Redirected walking for exploration of unknown environments

IF 3.2 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Frontiers in virtual reality Pub Date : 2024-01-08 DOI:10.3389/frvir.2023.1259816
Mathieu Lutfallah, Marco Ketzel, Andreas M. Kunz
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Abstract

Real walking is the most natural locomotion method for exploring Virtual Environments (VE), enhancing the immersion of Virtual Reality (VR). Redirected Walking (RDW) is employed to enable real walking within limited tracking spaces in large VEs by subtly manipulating the mapping between the virtual and real environments. However, the effectiveness of RDW is greatly influenced by the convex shape and size of the manually defined physical tracking space, subsequently impacting the user’s immersive experience. To improve performance, one strategy is to integrate exploration methods from mobile robotics with RDW. This will expand the usable tracking space, facilitating dynamic environments and rapid exploration. For this, we adapted a Unity framework for an RDW algorithm to facilitate simulations for such an exploration. We conducted a simulation with artificially created non-convex explorable tracking spaces and pre-recorded path elements, simulating two adapted RDW artificial potential field (APF) concepts. Three conceptualized modes were applied: repulsive APF, exploration APF, and exploration APF with a distance threshold. Additionally, one APF was extended with a frontier-based exploration approach that utilized the path between the user’s position and a targeted frontier. The analysis revealed a significant trade-off between exploration and immersion. APF combined with frontier-based the exploration technique showed the fastest exploration speed, but - however - resulted in the lowest distance between resets.
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探索未知环境的定向行走
真实行走是探索虚拟环境(VE)最自然的运动方式,可增强虚拟现实(VR)的沉浸感。重定向行走(RDW)通过巧妙地操纵虚拟环境和现实环境之间的映射,可在大型虚拟环境的有限跟踪空间内实现真实行走。然而,RDW 的有效性在很大程度上受到手动定义的物理跟踪空间的凸形和大小的影响,进而影响用户的沉浸式体验。为了提高性能,一种策略是将移动机器人探索方法与 RDW 相结合。这将扩大可用的跟踪空间,促进动态环境和快速探索。为此,我们对 RDW 算法的 Unity 框架进行了改编,以促进这种探索的模拟。我们利用人工创建的非凸可探索跟踪空间和预先录制的路径元素进行了模拟,模拟了两个经过改编的 RDW 人工势场 (APF) 概念。应用了三种概念化模式:排斥式人工势场、探索式人工势场和带有距离阈值的探索式人工势场。此外,一个 APF 还扩展了基于前沿的探索方法,该方法利用了用户位置与目标前沿之间的路径。分析表明,探索和沉浸感之间存在着明显的权衡。APF 与基于前沿的探索技术相结合,显示出最快的探索速度,但重置之间的距离却最小。
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来源期刊
CiteScore
5.80
自引率
0.00%
发文量
0
审稿时长
13 weeks
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