评估自适应扩展现实在现实-虚拟连续体上对人机交互的影响
Evaluating the Impact of Adaptive Extended Reality on Human-Robot Interaction Across the Reality-Virtuality Continuum
- Ritsumeikan University（立命馆大学）
- Université catholique de Louvain (UCLouvain)（鲁汶大学）
- Kyoto University（京都大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究通过对比固定与动态XR模态的实验，证明沿现实-虚拟连续体自适应调整界面能提升人机交互性能，降低工作负荷，实现更高吞吐量。
AI中文摘要：
随着发达国家人口老龄化加剧和劳动力短缺问题日益严重，控制论化身（Cybernetic Avatars, CAs）被提出通过机器人具身来扩展人类能力，这需要有效的人机交互（Human-Robot Interaction, HRI）框架。扩展现实（Extended Reality, XR）是增强现实（Augmented Reality, AR）、增强虚拟（Augmented Virtuality, AV）和虚拟现实（Virtual Reality, VR）的总称，提供了此类界面，但以往研究通常固定XR模态，未评估其对任务结果的影响。本研究探讨XR模态是否影响HRI性能，以及沿现实-虚拟连续体（Reality-Virtuality Continuum, RVC）在运行时调整虚拟化程度的自适应界面是否能提升性能。一个与移动机械臂交互的自定义XR应用支持沉浸式控制和运行时模态切换。在受试者内多房间拾取与放置实验中，通过任务指标、NASA-TLX和系统可用性量表（System Usability Scale, SUS）比较固定AR、AV、VR与动态RVC，研究表明：1）固定现实模态影响HRI结果；2）沿RVC动态改变模态可改善结果。AR在心理需求、努力和挫败感方面显著低于AV和VR，而动态RVC条件实现了最高吞吐量和最低工作负荷，凸显了自适应XR界面在人机共生中的价值。实现代码可在该https URL获取。
英文摘要：
As populations in developed countries age and labor shortages intensify, Cybernetic Avatars (CAs) are proposed to extend human capabilities through robotic embodiments, requiring effective Human-Robot Interaction (HRI) frameworks. Extended Reality (XR), an umbrella term for Augmented Reality (AR), Augmented Virtuality (AV), and Virtual Reality (VR), offers such interfaces, but prior research typically fixes the XR modality without evaluating its effect on task outcomes. This study examines whether the XR modality impacts HRI performance and whether an adaptive interface adjusting the level of virtuality along the Reality-Virtuality Continuum (RVC) at runtime improves it. A custom XR application interfaced with a mobile manipulator supports immersive control and runtime modality switching. In a within-participant multi-room pick-and-place experiment comparing fixed AR, AV, and VR with dynamic RVC through task metrics, the NASA-TLX, and the System Usability Scale (SUS), this study demonstrates that 1) the fixed reality modality affects HRI results, and 2) dynamically changing the modality along the RVC improves them. AR yielded significantly lower mental demand, effort, and frustration than AV and VR, while the dynamic RVC condition achieved the highest throughput and lowest workload, highlighting the value of adaptive XR interfaces for human-robot symbiosis. The implementation is available at https://github.com/CarlTornberg/XR-HRI.
