通过混合现实捕捉人类示范，让机器人实时生成自然情感表达。
Generation of Real-time Robotic Emotional Expressions Learning from Human Demonstration in Mixed Reality
- 用混合现实让专家以第一视角操控虚拟机器人，记录表情与动作
- 基于流匹配生成模型，实现情绪驱动的实时多样化行为输出
- 适合人机交互、情感计算领域研究者参考
机器人的情感表达在与人类互动时至关重要。本文提出一种框架，可基于混合现实（MR）中捕捉的人类专家示范，自动生成真实且多样的机器人情感表达。系统允许专家以第一人称视角远程操控虚拟机器人，采集其面部表情、头部动作及上半身手势，并映射到机器人的眼睛、耳朵、颈部和手臂等部件。利用基于流匹配的生成过程，模型能够根据给定的情绪状态，实时响应移动物体，生成连贯且多样的行为。初步测试验证了该方法在生成自主情感表达方面的有效性。
原文摘要 · Abstract (English)
Expressive behaviors in robots are critical for effectively conveying their emotional states during interactions with humans. In this work, we present a framework that autonomously generates realistic and diverse robotic emotional expressions based on expert human demonstrations captured in Mixed Reality (MR). Our system enables experts to teleoperate a virtual robot from a first-person perspective, capturing their facial expressions, head movements, and upper-body gestures, and mapping these behaviors onto corresponding robotic components including eyes, ears, neck, and arms. Leveraging a flow-matching-based generative process, our model learns to produce coherent and varied behaviors in real-time in response to moving objects, conditioned explicitly on given emotional states. A preliminary test validated the effectiveness of our approach for generating autonomous expressions.
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