十年的人机交互通过沉浸式镜头：回顾扩展现实作为社交机器人研究工具的综述
A Decade of Human-Robot Interaction Through Immersive Lenses: Reviewing Extended Reality as a Research Instrument in Social Robotics
AI总结：
本文综述了过去十年中扩展现实作为社交机器人研究工具的应用现状，指出其在实证研究中的不足，并提出四阶段路线图以推动其发展。
摘要：
在过去十年中，扩展现实（XR），包括虚拟、增强和混合现实，获得了在人机交互研究中的关注，但尚未在社交机器人的实证研究中得到充分探索。为了映射该领域，我们系统地回顾了2015至2025年间发表的实证研究。在6527篇同行评审文章中，只有33篇符合严格纳入标准。我们考察了（1）XR和虚拟社交机器人如何被使用，重点在于所使用的软件和硬件以及它们部署的应用场景，（2）数据收集和分析方法，（3）研究者和参与者的 demographics，以及（4）挑战和未来方向。我们的发现表明，社交XR-HRI研究仍然由实验室模拟驱动，而关键规格——如硬件、软件和机器人——往往未被报告。机器人通常作为被动且几乎不互动的视觉刺激，而现代头戴式显示器的丰富生物信号（如眼动追踪）和记录（如运动捕捉）功能仍 largely 未被利用。尽管在 demographics 报告中存在差距，但研究团队和样本主要是技术导向的、西方的、年轻的和男性化的。主要限制包括硬件延迟、小而同质的样本和短研究周期。我们提出了一条四阶段路线图，以建立社交XR-HRI作为可靠的研究所用工具，包括（1）加强应用场景，（2）更多稳健且可测试的技术迭代，（3）在样本和研究团队中嵌入多样性，以及（4）报告标准，例如以合适的方法学分类形式呈现。在这些方向上取得进展对于XR从实验室原型发展为社交机器人研究的生态效度工具至关重要。
英文摘要：
Over the past decade, Extended Reality (XR), including Virtual, Augmented, and Mixed Reality, gained attention as a research instrument in human-robot interaction studies, but remains underexplored in empirical investigations of social robotics. To map the field, we systematically reviewed empirical studies from 2015 to 2025. Of 6,527 peer-reviewed articles, only 33 met strict inclusion criteria. We examined (1) how XR and virtual social robots are used, focusing on the software and hardware employed and the application contexts in which they are deployed, (2) data collection and analysis methods, (3) demographics of the researchers and participants, and (4) the challenges and future directions. Our findings show that social XR-HRI research is still driven by laboratory simulations, while crucial specifications - such as the hardware, software, and robots used - are often not reported. Robots typically act as passive and hardly interactive visual stimulus, while the rich biosignal (e.g., eye-tracking) and logging (e.g. motion capturing) functions of modern head-mounted displays remain largely untapped. While there are gaps in demographic reporting, the research teams and samples are predominantly tech-centric, Western, young, and male. Key limitations include hardware delays, small homogeneous samples, and short study cycles. We propose a four-phase roadmap to establish social XR-HRI as a reliable research medium, which includes (1) strengthen application contexts, (2) more robust and testable technological iterations, (3) embedding diversity in samples and research teams, and (4) the need for reporting standards, e.g., in form of a suitable taxonomy. Advancing in these directions is essential for XR to mature from a lab prototype into an ecologically valid research instrument for social robotics.
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