TEAM3 Challenge: Tasks for Multi-Human and Multi-Robot Collaboration with Voice and Gestures
Intuitive human-robot collaboration requires adaptive modalities for humans and robots to communicate and learn from each other. For diverse teams of humans and robots to naturally collaborate on novel tasks, robots must be able to model roles for themselves and other team members, anticipate how team members may perceive their actions, and communicate back to team members to continuously promote inclusive team cohesion toward achieving a shared goal.
Here, we describe a set of tasks for studying mixed multi-human and multi-robot teams with heterogenous roles to achieve joint goals through both voice and gestural interactions. Based around the cooperative game TEAM3, we specify a series of dyadic and triadic human-robot collaboration tasks that require both verbal and nonverbal communication to effectively accomplish. Task materials are inexpensive and provide methods for studying a diverse set of challenges associated with human-robot communication, learning, and perspective-taking.
- Year: 2023
- Category: Artificial Intelligence
- Tag: non-dyadic HRI, interaction techniques in groups with robots, human-robot collaboration, robot-assisted tower construction, natural language interaction, interaction design and prototyping
- Author: Michael J. Munje, Lylybell K. Teran, Bradon Thymes
- Released: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
Featured Riverside Research Author(s)
Joseph P. Salisbury
Dr. Joseph Salisbury is a neuroscientist (Ph.D., Brandeis University, 2013) and software developer whose current research focuses on human-computer interaction, human-robot interaction, and applications of large language models.
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