Emotion encoding in Human-Drone Interaction

Abstract

Drones are becoming more popular and may soon be ubiquitous. As they enter our everyday environments, it becomes critical to ensure their usability through natural Human-Drone Interaction (HDI). Previous work in Human-Robot Interaction (HRI) shows that adding an emotional component is part of the key to success in robots' acceptability. We believe the adoption of personal drones would also benefit from adding an emotional component. This work defines a range of personality traits and emotional attributes that can be encoded in drones through their flight paths. We present a user study (N=20) and show how well three defined emotional states can be recognized. We draw conclusions on interaction techniques with drones and feedback strategies that use the drone's flight path and speed.