Direct and Indirect Communication in Multi-Human Multi-Robot Interaction
This addresses the problem of designing interfaces for multi-human multi-robot collaboration, but it is incremental as it focuses on a specific aspect of communication within a broader design space.
The paper tackled the problem of enabling multiple humans to collaboratively control robot teams in complex tasks by studying the impact of direct and indirect communication on metrics like awareness and workload. The result from a user study with 18 humans and 9 robots suggests that combining both communication types is the best approach for effective interaction.
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.