Planning search and rescue missions for UAV teams

File Description SizeFormat 
FAIA285-1777.pdfPublished version375.94 kBAdobe PDFDownload
Title: Planning search and rescue missions for UAV teams
Author(s): Jennings, N
Baker, CAB
Ramchurn, SD
Teacy, WLT
Item Type: Conference Paper
Abstract: The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out aerial surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. To aid in this process, it is desirable to exploit the increasing availability of data about a disaster from sources such as crowd reports, satellite re- mote sensing, or manned reconnaissance. In particular, such inform- ation can be a valuable resource to drive the planning of UAV flight paths over a space in order to discover people who are in danger. However challenges of computational tractability remain when plan- ning over the very large action spaces that result. To overcome these, we introduce the survivor discovery problem and present as our solu- tion, the first example of a continuous factored coordinated Monte Carlo tree search algorithm. Our evaluation against state of the art benchmarks show that our algorithm, Co-CMCTS, is able to localise more casualties faster than standard approaches by 7% or more on simulations with real-world data.
Publication Date: 1-Sep-2016
Date of Acceptance: 1-Aug-2016
ISBN: 978-1-61499-672-9
Publisher: IOS Press
Start Page: 1777
End Page: 1782
Journal / Book Title: Proceedings of the 22nd European Conference on Artificial Intelligence
Copyright Statement: © 2016 The Authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
Conference Name: ECAI 2016
Publication Status: Published
Start Date: 2016-08-29
Finish Date: 2016-09-02
Conference Place: The Hague, Holland
Appears in Collections:Faculty of Engineering
Faculty of Natural Sciences

Items in Spiral are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons