  Human-robot interactions can change significantly depending on how autonomous
humans perceive a robot to be. Yet, while previous work in the HRI community
measured perceptions of human autonomy, there is little work on measuring
perceptions of robot autonomy. In this paper, we present our progress toward
the creation of the Robot Autonomy Perception Scale (RAPS): a theoretically
motivated scale for measuring human perceptions of robot autonomy. We
formulated a set of fifteen Likert scale items that are based on the definition
of autonomy from Beer et al.'s work, which identifies five key autonomy
components: ability to sense, ability to plan, ability to act, ability to act
with an intent towards some goal, and an ability to do so without external
control. We applied RAPS to an experimental context in which a robot
communicated with a human teammate through different levels of Performative
Autonomy (PA): an autonomy-driven strategy in which robots may "perform" a
lower level of autonomy than they are truly capable of to increase human
situational awareness. Our results present preliminary validation for RAPS by
demonstrating its sensitivity to PA and motivate the further validation of
RAPS.
