用VR快速测试拟兽机器人的表情表达，发现面部表情最有效。
Evaluating Transferable Emotion Expressions for Zoomorphic Social Robots using VR Prototyping
- 通过VR虚拟原型+触觉反馈，快速测试多种情感表达方式。
- 面部表情识别率最高，混合动物特征与明确信号效果更佳。
- 适合机器人情感设计、人机交互研究者参考使用。
拟兽机器人有望作为宠物的低维护替代品，提供陪伴与福祉。然而，多数此类机器人情感表达有限，难以建立深厚的情感联结。传统硬件原型受物理与后勤限制，难以为继。本研究采用虚拟现实快速原型技术结合被动触觉交互，开展多方法评估情感表达模态，并参与式设计多模态表达方案。结果表明，不同表达方式在可识别性、有效性与用户共情方面存在差异，凸显面部表情的重要性及融合动物特征与明确信号的优势。研究据此提出情感化拟兽机器人设计方向，可通过硬件改造或增强现实实现。同时强调VR原型使该领域对设计者与研究者更具可及性。
原文摘要 · Abstract (English)
Zoomorphic robots have the potential to offer companionship and well-being as accessible, low-maintenance alternatives to pet ownership. Many such robots, however, feature limited emotional expression, restricting their potential for rich affective relationships with everyday domestic users. Additionally, exploring this design space using hardware prototyping is obstructed by physical and logistical constraints. We leveraged virtual reality rapid prototyping with passive haptic interaction to conduct a broad mixed-methods evaluation of emotion expression modalities and participatory prototyping of multimodal expressions. We found differences in recognisability, effectiveness and user empathy between modalities while highlighting the importance of facial expressions and the benefits of combining animal-like and unambiguous modalities. We use our findings to inform promising directions for the affective zoomorphic robot design and potential implementations via hardware modification or augmented reality, then discuss how VR prototyping makes this field more accessible to designers and researchers.
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