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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Tactile Cueing as a Gravitational Substitute for Spatial Navigation During Parabolic Flight

INTRODUCTION: Spatial navigation requires an accurate awareness of orientation in your environment. The purpose of this experiment was to examine how spatial awareness was impaired with changing gravitational cues during parabolic flight, and the extent to which vibrotactile feedback of orientation could be used to help improve performance. METHODS: Six subjects were restrained in a chair tilted relative to the plane floor, and placed at random positions during the start of the microgravity phase. Subjects reported their orientation using verbal reports, and used a hand-held controller to point to a desired target location presented using a virtual reality video mask. This task was repeated with and without constant tactile cueing of "down" direction using a belt of 8 tactors placed around the mid-torso. Control measures were obtained during ground testing using both upright and tilted conditions. RESULTS: Perceptual estimates of orientation and pointing accuracy were impaired during microgravity or during rotation about an upright axis in 1g. The amount of error was proportional to the amount of chair displacement. Perceptual errors were reduced during movement about a tilted axis on earth. CONCLUSIONS: Reduced perceptual errors during tilts in 1g indicate the importance of otolith and somatosensory cues for maintaining spatial awareness. Tactile cueing may improve navigation in operational environments or clinical populations, providing a non-visual non-auditory feedback of orientation or desired direction heading.

Montgomery, K. L.↗
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 NTRS1984

Spatial information technologies for remote sensing today and tomorrow; Proceedings of the Ninth Pecora Symposium, Sioux Falls, SD, October 2-4, 1984

Topics discussed at the symposium include hardware, geographic information system (GIS) implementation, processing remotely sensed data, spatial data structures, and NASA programs in remote sensing information systems. Attention is also given GIS applications, advanced techniques, artificial intelligence, graphics, spatial navigation, and classification. Papers are included on the design of computer software for geographic image processing, concepts for a global resource information system, algorithm development for spatial operators, and an application of expert systems technology to remotely sensed image analysis.

Source record↗
NASA NTRS2003

Hippocampal place cell instability after lesions of the head direction cell network

The occurrence of cells that encode spatial location (place cells) or head direction (HD cells) in the rat limbic system suggests that these cell types are important for spatial navigation. We sought to determine whether place fields of hippocampal CA1 place cells would be altered in animals receiving lesions of brain areas containing HD cells. Rats received bilateral lesions of anterodorsal thalamic nuclei (ADN), postsubiculum (PoS), or sham lesions, before place cell recording. Although place cells from lesioned animals did not differ from controls on many place-field characteristics, such as place-field size and infield firing rate, the signal was significantly degraded with respect to measures of outfield firing rate, spatial coherence, and information content. Surprisingly, place cells from lesioned animals were more likely modulated by the directional heading of the animal. Rotation of the landmark cue showed that place fields from PoS-lesioned animals were not controlled by the cue and shifted unpredictably between sessions. Although fields from ADN-lesioned animals tended to have less landmark control than fields from control animals, this impairment was mild compared with cells recorded from PoS-lesioned animals. Removal of the prominent visual cue also led to instability of place-field representations in PoS-lesioned, but not ADN-lesioned, animals. Together, these findings suggest that an intact HD system is not necessary for the maintenance of place fields, but lesions of brain areas that convey the HD signal can degrade this signal, and lesions of the PoS might lead to perceptual or mnemonic deficits, leading to place-field instability between sessions.

NASA Program Biomedical Research and Countermeasur↗
DOE OSTI2025

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1988

TASKILLAN - A simulation to predict the validity of multiple resource models of aviation workload

A study to establish the validity of five predictive models of workload in the context of a controlled helicopter mission, TASKILLAN, is presented. Ten subjects performed simulations involving combinations of a low level flight task with three cognitive side tasks pertaining to navigation, spatial awareness, and computation. It is found that the best predictors of subjective workload are relativly simple models that integrate the total demands of task over time.

Wickens, Christopher D.↗
NASA NTRS1999

Head and Trunk Movement Control During Locomotion After Long-Duration Spaceflight

Exposure to the microgravity environment encountered during spaceflight induces adaptive alteration in sensorimotor function that leads to postflight disturbances in locomotor control. Head and trunk movement control plays a central role in maintaining gaze stability and in providing a stable reference system to permit spatial navigation in a complex and constantly varying environment. The goal of the present study was to investigate the effects of long-duration spaceflight (3-6 months) on head and trunk movement control during postflight terrestrial locomotion. Before and after spaceflight, subjects walked on a motorized treadmill while performing a challenging gaze stabilization task requiring number recognition. Head and trunk kinematic data were collected with a video-based motion analysis system. Analysis of roll, pitch and yaw head and trunk movements during treadmill walking revealed postflight alterations in head and trunk movement control in all three planes of motion. Subjects also experienced oscillopsia during postflight walking which led to impairment in performance of the number recognition task. These data indicate that exposure to long-duration space flight causes alteration in head and trunk movement control during postflight locomotion. These changes have implications for the control of gaze and maintenance of dynamic stability during walking after long-duration spaceflight.

Bloomberg, Jacob J.↗
NASA NTRS1989

Spatial cognition and navigation

An experiment that provides data for the development of a cognitive model of pilot flight navigation is described. The experiment characterizes navigational awareness as the mental alignment of two frames of reference: (1) the ego centered reference frame that is established by the forward view out of the cockpit and (2) the world centered reference frame that is established by the aircraft's location on a map. The data support a model involving at least two components: (1) the perceptual encoding of the navigational landmarks and (2) the mental rotation of the map's world reference frame into alignment with the ego centered reference frame. The quantitative relationships of these two factors are provided as possible inputs for a computational model of spatial cognition during flight navigation.

Aretz, Anthony J.↗
NASA NTRS1989

A tesselated probabilistic representation for spatial robot perception and navigation

The ability to recover robust spatial descriptions from sensory information and to efficiently utilize these descriptions in appropriate planning and problem-solving activities are crucial requirements for the development of more powerful robotic systems. Traditional approaches to sensor interpretation, with their emphasis on geometric models, are of limited use for autonomous mobile robots operating in and exploring unknown and unstructured environments. Here, researchers present a new approach to robot perception that addresses such scenarios using a probabilistic tesselated representation of spatial information called the Occupancy Grid. The Occupancy Grid is a multi-dimensional random field that maintains stochastic estimates of the occupancy state of each cell in the grid. The cell estimates are obtained by interpreting incoming range readings using probabilistic models that capture the uncertainty in the spatial information provided by the sensor. A Bayesian estimation procedure allows the incremental updating of the map using readings taken from several sensors over multiple points of view. An overview of the Occupancy Grid framework is given, and its application to a number of problems in mobile robot mapping and navigation are illustrated. It is argued that a number of robotic problem-solving activities can be performed directly on the Occupancy Grid representation. Some parallels are drawn between operations on Occupancy Grids and related image processing operations.

Elfes, Alberto↗
NASA NTRS1989

Sensor fusion: Spatial reasoning and scene interpretation; Proceedings of the Meeting, Cambridge, MA, Nov. 7-9, 1988

The present conference discusses topics in the fusion of active and passive sensors, object estimation and verification, three-dimensional representation and knowledge integration, three-dimensional perception from multisensor data, the representation of uncertainty in multisensor fusion, and sensor calibration and registration. Also discussed are the areas of multisensor target detection and classification, multisensor processing architectures, knowledge structures and spatial reasoning, sensory interfaces to telerobotic systems, and navigation with spatial data bases.

Schenker, Paul S.↗
NASA NTRS1997

The Taxiway Navigation and Situation Awareness (T-NASA) System

The goal of NASA's Terminal Area Productivity (TAP) Low-Visibility Landing and Surface Operations (LVLASO) subelement is to improve the efficiency of airport surface operations for commercial aircraft operating in weather conditions to Category IIIB while maintaining a high degree of safety. Currently, surface operations are one of the least technologically sophisticated components of the air transport system, being conducted in the 1990's with the same basic technology as in the 1930's. Pilots are given little or no explicit information about their current position, and routing information is limited to ATC communications and airport charts. In TAP/LVLASO, advanced technologies such as satellite navigation systems, digital data communications, advanced information presentation technology, and ground surveillance systems will be integrated into flight deck displays to enable expeditious and safe traffic movement on the airport surface. The cockpit display suite is called the T-NASA (Taxiway Navigation and Situation Awareness) System. This system has three integrated components: 1) Moving Map track-up airport surface display with own-ship, traffic and graphical route guidance 2) Scene-Linked Symbology - route/taxi information virtually projected via a Head-up Display (HUD) onto the forward scene; and, 3) 3-D Audio Ground Collision Avoidance and Navigation system - spatially-localized auditory traffic and navigation alerts. In the current paper, the design philosophy of the T-NASA system will be presented, and the T-NASA system display components described.

Foyle, David C.↗
DOE OSTI2024

CORSAIR: A Framework for Human Mobility Prediction through Visit Characterization and Spatial Behavior Modeling

The rapid advancement of location acquisition technologies has led to the daily collection of vast amounts of mobile trajectory data, facilitating in-depth research on human mobility and enabling more accurate mobility prediction models. However, existing methodologies often fall short in capturing the intricate dynamics of human navigation and spatial behavior. This paper addresses this gap by exploring the multifaceted relationships between individuals and their environments, considering the diverse influences of personal preferences and experiences. Some places hold sentimental value and are visited frequently, while others serve as transient points of passage. To model these differences, we introduce CORSAIR, a novel visit characterization framework that leverages visitation patterns and dwell times to delineate an individual’s relationship with specific places. CORSAIR classifies visits into seven distinct types: casual, occasional, routine, special, anchor, important, and resettling. Also, we show that explicitly recognizing these distinct visit types and incorporating nuanced visit intents into mobility prediction models leads to a substantial improvement in prediction accuracy. This distinction allows for more precise modeling of the individual’s transitions, enhancing the personalization and relevance of location-based services. Our findings suggest that a deeper understanding of the complexities of individual-environment interactions is crucial for developing effective predictive tools in mobility research.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
NASA NTRS2002

Perceived orientation in physical and virtual environments: changes in perceived orientation as a function of idiothetic information available

Two experiments examined perceived spatial orientation in a small environment as a function of experiencing that environment under three conditions: real-world, desktop-display (DD), and head-mounted display (HMD). Across the three conditions, participants acquired two targets located on a perimeter surrounding them, and attempted to remember the relative locations of the targets. Subsequently, participants were tested on how accurately and consistently they could point in the remembered direction of a previously seen target. Results showed that participants were significantly more consistent in the real-world and HMD conditions than in the DD condition. Further, it is shown that the advantages observed in the HMD and real-world conditions were not simply due to nonspatial response strategies. These results suggest that the additional idiothetic information afforded in the real-world and HMD conditions is useful for orientation purposes in our presented task domain. Our results are relevant to interface design issues concerning tasks that require spatial search, navigation, and visualization.

NASA Center ARC↗
DOE OSTI2026

Regional specialization in prefrontal cortex manifests in the reliability of task progression codes

The brain has the remarkable ability to guide the performance of complex tasks. Distinct prefrontal cortical areas make specific contributions to this ability, with the orbitofrontal cortex (OFC) critical for processing information related to trial outcomes and the dorsomedial prefrontal cortex (dmPFC) critical for sustained effort and selecting the right action at the right time. Yet, in both areas, neural activity represents both outcome- and action-related quantities. How similar neural representations support different functions remains unclear. Here, we compared OFC and dmPFC activity in rats performing a spatial alternation task. We show that, in contrast to other task-related variables, task progression is represented in both areas, but with distinct patterns of across-trial reliability that match each area’s previously documented functional specialization. Our results indicate that the engagement of reliable, task-phase-specific activity patterns differs across prefrontal regions in a manner well suited to engage different computations at different times.

Biological and medical sciences↗
NASA NTRS2009

Space Flight and Manual Control: Implications for Sensorimotor Function on Future Missions

Control of vehicles, and other complex mechanical motion systems, is a high-level integrative function of the central nervous system (CNS) that requires good visual acuity, eye-hand coordination, spatial (and, in some cases, geographic) orientation perception, and cognitive function. Existing evidence from space flight research (Paloski et.al., 2008, Clement and Reschke 2008, Reschke et al., 2007) demonstrates that the function of each of these systems is altered by removing (and subsequently by reintroducing) a gravitational field that can be sensed by vestibular, proprioceptive, and haptic receptors and used by the CNS for spatial orientation, navigation, and coordination of movements. Furthermore, much of the operational performance data collected as a function of space flight has not been available for independent analysis, and those data that have been reviewed are equivocal owing to uncontrolled environmental and/or engineering factors. Thus, our current understanding, when it comes to manual control, is limited primarily to a review of those situations where manual control has been a factor. One of the simplest approaches to the manual control problem is to review shuttle landing data. See the Figure below for those landing for which we have Shuttle velocities over the runway threshold.

Reschke, Millard F.↗
NASA NTRS2012

Image Mapping and Visual Attention on the Sensory Ego-Sphere

The Sensory Ego-Sphere (SES) is a short-term memory for a robot in the form of an egocentric, tessellated, spherical, sensory-motor map of the robot s locale. Visual attention enables fast alignment of overlapping images without warping or position optimization, since an attentional point (AP) on the composite typically corresponds to one on each of the collocated regions in the images. Such alignment speeds analysis of the multiple images of the area. Compositing and attention were performed two ways and compared: (1) APs were computed directly on the composite and not on the full-resolution images until the time of retrieval; and (2) the attentional operator was applied to all incoming imagery. It was found that although the second method was slower, it produced consistent and, thereby, more useful APs. The SES is an integral part of a control system that will enable a robot to learn new behaviors based on its previous experiences, and that will enable it to recombine its known behaviors in such a way as to solve related, but novel, task problems with apparent creativity. The approach is to combine sensory-motor data association and dimensionality reduction to learn navigation and manipulation tasks as sequences of basic behaviors that can be implemented with a small set of closed-loop controllers. Over time, the aggregate of behaviors and their transition probabilities form a stochastic network. Then given a task, the robot finds a path in the network that leads from its current state to the goal. The SES provides a short-term memory for the cognitive functions of the robot, association of sensory and motor data via spatio-temporal coincidence, direction of the attention of the robot, navigation through spatial localization with respect to known or discovered landmarks, and structured data sharing between the robot and human team members, the individuals in multi-robot teams, or with a C3 center.

Fleming, Katherine Achim↗