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Redirecting Walking and Driving for Natural Navigation in Immersive Virtual Environments

机译:在沉浸式虚拟环境中为自然导航重定向步行和驾驶

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Walking is the most natural form of locomotion for humans, and real walking interfaces have demonstrated their benefits for several navigation tasks. With recently proposed redirection techniques it becomes possible to overcome space limitations as imposed by tracking sensors or laboratory setups, and, theoretically, it is now possible to walk through arbitrarily large virtual environments. However, walking as sole locomotion technique has drawbacks, in particular, for long distances, such that even in the real world we tend to support walking with passive or active transportation for longerȁ3;distance travel. In this article we show that concepts from the field of redirected walking can be applied to movements with transportation devices. We conducted psychophysical experiments to determine perceptual detection thresholds for redirected driving, and set these in relation to results from redirected walking. We show that redirected walkingȁ3;andȁ3;driving approaches can easily be realized in immersive virtual reality laboratories, e. g., with electric wheelchairs, and show that such systems can combine advantages of real walking in confined spaces with benefits of using vehiclebased selfȁ3;motion for longerȁ3;distance travel.
机译:步行是人类最自然的运动形式,并且真实的步行界面已经证明了其在一些导航任务中的优势。使用最近提出的重定向技术,有可能克服跟踪传感器或实验室设置所施加的空间限制,并且从理论上讲,现在可以遍历任意大型虚拟环境。但是,步行作为唯一的运动技术存在弊端,特别是对于长途旅行而言,这样,即使在现实世界中,我们也倾向于支持被动或主动运输方式进行更长距离的ȁ3步行。在本文中,我们展示了重定向步行领域的概念可以应用于带有运输设备的运动。我们进行了心理物理实验,以确定重定向驾驶的知觉检测阈值,并将这些阈值与重定向步行的结果相关联。我们证明重定向的步行ȁ3和ȁ3驾驶方法可以在沉浸式虚拟现实实验室中轻松实现。例如,使用电动轮椅,并证明了这样的系统可以将在狭窄空间中真实行走的优点与使用基于车辆的自我ȁ3,更长的motion3的运动以及远距离旅行的好处结合起来。

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