Robots are increasingly used in shared environments with humans, making effective communication a necessity for successful human-robot interaction. In our work, we study a crucial component: active communication of robot intent. Here, we present an anthropomorphic solution where a humanoid robot communicates the intent of its host robot acting as an "Anthropomorphic Robotic Mock Driver" (ARMoD). We evaluate this approach in two experiments in which participants work alongside a mobile robot on various tasks, while the ARMoD communicates a need for human attention, when required, or gives instructions to collaborate on a joint task. The experiments feature two interaction styles of the ARMoD: a verbal-only mode using only speech and a multimodal mode, additionally including robotic gaze and pointing gestures to support communication and register intent in space. Our results show that the multimodal interaction style, including head movements and eye gaze as well as pointing gestures, leads to more natural fixation behavior. Participants naturally identified and fixated longer on the areas relevant for intent communication, and reacted faster to instructions in collaborative tasks. Our research further indicates that the ARMoD intent communication improves engagement and social interaction with mobile robots in workplace settings.

翻译：机器人越来越多地应用于与人共享的环境中，这使得有效通信成为成功人机交互的关键。在本研究中，我们聚焦于一个核心要素：机器人意图的主动传递。为此，我们提出一种拟人化解决方案：由人形机器人作为“拟人化机器人驾驶模拟器”（ARMoD）来传递宿主机器人的意图。我们通过两项实验评估该方法：实验参与者与移动机器人协作完成不同任务，而ARMoD在需要时传递请求人类注意的信号，或发出指令以协作完成联合任务。实验设计了两种ARMoD交互模式：纯语言模式（仅使用语音）和多模态模式（除语音外，还结合机器人注视与指向手势以支持空间意图传递）。结果表明，包含头部运动、眼神注视及指向手势的多模态交互方式能引导更自然的注视行为——参与者会本能地更长时间注视与意图通信相关的区域，并在协作任务中对指令的反应速度更快。本研究进一步表明，ARMoD的意图通信机制可提升工作场景中与移动机器人的互动参与度及社交交互质量。