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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 73 records · Page 4

Remote Sensing Application to Land Use Classification in a Rapidly Changing Agricultural/Urban Area: City of Virginia Beach, Virginia

Remote sensing data on computer-compatible tapes of LANDSAT 1 multispectral scanner imager were analyzed to generate a land use map of the City of Virginia Beach. All four bands were used in both the supervised and unsupervised approaches with the LAYSYS software system. Color IR imagery of a U-2 flight of the same area was also digitized and two sample areas were analyzed via the unsupervised approach. The relationships between the mapped land use and the soils of the area were investigated. A land use land cover map at a scale of 1:24,000 was obtained from the supervised analysis of LANDSAT 1 data. It was concluded that machine analysis of remote sensing data to produce land use maps was feasible; that the LAYSYS software system was usable for this purpose; and that the machine analysis was capable of extracting detailed information from the relatively small scale LANDSAT data in a much shorter time without compromising accuracy.

Odenyo, V. A. O.↗

Advances in space robotics

The problem of the remote control of space operations is addressed by identifying the key technical challenge: the management of contact forces and the principal performance parameters. Three principal classes of devices for remote operation are identified: anthropomorphic exoskeletons, computer aided teleoperators, and supervised telerobots. Their fields of application are described, and areas in which progress has reached the level of system or subsystem laboratory demonstrations are indicated. Key test results, indicating performance at a level useful for design tradeoffs, are reported.

Varsi, Giulio↗

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

Hepner, George F.↗

A Prototype System for Ground Control Space Telerobotics

A telerobotics system is described which provides supervised autonomous control capability for time-delayed ground-remote control applications. The system includes a local site operator interface for interactive task description and a remote site task execution system. Interactive stereo graphics overlay on video is provided at the local site to update the remote environmental model. The remote site system is capable of nominal task execution as well as monitoring and reflex action. Execution utilizes multiple control modules which execute based upon command parameterization.

robotics autonomous control telerobotics manipulat↗

Human Factors Research Considerations for Terminal Area Urban Air Mobility Operations

In this presentation, we discuss the human factors research challenges from introducing greater levels of automation in a future air transportation concept called Urban Air Mobility (UAM). UAM is an air transportation concept that aims to provide air transportation services to the daily commuter, as well as emergency response and package delivery. The principal innovation over current day large air transport system is the greater distribution of important safety functions to automated and human agents; these functions include air traffic management, traditionally an air traffic controller responsibility. A central aspect of UAM is the development of an automated air traffic manager, whose primary responsibility is to approve airspace access for vehicle operators. Vehicle operator roles may include onboard and remote pilots, as well as a human manager who will supervise an entire fleet. Alternatively, both fleet manager and vehicle operators can be merged into a single role – a feasible option if UAM aircraft are autonomous. In lieu of tower controllers, vertiport managers, with the assistance of automation, will manage arrival and departure schedules between vertiports, as well as supervise surface operations. Our approach here will be to introduce use cases currently being developed by NASA, and then provide preliminary definitions for each of the roles introduced above and how coordination between them can be configured to support the operations within the use cases described. Subsequently, we review the tools and interfaces being developed to support the various roles. To conclude, we present current human factors work related to defining the roles above and suggest future work to advance the UAM concept.

trial planning↗

High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants

High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset to enable accurate segmentation of overlapping plants. However, preparing such training data is both time and labor intensive. To solve this problem, we propose a plant image processing pipeline using a self-supervised sequential convolutional neural network method for in-field phenotyping systems. This first step uses plant pixels from greenhouse images to segment nonoverlapping in-field plants in an early growth stage and then applies the segmentation results from those early-stage images as training data for the separation of plants at later growth stages. The proposed pipeline is efficient and self-supervising in the sense that no human-labeled data are needed. We then combine this approach with functional principal components analysis to reveal the relationship between the growth dynamics of plants and genotypes. We show that the proposed pipeline can accurately separate the pixels of foreground plants and estimate their heights when foreground and background plants overlap and can thus be used to efficiently assess the impact of treatments and genotypes on plant growth in a field environment by computer vision techniques. This approach should be useful for answering important scientific questions in the area of high-throughput phenotyping.

59 BASIC BIOLOGICAL SCIENCES↗

Studies to design and develop improved remote manipulator systems

Remote manipulator control considered is based on several levels of automatic supervision which derives manipulator commands from an analysis of sensor states and task requirements. Principle sensors are manipulator joint position, tactile, and currents. The tactile sensor states can be displayed visually in perspective or replicated in the operator's control handle of perceived by the automatic supervisor. Studies are reported on control organization, operator performance and system performance measures. Unusual hardware and software details are described.

Hill, J. W.↗

Evaluation of a Remote Data Collection Method to Study Human-Automation Interaction and Workload

Introduction - Paradigm shift from one operator supervising a single vehicle, to an operator supervising multiple highly automated vehicles (One-to-Many) - One-to-Many application - Search and Rescue - Foraging - Military ops - Etc. - Calibrated trust in automation enables human operators to effectively manage highly automated vehicles - Past studies show that trust mediates relationship between reliability and dependence (Chancey et al., 2017; Chancey et al., 2015) - Future studies needed to further understand relationship

trust↗

Supervisory autonomous local-remote control system design: Near-term and far-term applications

The JPL Supervisory Telerobotics Laboratory (STELER) has developed a unique local-remote robot control architecture which enables management of intermittent bus latencies and communication delays such as those expected for ground-remote operation of Space Station robotic systems via the TDRSS communication platform. At the local site, the operator updates the work site world model using stereo video feedback and a model overlay/fitting algorithm which outputs the location and orientation of the object in free space. That information is relayed to the robot User Macro Interface (UMI) to enable programming of the robot control macros. The operator can then employ either manual teleoperation, shared control, or supervised autonomous control to manipulate the object under any degree of time-delay. The remote site performs the closed loop force/torque control, task monitoring, and reflex action. This paper describes the STELER local-remote robot control system, and further describes the near-term planned Space Station applications, along with potential far-term applications such as telescience, autonomous docking, and Lunar/Mars rovers.

Zimmerman, Wayne↗

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↗

Designing minimal space telerobotics systems for maximum performance

The design of the remote site of a local-remote telerobot control system is described which addresses the constraints of limited computational power available at the remote site control system while providing a large range of control capabilities. The Modular Telerobot Task Execution System (MOTES) provides supervised autonomous control, shared control and teleoperation for a redundant manipulator. The system is capable of nominal task execution as well as monitoring and reflex motion. The MOTES system is minimized while providing a large capability by limiting its functionality to only that which is necessary at the remote site and by utilizing a unified multi-sensor based impedance control scheme. A command interpreter similar to one used on robotic spacecraft is used to interpret commands received from the local site. The system is written in Ada and runs in a VME environment on 68020 processors and initially controls a Robotics Research K1207 7 degree of freedom manipulator.

Backes, Paul G.↗

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗

Multiaxis, Lightweight, Computer-Controlled Exercise System

The multipurpose, multiaxial, isokinetic dynamometer (MMID) is a computer-controlled system of exercise machinery that can serve as a means for quantitatively assessing a subject s muscle coordination, range of motion, strength, and overall physical condition with respect to a wide variety of forces, motions, and exercise regimens. The MMID is easily reconfigurable and compactly stowable and, in comparison with prior computer-controlled exercise systems, it weighs less, costs less, and offers more capabilities. Whereas a typical prior isokinetic exercise machine is limited to operation in only one plane, the MMID can operate along any path. In addition, the MMID is not limited to the isokinetic (constant-speed) mode of operation. The MMID provides for control and/or measurement of position, force, and/or speed of exertion in as many as six degrees of freedom simultaneously; hence, it can accommodate more complex, more nearly natural combinations of motions and, in so doing, offers greater capabilities for physical conditioning and evaluation. The MMID (see figure) includes as many as eight active modules, each of which can be anchored to a floor, wall, ceiling, or other fixed object. A cable is payed out from a reel in each module to a bar or other suitable object that is gripped and manipulated by the subject. The reel is driven by a DC brushless motor or other suitable electric motor via a gear reduction unit. The motor can be made to function as either a driver or an electromagnetic brake, depending on the required nature of the interaction with the subject. The module includes a force and a displacement sensor for real-time monitoring of the tension in and displacement of the cable, respectively. In response to commands from a control computer, the motor can be operated to generate a required tension in the cable, to displace the cable a required distance, or to reel the cable in or out at a required speed. The computer can be programmed, either locally or via a remote terminal, to support exercises in one or more of the usual exercise modes (isometric, isokinetic, or isotonic) along complex, multiaxis trajectories. The motions of, and forces applied by, the subject can be monitored in real time and recorded for subsequent evaluation. Through suitable programming, the exercise can be adjusted in real time according to the physical condition of the subject. The remote- programming capability makes it possible to connect multiple exercise machines into a network for supervised exercise by multiple subjects or even for competition by geographically dispersed subjects.

Haynes, Leonard↗

Remote sensing of environmental impact of land use activities

The capability to monitor land cover, associated in the past with aerial film cameras and radar systems, was discussed in regard to aircraft and spacecraft multispectral scanning sensors. A proposed thematic mapper with greater spectral and spatial resolutions for the fourth LANDSAT is expected to usher in new environmental monitoring capability. In addition, continuing improvements in image classification by supervised and unsupervised computer techniques are being operationally verified for discriminating environmental impacts of human activities on the land. The benefits of employing remote sensing for this discrimination was shown to far outweigh the incremental costs of converting to an aircraft-satellite multistage system.

Paul, C. K.↗

Intelligent Rover Execution for Detecting Life in the Atacama Desert

On-board supervisory execution is crucial for the deployment of more capable and autonomous remote explorers. Planetary science is considering robotic explorers operating for long periods of time without ground supervision while interacting with a changing and often hostile environment. Effective and robust operations require on-board supervisory control with a high level of awareness of the principles of functioning of the environment and of the numerous internal subsystems that need to be coordinated. We describe an on-board rover executive that was deployed on a rover as past of the "Limits of Life in the Atacama Desert (LITA)" field campaign sponsored by the NASA ASTEP program. The executive was built using the Intelligent Distributed Execution Architecture (IDEA), an execution framework that uses model-based and plan-based supervisory control of its fundamental computational paradigm. We present the results of the third field experiment conducted in the Atacama desert (Chile) in August - October 2005.

Baskaran, Vijayakumar↗

Supervised Autonomy for Space Telerobotics

Telerobotics continues to provide a means for extending human presence in space as an integral part of the control architecture of unmanned spacecraft. Supervised autonomy for control of space manipulators provides a safe and effective means for time delayed remote control of unmanned spacecraft.

space↗

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.↗