arXiv:2512.17241cs.ROcs.HC2025-12

研究服务机器人如何有效与忙碌顾客沟通。

A Service Robot's Guide to Interacting with Busy Customers

  • 用语音、视觉和微动作三种方式测试机器人吸引注意力的效果。
  • 视觉提示最能清晰传达意图,语音虽吸睛但传意效果差。
  • 适合酒店、餐厅等繁忙场景中机器人交互设计参考。

服务机器人在酒店业的应用日益广泛,亟需理解如何有效与分心的顾客沟通。本研究在模拟餐厅场景中,通过使用Temi机器人进行两阶段用户实验(N=24),考察语音、视觉显示和微动作手势在吸引注意力及传达意图方面的有效性。参与者需进行打字游戏(MonkeyType)以模拟忙碌状态,其专注程度通过每分钟打字数(WPM)和准确率衡量。第一阶段比较非语言声学提示与基线条件在单杯配送任务中吸引注意力的效果;第二阶段评估语音、视觉、微动作及其多模态组合在双杯配送任务中传递“正确选杯”意图的有效性。结果显示,语音在吸引注意力方面表现优异,但在传达意图上效果不佳;视觉提示在意图清晰度上得分最高,其次为语音,微动作表现最弱。研究揭示了注意力吸引与意图传达的不同作用,为动态服务场景中机器人沟通策略优化提供了依据。

原文摘要 · Abstract (English)

The growing use of service robots in hospitality highlights the need to understand how to effectively communicate with pre-occupied customers. This study investigates the efficacy of commonly used communication modalities by service robots, namely, acoustic/speech, visual display, and micromotion gestures in capturing attention and communicating intention with a user in a simulated restaurant scenario. We conducted a two-part user study (N=24) using a Temi robot to simulate delivery tasks, with participants engaged in a typing game (MonkeyType) to emulate a state of busyness. The participants' engagement in the typing game is measured by words per minute (WPM) and typing accuracy. In Part 1, we compared non-verbal acoustic cue versus baseline conditions to assess attention capture during a single-cup delivery task. In Part 2, we evaluated the effectiveness of speech, visual display, micromotion and their multimodal combination in conveying specific intentions (correct cup selection) during a two-cup delivery task. The results indicate that, while speech is highly effective in capturing attention, it is less successful in clearly communicating intention. Participants rated visual as the most effective modality for intention clarity, followed by speech, with micromotion being the lowest ranked.These findings provide insights into optimizing communication strategies for service robots, highlighting the distinct roles of attention capture and intention communication in enhancing user experience in dynamic hospitality settings.

服务机器人人机交互注意力吸引多模态通信

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