2,976 research outputs found
Advancing automation and robotics technology for the Space Station Freedom and for the US economy
Described here is the progress made by Levels 1, 2, and 3 of the Space Station Freedom in developing and applying advanced automation and robotics technology. Emphasis was placed on the Space Station Freedom program responses to specific recommendations made in the Advanced Technology Advisory Committee (ATAC) Progress Report 13, and issues of A&R implementation into the payload operations integration Center at Marshall Space Flight Center. Assessments are presented for these and other areas as they apply to the advancement of automation and robotics technology for Space Station Freedom
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
ProtoDESI: First On-Sky Technology Demonstration for the Dark Energy Spectroscopic Instrument
The Dark Energy Spectroscopic Instrument (DESI) is under construction to
measure the expansion history of the universe using the baryon acoustic
oscillations technique. The spectra of 35 million galaxies and quasars over
14,000 square degrees will be measured during a 5-year survey. A new prime
focus corrector for the Mayall telescope at Kitt Peak National Observatory will
deliver light to 5,000 individually targeted fiber-fed robotic positioners. The
fibers in turn feed ten broadband multi-object spectrographs. We describe the
ProtoDESI experiment, that was installed and commissioned on the 4-m Mayall
telescope from August 14 to September 30, 2016. ProtoDESI was an on-sky
technology demonstration with the goal to reduce technical risks associated
with aligning optical fibers with targets using robotic fiber positioners and
maintaining the stability required to operate DESI. The ProtoDESI prime focus
instrument, consisting of three fiber positioners, illuminated fiducials, and a
guide camera, was installed behind the existing Mosaic corrector on the Mayall
telescope. A Fiber View Camera was mounted in the Cassegrain cage of the
telescope and provided feedback metrology for positioning the fibers. ProtoDESI
also provided a platform for early integration of hardware with the DESI
Instrument Control System that controls the subsystems, provides communication
with the Telescope Control System, and collects instrument telemetry data.
Lacking a spectrograph, ProtoDESI monitored the output of the fibers using a
Fiber Photometry Camera mounted on the prime focus instrument. ProtoDESI was
successful in acquiring targets with the robotically positioned fibers and
demonstrated that the DESI guiding requirements can be met.Comment: Accepted versio
Advancing automation and robotics technology for the Space Station Freedom and for the US economy
The progress made by levels 1, 2, and 3 of the Office of Space Station in developing and applying advanced automation and robotics technology is described. Emphasis is placed upon the Space Station Freedom Program responses to specific recommendations made in the Advanced Technology Advisory Committee (ATAC) progress report 10, the flight telerobotic servicer, and the Advanced Development Program. Assessments are presented for these and other areas as they apply to the advancement of automation and robotics technology for the Space Station Freedom
A Theory of Consciousness from a Theoretical Computer Science Perspective: Insights from the Conscious Turing Machine
The quest to understand consciousness, once the purview of philosophers and
theologians, is now actively pursued by scientists of many stripes. We examine
consciousness from the perspective of theoretical computer science (TCS), a
branch of mathematics concerned with understanding the underlying principles of
computation and complexity, including the implications and surprising
consequences of resource limitations. In the spirit of Alan Turing's simple yet
powerful definition of a computer, the Turing Machine (TM), and perspective of
computational complexity theory, we formalize a modified version of the Global
Workspace Theory (GWT) of consciousness originated by cognitive neuroscientist
Bernard Baars and further developed by him, Stanislas Dehaene, Jean-Pierre
Changeaux and others. We are not looking for a complex model of the brain nor
of cognition, but for a simple computational model of (the admittedly complex
concept of) consciousness. We do this by defining the Conscious Turing Machine
(CTM), also called a conscious AI, and then we define consciousness and related
notions in the CTM. While these are only mathematical (TCS) definitions, we
suggest why the CTM has the feeling of consciousness. The TCS perspective
provides a simple formal framework to employ tools from computational
complexity theory and machine learning to help us understand consciousness and
related concepts. Previously we explored high level explanations for the
feelings of pain and pleasure in the CTM. Here we consider three examples
related to vision (blindsight, inattentional blindness, and change blindness),
followed by discussions of dreams, free will, and altered states of
consciousness.Comment: arXiv admin note: text overlap with arXiv:2011.0985
Earth Observatory Satellite system definition study. Report 5: System design and specifications. Volume 3: General purpose spacecraft segment and module specifications
The specifications for the Earth Observatory Satellite (EOS) general purpose aircraft segment are presented. The satellite is designed to provide attitude stabilization, electrical power, and a communications data handling subsystem which can support various mission peculiar subsystems. The various specifications considered include the following: (1) structures subsystem, (2) thermal control subsystem, (3) communications and data handling subsystem module, (4) attitude control subsystem module, (5) power subsystem module, and (6) electrical integration subsystem
ECLSS advanced automation preliminary requirements
A description of the total Environmental Control and Life Support System (ECLSS) is presented. The description of the hardware is given in a top down format, the lowest level of which is a functional description of each candidate implementation. For each candidate implementation, both its advantages and disadvantages are presented. From this knowledge, it was suggested where expert systems could be used in the diagnosis and control of specific portions of the ECLSS. A process to determine if expert systems are applicable and how to select the expert system is also presented. The consideration of possible problems or inconsistencies in the knowledge or workings in the subsystems is described
Computational needs survey of NASA automation and robotics missions. Volume 1: Survey and results
NASA's operational use of advanced processor technology in space systems lags behind its commercial development by more than eight years. One of the factors contributing to this is that mission computing requirements are frequently unknown, unstated, misrepresented, or simply not available in a timely manner. NASA must provide clear common requirements to make better use of available technology, to cut development lead time on deployable architectures, and to increase the utilization of new technology. A preliminary set of advanced mission computational processing requirements of automation and robotics (A&R) systems are provided for use by NASA, industry, and academic communities. These results were obtained in an assessment of the computational needs of current projects throughout NASA. The high percent of responses indicated a general need for enhanced computational capabilities beyond the currently available 80386 and 68020 processor technology. Because of the need for faster processors and more memory, 90 percent of the polled automation projects have reduced or will reduce the scope of their implementation capabilities. The requirements are presented with respect to their targeted environment, identifying the applications required, system performance levels necessary to support them, and the degree to which they are met with typical programmatic constraints. Volume one includes the survey and results. Volume two contains the appendixes
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Randomized Computations for Efficient and Robust Finite Element Domain Decomposition Methods in Electromagnetics
Numerical modeling of electromagnetic (EM) phenomenon has proved to become an effective and efficient tool in design and optimization of modern electronic devices, integrated circuits (IC) and RF systems. However the generality, efficiency and reliability/resilience of the computational EM solver is often criticised due to the fact that the underlying characteristics of the simulated problems are usually different, which makes the development of a general, \u27\u27black-box\u27\u27 EM solver to be a difficult task.
In this work, we aim to propose a reliable/resilient, scalable and efficient finite elements based domain decomposition method (FE-DDM) as a general CEM solver to tackle such ultimate CEM problems to some extent. We recognize the rank deficiency property of the Dirichlet-to-Neumann (DtN) operators involved in the previously proposed FETI-2 DDM formulation and apply such principle to improve the computational efficiency and robustness of FETI-2 DDM. Specifically, the rank deficient DtN operator is computed by a randomized computation method that was originally proposed to approximate matrix singular value decomposition (SVD). Numerical results show a up to 35\% run-time and 75% memory saving of the DtN operators computation can be achieved on a realistic example. Later, such rank deficiency principle is incorporated into a new global DDM preconditioner (W-FETI) that is inspired by the matrix Woodbury identity. Numerical study of the eigenspectrum shows the validity of the proposed W-FETI global preconditioner. Several industrial-scaled examples show significant iterative convergence advantage of W-FETI that uses 35%-80% matrix-vector-products (MxVs) than state-of-the-art DDM solvers
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