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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Remote Science at Sea With Remotely Operated Vehicles

Conducting sea-going ocean science no longer needs to be limited to the number of berths on a ship given that telecommunications, computing, and networking technologies onboard ships have become familiar mechanisms for expanding scientists’ reach from onshore. The oceanographic community routinely works with remotely operated vehicles (ROVs) and pilots to access real-time video and data from the deep sea, while onboard a ship. The extension of using an ROV and its host vessel’s live-streaming capabilities has been popularized for almost 3 decades as a telepresence technology. Telepresence-enabled vessels with ROVs have been employed for science, education, and outreach, giving a greater number of communities viewing access to ocean science. However, the slower development of technologies and social processes enabling sustained real-time involvement between scientists on-ship and onshore undermines the potential for broader access, which limits the possibility of increasing inclusivity and discoveries through a diversity of knowledge and capabilities. This article reviews ocean scientists’ use of telepresence for ROV-based deep-sea research and funded studies of telepresence capabilities. The authors summarize these studies findings and conditions that lead to defining the use of telepresence-enabled vessels for “remote science at sea.” Authors define remote science at sea as a type of ocean expedition, an additional capability, not a replacement for all practices by which scientists conduct ocean research. Remote science for ocean research is an expedition at-sea directed by a distributed science team working together from at least two locations (on-ship and onshore) to complete their science objectives for which primary data is acquired by robotic technologies, with connectivity supported by a high-bandwidth satellite and the telepresence-enabled ship’s technologies to support the science team actively engaged before, during, and after dives across worksites. The growth of productive ocean expeditions with remote science is met with social, technical, and logistical challenges that impede the ability of remote scientists to succeed. In this article, authors review telepresence-enabled ocean science, define and situate the adjoined model of remote science at sea, and some infrastructural, technological and social considerations for conducting and further developing remote science at sea.

marine technology↗
NASA NTRS1994

Automated Advisors for Remote Science Experimentation

This paper details flight results from the PI-in-a-Box project. The project is an attempt to understand the issues involved in building automated real-time advisory systems to improve the conduct of science in remote laboratory settings. This is an important problem as examples of these situations can be found throughout aerospace. A knowledge-based approach is used to facilitate real-time reactions to experiment data as it is collected by a competent, but not expert, operator. The system was flown on the Space Shuttle in October, 1993. The PI-in-a-Box system was able to outperform humans in a variety of science-related tasks. These tasks include data integrity assurance, data analysis, and scientific model validation.

Frainier, Richard↗
NASA NTRS2020

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗
NASA NTRS2012

Smart Cameras for Remote Science Survey

Communication with remote exploration spacecraft is often intermittent and bandwidth is highly constrained. Future missions could use onboard science data understanding to prioritize downlink of critical features [1], draft summary maps of visited terrain [2], or identify targets of opportunity for followup measurements [3]. We describe a generic approach to classify geologic surfaces for autonomous science operations, suitable for parallelized implementations in FPGA hardware. We map these surfaces with texture channels - distinctive numerical signatures that differentiate properties such as roughness, pavement coatings, regolith characteristics, sedimentary fabrics and differential outcrop weathering. This work describes our basic image analysis approach and reports an initial performance evaluation using surface images from the Mars Exploration Rovers. Future work will incorporate these methods into camera hardware for real-time processing.

robotics↗
NASA NTRS1983

Design of the Galileo remote science pointing actuators

This paper describes the two actuators developed for pointing the remote science instruments from the spinning Galileo spacecraft. Details of the key elements are presented together with their design features and developmental difficulties. Four techniques used for power and signal transfer across the actuators' rotating joints are also discussed.

Osborn, F. W.↗
NASA NTRS1986

Remote Science Operation Center research

Progress in the following areas is discussed: the design, planning and operation of a remote science payload operations control center; design and planning of a data link via satellite; and the design and prototyping of an advanced workstation environment for multi-media (3-D computer aided design/computer aided engineering, voice, video, text) communications and operations.

Banks, P. M.↗
NASA NTRS1990

Mars Observer remote science operations

The objectives and the background of the Mars Observer mission are briefly reviewed with emphasis on the remote science operations portion of the mission. In particular, the discussion covers observational planning and instrument sequences, data retrieval, instrument health monitoring, and science analysis. Attention is also given to workstation technology utilization, science team, project data base, common data formats, and security.

Kahn, Peter B.↗
NASA NTRSDate not supplied

Efficient Power Amplifiers for Radio Science, Remote Sensing, and Space Communications

The paper presents the development of high efficiency traveling-wave tube power amplifiers at K-band, Ka-band, and Q-band frequencies for radio science, remote sensing, and space communications. The saturated output power of these amplifiers is in the range of 40 to 200 watts and the corresponding efficiency is in the range of 45 to 60%.

Rainee N. Simons↗
NASA NTRSDate not supplied

Remote Science Work Support, Context, and Approach on NASA's VIPER Mission

Returning humans to the Moon, sending humans for the first time to Mars will necessarily include an accompaniment of robotic vehicles. A mission work system will be needed that supports remote teams of humans and robots in cooperation (synchronous and asynchronous) with earthbound systems, engineering and science teams. All of these elements have individual development contexts and manners of operation; at the same time, all are in varying degrees conjoined during mission development stages and operations. As such, the assembly of elements (people, activities, disciplinary knowledge, and machines) that constitute a mission work system can be developed independently and cooperatively. Current missions and those in development, in keeping with NASA’s history of employing prior mission knowledge, will shape how and by which organizational schemas, or elements of, future missions will draw from, or wholly rely. NASA’s Volatiles Investigating Polar Exploration Rover mission, VIPER, presents an opportunity for a unique operational schema within the history of space exploration and remotely conducted science research.

science operations↗
NASA NTRS2004

Expanding Remote Science Operations Capabilities Onboard the International Space Station

EXPRESS Racks have been supporting payload science operations onboard the International Space Station (ISS) since April of 2001. EXPRESS is an acronym that stands for "EXpedite the PRocessing of Experiments to Space Station." This name reflects NASA's focus to simplify the process of manifesting experiments and maximizing scientific research capabilities by providing a robust, remotely operated payload support platform. The EXPRESS Rack System was developed by NASA's Marshall Space Flight Center (MSFC) and built by The Boeing Company in Huntsville, Alabama. Eight EXPRESS racks were built and five are currently onboard the ISS supporting science operations. The design and development of the EXPRESS Rack System is a long story that has been documented in previous publications. This paper briefly describes the facilities used to develop and verify flight software, test operational capabilities. It then traces the advancements made in the operational capabilities of the EXPRESS Racks from the time they were launched on STS-100 through the present. The paper concludes with a description of potential enhancements that will make the EXPRESS racks one of the most advanced and capable remote science platforms ever developed.

Cruzen, Craig A.↗
NASA NTRS2007

Data Fusion for Earth Science Remote Sensing

Beginning in 2004, NASA has supported the development of an international network of ground-based remote sensing installations for the measurement of greenhouse gas columns. This collaboration has been successful and is currently used in both carbon cycle investigations and in the efforts to validate the GOSAT space-based column observations of CO2 and CH4. With the support of a grant, this research group has established a network of ground-based column observations that provide an essential link between the satellite observations of CO2, CO, and CH4 and the extensive global in situ surface network. The Total Carbon Column Observing Network (TCCON) was established in 2004. At the time of this report seven sites, employing modern instrumentation, were operational or were expected to be shortly. TCCON is expected to expand. In addition to providing the most direct means of tying the in situ and remote sensing data sets together, TCCON provides a means of testing the retrieval algorithms of SCIAMACHY and GOSAT over the broadest variation in atmospheric state. TCCON provides a critically maintained and long timescale record for identification of temporal drift and spatial bias in the calibration of the space-based sensors. Finally, the global observations from TCCON are improving our understanding of how to use column observations to provide robust estimates of surface exchange of C02 and CH4 in advance of the launch of OCO and GOSAT. TCCON data are being used to better understand the impact of both regional fluxes and long-range transport on gradients in the C02 column. Such knowledge is essential for identifying the tools required to best use the space-based observations. The technical approach and methodology of retrieving greenhouse gas columns from near-IR solar spectra, data quality and process control are described. Additionally, the impact of and relevance to NASA of TCCON and satellite validation and carbon science are addressed.

data fusion↗
NASA NTRS2003

Acquisition of Earth Science Remote Sensing Observations from Commercial Sources: Lessons Learned from the Space Imaging IKONOS Example

In an effort to more full explore the potential of commercial remotely sensed land data sources, the NASA Earth Science Enterprise (ESE) implemented an experimental Scientific Data Purchase (SDP) that solicited bids from the private sector to meet ESE-user data needs. The images from the Space Imaging IKONOS system provided a particularly good match to the current ESE missions such as Terra and Landsat 7 and therefore serve as a focal point in this analysis.

Goward, Samuel N.↗
NASA NTRS1986

Support for global science: Remote sensing's challenge

Remote sensing uses a wide variety of techniques and methods. Resulting data are analyzed by man and machine, using both analog and digital technology. The newest and most important initiatives in the U. S. civilian space program currently revolve around the space station complex, which includes the core station as well as co-orbiting and polar satellite platforms. This proposed suite of platforms and support systems offers a unique potential for facilitating long term, multidisciplinary scientific investigations on a truly global scale. Unlike previous generations of satellites, designed for relatively limited constituencies, the space station offers the potential to provide an integrated source of information which recognizes the scientific interest in investigating the dynamic coupling between the oceans, land surface, and atmosphere. Earth scientist already face problems that are truly global in extent. Problems such as the global carbon balance, regional deforestation, and desertification require new approaches, which combine multidisciplinary, multinational research teams, employing advanced technologies to produce a type, quantity, and quality of data not previously available. The challenge before the international scientific community is to continue to develop both the infrastructure and expertise to, on the one hand, develop the science and technology of remote sensing, while on the other hand, develop an integrated understanding of global life support systems, and work toward a quantiative science of the biosphere.

Estes, J. E.↗
NASA NTRS2002

Geologist's Field Assistant: Developing Image and Spectral Analyses Algorithms for Remote Science Exploration

We are developing science analyses algorithms to interface with a Geologist's Field Assistant device to allow robotic or human remote explorers to better sense their surroundings during limited surface excursions. Our algorithms will interpret spectral and imaging data obtained by various sensors. Additional information is contained in the original extended abstract.

Gulick, V. C.↗
NASA NTRS2009

Virtual Planetary Analysis Environment for Remote Science

All of the data for NASA's current planetary missions and most data for field experiments are collected via orbiting spacecraft, aircraft, and robotic explorers. Mission scientists are unable to employ traditional field methods when operating remotely. We have developed a virtual exploration tool for remote sites with data analysis capabilities that extend human perception quantitatively and qualitatively. Scientists and mission engineers can use it to explore a realistic representation of a remote site. It also provides software tools to "touch" and "measure" remote sites with an immediacy that boosts scientific productivity and is essential for mission operations.

Keely, Leslie↗
NASA NTRS1984

Fundamental remote science research program. Part 2: Status report of the mathematical pattern recognition and image analysis project

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of he Earth from remotely sensed measurements of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inferences about the Earth. This report summarizes the progress that has been made toward this program goal by each of the principal investigators in the MPRIA Program.

Heydorn, R. P.↗
NASA NTRS2007

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

massive data sets↗