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
11 May 2010
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.
.
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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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
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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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