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Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm

Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm
Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm
This paper considers the coordination of a team of Unmanned Aerial Vehicles (UAVs) that are deployed to search for a moving target within a continuous space. We present an online and decentralised coordination mechanism, based on the max-sum algorithm, to address this problem. In doing so, we introduce a novel coordination technique to the field of robotic search, and we extend the max-sum algorithm beyond the much simpler coordination problems to which it has been applied to date. Within a simulation environment, we benchmarked our max-sum algorithm against three other existing approaches for coordinating UAVs. The results showed that coordination with the max sum algorithm out-performed a best response algorithm, which represents the state of the art in the coordination of UAVs for search, by up to 26%. The results further showed that the max-sum algorithm out-performed an implicitly coordinated approach, where the coordination arises from the agents making decisions based on a common belief, by up to 34% and finally a non-coordinated approach by up to 68%.
multi-agent coordination
35-44
Delle Fave, Francesco Maria
1a71a79a-fb96-4bfc-9158-36f8dcb5d96f
Xu, Zhe
b377e17c-b1dc-45d0-84ec-7f7862743d55
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Delle Fave, Francesco Maria
1a71a79a-fb96-4bfc-9158-36f8dcb5d96f
Xu, Zhe
b377e17c-b1dc-45d0-84ec-7f7862743d55
Rogers, Alex
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Delle Fave, Francesco Maria, Xu, Zhe, Rogers, Alex and Jennings, Nicholas R. (2010) Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm. AAMAS 2010 Workshop on Agents in Real Time and Environment, Toronto, Canada. 10 - 14 May 2010. pp. 35-44 .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper considers the coordination of a team of Unmanned Aerial Vehicles (UAVs) that are deployed to search for a moving target within a continuous space. We present an online and decentralised coordination mechanism, based on the max-sum algorithm, to address this problem. In doing so, we introduce a novel coordination technique to the field of robotic search, and we extend the max-sum algorithm beyond the much simpler coordination problems to which it has been applied to date. Within a simulation environment, we benchmarked our max-sum algorithm against three other existing approaches for coordinating UAVs. The results showed that coordination with the max sum algorithm out-performed a best response algorithm, which represents the state of the art in the coordination of UAVs for search, by up to 26%. The results further showed that the max-sum algorithm out-performed an implicitly coordinated approach, where the coordination arises from the agents making decisions based on a common belief, by up to 34% and finally a non-coordinated approach by up to 68%.

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More information

Published date: 11 May 2010
Additional Information: Event Dates: 10 - 14 May
Venue - Dates: AAMAS 2010 Workshop on Agents in Real Time and Environment, Toronto, Canada, 2010-05-10 - 2010-05-14
Keywords: multi-agent coordination
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 270812
URI: http://eprints.soton.ac.uk/id/eprint/270812
PURE UUID: cb2e61d0-4541-42b7-a9b1-e9abc7caad41

Catalogue record

Date deposited: 08 Apr 2010 16:02
Last modified: 14 Mar 2024 09:16

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Contributors

Author: Francesco Maria Delle Fave
Author: Zhe Xu
Author: Alex Rogers
Author: Nicholas R. Jennings

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