Intelligent Agent Supporting Human-Multi-Robot Team Collaboration
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1902-1907.
Abstract
The number of multi-robot systems deployed in field applications has risen dramatically over the years. Nevertheless, supervising and operating multiple robots at once is a difficult task for a single operator to execute. In this paper we propose a novel approach for utilizing advising automated agents when assisting an operator to better manage a team of multiple robots in complex environments. We introduce the Myopic Advice Optimization (MYAO) Problem and exemplify its implementation using an agent for the Search And Rescue (SAR) task. Our intelligent advising agent was evaluated through extensive field trials, with 44 non-expert human operators and 10 low-cost mobile robots, in simulation and physical deployment, and showed a significant improvement in both team performance and the operator’s satisfaction.
@inproceedings{ijcai2015p270,
title = {Intelligent Agent Supporting Human-Multi-Robot Team Collaboration},
author = {Rosenfeld, Ariel and Agmon, Noa and Maksimov, Oleg and Azaria, Amos and Kraus, Sarit},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1902--1907},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/270},
}
TY - CPAPER TI - Intelligent Agent Supporting Human-Multi-Robot Team Collaboration AU - Rosenfeld, Ariel AU - Agmon, Noa AU - Maksimov, Oleg AU - Azaria, Amos AU - Kraus, Sarit T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1902 EP - 1907 UR - https://ijcai.org/proceedings/2015/270 ER -Copied
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