Enabling humans and robots to collaborate effectively requires purposeful communication and an understanding of each other's affordances. Prior work in human-robot collaboration has incorporated knowledge of human affordances, i.e., their action possibilities in the current context, into autonomous robot decision-making. This "affordance awareness" is especially promising for service robots that need to know when and how to assist a person that cannot independently complete a task. However, robots still fall short in performing many common tasks autonomously. In this work-in-progress paper, we propose an augmented reality (AR) framework that bridges the gap in an assistive robot's capabilities by actively engaging with a human through a shared affordance-awareness representation. Leveraging the different perspectives from a human wearing an AR headset and a robot's equipped sensors, we can build a perceptual representation of the shared environment and model regions of respective agent affordances. The AR interface can also allow both agents to communicate affordances with one another, as well as prompt for assistance when attempting to perform an action outside their affordance region. This paper presents the main components of the proposed framework and discusses its potential through a domestic cleaning task experiment.

翻译：实现人类与机器人的有效协作需要有目的性的沟通以及对彼此动作可能性的理解。先前的人机协作研究已将对人类可负担性（即当前情境中的动作可能性）的认识融入自主机器人决策过程。这种“可负担性感知”对于需要判断何时及如何协助无法独立完成任务的用户的服务机器人尤为关键。然而，机器人在自主执行常见任务方面仍存在局限性。本项进行中的研究提出一种增强现实框架，通过构建共享的可负担性感知表征来弥合辅助机器人的能力差距。通过整合佩戴AR头显的人类视角与机器人搭载的传感器数据，我们能够建立共享环境的感知表征，并建模各智能体的可负担性区域。该AR界面可使双方智能体互相传递可负担性信息，并在尝试执行超出其可负担性区域的动作时触发辅助请求。本文阐述了该框架的核心组成部分，并通过家务清洁任务实验探讨其应用潜力。