See What I Mean? Expressiveness and Clarity in Robot Display Design

TL;DR

This study investigates how different non-verbal display types on robots affect human trust, satisfaction, interpretation, and task success in a collaborative navigation task, revealing trade-offs between animation and static icons.

Contribution

It provides empirical evidence on the effects of animated versus static non-verbal cues in robot displays during real-world human-robot collaboration.

Findings

Animated displays increase trust and satisfaction.

Static icons are better interpreted by users.

Static eyes lead to higher task success.

Abstract

Nonverbal visual symbols and displays play an important role in communication when humans and robots work collaboratively. However, few studies have investigated how different types of non-verbal cues affect objective task performance, especially in a dynamic environment that requires real time decision-making. In this work, we designed a collaborative navigation task where the user and the robot only had partial information about the map on each end and thus the users were forced to communicate with a robot to complete the task. We conducted our study in a public space and recruited 37 participants who randomly passed by our setup. Each participant collaborated with a robot utilizing either animated anthropomorphic eyes and animated icons, or static anthropomorphic eyes and static icons. We found that participants that interacted with a robot with animated displays reported the greatest level of trust and satisfaction; that participants interpreted static icons the best; and that participants with a robot with static eyes had the highest completion success. These results suggest that while animation can foster trust with robots, human-robot communication can be optimized by the addition of familiar static icons that may be easier for users to interpret. We published our code, designed symbols, and collected results online at: https://github.com/mattufts/huamn_Cozmo_interaction.