Localizing and Tracking Targets with a Reactive Multi-Agent System
Identifieur interne : 003E64 ( Crin/Curation ); précédent : 003E63; suivant : 003E65Localizing and Tracking Targets with a Reactive Multi-Agent System
Auteurs : Franck Gechter ; Vincent Chevrier ; Francois CharpilletSource :
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Abstract
Localizing and Tracking an object, with both mobile or static sensors, is a complex but essential task when we want to use moving robots in a structured and uncertain environment. We propose in this paper a swarm approach for addressing this issue using an interaction paradigm inspired from Physics. The combination of different interactions results in a self-organised process that builds patterns interpreted as solutions of the problem. After a description of the model, this paper analyses the properties and the performance of our device through various experiments. In particular, a comparison with the standard Kalman filtering method demonstrates the relevancy of our approach.
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<front><div type="abstract" xml:lang="en" wicri:score="1665">Localizing and Tracking an object, with both mobile or static sensors, is a complex but essential task when we want to use moving robots in a structured and uncertain environment. We propose in this paper a swarm approach for addressing this issue using an interaction paradigm inspired from Physics. The combination of different interactions results in a self-organised process that builds patterns interpreted as solutions of the problem. After a description of the model, this paper analyses the properties and the performance of our device through various experiments. In particular, a comparison with the standard Kalman filtering method demonstrates the relevancy of our approach.</div>
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<BibTex type="inproceedings"><ref>gechter04a</ref>
<crinnumber>A04-R-204</crinnumber>
<category>3</category>
<equipe>MAIA</equipe>
<author><e>Gechter, Franck</e>
<e>Chevrier, Vincent</e>
<e>Charpillet, Francois</e>
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<title>Localizing and Tracking Targets with a Reactive Multi-Agent System</title>
<booktitle>{Third International Joint Conference on Autonomous Agents and Multi-Agent Systems - AAMAS'04, New York, USA}</booktitle>
<year>2004</year>
<pages>1488-1489</pages>
<month>Jul</month>
<publisher>ACM</publisher>
<keywords><e>multi-agent system</e>
<e>localization</e>
<e>swarm intelligence</e>
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<abstract>Localizing and Tracking an object, with both mobile or static sensors, is a complex but essential task when we want to use moving robots in a structured and uncertain environment. We propose in this paper a swarm approach for addressing this issue using an interaction paradigm inspired from Physics. The combination of different interactions results in a self-organised process that builds patterns interpreted as solutions of the problem. After a description of the model, this paper analyses the properties and the performance of our device through various experiments. In particular, a comparison with the standard Kalman filtering method demonstrates the relevancy of our approach.</abstract>
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