用大模型驱动机器人，帮自闭症儿童和家长一起调节情绪。
Towards Emotion Co-regulation with LLM-powered Socially Assistive Robots: Integrating LLM Prompts and Robotic Behaviors to Support Parent-Neurodivergent Child Dyads
- 将大模型提示与机器人行为结合，实现亲子共调节干预。
- 试点测试显示机器人改善互动动态，助力情绪调节。
- 适合心理干预、智能陪护领域研究者参考。
社交助手机器人（SAR）在支持神经多样性儿童情绪调节方面展现出潜力。近年来，利用先进技术辅助家长与孩子共同调节情绪受到关注，但将大语言模型（LLMs）与SAR整合以促进亲子间情绪共调节的研究仍有限。为此，我们基于MiRo-E机器人平台部署语音通信模块，开发了一款由大模型驱动的自主社交机器人系统。该系统通过集成LLM提示与机器人行为，为家长和神经多样性儿童提供定制化干预。在两个亲子二元组上进行了试点测试，并开展定性分析。结果表明，MiRo-E对互动动态产生积极影响，具备促进情绪调节的潜力，同时也暴露出设计与技术挑战。基于这些发现，我们提出设计建议，以推动未来大模型赋能社交助手机器人在心理健康应用中的发展。
原文摘要 · Abstract (English)
Socially Assistive Robotics (SAR) has shown promise in supporting emotion regulation for neurodivergent children. Recently, there has been increasing interest in leveraging advanced technologies to assist parents in co-regulating emotions with their children. However, limited research has explored the integration of large language models (LLMs) with SAR to facilitate emotion co-regulation between parents and children with neurodevelopmental disorders. To address this gap, we developed an LLM-powered social robot by deploying a speech communication module on the MiRo-E robotic platform. This supervised autonomous system integrates LLM prompts and robotic behaviors to deliver tailored interventions for both parents and neurodivergent children. Pilot tests were conducted with two parent-child dyads, followed by a qualitative analysis. The findings reveal MiRo-E's positive impacts on interaction dynamics and its potential to facilitate emotion regulation, along with identified design and technical challenges. Based on these insights, we provide design implications to advance the future development of LLM-powered SAR for mental health applications.
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