23 research outputs found

    Comparing Virtual Reality to Conventional Simulator Visuals: Effects of Peripheral Visual Cues in Roll-Axis Tracking Tasks

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    This paper compares the effects of peripheral visual cues on manual control between a conventional fixed-base simulator and virtual reality. The results were also compared with those from a previous experiment conducted in a motion-base simulator. Fifteen participants controlled a system with second-order dynamics in a disturbance-rejection task. Tracking performance, control activity, simulator sickness questionnaire answers, and biometrics were collected. Manual control behavior was modeled for the first time in a virtual reality environment. Virtual reality did not degrade participants manual control performance or alter their control behavior. However, peripheral cues were significantly more effective in virtual reality. Control activity decreased for all conditions with peripheral cues. The trends introduced by the peripheral visual cues from the previous experiment were replicated. Finally, VR was not more nauseogenic than the conventional simulator. These results suggest that virtual reality might be a good alternative to conventional fixed-base simulators for training manual control skills

    Rotational and Translational Velocity and Acceleration Thresholds for the Onset of Cybersickness in Virtual Reality

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    This paper determined rotational and translational velocity and acceleration thresholds for the onset of cybersickness. Cybersickness causes discomfort and discourages the widespread use of virtual reality systems for both recreational and professional use. Visual motion or optic flow is known to be one of the main causes of cybersickness due to the sensory conflict it creates with the vestibular system. The aim of this experiment is to detect rotational and translational velocity and acceleration thresholds that cause the onset of cybersickness. Participants were exposed to a moving particle field in virtual reality for a few seconds per run. The field moved in different directions (longitudinal, lateral, roll, and yaw), with different velocity profiles (steady and accelerating), and different densities. Using a staircase procedure, that controlled the speed or acceleration of the field, we detected the threshold at which participant started to feel temporary symptoms of cybersickness. The optic flow was quantified for each motion type and by modifying the number of features, the same amount of optic flow was present in each scene. Having the same optic flow in each scene allows a direct comparison of the thresholds. The results show that the velocity and acceleration thresholds for rotational optic flow were significantly lower than for translational optic flow. The thresholds suggestively decreased with the decreasing particle density of the scene. Finally, it was found that all the rotational and translational thresholds strongly correlate with each other. While the mean values of the thresholds could be used as guidelines to develop virtual reality applications, the high variability between individuals implies that the individual tuning of motion controls would be more effective to reduce cybersickness while minimizing the impact on the experience of immersion

    Adaptive Hexapod Simulator Motion Based on Aircraft Stability

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    This paper determined the feasibility of an adaptive hexapod simulator motion algorithm based on aircraft roll stability. An experiment was conducted that used a transport aircraft model in the Vertical Motion Simulator at NASA Ames Research Center. Eighteen general aviation pilots flew a heading-capture task and a stall task consecutively under four motion configurations: baseline hexapod, adaptive hexapod, optimized hexapod, and full motion. The adaptive motion was more similar to the baseline hexapod motion in the heading-capture task when the aircraft was more stable, and more similar to the optimized hexapod motion in the stall task when the aircraft was more unstable. Pilot motion ratings and task performance in the heading-capture task under the adaptive hexapod motion were more similar to baseline hexapod motion compared to optimized hexapod motion. However, motion ratings and task performance in the stall task under the adaptive motion were not significantly more similar to the optimized hexapod motion compared to baseline hexapod motion. Motion ratings and overall task performance under optimized hexapod motion as opposed to baseline hexapod motion were always more similar to the full motion condition. This paper showed that adaptive motion based on aircraft stability is feasible and can be implemented in a straightforward way. More research is required to test the adaptive motion algorithm in different tasks

    Estimation of Time-Varying Pilot Model Parameters

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    Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior

    Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

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    Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes

    Effects of Retinal Eccentricity on Human Manual Control

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    This study investigated the effects of viewing a primary flight display at different retinal eccentricities on human manual control behavior and performance. Ten participants performed a pitch tracking task while looking at a simplified primary flight display at different horizontal and vertical retinal eccentricities, and with two different controlled dynamics. Tracking performance declined at higher eccentricity angles and participants behaved more nonlinearly. The visual error rate gain increased with eccentricity for single-integrator-like controlled dynamics, but decreased for double-integrator-like dynamics. Participants' visual time delay was up to 100 ms higher at the highest horizontal eccentricity compared to foveal viewing. Overall, vertical eccentricity had a larger impact than horizontal eccentricity on most of the human manual control parameters and performance. Results might be useful in the design of displays and procedures for critical flight conditions such as in an aerodynamic stall

    Effects of Motion Cues on the Training of Multi-Axis Manual Control Skills

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    The study described in this paper investigated the effects of two different hexapod motion configurations on the training and transfer of training of a simultaneous roll and pitch control task. Pilots were divided between two groups which trained either under a baseline hexapod motion condition, with motion typically provided by current training simulators, or an optimized hexapod motion condition, with increased fidelity of the motion cues most relevant for the task. All pilots transferred to the same full-motion condition, representing motion experienced in flight. A cybernetic approach was used that gave insights into the development of pilots use of visual and motion cues over the course of training and after transfer. Based on the current results, neither of the hexapod motion conditions can unambiguously be chosen as providing the best motion for training and transfer of training of the used multi-axis control task. However, the optimized hexapod motion condition did allow pilots to generate less visual lead, control with higher gains, and have better disturbance-rejection performance at the end of the training session compared to the baseline hexapod motion condition. Significant adaptations in control behavior still occurred in the transfer phase under the full-motion condition for both groups. Pilots behaved less linearly compared to previous single-axis control-task experiments; however, this did not result in smaller motion or learning effects. Motion and learning effects were more pronounced in pitch compared to roll. Finally, valuable lessons were learned that allow us to improve the adopted approach for future transfer-of-training studies

    Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

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    A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces

    Transfer-of-Training Research at NASA Ames Research Center

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    In this presentation, I will first give an overview of some of the research being performed at the Human Systems Integration Division of NASAs Ames Research Center. In the second part of the presentation, I will discuss two studies that investigate the effects of simulator motion on pilot transfer of training. In a study funded by the Federal Aviation Administration, task performance is used to investigate the effects of motion on the training of 4 challenging tasks in a transport category aircraft. In addition, the effectiveness of recently proposed objective motion cueing criteria for training simulators are evaluated. The second study, part of the NASA Aeronautics Research Program, focuses on optimizing simulator motion for maximum transfer of stall recovery training and utilizes a cybernetic approach to measure transfer of training

    Effects of False Tilt Cues on the Training of Manual Roll Control Skills

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    This paper describes a transfer-of-training study performed in the NASA Ames Vertica lMotion Simulator. The purpose of the study was to investigate the effect of false tilt cues on training and transfer of training of manual roll control skills. Of specific interest were the skills needed to control unstable roll dynamics of a mid-size transport aircraft close to the stall point. Nineteen general aviation pilots trained on a roll control task with one of three motion conditions: no motion, roll motion only, or reduced coordinated roll motion. All pilots transferred to full coordinated roll motion in the transfer session. A novel multimodal pilot model identification technique was successfully applied to characterize how pilots' use of visual and motion cues changed over the course of training and after transfer. Pilots who trained with uncoordinated roll motion had significantly higher performance during training and after transfer, even though they experienced the false tilt cues. Furthermore, pilot control behavior significantly changed during the two sessions, as indicated by increasing visual and motion gains, and decreasing lead time constants. Pilots training without motion showed higher learning rates after transfer to the full coordinated roll motion case
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