Abstract
Mental models and expectations underlying human-human interaction (HHI) inform human-robot interaction (HRI) with domestic robots. To ease collaborative home tasks by improving domestic robot speech and behaviours for human-robot communication, we designed a study to understand how people communicated when failure occurs. To identify patterns of natural communication, particularly in response to robotic failures, participants instructed Laundrobot to move laundry into baskets using natural language and gestures. Laundrobot either worked error-free, or in one of two error modes. Participants were not advised Laundrobot would be a human actor, nor given information about error modes. Video analysis from 42 participants found speech patterns, included laughter, verbal expressions, and filler words, such as ``oh'' and ``ok'', also, sequences of body movements, including touching one's own face, increased pointing with a static finger, and expressions of surprise. Common strategies deployed when errors occurred, included correcting and teaching, taking responsibility, and displays of frustration. The strength of reaction to errors diminished with exposure, possibly indicating acceptance or resignation. Some used strategies similar to those used to communicate with other technologies, such as smart assistants. An anthropomorphic robot may not be ideally suited to this kind of task. Laundrobot's appearance, morphology, voice, capabilities, and recovery strategies may have impacted how it was perceived. Some participants indicated Laundrobot's actual skills were not aligned with expectations; this made it difficult to know what to expect and how much Laundrobot understood. Expertise, personality, and cultural differences may affect responses, however these were not assessed.
Abstract (translated)
人类与人类之间的互动（HHI）中的心理模型和期望对人机交互（HRI），特别是家庭机器人而言具有指导意义。为了通过改善家用机器人的语音和行为来简化合作的家庭任务，我们设计了一项研究，旨在了解人们在出现故障时如何进行沟通。 为了识别自然交流的模式，特别是在面对机器人故障时的反应，参与者被要求用自然语言和手势指示Laundrobot（一款洗衣专用机器人）将衣物移动到篮子中。Laundrobot要么可以无错误地完成任务，或者工作在两种不同的错误模式之一下。参与者没有被告知Laundrobot实际上是由人类演员扮演的，也没有获得关于故障模式的信息。 通过对42名参与者的视频分析发现，言语模式包括笑声、口头表达以及诸如“哦”和“好的”这样的填充词有所增加；身体动作序列包括摸自己的脸、用手指指向静止物体的动作以及表现出惊讶的表情。当出现错误时，参与者通常采用纠正和教导机器人、承担责任以及展示挫败感的策略。 对错误的反应强度随着暴露次数的增加而减弱，这可能表明了接受或放弃的心态。一些参与者的沟通方式与他们使用其他技术（如智能助手）时的方式相似。这种类型的任务可能并不适合拟人化的机器人。Laundrobot的外观、形态、声音、能力以及故障恢复策略可能对其被感知的方式产生了影响。 部分参与者表示，Laundrobot的实际技能与其期望不匹配，这使得了解其功能范围和理解能力变得困难。然而，专业知识、个性和文化差异的影响没有在本研究中进行评估。
URL
https://arxiv.org/abs/2504.08395
