The Robot Olympics: Estimating and Influencing Beliefs About a Robot’s Perceptual Capabilities

Abstract

People often hold inaccurate mental models of robots. When such misconceptions regard a robot’s perceptual capabilities, they can lead to issues with safety, privacy, and interaction efficiency. This work is the first attempt to model users’ beliefs about a robot’s perceptual capabilities and make plans to improve their accuracy—i.e., to perform belief repair. We designed a new domain called the Robot Olympics, implemented it as a web-based game platform for collecting data about users’ beliefs, and developed an approach to estimating and influencing users’ beliefs about a virtual robot in that domain. We then conducted a study that collected user behavior and belief data from 240 online participants who played the game. Results revealed shortcomings in modeling the participant’s interpretations of the robot’s actions, as well as the decision making process behind their own actions. The insights from this work provide recommendations for designing further studies and improving user models to support belief repair in human-robot interaction.