  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.
