Legible Robot Pointing

Abstract

Good communication is critical to seamless human-robot interaction. Among numerous communication channels, here we focus on gestures, and in particular on spacial deixis: pointing at objects in the environment in order to reference them. We propose a mathematical model that enables robots to generate pointing configurations that make the goal object as clear as possible --- pointing configurations that are legible. We study the implications of legibility on pointing, e.g. that the robot will sometimes need to trade off efficiency for the sake of clarity. Finally, we test how well our model works in practice in a series of user studies, showing that the resulting pointing configurations make the goal object easier to infer for novice users.