Robotic eye-gaze-based cueing has been studied and proved to be effective, in controlled environments, in achieving social functions as humans gaze. However, its dynamic adaptability in various real interactions has not been explored in-depth. This paper addresses a case where a simplistic robotic gaze fails to achieve effective social cueing in human–robot communication, primarily due to in-attentional blindness (IB), and presents a method that enables the robot to deliver gaze-based social signals adequately. To understand the implications of IB and figure out ways to overcome any limitations from IB, which frequently arise in task-oriented situations, we designed a set of 1-on-1 communication experiments consisting of a robotic tutor and human learners participating in multiple-choice quiz sessions (task-oriented situation). Here, multimedia contents were utilized alongside the robot as visual stimuli competing for the human’s attention. We hypothesized that quiz scores would increase when humans successfully recognize the robot’s gaze-based cue signals hinting answers. We compared the impacts of two different cueing methods: oblique cueing (OC), where cues were straightforwardly provided regardless of whether participants were potentially experiencing IB or not, and leading cueing (LC), where cueing procedures were led through achieving eye contact and securing the participants’ attention before signaling the cue. By comparing participants’ test scores achieved by the control group with no cueing (NC) and two experimental groups of OC and LC, respectively, we found that there was a significant increase in test scores only when the LC method was utilized. This experiment illustrates the importance of proactively guiding a user’s attention through sophisticated interaction design in effectively attaining a user’s attention and successfully delivering cues. In future studies, we aim to evaluate different methods by which a social robot can intentionally shift a human’s attention, such as incorporating stimuli from various multi-modal human communication channels.

中文翻译：

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在面向任务的情况下，针对用户的有效基于机器人注视的社交提示设计：如何克服注意力不集中的情况？

已经研究了基于机器人眼睛注视的提示，并证明在受控环境中，它可以有效地实现人类注视的社会功能。但是，尚未深入探讨其在各种实际交互中的动态适应性。本文介绍了一种情况，其中简单的机器人注视主要是由于注意力不集中（IB）导致无法在人机对话中获得有效的社交提示，并提出了一种使机器人能够充分传递基于注视的社交信号的方法。为了了解IB的含义并找出克服IB局限性的方法，这种局限性经常出现在面向任务的情况下，我们设计了一套1对1交流实验，由机器人导师和人类学习者共同参与，选择测验会话（面向任务的情况）。这里，多媒体内容与机器人一起被用作竞争人类注意力的视觉刺激。我们假设，当人类成功识别出机器人的基于凝视的提示信号提示答案时，测验分数将增加。我们比较了两种不同的提示方法的影响：倾斜提示（OC），无论参与者是否可能经历IB，都直接提供提示；领先提示（LC），通过实现目光接触和固定来引导提示程序在发出提示之前，请参与者注意。通过分别比较没有提示（NC）和两个实验组的OC和LC的参与者的测验分数，我们发现只有使用LC方法时测验分数才会显着增加。该实验说明了通过复杂的交互设计主动引导用户的注意力在有效地获得用户的注意力并成功传递线索方面的重要性。在未来的研究中，我们旨在评估社交机器人可以有意转移人们注意力的不同方法，例如从各种多模式人类交流渠道中引入刺激。