Adaptive-based Distributed Cooperative Multi-Robot Coverage
Identifieur interne : 000678 ( Main/Exploration ); précédent : 000677; suivant : 000679Adaptive-based Distributed Cooperative Multi-Robot Coverage
Auteurs : Alessandro Renzaglia [France] ; Lefteris Doitsidis [Grèce] ; Agostino Martinelli [France] ; Elias Kosmatopoulos [Grèce]Source :
Abstract
In this paper we present a solution to the problem of positioning a team of mobile robots for a surveillance task in a non-convex environment with unknown obstacles. The problem is addressed taking into account several physical and environmental constraints like limited sensor capabilities, obstacle-avoidance, etc. The goal is to maximize the area monitored by the team, by identifying the best configuration of the team members. Due to the non-convex nature of the problem, an analytical solution cannot be obtained. The proposed method is based on a new cognitive-based, adaptive optimization algorithm (CAO). This method allows getting coordinated and scalable controls to accomplish the task. Furthermore, we propose a different formulation of the problem in order to obtain a distributed solution which allows us to consider also limited communication capabilities. Extensive simulations are presented to evaluate the efficiency of the proposed algorithm and to compare centralized and distributed approach.
Url:
Affiliations:
- France, Grèce
- Auvergne-Rhône-Alpes, Rhône-Alpes
- Grenoble
- Université Joseph Fourier, Université de Grenoble
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Le document en format XML
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Rhône-Alpes</orgName><desc><address><addrLine>Inovallée655 avenue de l'Europe38330 Montbonnot</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/centre/grenoble</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-300009" type="indirect"><org type="institution" xml:id="struct-300009" status="VALID"><orgName>Institut National de Recherche en Informatique et en Automatique</orgName><orgName type="acronym">Inria</orgName><desc><address><addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Grenoble</settlement><region type="region" nuts="2">Auvergne-Rhône-Alpes</region><region type="old region" nuts="2">Rhône-Alpes</region></placeName><orgName type="university">Université Joseph Fourier</orgName><orgName type="institution" wicri:auto="newGroup">Université de Grenoble</orgName></affiliation></author><author><name sortKey="Kosmatopoulos, Elias" sort="Kosmatopoulos, Elias" uniqKey="Kosmatopoulos E" first="Elias" last="Kosmatopoulos">Elias Kosmatopoulos</name><affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-133133" status="VALID"><orgName>Informatics & Telematics Insitute [Thessaloniki]</orgName><orgName type="acronym">ITT</orgName><desc><address><addrLine>P.O.Box 60361, 6th km Xarilaou - Thermi, 57001, Thessaloniki, Greece</addrLine><country key="GR"></country></address><ref type="url">http://www.iti.gr/iti/index.html</ref></desc><listRelation><relation active="#struct-301762" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-301762" type="direct"><org type="institution" xml:id="struct-301762" status="VALID"><orgName>Greek Ministry of Education</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation><country>Grèce</country></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper we present a solution to the problem of positioning a team of mobile robots for a surveillance task in a non-convex environment with unknown obstacles. The problem is addressed taking into account several physical and environmental constraints like limited sensor capabilities, obstacle-avoidance, etc. The goal is to maximize the area monitored by the team, by identifying the best configuration of the team members. Due to the non-convex nature of the problem, an analytical solution cannot be obtained. The proposed method is based on a new cognitive-based, adaptive optimization algorithm (CAO). This method allows getting coordinated and scalable controls to accomplish the task. Furthermore, we propose a different formulation of the problem in order to obtain a distributed solution which allows us to consider also limited communication capabilities. Extensive simulations are presented to evaluate the efficiency of the proposed algorithm and to compare centralized and distributed approach.</div></front></TEI><affiliations><list><country><li>France</li><li>Grèce</li></country><region><li>Auvergne-Rhône-Alpes</li><li>Rhône-Alpes</li></region><settlement><li>Grenoble</li></settlement><orgName><li>Université Joseph Fourier</li><li>Université de Grenoble</li></orgName></list><tree><country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="Renzaglia, Alessandro" sort="Renzaglia, Alessandro" uniqKey="Renzaglia A" first="Alessandro" last="Renzaglia">Alessandro Renzaglia</name></region><name sortKey="Martinelli, Agostino" sort="Martinelli, Agostino" uniqKey="Martinelli A" first="Agostino" last="Martinelli">Agostino Martinelli</name></country><country name="Grèce"><noRegion><name sortKey="Doitsidis, Lefteris" sort="Doitsidis, Lefteris" uniqKey="Doitsidis L" first="Lefteris" last="Doitsidis">Lefteris Doitsidis</name></noRegion><name sortKey="Kosmatopoulos, Elias" sort="Kosmatopoulos, Elias" uniqKey="Kosmatopoulos E" first="Elias" last="Kosmatopoulos">Elias Kosmatopoulos</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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