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Localizing and Tracking Targets with a Reactive Multi-Agent System

Identifieur interne : 003E64 ( Crin/Curation ); précédent : 003E63; suivant : 003E65

Localizing and Tracking Targets with a Reactive Multi-Agent System

Auteurs : Franck Gechter ; Vincent Chevrier ; Francois Charpillet

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RBID : CRIN:gechter04a

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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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CRIN:gechter04a

Le document en format XML

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<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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<crinnumber>A04-R-204</crinnumber>
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<e>Gechter, Franck</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>
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<pages>1488-1489</pages>
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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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