Direct and Indirect Communication in Multi-Human Multi-Robot Interaction

TL;DR

This study investigates how combining direct verbal communication and indirect interface-based signals affects multi-human multi-robot collaboration, showing that a hybrid approach enhances awareness, trust, and usability.

Contribution

It provides empirical evidence that integrating both communication modes improves multi-robot team coordination and user experience.

Findings

Combining direct and indirect communication improves team awareness.

Hybrid communication methods increase trust and usability.

The study involves 18 participants and 9 robots in a collective transport task.

Abstract

How can multiple humans interact with multiple robots? The goal of our research is to create an effective interface that allows multiple operators to collaboratively control teams of robots in complex tasks. In this paper, we focus on a key aspect that affects our exploration of the design space of human-robot interfaces -- inter-human communication. More specifically, we study the impact of direct and indirect communication on several metrics, such as awareness, workload, trust, and interface usability. In our experiments, the participants can engage directly through verbal communication, or indirectly by representing their actions and intentions through our interface. We report the results of a user study based on a collective transport task involving 18 human subjects and 9 robots. Our study suggests that combining both direct and indirect communication is the best approach for effective multi-human / multi-robot interaction.