We implemented a computational framework for Shared Mental Models (SMMs) in which robots use a distributed knowledgebase to coordinate activity. We also built a novel system connecting the robotic architecture, DIARC, to the 3D simulation environment, Unity, to serve as an evaluation platform for the framework implementation. Using this platform, we ran a user study to evaluate the framework by comparing performance of teams in which the robots used SMMs with those that did not. We found that teams in which the robots used SMMs significantly outperformed those without SMMs. This represents the first empirical demonstration that SMMs can be successfully used by fully autonomous robots interacting in natural language to improve team performance, bringing robots a step closer to genuine teammates.
@inproceedings{Gervits2020AAMAS,
title={Toward Genuine Robot Teammates: Improving Human-Robot Team Performance Using Robot Shared Mental Models},
author={Felix Gervits and Dean Thurston and Ravenna Thielstrom and Terry Fong and Quinn Pham and Matthias Scheutz},
year={2020},
booktitle={Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS)},
url={https://hrilab.tufts.edu/publications/Gervits2020AAMAS.pdf}
}