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首页> 外文会议>Head- and helmet-mounted displays XV: Design and applications >Measurement and Reduction of System Latency in See-Through Helmet Mounted Display (HMD) Systems
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Measurement and Reduction of System Latency in See-Through Helmet Mounted Display (HMD) Systems

机译：测量和减少透明头盔显示器（HMD）系统中的系统延迟

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摘要

Future military aviation platforms such as the proposed Joint Strike Fighter F-35 will integrate helmet mounted displays (HMDs) with the avionics and weapon systems to the degree that the HMDs will become the aircraft's primary display system. In turn, training of pilot flight skills using HMDs will be essential in future training systems. In order to train these skills using simulation based training, improvements must be made in the integration of HMDs with out-the-window (OTW) simulations. Currently, problems such as latency contribute to the onset of simulator sickness and provide distractions during training with HMD simulator systems that degrade the training experience. Previous research has used Kalman predictive filters as a means of mitigating the system latency present in these systems. While this approach has yielded some success, more work is needed to develop innovative and improved strategies that reduce system latency as well as to include data collected from the user perspective as a measured variable during test and evaluation of latency reduction strategies. The purpose of this paper is twofold. First, the paper describes a new method to measure and assess system latency from the user perspective. Second, the paper describes use of the testbed to examine the efficacy of an innovative strategy that combines a customized Kalman filter with a neural network approach to mitigate system latency. Results indicate that the combined approach reduced system latency significantly when compared to baseline data and the traditional Kalman filter. Reduced latency errors should mitigate the onset of simulator sickness and ease simulator sickness symptomology. Implications for training systems will be discussed.
机译：未来的军事航空平台，例如拟议中的联合攻击战斗机F-35，将头盔显示器（HMD）与航空电子和武器系统集成在一起，以使HMD成为飞机的主要显示系统。反过来，在将来的培训系统中，使用HMD训练飞行员飞行技能将至关重要。为了使用基于模拟的训练来训练这些技能，必须改进HMD与窗口（OTW）模拟的集成。当前，诸如等待时间之类的问题加剧了模拟器疾病的发作，并在使用HMD模拟器系统进行训练期间分散了注意力，从而降低了训练体验。先前的研究已使用卡尔曼预测滤波器作为减轻这些系统中存在的系统延迟的一种方法。尽管这种方法取得了一定的成功，但还需要做更多的工作来开发创新和改进的策略，以减少系统等待时间，并将从用户角度收集的数据作为对等待时间减少策略的测试和评估期间的测量变量。本文的目的是双重的。首先，本文描述了一种从用户角度衡量和评估系统延迟的新方法。其次，本文描述了如何使用测试平台来检验将定制的卡尔曼滤波器与神经网络方法相结合以减轻系统延迟的创新策略的有效性。结果表明，与基线数据和传统的卡尔曼滤波器相比，该组合方法显着减少了系统延迟。减少的等待时间错误应减轻模拟器疾病的发作并减轻模拟器疾病的症状。将讨论对培训系统的影响。

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