研究低自由度机器人如何通过有限动作传递情绪，发现人们能准确感知情绪基调但难辨具体情绪。
Emotional Expression in Low-Degrees-of-Freedom Robots: Assessing Perception with Reachy Mini
- 用100人观看机器人视频，测试其简单动作传递情绪的效果。
- 对愤怒、悲伤等情绪识别率较高，但爱、羞耻等较难分辨。
- 即使动作简单，情绪表达仍影响人们对机器人的社交评价。
情绪表达在人机交互中至关重要，但人们对缺乏类人表达能力的低自由度机器人如何理解情感仍知之甚少。本研究考察了Reachy Mini（Pollen Robotics与Hugging Face联合开发）这一低自由度机器人在受限非人形表达下的情绪感知效果。在一项在线被试内实验中，100名参与者观看了10段机器人表现不同情绪的短视频，对每段视频判断感知情绪、评估情绪效价与唤醒度，并评价机器人社会属性。总体上，精确情绪识别水平一般，且在不同情绪间差异显著：愤怒、悲伤和兴趣识别更可靠，而爱、愉悦、羞耻和厌恶等情绪识别困难。然而，参与者在恢复情绪基调（如效价与唤醒度）方面表现更好。情绪表达也显著影响社交评价——积极情绪使机器人被视为更温暖、更具社交性，而拟人性在各条件间变化较小。结果表明，即使表达受限，机器人仍可传递有效情感信息并塑造社交印象，支持将Reachy Mini作为低自由度机器人情感通信研究的基准平台。
原文摘要 · Abstract (English)
Emotion expression is central to human--robot interaction, yet little is known about how people interpret affect on robots with sparse, non-anthropomorphic expressive capabilities. This study examined how people perceive emotional expressions displayed by Reachy Mini (Pollen Robotics and Hugging Face), a low-degree-of-freedom (low-DoF) robot with a constrained and distinctly non-human expressive repertoire. In an online within-subjects study, 100 participants viewed 10 short video clips of Reachy Mini expressing different emotions and, for each clip, identified the perceived emotion, rated its valence and arousal, and evaluated the robot on social-perception traits. Exact emotion recognition was modest overall and varied considerably across expressions, with anger, sadness, and interest recognized more reliably than emotions such as love, pleasure, shame, and disgust. However, participants were generally more successful at recovering broader affective meaning than exact emotion labels, particularly along valence and arousal dimensions. Emotional expressions also shaped social evaluation, as positive expressions were perceived as warmer and more sociable than negative ones, and animacy varied less across conditions. These findings suggest that even constrained robotic expressions can communicate affective meaning and influence social impressions, positioning Reachy Mini as a useful benchmark for studying affective communication in low-DoF robots.
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