Licea, DB, McLernon, D and Ghogho, M (2014) Optimal trajectory design for a DTOA based multi-robot angle of arrival estimation system for rescue operations. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). ICASSP, 04-09 May 2014, Florence, Italy. IEEE , pp. 6800-6804. ISBN 978-1-4799-2893-4
Abstract
In this article we present an angle of arrival (AoA) multi-robot system for rescue purposes which takes advantage of robots' mobility to improve the position estimate of an unknown target. The robots move according to a certain trajectory (a sequence of stopping points) designed to minimize the variance of the AoA estimation. We present two different techniques to generate these optimal trajectories, with each technique having its own advantage.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 IEEE. This is an author produced version of a paper published in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | AoA estimation; multi-robot; trajectory planning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Jul 2016 09:18 |
Last Modified: | 20 Jan 2018 19:37 |
Published Version: | http://dx.doi.org/10.1109/ICASSP.2014.6854917 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICASSP.2014.6854917 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88225 |