The number of multi-robot systems deployed in field applications has risen dramatically over the years. Nevertheless, the part of the human operator in these systems has been mostly overlooked. In this work we propose a novel approach for utilizing automated advising agents when assisting an operator to better manage a team of multiple robots in complex environments. We introduce an advice provision methodology and exemplify its implementation using automated advising agents in two real-world human-multi-robot team collaboration tasks: the Search And Rescue (SAR) task and the warehouse operation task. Our intelligent advising agents were evaluated through extensive field trials, with over 100 human operators and both simulated and physical mobile robots, and showed a significant improvement in the team's performance.
|Title of host publication||AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems|
|Publisher||International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)|
|Number of pages||2|
|State||Published - 2016|
|Event||15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 - Singapore, Singapore|
Duration: 9 May 2016 → 13 May 2016
|Name||Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS|
|Conference||15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016|
|Period||9/05/16 → 13/05/16|
Bibliographical notePublisher Copyright:
Copyright © 2016, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
- Advice provision
- Human-Robot interaction
- Human-agent interaction