Planning with Partner Uncertainty Modeling for Efficient Information Revealing in Teamwork

Communication among team members is important for efficient teamwork, to coordinate behavior and ensure that all team members have the information they need to complete the task. To enable effective communication and thus efficient teamwork, we propose a multi-agent planning approach to revealing information based on its benefit to joint team performance. By explicitly modeling the partner’s knowledge and behavior, our approach allows a robot in a team to reason about when information is useful, how the communication is effective, and to communicate through efficient actions. That is, the robot provides only the necessary information for task completion, provides the information at the time that it is needed, and through the action(s) that optimizes team performance. We validated this approach in a human study in which participants walk together with a robot to a destination that is known only to the robot. We compared to a legible motion generation approach, and showed that users perceived our approach as more natural, socially appropriate, and fluent to team with, while being both more predictable and intent-clear. The ratings of our approach are equal or higher than legible motion across a1118 survey items.CCS CONCEPTS. Computing methodologies →Robotic planning; Multi-agent planning; • Human-centered computing →User studies. ACM Reference Format:Shih-Yun Lo, Elaine Schaertl Short, and Andrea L. Thomaz. 2020. Planning with Partner Uncertainty Modeling for Efficient Information Revealing in Teamwork. In Proceedings of the 2020 ACMlIEEE Intemational Conference on Human-Robot Interaction (HRI’20), March 23-26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3319502.3374827