Image motion stabilization requirements for dynamic visual tasks in space
Image motion stabilization for dynamic visual task by astronauts on future space missions
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Image motion stabilization for dynamic visual task by astronauts on future space missions
Computer system VISTA, automatically plots selective PERT networks in order to develop accurate, standardized scheduling documentation as an essential element to project planning. This automation of plotting networks generates standardized networks due to a priority scheme adopted for calculating paths between events.
A piloted simulator experiment was conducted to assess the effects of side-stick controller characteristics and level of stability and control augmentation on handling qualities for several low-altitude control tasks. Visual flight tasks were simulated using four-window computer-generated imagery depicting either a nap-of-the-earth course or a runway with obstacles positioned to provide a slalom course. Both low speed and forward flight control laws were implemented, and a method for automatically switching control modes was developed. Variations in force-deflection characteristics and the number of axes controlled through an integrated side-stick were investigated. With high levels of stability and control augmentation, a four-axis controller with small-deflection in all four axes achieved satisfactory handling qualities for low-speed tasks.
Visual systems with a single window display are often utilized in ground based simulators used to study helicopter flying qualities during visual low altitude maneuvering tasks. The effects of this limited field of view (FOV) on pilot assessments of flying qualities are uncertain. A study was conducted using a variable stability UH-1H helicopter to compare restricted and unrestricted FOV for a range of flying qualities. With the restricted FOV, the pilots reported reduced ground track precision owing to loss of visual contact with the course markers. However, the predictable ground track of the repeated S-turn task with no obstacles made it easy for them to anticipate their maneuvers, and resulted in only a slight degradation of pilot ratings. This degradation was not sensitive to large changes in helicopter flying qualities.
Despite decision-making being a vital goal of data visualization, little work has been done to differentiate decision-making tasks within the field. While visualization task taxonomies and typologies exist, they often focus on more granular analytical tasks that are too low-level to describe large complex decisions, which can make it difficult to reason about and design decision-support tools. In this paper, we contribute a typology of decision-making tasks that were iteratively refined from a list of design goals distilled from a literature review. Our typology is concise and consists of only three tasks: CHOOSE, ACTIVATE, and CREATE. Although decision types originating in other disciplines exist, we provide definitions for these tasks that are suitable for the visualization community. Our proposed typology offers two benefits. First, the ability to compose and hierarchically organize the tasks enables flexible and clear descriptions of decisions with varying levels of complexities. Second, the typology encourages productive discourse between visualization designers and domain experts by abstracting the intricacies of data, thereby promoting clarity and rigorous analysis of decision-making processes. We demonstrate the benefits of our typology through four case studies, and present an evaluation of the typology from semi-structured interviews with experienced members of the visualization community who have contributed to developing or publishing decision support systems for domain experts. Our interviewees used our typology to delineate the decision-making processes supported by their systems, demonstrating its descriptive capacity and effectiveness. Finally, we present preliminary findings on the usefulness of our typology for visualization design.
Control power and damping requirements for visual hovering tasks in vtol aircraft-bell x-14 testing
Explicit payoffs were used to control pressures for speed and accuracy in experiments seeking tradeoffs for difficult visual discrimination tasks. The experiments involved stimuli on a cathode ray tube display controlled by a PDP-1 computer, with the subjects performing increasingly complex discrimination tasks and their earnings increasing with their performance. Models for discrimination under time pressure are proposed on the basis of the results.
Visual estimates of roll-tilt perception during static roll-tilt are confounded by an offset due to the ocular counterroll that simultaneously occurs. An alternative, non-visual ('somatosensory') measure of roll-tilt perception was developed which is not contaminated by this offset. The aims of this study were to determine: 1) inter-subject variability of somatosensory settings across test session in normal subjects and patients with unilateral or bilateral vestibular loss and 2) intra-subject variability of settings across test session in normal subjects.
The increasing adoption of Deep Neural Networks (DNNs) has led to their application in many challenging scientific visualization tasks. While advanced DNNs offer impressive generalization capabilities, understanding factors such as model prediction quality, robustness, and uncertainty is crucial. These insights can enable domain scientists to make informed decisions about their data. However, DNNs inherently lack ability to estimate prediction uncertainty, necessitating new research to construct robust uncertainty-aware visualization techniques tailored for various visualization tasks. In this work, we propose uncertainty-aware implicit neural representations to model scalar field data sets effectively and comprehensively study the efficacy and benefits of estimated uncertainty information for volume visualization tasks. We evaluate the effectiveness of two principled deep uncertainty estimation techniques: (1) Deep Ensemble and (2) Monte Carlo Dropout (MC-Dropout). These techniques enable uncertainty-informed volume visualization in scalar field data sets. Our extensive exploration across multiple data sets demonstrates that uncertainty-aware models produce informative volume visualization results. Moreover, integrating prediction uncertainty enhances the trustworthiness of our DNN model, making it suitable for robustly analyzing and visualizing real-world scientific volumetric data sets.
The issues are described which are associated with using a laser scanner for visual sensing and the methods developed by the author to address them. A laser scanner is a device that controls the direction of a laser beam by deflecting it through a pair of orthogonal mirrors, the orientations of which are specified by a computer. If a calibrated laser scanner is combined with a calibrated camera, it is possible to perform three dimensional sensing by directing the laser at objects within the field of view of the camera. There are several issues associated with using a laser scanner for three dimensional visual sensing that must be addressed in order to use the laser scanner effectively. First, methods are needed to calibrate the laser scanner and estimate three dimensional points. Second, methods to estimate three dimensional points using a calibrated camera and laser scanner are required. Third, methods are required for locating the laser spot in a cluttered image. Fourth, mathematical models that predict the laser scanner's performance and provide structure for three dimensional data points are necessary. Several methods were developed to address each of these and has evaluated them to determine how and when they should be applied. The theoretical development, implementation, and results when used in a dual arm eighteen degree of freedom robotic system for space assembly is described.
Control of locomotion requires precise interaction between several sensorimotor subsystems. During locomotion the performer must satisfy two performance criteria: maintain stable forward translation and to stabilize gaze (McDonald, et al., 1997). Precise coordination demands integration of multiple sensorimotor subsystems for fulfilling both criteria. In order to test the general hypothesis that the whole body can serve as an integrated gaze stabilization system, we have previously investigated how the multiple, interdependent full-body sensorimotor subsystems respond to changes in gaze stabilization task constraints during locomotion (Mulavara and Bloomberg, 2003). The results suggest that the full body contributes to gaze stabilization during locomotion, and that its different functional elements respond to changes in visual task constraints. The goal of this study was to determine how the multiple, interdependent, full-body sensorimotor subsystems aiding gaze stabilization during locomotion are functionally coordinated after the vestibulo-ocular reflex (VOR) gain has been altered. We investigated the potential of adaptive remodeling of the full-body gaze control system following exposure to visual-vestibular conflict known to adaptively reduce the VOR. Subjects (n=14) walked (6.4 km/h) on the treadmill before and after they were exposed to 0.5X manifying lenses worn for 30 minutes during self-generated sinusoidal vertical head rotations performed while seated. In this study we measured: temporal parameters of gait, full body sagittal plane segmental kinematics of the head, trunk, thigh, shank and foot, accelerations along the vertical axis at the head and the shank, and the vertical forces acting on the support surface. Results indicate that, following exposure to the 0.5X minifying lenses, there was a significant increase in the duration of stance and stride times, alteration in the amplitude of head movement with respect to space and a significant increase in the amount of knee flexion during the initial stance phase of the gait cycle. This study provides further evidence that the full body contributes to gaze stabilization during locomotion, and that different functional elements are responsive to changes in visual task constraints and are subject to adaptive alteration following exposure to visual-vestibular conflict.
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We explored the training potential of Virtual Reality (VR) technology. Thirty-one adults were trained and tested on spatial skills in a VR. They learned a sequence of button and knob responses on a VR console and performed flawlessly on the same console. Half were trained with a rote strategy; the rest used a meaningful strategy. Response times were equivalent for both groups and decreased significantly over five test trials indicating that learning continued on VR tests. The same subjects practiced navigating through a VR building, which had three floors with four rooms on each floor. The dependent measure was the number of rooms traversed on routes that differed from training routes. Many subjects completed tests in the fewest rooms possible. All subjects learned configurational knowledge according to the criterion of taking paths that were significantly shorter than those predicted by a random walk as determined by a Monte Carlo analysis. The results were discussed as a departure point for empirically testing the training potential of VR technology.
An experiment is described which examined the benefits of distributing the input demands of two tracking tasks as a function of task integrality. Visual and auditory compensatory tracking tasks were utilized. Results indicate that presenting the two tracking signals in two input modalities did not improve time-sharing efficiency. This was attributed to the difficulty insensitivity phenomenon.
In many passive visual tasks, human perceptual judgments are contrast dependent. To explore whether these contrast dependencies of visual perception also affect closed-loop manual control tasks, we examined visuomotor performance as humans actively controlled a moving luminance-defined line over a range of contrasts. Four subjects were asked to use a joystick to keep a horizontal line centered on a display as its vertical position was perturbed by a sum of sinusoids under two control regimes. The total root mean square (RMS) position error decreased quasi-linearly with increasing log contrast across the tested range (mean slope across subjects: -8.0 and -7.7% per log2 contrast, for the two control regimes, respectively). Frequency-response (Bode) plots showed a systematic increase in open-loop gain (mean slope: 1.44 and 1.30 dB per log2 contrast, respectively), and decrease in phase lag with increasing contrast, which can be accounted for by a decrease in response time delay (mean slope: 32 and 40 ms per log2 contrast, respectively). The performance data are well fit by a Crossover Model proposed by McRuer and Krendel, which allowed us to identify both visual position and motion cues driving performance. This analysis revealed that the position and motion cues used to support manual control under both control regimes appear equally sensitive to changes in stimulus contrast. In conclusion, our data show that active control of a moving visual stimulus is as dependent on contrast as passive perception and suggest that this effect is attributed to a shared contrast sensitivity early in the visual pathway, before any specialization for motion processing.
The relevance of codes and modalities in a multiple-resource model to the prediction of task interference was investigated in an experiment in which either verbal or spatial decision tasks, responded to with either voice or key press, were time-shared with second-order tracking. Results indicate the importance of the dichotomy between verbal and spatial processing codes in accounting for task interference. Interference with tracking was consistently greater, and difficulty/performance trade-offs were stronger, when the spatial decision task was performed and the manual response was used. A review of the literature on the interference between a continuous visual task and a discrete task whose modality is either auditory or visual suggests that scanning produces a dominant cost to intramodal configurations when visual channels are separated in space. In absence of visual separation, the differences between cross-modal and intramodal performance may be best accounted for by a mechanism of preemption.
We describe a system for interactive visualization and tracking of a 3-D unsteady computational fluid dynamics (CFD) simulation on a parallel computer. CM/AVS, a distributed, parallel implementation of a visualization environment (AVS) runs on the CM-5 parallel supercomputer. A CFD solver is run as a CM/AVS module on the CM-5. Data communication between the solver, other parallel visualization modules, and a graphics workstation, which is running AVS, are handled by CM/AVS. Partitioning of the visualization task, between CM-5 and the workstation, can be done interactively in the visual programming environment provided by AVS. Flow solver parameters can also be altered by programmable interactive widgets. This system partially removes the requirement of storing large solution files at frequent time steps, a characteristic of the traditional 'simulate (yields) store (yields) visualize' post-processing approach.
This grant funded research on human-computer interaction design and analysis techniques, using future ATC environments as a testbed. The basic approach was to model the nominal behavior of both the automated and human procedures and then to apply safety analysis techniques to these models. Our previous modeling language, RSML, had been used to specify the system requirements for TCAS II for the FAA. Using the lessons learned from this experience, we designed a new modeling language that (among other things) incorporates features to assist in designing less error-prone human-computer interactions and interfaces and in detecting potential HCI problems, such as mode confusion. The new language, SpecTRM-RL, uses "intent" abstractions, based on Rasmussen's abstraction hierarchy, and includes both informal (English and graphical) specifications and formal, executable models for specifying various aspects of the system. One of the goals for our language was to highlight the system modes and mode changes to assist in identifying the potential for mode confusion. Three published papers resulted from this research. The first builds on the work of Degani on mode confusion to identify aspects of the system design that could lead to potential hazards. We defined and modeled modes differently than Degani and also defined design criteria for SpecTRM-RL models. Our design criteria include the Degani criteria but extend them to include more potential problems. In a second paper, Leveson and Palmer showed how the criteria for indirect mode transitions could be applied to a mode confusion problem found in several ASRS reports for the MD-88. In addition, we defined a visual task modeling language that can be used by system designers to model human-computer interaction. The visual models can be translated into SpecTRM-RL models, and then the SpecTRM-RL suite of analysis tools can be used to perform formal and informal safety analyses on the task model in isolation or integrated with the rest of the modeled system. We had hoped to be able to apply these modeling languages and analysis tools to a TAP air/ground trajectory negotiation scenario, but the development of the tools took more time than we anticipated.