Decentralised Coordination of Unmanned Aerial Vehicles for Target Search using the Max-Sum Algorithm
OA Location
Author(s)
Fave, Francesco Maria Delle
Xu, Zhe
Rogers, Alex
Jennings, Nicholas R
Type
Conference 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%.
Date Issued
2010-05
Citation
2010, pp.35-44
Start Page
35
End Page
44
Copyright Statement
© 2010 by the International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). Permissions to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that the copies bear the full citation on the first page. Copyrights for components of this work owned by others than IFAAMAS must be honoured. Abstracting with credit is permitted.
Identifier
http://eprints.soton.ac.uk/270812/
Source
AAMAS 2010 Workshop on Agents in Real Time and Environment
Source Place
Toronto, Canada
Notes
Event Dates: 10 - 14 May keywords: multi-agent coordination
Publication Status
Unpublished
Start Date
2010-05-10
Finish Date
2010-05-14