For robots to become effective apprentices and collaborators, they must exhibit some level of autonomy, for example, recognizing failures and identifying ways to address them with the aid of their human teammates. In this systems paper, we present an integrated cognitive robotic architecture for a "robot apprentice" that is capable of assessing its own performance, identifying task execution failures, communicating them to humans, and resolving them, if possible. We demonstrate the capabilities of our proposed architecture with a series of demonstrations and confirm with an online user study that people prefer our robot apprentice compared to robots without those capabilities.
@article{thieraufetal24mdpi,
title={Toward Competent Robot Apprentices: Enabling Proactive Troubleshooting in Collaborative Robots},
author={Christopher Thierauf and Theresa Law and Tyler Frasca and Matthias Scheutz},
year={2024},
journal={Machines},
url={https://hrilab.tufts.edu/publications/thieraufetal24mdpi.pdf}
doi={10.3390/machines12010073}
}