This work presents REFLEX: Robotic Explanations to FaiLures and Human EXpressions, a comprehensive multimodal dataset capturing human reactions to robot failures and subsequent explanations in collaborative settings. It aims to facilitate research into human-robot interaction dynamics, addressing the need to study reactions to both initial failures and explanations, as well as the evolution of these reactions in long-term interactions. By providing rich, annotated data on human responses to different types of failures, explanation levels, and explanation varying strategies, the dataset contributes to the development of more robust, adaptive, and satisfying robotic systems capable of maintaining positive relationships with human collaborators, even during challenges like repeated failures.

翻译：本研究提出REFLEX（Robotic Explanations to FaiLures and Human EXpressions）数据集，这是一个在协作场景中捕获人类对机器人故障及后续解释反应的综合多模态数据集。该数据集旨在促进人机交互动态研究，满足对初始故障反应、解释反应以及长期交互中这些反应演变的研究需求。通过提供关于人类对不同故障类型、解释层级和解释策略反应的丰富标注数据，本数据集有助于开发更鲁棒、自适应且令人满意的机器人系统，使其即使在面临重复故障等挑战时，仍能维持与人类协作伙伴的积极关系。