Virtual borders are employed to allow humans the interactive and flexible restriction of their mobile robots' workspaces in human-centered environments, e.g. to exclude privacy zones from the workspace or to indicate certain areas for working. They have been successfully specified in interaction processes using methods from human-robot interaction. However, these methods often lack an expressive feedback system, are restricted to robot's on-board interaction capabilities and require a direct line of sight between human and robot. This negatively affects the user experience and interaction time. Therefore, we investigate the effect of a smart environment on the teaching of virtual borders with the objective to enhance the perceptual and interaction capabilities of a robot. For this purpose, we propose a novel interaction method based on a laser pointer, that leverages a smart home environment in the interaction process. This interaction method comprises an architecture for a smart home environment designed to support the interaction process, the cooperation of human, robot and smart environment in the interaction process, a cooperative perception including stationary and mobile cameras to perceive laser spots and an algorithm to extract virtual borders from multiple camera observations. The results of an experimental evaluation support our hypotheses that our novel interaction method features a significantly shorter interaction time and a better user experience compared to an approach without support of a smart environment. Moreover, the interaction method does not negatively affect other user requirements concerning completeness and accuracy.

中文翻译：

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智能家居环境中对移动机器人工作空间的交互式限制

虚拟边界用于允许人员在以人为中心的环境中对其移动机器人的工作区进行交互且灵活的限制，例如从工作区中排除隐私区域或指示某些工作区域。已使用人机交互方法在交互过程中成功指定了它们。但是，这些方法通常缺乏表现力的反馈系统，仅限于机器人的机载交互功能，并且需要人与机器人之间有直接的视野。这会对用户体验和交互时间产生负面影响。因此，我们研究了智能环境对虚拟边界教学的影响，目的是增强机器人的感知和交互能力。以此目的，我们提出了一种基于激光笔的新颖交互方法，该方法在交互过程中利用了智能家居环境。这种交互方法包括用于支持交互过程的智能家居环境的体系结构，交互过程中人，机器人和智能环境的协作，包括静止和移动相机的协同感知（感知激光点）以及提取虚拟图像的算法。多个相机观察结果的边界。实验评估的结果支持了我们的假设，即与不支持智能环境的方法相比，我们新颖的交互方法具有明显缩短的交互时间和更好的用户体验。而且，