让机器人和孩子共编故事，测试其社交互动能力
Would you let a humanoid play storytelling with your child? A usability study on LLM-powered narrative Human-Robot Interaction
- 用大模型增强机器人感知社交线索能力
- 人机共同编故事，用户满意度高
- 适合教育、康复场景中的交互研究
人机交互研究的关键挑战在于开发能有效感知和理解社交线索的机器人系统，以实现自然且自适应的互动。本文提出一种新框架，通过整合先进感知能力，使iCub人形机器人能够识别社交线索、借助生成模型（如ChatGPT）理解环境，并以符合情境的社交行为作出回应。具体设计了一个叙事交互任务——由人与机器人轮流使用带有创意图像的积木共同创作一段虚构故事。为验证该协议与框架的有效性，开展了实验，量化了用户对系统可用性和体验质量的感知。结果表明，该系统在辅助、教育及康复等需要高度社会意识与响应性的场景中具有显著应用潜力。
原文摘要 · Abstract (English)
A key challenge in human-robot interaction research lies in developing robotic systems that can effectively perceive and interpret social cues, facilitating natural and adaptive interactions. In this work, we present a novel framework for enhancing the attention of the iCub humanoid robot by integrating advanced perceptual abilities to recognise social cues, understand surroundings through generative models, such as ChatGPT, and respond with contextually appropriate social behaviour. Specifically, we propose an interaction task implementing a narrative protocol (storytelling task) in which the human and the robot create a short imaginary story together, exchanging in turn cubes with creative images placed on them. To validate the protocol and the framework, experiments were performed to quantify the degree of usability and the quality of experience perceived by participants interacting with the system. Such a system can be beneficial in promoting effective human robot collaborations, especially in assistance, education and rehabilitation scenarios where the social awareness and the robot responsiveness play a pivotal role.
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