Due to humans and robots complementary capabilities, mixed human-robot teams are considerably deployed in real-world settings. A favored communication means is the natural language used by humans that is still a challenge for robotic teammates. They need to understand the environment from the viewpoint of their human teammates in order to be able to translate the instructions received in the natural language into plans. To deal with human-robot teaming, we report the results from an empirical study in a visual search and rescue task application for mixed human-robot teams. We show how those results and ideas can be interpreted into robot action plans by using a cognition-enabled task interpretation system.
@inproceedings{yazdanietal17aamas,
title={Cognition-enabled Task Interpretation for Human-Robot Teams in a Simulation-based Search and Rescue Mission},
author={Yazdani, Fereshta and Scheutz, Matthias and Beetz, Michael},
year={2017},
booktitle={Proceedings of AAMAS 2017},
pages={1772--1774}
url={https://hrilab.tufts.edu/publications/yazdanietal17aamas.pdf}
doi={10.5555/3091125.3091434}
}