Wan Dayu, Guo Xiaolei, Dong Jiahui, Mousas Christos, Chen Yingjie
Purdue University, USA.
Proc ACM Comput Graph Interact Tech. 2023 May;6(1). doi: 10.1145/3585502. Epub 2023 May 16.
The use of virtual reality (VR) in laboratory skill training is rapidly increasing. In such applications, users often need to explore a large virtual environment within a limited physical space while completing a series of hand-based tasks (e.g., object manipulation). However, the most widely used controller-based teleport methods may conflict with the users' hand operation and result in a higher cognitive load, negatively affecting their training experiences. To alleviate these limitations, we designed and implemented a locomotion method called ManiLoco to enable hands-free interaction and thus avoid conflicts and interruptions from other tasks. Users can teleport to a remote object's position by taking a step toward the object while looking at it. We evaluated ManiLoco and compared it with state-of-the-art Point & Teleport in a within-subject experiment with 16 participants. The results confirmed the viability of our foot- and head-based approach and better support concurrent object manipulation in VR training tasks. Furthermore, our locomotion method does not require any additional hardware. It solely relies on the VR head-mounted display (HMD) and our implementation of detecting the user's stepping activity, and it can be easily applied to any VR application as a plugin.
虚拟现实(VR)在实验室技能培训中的应用正在迅速增加。在这类应用中,用户在完成一系列基于手部的任务(如物体操作)时,通常需要在有限的物理空间内探索一个大型虚拟环境。然而,最广泛使用的基于控制器的瞬移方法可能会与用户的手部操作产生冲突,并导致更高的认知负荷,对他们的训练体验产生负面影响。为了缓解这些限制,我们设计并实现了一种名为ManiLoco的移动方法,以实现免手持交互,从而避免与其他任务产生冲突和干扰。用户在看着远程物体的同时朝它迈出一步,就可以瞬移到该物体的位置。我们对ManiLoco进行了评估,并在一项有16名参与者的受试者内实验中将其与最先进的指向与瞬移方法进行了比较。结果证实了我们基于脚部和头部的方法的可行性,并在VR训练任务中更好地支持并发物体操作。此外,我们的移动方法不需要任何额外的硬件。它仅依赖于VR头戴式显示器(HMD)以及我们对用户脚步活动检测的实现,并且可以作为插件轻松应用于任何VR应用程序。