles. Forms of electromagnetic waves such as light, radio waves and lasers must control deep space engines. We won't get far on our Earth accustomed hydrocarbon fuels.

Rodgers, Stephen L.↗

NASA NTRS2003

Solidifying Safety

Contents include the following: 1. Solidifying Safety: NASA s new safety organization spools up, as the 1SS program grapples with long-term risk. 2. Earth to Orbit O'Keefe telling skeptical lawmakers Orbital Space Plan (OSP) will cover exploration vision. China's rapid pace.

Covault, Craig↗

NASA NTRS2006

Fabrication and Evaluation of Titanium and Zirconium based Wires for use during Extended, Deep Space, Missions

Novel materials and designs are necessary for transport vessels and propulsion systems to fulfill NASA's vision of easier access to space and the expansion of human exploration beyond low-earth orbit. Spacecraft components must necessarily be lighter and stronger than their predecessors and will likely be required to serve new purposes. Furthermore, they must be resilient to the thermal, vacuum, and radiation environment of space for extended periods of time and may need to perform in the near proximity of a nuclear fuel source. To this end research has been initiated to fabricate novel, composite, wires based on titanium and zirconium pearlitic alloys. It is expected that the fabricated wire will well endure in the space environment with application as tethers, sail components, fasteners, and a myriad of other (including earth-based) uses. A background on pearlitic wire, novel alloy development, microstructural characterization, and initial mechanical testing results will be presented and discussed.

Grugel, Richard N.↗

NASA NTRS2012

Remote Measurement of Pollution-A 40-Year Langley Retrospective: Aerosols and Clouds - Part 2

A workshop was convened in 1971 by the National Aeronautics and Space Administration (NASA) on the Remote Measurement of Pollution (RMOP), and the findings and recommendations of its participants are in a NASA Special Publication (NASA SP-285). The three primary workshop panels and their chairmen were focused on trace gas species (Will Kellogg), atmospheric particulates or aerosols (Verner Suomi), and water pollution (Gifford Ewing). Many of the workshop participants were specialists in the techniques that might be employed for regional to global-scale, remote measurements of the atmospheric parameters from Earth-orbiting satellites. In 2011 the author published a 40-year retrospective (or Part I) of the instrumental developments that were an outgrowth of the RMOP panel headed by Will Kellogg, i.e., on atmospheric temperature and gaseous species. The current report (or Part II) is an analogous retrospective of the vision of the panel led by Verner Suomi for the measurement of particulates (or aerosols) and clouds and for their effects on Earth s radiation budget. The class of measurement techniques includes laser radar or lidar, solar occultation, limb emission and scattering, nadir-viewing photometry or radiometry, and aerosol polarimetry. In addition, the retrospective refers to the scientific imperatives that led to those instrument developments of 1971-2010. Contributions of the atmospheric technologists at the Langley Research Center are emphasized, and their progress is placed in the context of the parallel and complementary work from within the larger atmospheric science community.

Remsberg, Ellis E.↗

NASA NTRS2003

High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations

Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.

Parks, John↗

NASA NTRSDate not supplied

Estimates of Future Numerical Weather Prediction Impacts from Hyperspectral Sounders

The United States’ satellite programs are currently in the process of evaluating the future of satellite observations of the Earth’s atmosphere, both as an individual nation and within the context of international partnerships. In an effort to better understand the impacts of various alternatives, the Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework has been utilized to evaluate several configurations of the international hyperspectral infrared sounder constellation from the perspective of global numerical weather prediction (NWP). This was done with an emphasis on the proposed NOAA/NASA Geostationary eXtended Observations (GeoXO) Sounder (GXS), planned to launch in the mid-2030s, and similar planned missions from international partners. GXS, in addition to contributions from EUMETSAT and JMA, will form a global ring of geostationary sounders consistent with the WMO’s 2040 vision. In addition to a novel geostationary IR sounder program, considerations extend to the future of the Low Earth Orbit (LEO) sounder program with the upcoming demise of several existing instruments and plans for future missions ongoing. The GMAO OSSE framework has examined the potential roles of GEO and LEO sounders in weather prediction improvement. Overall, the inclusion of both GEO sounders in a global ring and LEO sounders produces the most beneficial observation impact and the most accurate global weather forecasts as evaluated using several metrics, including hurricanes and the FSOI.

Erica Mcgrath-Spangler↗

NASA NTRSDate not supplied

Processes and Methods used for NASA Communications Services Project Conceptualization and Formulation

The U.S. National Aeronautics and Space Administration (NASA) is partnering with the commercial SATCOM industry to demonstrate the industry’s capabilities to provide services to NASA’s near-Earth missions. Leveraging commercial capabilities will become increasingly necessary for NASA, as its incumbent Government-owned-and-operated near-Earth satellite network, the Tracking and Data Relay Satellite System (TDRSS), will approach retirement towards the end of the current decade. NASA is actively taking the first steps to making the vision of using commercial SATCOM a reality. For more than two years, NASA’s Communication Services Project (CSP) has been evaluating the feasibility of employing commercial satellite communication (SATCOM) networks for near-Earth operations. This past April, CSP awarded US$278.5 million in Funded Space Act Agreements to select commercial SATCOM providers, so they may begin developing and demonstrating their specific near-Earth space communication services that may support future agency missions. Each company will match or exceed agency contributions during the five-year development and demonstration period, totaling more than $1.5 billion of cost-share investment. The companies will complete technology development and in-space demonstrations by 2025, after which NASA intends to seek multiple long-term contracts to acquire these kinds of services. The six companies (Inmarsat Government Inc., Kuiper Government Solutions (KGS), SES Government Solutions, Space Exploration Technologies (SpaceX), Telesat U.S. Services and Viasat Inc.) will shortly begin developing and demonstrating their capabilities to provide services, ranging from launch to standard on-orbit operations. The demonstrations will be across multiple spectrum regimes from L-Band to optical, and will utilize Geostationary Orbit (GEO), Medium-Earth Orbit (MEO) and Low-Earth Orbit (LEO) constellations. This paper discusses methodologies and processes used over the past two years to reach the point of entering into these partnerships. It also includes CSP’s goals and objectives going forward, following the award of six Funded Space Act Agreements to commercial SATCOM providers to develop and demonstrate these capabilities.

Communications Services Project↗

NASA NTRSDate not supplied

Processes and Methods used for Nasa Communications Services Project Conceptualization and Formulation

Communications Services Project↗

DOE OSTI2025

Applying AI to Help Predict Solar Power Output Over Time

Poster with results from ongoing research on re-training pv-vision to segment images of solar modules. Presenting at the Sandia Analytics for Climate, Energy, and Earth Sciences (ACEES) 2025 Symposium.

Sanghi, Ojas NMN [Sandia National Laboratories (SN↗