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At least 433 records · Page 24

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NASA NTRS1976

Geologic mapping using LANDSAT data

The feasibility of automated classification for lithologic mapping with LANDSAT digital data was evaluated using three classification algorithms. The two supervised algorithms analyzed, a linear discriminant analysis algorithm and a hybrid algorithm which incorporated the Parallelepiped algorithm and the Bayesian maximum likelihood function, were comparable in terms of accuracy; however, classification was only 50 per cent accurate. The linear discriminant analysis algorithm was three times as efficient as the hybrid approach. The unsupervised classification technique, which incorporated the CLUS algorithm, delineated the major lithologic boundaries and, in general, correctly classified the most prominent geologic units. The unsupervised algorithm was not as efficient nor as accurate as the supervised algorithms. Analysis of spectral data for the lithologic units in the 0.4 to 2.5 microns region indicated that a greater separability of the spectral signatures could be obtained using wavelength bands outside the region sensed by LANDSAT.

Siegal, B. S.↗

NASA NTRS1976

DHARMA - Discriminant hyperplane abstracting residuals minimization algorithm for separating clusters with fuzzy boundaries

Learning of discriminant hyperplanes in imperfectly supervised or unsupervised training sample sets with unreliably labeled samples along the fuzzy joint boundaries between sample clusters is discussed, with the discriminant hyperplane designed to be a least-squares fit to the unreliably labeled data points. (Samples along the fuzzy boundary jump back and forth from one cluster to the other in recursive cluster stabilization and are considered unreliably labeled.) Minimization of the distances of these unreliably labeled samples from the hyperplanes does not sacrifice the ability to discriminate between classes represented by reliably labeled subsets of samples. An equivalent unconstrained linear inequality problem is formulated and algorithms for its solution are indicated. Landsat earth sensing data were used in confirming the validity and computational feasibility of the approach, which should be useful in deriving discriminant hyperplanes separating clusters with fuzzy boundaries, given supervised training sample sets with unreliably labeled boundary samples.

Dasarathy, B. V.↗

NASA NTRS1982

Image processing developments and applications for water quality monitoring and trophic state determination

Remote sensing data analysis of water quality monitoring is evaluated. Data anaysis and image processing techniques are applied to LANDSAT remote sensing data to produce an effective operational tool for lake water quality surveying and monitoring. Digital image processing and analysis techniques were designed, developed, tested, and applied to LANDSAT multispectral scanner (MSS) data and conventional surface acquired data. Utilization of these techniques facilitates the surveying and monitoring of large numbers of lakes in an operational manner. Supervised multispectral classification, when used in conjunction with surface acquired water quality indicators, is used to characterize water body trophic status. Unsupervised multispectral classification, when interpreted by lake scientists familiar with a specific water body, yields classifications of equal validity with supervised methods and in a more cost effective manner. Image data base technology is used to great advantage in characterizing other contributing effects to water quality. These effects include drainage basin configuration, terrain slope, soil, precipitation and land cover characteristics.

Blackwell, R. J.↗

NASA NTRS1981

Lake classification in Vermont

In order to comply with the Federal Clean Water Act and, in so doing, develop a procedure to periodically update the classification, the State of Vermont evaluated the ability of LANDSAT to detect general water quality and specific water quality parameters in Vermont lakes. Unsupervised and supervised classifications as well as regression analyses were used to examine LANDSAT data from Lake Champlain and from four small nearby lakes. Unsupervised and supervised classifications were found to be of somewhat limited value. Regression analyses revealed a good correlation between depth-integrated total phosphorus concentrations and LANDSAT band 4 data (r2= 0.92) and between Secchi disk transparencies and LANDSAT band 4 data (r2 - 0.85). No correlation was found between depth-integrated chlorophyll-a samples and LANDSAT data. Vermont is expanding this LANDSAT evaluation to include the remaining lakes in the state greater than twenty acres and steps are being taken to incorporate LANDSAT into the state's ongoing water quality monitoring programs.

Garrison, V.↗

NASA NTRS1983

A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data

Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.

Parada, N. D. J.↗

NASA NTRS1982

An evaluation of thematic mapper simulator data for mapping forest cover

Computer-aided analysis techniques applied to Thematic Mapper Simulator (TMS) data were evaluated for the purpose of mapping forest cover types. Classification results obtained using a supervised set of training statistics and various combinations of three and four channel subsets of the seven available TMS channels are compared for the L2 (Minimum Euclidean Distance), GML (Gaussian Maximum Likelihood), and SECHO (Supervised Extraction and Classification of Homogeneous Objects) classification algorithms. SECHO performed significantly better than either of the two per-point classifiers for the untransformed data. Overall classification results of the Karhunen-Loeve transformation increased for the L2 algorithm, but decreased for both the GML and SECHO algorithms.

Dean, M. E.↗

NASA NTRS1983

Shuttle Imaging Radar-A (SIR-A) data as a complement to Landsat Multispectral Scanner (MSS) data

Principal components analysis and supervised classifications were performed on two dates of Landsat multispectral scanner (MSS) data registered to one date of Shuttle Imaging Radar-A (SIR-A) data in a wheat-growing area of New South Wales, Australia. The purpose was to evaluate SIR-A data as a complement to Landsat MSS data in an agricultural environment. The SIR-A data was filtered using a 7 x 7 pixel moving window median filter. Principal components analysis indicated the SIR-A data were discriminating between trees and agricultural fields. Supervised classifications using wheat, pasture, trees, and idle classes resulted in increased accuracies for wheat and pasture and slightly decreased accuracies for trees and idle for the Landsat MSS/SIR-A registered data sets over the Landsat MSS alone. Overall classification accuracies were unchanged for one date and substantially increased for the other when the SIR-A data were added to the Landsat MSS data.

Henninger, D. L.↗

NASA NTRS1988

Telerobotics for the efficient utilization of space

Telerobotics is a new technology that is being developed to perform remote manipulation in space. It seeks to accommodate the needs arising from a rapidly increasing investment in space assets and from the large costs deriving from human operations in space, especially EVA. Telerobotics applies advanced automation and artificial intelligence technology and combines the immediacy of execution of teleoperation (the replication at a distance of the physical motions of the operator) with the efficiency and precision of supervised robotic autonomy (the accomplishment of assignments through machine task decomposition and interpretation of sensor information). One of the key goals of this approach is the achievement of a seamless transition between teleoperation and supervised autonomy. The basis of this technology and of the NASA telerobotics research and development activities are described. They consist of five elements: core research, laboratory integration testbed, mission analysis, application demonstrations and flight experiments. Current advances, both in research and system integration are reported including the first integration of the laboratory testbed and quantitative comparisons obtained in a buoyant facility. Planned future goals are outlined.

Varsi, Giulio↗

NASA NTRS1989

Satellite servicer system flight demonstration program

A program to develop the capability of servicing satellites in remote locations, where a series of flight that will demonstrate autonomous rendezvous and docking, supervised autonomous Orbital Replacement Unit (ORU) exchange, supervised autonomous fluid transfer and, proximity operations for Space Station Freedom were planned, is described. The flight demonstrations are the results of several mission scenarios with complex technical objectives. Three Shuttle flights are planned to complete the multi-objective program. The major hardware elements of the program are described and discussed. Demonstration objectives and technical approaches to the flight demonstrations are discussed. Existing and developing technologies are assessed for applicability to the Satellite Servicer System (SSSFD) program.

James S. Moore↗

NASA NTRS1989

A prototype autonomous agent for crew and equipment retrieval in space

The ground-based demonstration of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles. The software architecture incorporates a hierarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: perception, world model, reasoning, sensing, and acting. The design provides for supervised autonomy as the primary mode of operation with teleoperation as the backup mode. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable operation.

Erickson, J. D.↗

NASA NTRS1990

Satellite Servicer System flight demonstration program

The major hardware elements, demonstration objectives, and technical approaches, as well as existing and developing technologies for applicability to the Satellite Servicer System (SSSFD) program are presented. In a project to develop the capability of servicing satellites in remote locations, NASA and SDI have planned a series of flights to demonstrate autonomous rendezvous and docking, supervised autonomous fluid transfer, and supervised autonomous orbital replacement unit exchange. Program objectives, design reference mission, and flight demonstrations are described. The expanded capability demonstrated by the SSSFD program will provide alternatives to excessive dependence on ground operations personnel and training, increase the reach into unique space environments, and decrease the costs of managing and operating space assets.

Moore, James S.↗

NASA NTRS1992

Software design for automated assembly of truss structures

Concern over the limited intravehicular activity time has increased the interest in performing in-space assembly and construction operations with automated robotic systems. A technique being considered at LaRC is a supervised-autonomy approach, which can be monitored by an Earth-based supervisor that intervenes only when the automated system encounters a problem. A test-bed to support evaluation of the hardware and software requirements for supervised-autonomy assembly methods was developed. This report describes the design of the software system necessary to support the assembly process. The software is hierarchical and supports both automated assembly operations and supervisor error-recovery procedures, including the capability to pause and reverse any operation. The software design serves as a model for the development of software for more sophisticated automated systems and as a test-bed for evaluation of new concepts and hardware components.

Herstrom, Catherine L.↗

NASA NTRS1992

Future needs for space robots for SEI

High level systems engineering modeling and analysis activities for the Space Exploration Initiative (SEI) are reviewed, with emphasis on planet surface systems. Particular attention is given to SEI studies, preliminary space robotic system requirements, and usefulness of space robotic systems developed to operate on planetary surfaces on earth. It is concluded that supervised intelligent systems on the planet surfaces are necessary to make SEI planet surface activities reliable and productive and encompass capabilities for control and monitoring of all elements, including supervised autonomous robotic systems. Amplification of human capabilities due to applying more knowledge and reasoning in more flexible and appropriate ways than conventional automation approaches will provide more robust performance, greater choice of interaction modes with operators, and greater transparency of operation.

Erickson, Jon D.↗

NASA NTRS1992

Technology test results from an intelligent, free-flying robot for crew and equipment retrieval in space

The ground-based demonstrations of Extra Vehicular Activity (EVA) Retriever, a voice-supervised, intelligent, free-flying robot, are designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The EVA Retriever software is required to autonomously plan and execute a target rendezvous, grapple, and return to base while avoiding stationary and moving obstacles with subsequent object handover. The software architecture incorporates a heirarchical decomposition of the control system that is horizontally partitioned into five major functional subsystems: sensing, perception, world model, reasoning, and acting. The design provides for supervised autonomy as the primary mode of operation. It is intended to be an evolutionary system improving in capability over time and as it earns crew trust through reliable and safe operation. This paper gives an overview of the hardware, a focus on software, and a summary of results achieved recently from both computer simulations and air bearing floor demonstrations. Limitations of the technology used are evaluated. Plans for the next phase, during which moving targets and obstacles drive realtime behavior requirements, are discussed.

Erickson, J.↗

NASA NTRS1992

A distributed telerobotics system for space operations

Robotic systems for space operations will require a combination of teleoperation, closely supervised autonomy, and loosely supervised autonomy. They may involve multiple robots, multiple controlling sites, and long communication delays. We have constructed a distributed telerobotics system as a framework for studying these problems. Our system is based on a modular interconnection scheme which allows the components of either manual or autonomous control systems to communicate and share information. It uses a wide area network to connect robots and operators at several different sites. This presentation will describe the structure of our system, the components used in our configurations, and results of some of our teleoperation experiments.

Wise, James D.↗

NASA NTRS1992

A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain

Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms and a supervised computational neural network, a dynamic multilayered perception trained with the cascade correlation learning algorithm. Initial clinical results are presented on both normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. However, for a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed.

Hall, Lawrence O.↗

NASA NTRS1994

Intelligent robotics can boost America's economic growth

A case is made for strategic investment in intelligent robotics as a part of the solution to the problem of improved global competitiveness for U.S. manufacturing, a critical industrial sector. Similar cases are made for strategic investments in intelligent robotics for field applications, construction, and service industries such as health care. The scope of the country's problems and needs is beyond the capability of the private sector alone, government alone, or academia alone to solve independently of the others. National cooperative programs in intelligent robotics are needed with the private sector supplying leadership direction and aerospace and non-aerospace industries conducting the development. Some necessary elements of such programs are outlined. The National Aeronautics and Space Administration (NASA) and the Lyndon B. Johnson Space Center (JSC) can be key players in such national cooperative programs in intelligent robotics for several reasons: (1) human space exploration missions require supervised intelligent robotics as enabling tools and, hence must develop supervised intelligent robotic systems; (2) intelligent robotic technology is being developed for space applications at JSC (but has a strong crosscutting or generic flavor) that is advancing the state of the art and is producing both skilled personnel and adaptable developmental infrastructure such as integrated testbeds; and (3) a NASA JSC Technology Investment Program in Robotics has been proposed based on commercial partnerships and collaborations for precompetitive, dual-use developments.

Erickson, Jon D.↗

NASA NTRS1991

Human factors requirements for telerobotic command and control: The European Space Agency experimental programme

Space Telerobotics research, performed under contract to the European Space Agency (ESA), concerning the execution of human factors experiments, and ultimately leading to the development of a telerobotics test bed, has been carried out since 1985 by a British Consortium consisting of British Aerospace, the United Kingdom Atomic Energy Authority and, more recently, the UK National Advanced Robotics Research Centre. The principal aim of the first study of the series was to derive preliminary requirements for a teleoperation servicing system, with reference to two mission model scenarios. The first scenario introduced the problem of communications time delays, and their likely effect on the ground-based operator in control of a manipulator system on board an unmanned servicing vehicle in Low Earth Orbit. In the second scenario, the operator was located on the NASA Orbiter aft flight deck, supervising the control of a prototype manipulator in the 'servicing' of an experimental payload in the cargo bay area. Human factors analyses centered on defining the requirements for the teleoperator workstation, such as identifying basic ergonomic requirements for workstation and panel layouts, defining teleoperation strategies, developing alphanumeric and graphic screen formats for the supervision or direct control of the manipulator, and the potential applications of expert system technology. The second study for ESA involved an experimental appraisal of some of the important issues highlighted in the first study, for which relevant human factors data did not exist. Of central importance during the second study was the issue of communications time delays and their effect on the manual control of a teleoperated manipulator from a ground-based command and control station.

Stone, Robert J.↗