发表机构
Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich (TUM); Centre for Applied Autonomous Sensor Systems (AASS), Örebro University; Robotics Insitute Germany (RIG)（慕尼黑工业大学慕尼黑机器人与机器智能研究所 (MIRMI); 厄勒布鲁大学应用自主传感器系统中心 (AASS); 德国机器人研究所 (RIG)）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究在协作式词语联想游戏中机器人注视对人类视觉注意力的影响及人类是否向机器人寻求确认注视，通过与NAO机器人实验，用多种方式分析互动，发现任务语言方面掩盖注视影响，为相关设计提供见解。
AI 中文摘要
机器人注视是人机对话协调的主要组成部分。大多数人机对话注视研究集中在面对面社交对话，对要求高的任务型互动中的注视了解甚少。本文研究机器人游戏伙伴的注视如何影响人类视觉注意力，以及人类是否倾向于向机器人投以寻求确认的注视。让参与者与作为具身化、由语言模型驱动的对话伙伴的NAO机器人玩协作式词语联想游戏。实验在两种条件下进行，分别实现机器人的相互注视和参照注视。用眼部追踪眼镜记录参与者注视，并用注视坐标、语音片段、关键事件和兴趣区域分析互动。发现机器人注视方向不影响首次注视机器人提出词语的时间。还发现与无确认请求时相比，对话中有确认请求时参与者更常注视机器人。结果表明（可能也因游戏认知要求高）该任务的语言方面掩盖了机器人参照注视的影响。这些发现为设计和验证协作任务中机器人注视和轮流行为提供了有价值的见解。
英文摘要
Robot gaze is a major component of human-robot dialogue coordination. Most studies of gaze in human-robot dialogue focus on face-to-face social conversations, but little is known about gaze in demanding task-focused interactions. In this paper, we investigate how the gaze of a robot game partner affects human visual attention and if humans tend to direct confirmation-seeking gazes towards the robot. In our study, we let participants play a collaborative word association game with a NAO robot acting as an embodied, LLM-driven conversational partner. Our experiments are conducted under two conditions, which implement mutual and referential gazes of the robot respectively. We record participants' gaze using eye tracking glasses and analyze the interactions using gaze coordinates, speech segments, key events and areas of interests. We find that robot gaze orientation does not affect the time to first fixation on words the robot proposed. We also find that participants gaze more often at the robot when their dialogue line contains confirmation requests, compared to when it does not. Our results indicate (likely also due to the cognitively demanding nature of the game) that the verbal aspect of this task overshadows the effects of referential robot gaze. These findings offer valuable insights for designing and validating robot gaze and turn-taking behavior in collaborative tasks which require coordination and efficient communication.
CommentsThis paper has been accepted as a Late-Breaking Report to the 35th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), which will be held in Kitakyushu, Netherlands on August 24-28, 2026. Copyright 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses
