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A Study of Human-Agent Collaboration for Multi-UAV Task Allocation in Dynamic Environments

A Study of Human-Agent Collaboration for Multi-UAV Task Allocation in Dynamic Environments
A Study of Human-Agent Collaboration for Multi-UAV Task Allocation in Dynamic Environments
We consider a setting where a team of humans oversee the coordination of multiple Unmanned Aerial Vehicles (UAVs) to perform a number of search tasks in dynamic environments that may cause the UAVs to drop out. Hence, we develop a set of multi-UAV supervisory control interfaces and a multi-agent coordination algorithm to support human decision making in this setting. To elucidate the resulting interactional issues, we compare manual and mixed-initiative task allocation in both static and dynamic environments in lab studies with 40 participants and observe that our mixed-initiative system results in lower workloads and better performance in re-planning tasks than one which only involves manual task allocation. Our analysis points to new insights into the way humans appropriate flexible autonomy.
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Fischer, Joel
a320ad79-0fb5-464b-9eac-f74918b5ea68
Ikuno, Yuki
2d92d5e3-3377-44fb-b573-5b140be71a8b
Wu, Feng
b79f9800-2819-40c8-96e7-3ad85f866f5e
Flann, Jack
e7c45bef-2d6b-410f-a7ab-4629f34fa086
Waldock, Antony
cae54123-b67d-4fbc-81d9-d7ea6a86dfc0
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Fischer, Joel
a320ad79-0fb5-464b-9eac-f74918b5ea68
Ikuno, Yuki
2d92d5e3-3377-44fb-b573-5b140be71a8b
Wu, Feng
b79f9800-2819-40c8-96e7-3ad85f866f5e
Flann, Jack
e7c45bef-2d6b-410f-a7ab-4629f34fa086
Waldock, Antony
cae54123-b67d-4fbc-81d9-d7ea6a86dfc0

Ramchurn, Sarvapali, Fischer, Joel, Ikuno, Yuki, Wu, Feng, Flann, Jack and Waldock, Antony (2015) A Study of Human-Agent Collaboration for Multi-UAV Task Allocation in Dynamic Environments. At International Joint Conference on Artificial Intelligence International Joint Conference on Artificial Intelligence.

Record type: Conference or Workshop Item (Paper)

Abstract

We consider a setting where a team of humans oversee the coordination of multiple Unmanned Aerial Vehicles (UAVs) to perform a number of search tasks in dynamic environments that may cause the UAVs to drop out. Hence, we develop a set of multi-UAV supervisory control interfaces and a multi-agent coordination algorithm to support human decision making in this setting. To elucidate the resulting interactional issues, we compare manual and mixed-initiative task allocation in both static and dynamic environments in lab studies with 40 participants and observe that our mixed-initiative system results in lower workloads and better performance in re-planning tasks than one which only involves manual task allocation. Our analysis points to new insights into the way humans appropriate flexible autonomy.

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More information

Accepted/In Press date: April 2015
Published date: July 2015
Venue - Dates: International Joint Conference on Artificial Intelligence, 2015-04-01
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 377185
URI: https://eprints.soton.ac.uk/id/eprint/377185
PURE UUID: 9d31626d-57fe-49d7-9a91-6f4f8428c655
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

Catalogue record

Date deposited: 17 May 2015 17:53
Last modified: 06 Jun 2018 12:42

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Contributors

Author: Sarvapali Ramchurn ORCID iD
Author: Joel Fischer
Author: Yuki Ikuno
Author: Feng Wu
Author: Jack Flann
Author: Antony Waldock

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