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At least 145 records · Page 8

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NASA NTRS2001

Interferometric Characterization of the Earth's Atmosphere from Lagrange Point 2

Part of the NASA plans for future Earth Science missions calls for observations using novel vantage points that can produce science products otherwise unobtainable. Observations of the Earth from the Lagrange-2 point, L-2, (1.5 million km behind the Earth on the Earth-Sun line) affords a unique vantage point for atmospheric science. Spectral observation of the Earth's atmosphere using solar occultation techniques in the near infrared (1 to 4 microns) provides one of the most accurate methods of passively sensing attitude profiles of the major species (CO2, O3, O2, CH4, H2O N2O). While traditional polar orbiting occultation measurements can obtain about 14 measurements per day (2 per orbit), solar occultation observations from the Lagrange-2 point will yield hourly profile measurements at all latitudes. The expected spatial resolution is 2 km in altitude, 0.5 degrees in latitude, and 2 degrees in longitude. The result from 24 hours of observations will be a three-dimensional map of atmospheric composition. To accomplish this task from L-2 requires the development of a large moderate spectral resolution instrument whose entrance aperture is about 10 meters. Use of a standard telescope design with a 10-meter circular mirror or a 10-meter strip mirror would be prohibitively expensive and excessively massive. Instead, we are proposing the development of a 10-meter linear interferometer coupled to a Fourier transform imaging spectrometer. The result will be a highly efficient design with sufficient sensitivity, while having both spatial and spectral resolution to produce the desired results. Preliminary calculations show that seven species (CO2, O3, O2, CH4, H2O N2O) have clearly separated spectral features in the I to 4 microns range with sufficient absorption to produce profile information from near the Earth's surface to the middle stratosphere. For CO2 the estimated sensitivity to change is 0.33% or 1 part in 330. This should be sufficient to detect changes that are significant for the carbon cycle studies. Initial instrument design studies are underway to determine the optimum optical design for the interferometer-spectrometer as well as the necessary highly stable mechanical designs. Separate design studies are being conducted for the spacecraft. shuttle launch facility, low-light solar power design, thermal control, and unique navigation requirements to reach and maintain the tight halo orbit about L-2.

Herman, Jay R.↗

NASA NTRS2003

Flood warnings, flood disaster assessments, and flood hazard reduction : the roles of orbital remote sensing

Orbital remote sensing is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent (near-daily) radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction. These latter tasks are accomplished, in part, by accurate mapping of flooded lands and commonly over periods of several days or more. We use radar scatterometer data from QuikSCAT to detect changes in surface water area and with a full global coverage every 2.5 days. Also, MODIS, RADARSAT, and other higher spatial resolution data are used for flood mapping and other flood measurements. These records are preserved in a global flood hazard atlas at http://www.dartmouth.edu/-floods/Atlas.html.

Shabaneh, Tamer B.↗

NASA NTRS1995

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

Kohonen Feature Map↗

NASA NTRS1993

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated.

Cao, Tiehua↗

NASA NTRS1991

Rotational wind indicator enhances control of rotated displays

Rotation by 108 deg of the spatial mapping between a visual display and a manual input device produces large spatial errors in a discrete aiming task. These errors are not easily corrected by voluntary mental effort, but the central nervous system does adapt gradually to the new mapping. Bernotat (1970) showed that adding true hand position to a 90 deg rotated display improved performance of a compensatory tracking task, but tracking error rose again upon removal of the explicit cue. This suggests that the explicit error signal did not induce changes in the neural mapping, but rather allowed the operator to reduce tracking error using a higher mental strategy. In this report, we describe an explicit visual display enhancement applied to a 108 deg rotated discrete aiming task. A 'wind indicator' corresponding to the effect of the mapping rotation is displayed on the operator-controlled cursor. The human operator is instructed to oppose the virtual force represented by the indicator, as one would do if flying an airplane in a crosswind. This enhancement reduces spatial aiming error in the first 10 minutes of practice by an average of 70 percent when compared to a no enhancement control condition. Moreover, it produces adaptation aftereffect, which is evidence of learning by neural adaptation rather than by mental strategy. Finally, aiming error does not rise upon removal of the explicit cue.

Cunningham, H. A.↗

NASA NTRS2011

Development of a Rover Simulation to Assess Operational Proficiency Following Long Duration Spaceflights

Following long-duration space transits, adaptive changes in sensorimotor and cognitive function may impair the crew s ability to safely control pressurized rovers designed to explore the new environment. We describe a rover simulation developed to quantify post-flight decrements in operational proficiency following International Space Station expeditions. The rover simulation consists of a serial presentation of discrete tasks to be completed as quickly and accurately as possible. Each task consists of 1) perspective taking using a map that defines a docking target, 2) navigation toward the target around a Martian outpost, and 3) docking a side hatch of the rover to a visually guided target. The simulator utilizes a Stewart-type motion base (CKAS, Australia), single seat cabin with triple scene projection covering approximately 150 horizontal by 40 vertical, and joystick controller. The software was implemented using Unity3 with next-gen PhysX engine to tightly synchronize simulation and motion platform commands. Separate C# applications allow investigators to customize session sequences with different lighting and gravitational conditions, and then execute tasks to be performed as well as record performance data. Preliminary tests resulted in low incidence of motion sickness (<15% unable to complete first session), with only negligible after effects and symptoms after familiarization sessions. Functionally relevant testing early post-flight will develop evidence regarding the limitations to early surface operations and what countermeasures are needed. This approach can be easily adapted to other vehicle designs to provide a platform to safely assess how sensorimotor and cognitive function impact manual control performance.

DeDios, Y. E.↗

NASA NTRS1981

Modeling the human controller in environments that include continuous and discrete tasks

In complex environments where the human operator is a supervisor, he must allocate his attention between different kinds of tasks for satisfactory overall performance. When a portion of the future reference trajectory for a continuous control task is available for preview, scheduling various other discrete activities is possible. A model has been developed for this situation using dynamic programming to solve an optimal control problem. An experiment was conducted where subjects controlled an airplane symbol over a map, shown a fixed distance into the future. Discrete tasks were introduced as data entry tasks. Results showed that the model compared favorably with experimental results.

Govindaraj, T.↗

NASA NTRS1998

Planning Paths Through Singularities in the Center of Mass Space

The center of mass space is a convenient space for planning motions that minimize reaction forces at the robot's base or optimize the stability of a mechanism. A unique problem associated with path planning in the center of mass space is the potential existence of multiple center of mass images for a single Cartesian obstacle, since a single center of mass location can correspond to multiple robot joint configurations. The existence of multiple images results in a need to either maintain multiple center of mass obstacle maps or to update obstacle locations when the robot passes through a singularity, such as when it moves from an elbow-up to an elbow-down configuration. To illustrate the concepts presented in this paper, a path is planned for an example task requiring motion through multiple center of mass space maps. The object of the path planning algorithm is to locate the bang- bang acceleration profile that minimizes the robot's base reactions in the presence of a single Cartesian obstacle. To simplify the presentation, only non-redundant robots are considered and joint non-linearities are neglected.

Doggett, William R.↗

NASA NTRS1998

Preliminary Work for Examining the Scalability of Reinforcement Learning

Researchers began studying automated agents that learn to perform multiple-step tasks early in the history of artificial intelligence (Samuel, 1963; Samuel, 1967; Waterman, 1970; Fikes, Hart & Nilsonn, 1972). Multiple-step tasks are tasks that can only be solved via a sequence of decisions, such as control problems, robotics problems, classic problem-solving, and game-playing. The objective of agents attempting to learn such tasks is to use the resources they have available in order to become more proficient at the tasks. In particular, each agent attempts to develop a good policy, a mapping from states to actions, that allows it to select actions that optimize a measure of its performance on the task; for example, reducing the number of steps necessary to complete the task successfully. Our study focuses on reinforcement learning, a set of learning techniques where the learner performs trial-and-error experiments in the task and adapts its policy based on the outcome of those experiments. Much of the work in reinforcement learning has focused on a particular, simple representation, where every problem state is represented explicitly in a table, and associated with each state are the actions that can be chosen in that state. A major advantage of this table lookup representation is that one can prove that certain reinforcement learning techniques will develop an optimal policy for the current task. The drawback is that the representation limits the application of reinforcement learning to multiple-step tasks with relatively small state-spaces. There has been a little theoretical work that proves that convergence to optimal solutions can be obtained when using generalization structures, but the structures are quite simple. The theory says little about complex structures, such as multi-layer, feedforward artificial neural networks (Rumelhart & McClelland, 1986), but empirical results indicate that the use of reinforcement learning with such structures is promising. These empirical results make no theoretical claims, nor compare the policies produced to optimal policies. A goal of our work is to be able to make the comparison between an optimal policy and one stored in an artificial neural network. A difficulty of performing such a study is finding a multiple-step task that is small enough that one can find an optimal policy using table lookup, yet large enough that, for practical purposes, an artificial neural network is really required. We have identified a limited form of the game OTHELLO as satisfying these requirements. The work we report here is in the very preliminary stages of research, but this paper provides background for the problem being studied and a description of our initial approach to examining the problem. In the remainder of this paper, we first describe reinforcement learning in more detail. Next, we present the game OTHELLO. Finally we argue that a restricted form of the game meets the requirements of our study, and describe our preliminary approach to finding an optimal solution to the problem.

Clouse, Jeff↗

NASA NTRS1991

Pictorial communication in virtual and real environments

Papers about the communication between human users and machines in real and synthetic environments are presented. Individual topics addressed include: pictorial communication, distortions in memory for visual displays, cartography and map displays, efficiency of graphical perception, volumetric visualization of 3D data, spatial displays to increase pilot situational awareness, teleoperation of land vehicles, computer graphics system for visualizing spacecraft in orbit, visual display aid for orbital maneuvering, multiaxis control in telemanipulation and vehicle guidance, visual enhancements in pick-and-place tasks, target axis effects under transformed visual-motor mappings, adapting to variable prismatic displacement. Also discussed are: spatial vision within egocentric and exocentric frames of reference, sensory conflict in motion sickness, interactions of form and orientation, perception of geometrical structure from congruence, prediction of three-dimensionality across continuous surfaces, effects of viewpoint in the virtual space of pictures, visual slant underestimation, spatial constraints of stereopsis in video displays, stereoscopic stance perception, paradoxical monocular stereopsis and perspective vergence. (No individual items are abstracted in this volume)

Ellis, Stephen R.↗

NASA NTRS2011

Acquisition of Skill Proficiency Over Multiple Sessions of a Novel Rover Simulation

Following long-duration exploration transits, adaptive changes in sensorimotor function may impair the crew's ability to safely perform manual control tasks such as operating pressurized rovers. Postflight performance will also be influenced by the level of preflight skill proficiency they have attained. The purpose of this study was to characterize the acquisition of skills in a motion-based rover simulation over multiple sessions, and to investigate the effects of varying the simulation scenarios. METHODS: Twenty healthy subjects were tested in 5 sessions, with 1-3 days between sessions. Each session consisted of a serial presentation of 8 discrete tasks to be completed as quickly and accurately as possible. Each task consisted of 1) perspective-taking, using a map that defined a docking target, 2) navigation toward the target around a Martian outpost, and 3) docking a side hatch of the rover to a visually guided target. The simulator utilized a Stewart-type motion base (CKAS, Australia), single-seat cabin with triple scene projection covering 150 deg horizontal by 50 deg vertical, and joystick controller. Subjects were randomly assigned to a control group (tasks identical in the first 4 sessions) or a varied-practice group. The dependent variables for each task included accuracy toward the target and time to completion. RESULTS: The greatest improvements in time to completion occurred during the docking phase. The varied-practice group showed more improvement in perspective-taking accuracy. Perspective-taking accuracy was also affected by the relative orientation of the rover to the docking target. Skill acquisition was correlated with self-ratings of previous gaming experience. DISCUSSION: Varying task selection and difficulty will optimize the preflight acquisition of skills when performing novel operational tasks. Simulation of operational manual control will provide functionally relevant evidence regarding the impact of sensorimotor adaptation on early surface operations and what countermeasures are needed. Learning Objective: The use of a motion-based simulation to investigate decrements in the proficiency to operate pressurized rovers during early surface operations of space exploration missions, along with the acquisition of skill proficiency needed during the preflight phase of the mission.

Dean, S. L.↗

NASA NTRS1993

Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.

Weaver, Johnathan M.↗

NASA NTRS1977

Digital processing system for developing countries

An effort was undertaken to perform simple digital processing tasks using pre-existing general purpose digital computers. An experimental software package, LIGMALS, was obtained and modified for this purpose. The resulting software permits basic processing tasks to be performed including level slicing, gray mapping and ratio processing. The experience gained in this project indicates a possible direction which may be used by other developing countries to obtain digital processing capabilities.

Nanayakkara, C.↗

NASA NTRS1990

Two-Wavelength Optical-Path-Difference Mapping

Proposed technique for measuring shapes and alignments of reflectors based on use of two-wavelength absolute-distance interferometer to generate optical-path-difference maps of reflecting or refracting surfaces. Facilitates such tasks as determining manufacturing and alignment errors of off-axis segment of large-aperture paraboloidal telescope mirror, or aligning all segments of such mirror. Suitable for use where reflecting surfaces highly aspherical, initial misalignments large, and/or surface errors exceed optical wavelengths.

Manhart, Paul K.↗

NASA NTRSDate not supplied

Visualizing Geospatial Data through ESRI Story Maps for Earth Science Education: Lessons Learned from My NASA Data

For 20 years My NASA Data (MND) has curated NASA Earth science data and provided the data to educators in engaging learner-centered resources. MND has recently featured story maps as an innovative way to engage students in NASA Earth data. A story map is a cloud-based lesson that engages the learner in interactive geospatial maps using NASA data, and other multimedia content, text, and tasks that can be seamlessly incorporated in classroom instruction. This immersive technology eliminates the need for the user to move among tricky interfaces to access and visualize Earth science data, and no special software is required to be downloaded. Each story map integrates data from different NASA satellite missions, retrieved from Distributed Active Archive Centers (DAACs). Story maps also employ data analysis tools, such as time series options and swipe tools that allow learners to view and analyze relationships between scientific variables. MND has produced 25 story map lesson plans on the topics of air quality, the urban heat island effect, Earth’s energy budget, phytoplankton distribution, hurricane formation, solar eclipses, ocean circulation patterns, sea ice extent, and volcanic eruptions. Nine of them are extended story maps and written in the 5E format, which is internationally recognized as best practice based on how children learn science. Each story map resource is developed by the MND team featuring a GIS programming specialist, a lead scientist, and educational specialist/s to ensure the context, content, and methods are scientifically and educationally sound. The MND story maps are written for middle and high school science teachers and students as they connect with the Earth Systems Science phenomena featured in the Next Generation Science Standards. Each story map includes supporting resources for smooth integration in the classroom. During Fiscal Year 2023, The My NASA Data website received over 100,000 story map engagements during. These metrics highlight the interest in story maps as an Earth Science educational resource.

Desiray Wilson↗

NASA NTRS2010

Assessment of Spatial Navigation and Docking Performance During Simulated Rover Tasks

INTRODUCTION: Following long-duration exploration transits, pressurized rovers will enhance surface mobility to explore multiple sites across Mars and other planetary bodies. Multiple rovers with docking capabilities are envisioned to expand the range of exploration. However, adaptive changes in sensorimotor and cognitive function may impair the crew s ability to safely navigate and perform docking tasks shortly after transition to the new gravitoinertial environment. The primary goal of this investigation is to quantify post-flight decrements in spatial navigation and docking performance during a rover simulation. METHODS: Eight crewmembers returning from the International Space Station will be tested on a motion simulator during four pre-flight and three post-flight sessions over the first 8 days following landing. The rover simulation consists of a serial presentation of discrete tasks to be completed within a scheduled 10 min block. The tasks are based on navigating around a Martian outpost spread over a 970 sq m terrain. Each task is subdivided into three components to be performed as quickly and accurately as possible: (1) Perspective taking: Subjects use a joystick to indicate direction of target after presentation of a map detailing current orientation and location of the rover with the task to be performed. (2) Navigation: Subjects drive the rover to the desired location while avoiding obstacles. (3) Docking: Fine positioning of the rover is required to dock with another object or align a camera view. Overall operator proficiency will be based on how many tasks the crewmember can complete during the 10 min time block. EXPECTED RESULTS: Functionally relevant testing early post-flight will develop evidence regarding the limitations to early surface operations and what countermeasures are needed. This approach can be easily adapted to a wide variety of simulated vehicle designs to provide sensorimotor assessments for other operational and civilian populations.

Wood, S. J.↗

NASA NTRS2024

Safe Exploration: Sensorimotor Assessments for Early Extravehicular Activities

BACKGROUND: Artemis missions will require a new level of crew autonomy around periods of gravitational transition, where sensorimotor disturbances are at their highest. There is a need to define performance thresholds for key sensorimotor assessments that indicate when performance in early extravehicular activities (EVAs) might be impacted or unsafe. This panel presentation will discuss the development of sensorimotor assessments for determining crew preparedness of early EVAs by utilizing a novel portable sensorimotor disorientation analog and other spaceflight analogs. OVERVIEW: To define performance thresholds, a proposed set of sensorimotor assessment tasks must be validated under various spaceflight analogs. A Sensorimotor Disorientation Analog (SDA) was developed that could induce varying levels of disorientation through combined vestibular (galvanic vestibular stimulation (GVS)) and proprioceptive (weighted chest, ankles, and wrists) disruptions. The SDA was first pilot tested using subjective feedback from previously flown astronauts to determine the levels of disorientation that mimic motor performance immediately (R+0) and +24 hours (R+1) postflight. A second study was performed using healthy non-astronaut ground subjects to validate the SDA levels by comparing to astronaut postflight data. The validated SDA was utilized in a third study to map performance in the proposed set of sensorimotor assessment tasks to operational tasks. The assessment tasks were defined based on lessons learned from Apollo and subject matter experts (e.g., flight surgeons) to include the following: 1) aid in progressive adaptation to the novel gravitational environment; 2) provide opportunities to develop strategies to recover from off-nominal body positions; and 3) mimic operational tasks such that crew can self-assess their potential ability to complete their missions. This presentation will conclude with a discussion on future validation studies of the proposed assessment tasks using other spaceflight analogs such as centrifugation and gravity offload systems. DISCUSSION: Exploration class missions will require crew to be able to self-assess and treat their sensorimotor dysfunction after gravity transitions, and in off-nominal situations they may be required to perform provocative, challenging tasks soon after landing. This panel presentation will discuss current and ongoing research strategies to address the sensorimotor risk on safe exploration during Artemis missions.

Sarah Moudy↗

NASA NTRS1990

Visualization of three dimensional data

The objective of research is to characterize patterns of errors observers make when relating the judged exocentric direction of a target presented on a perspective display to their egocentric sense of visual direction. This type of spatial task is commonly faced by operators of telerobotic systems when using a map-like display of their workspace to determine the visual location and orientation of objects seen by direct view. It is also essentially the same task as faced by an aircraft pilot using a cockpit perspective traffic display of his surrounding airspace to locate traffic out his windows. The results of the current study clearly show that the visual direction is a significantly biased metric of virtual space presented by flat panel perspective displays. Modeling and explanation of the causes of the observed biases will allow design of compensated perspective displays.

Ellis, Stephen R.↗