The current spread of social and assistive robotics applications is increasingly highlighting the need for robots that can be easily taught and interacted with, even by users with no technical background. Still, it is often difficult to grasp what such robots know or to assess if a correct representation of the task is being formed. Augmented Reality (AR) has the potential to bridge this gap. We demonstrate three use cases where AR design elements enhance the explainability and efficiency of human-robot interaction: 1) a human teaching a robot some simple kitchen tasks by demonstration, 2) the robot showing its plan for solving novel tasks in AR to a human for validation, and 3) a robot communicating its intentions via AR while assisting people with limited mobility during daily activities.

翻译：当前社交与辅助机器人应用的广泛普及日益凸显出对易教易用机器人的需求，即便用户不具备技术背景也能轻松操作。然而，人们往往难以理解这类机器人所知内容，或无法评估其是否形成了正确的任务表征。增强现实技术有潜力弥合这一鸿沟。我们通过三个应用场景展示了AR设计元素如何提升人机交互的可解释性与效率：1) 人类通过示范向机器人教授简单厨房任务；2) 机器人在AR中向人类展示其解决新任务的计划以进行验证；3) 机器人在协助行动受限者完成日常活动时通过AR传达其意图。