Autonomous multiple teams establishment for mobile sensor networks by SVMs within a potential field

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dc.citation.epage987en_US
dc.citation.issueNumber5en_US
dc.citation.spage971en_US
dc.citation.volumeNumber45en_US
dc.contributor.authorNazlibilek, S.en_US
dc.date.accessioned2016-02-08T09:46:33Z
dc.date.available2016-02-08T09:46:33Z
dc.date.issued2012en_US
dc.departmentNanotechnology Research Center (NANOTAM)en_US
dc.description.abstractIn this work, a new method and algorithm for autonomous teams establishment with mobile sensor network units by SVMs based on task allocations within a potential field is proposed. The sensor network deployed into the environment using the algorithm is composed of robot units with sensing capability of magnetic anomaly of the earth. A new algorithm is developed for task assignment. It is based on the optimization of weights between robots and tasks. The weights are composed of skill ratings of the robots and priorities of the tasks. Multiple teams of mobile units are established in a local area based on these mission vectors. A mission vector is the genetic and gained background information of the mobile units. The genetic background is the inherent structure of their knowledge base in a vector form but it can be dynamically updated with the information gained later on by experience. The mission is performed in a magnetic anomaly environment. The initial values of the mission vectors are loaded by the task assignment algorithm. The mission vectors are updated at the beginning of each sampling period of the motion. Then the teams of robots are created by the support vector machines. A linear optimal hyperplane is calculated by the use of SVM algorithm during training period. Then the robots are classified as teams by use of SVM mechanism embedded in the robots. The support vector machines are implemented in the robots by ordinary op-amps and basic logical gates. Team establishment is tested by simulations and a practical test-bed. Both simulations and the actual operation of the system prove that the system functions satisfactorily. © 2012 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.measurement.2012.01.046en_US
dc.identifier.issn0263-2241
dc.identifier.urihttp://hdl.handle.net/11693/21453
dc.language.isoEnglishen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.measurement.2012.01.046en_US
dc.source.titleMeasurement: Journal of the International Measurement Confederationen_US
dc.subjectAlgorithmsen_US
dc.subjectMagnetic field measurementen_US
dc.subjectMeasurementen_US
dc.subjectNetworksen_US
dc.subjectRobotsen_US
dc.subjectVectorsen_US
dc.subjectActual operationen_US
dc.subjectArea-baseden_US
dc.subjectBackground informationen_US
dc.subjectGenetic backgroundsen_US
dc.subjectInherent structuresen_US
dc.subjectInitial valuesen_US
dc.subjectKnowledge baseen_US
dc.subjectLogical gatesen_US
dc.subjectMagnetic anomaliesen_US
dc.subjectMobile sensor networksen_US
dc.subjectMobile unitsen_US
dc.subjectMultiple teamsen_US
dc.subjectPotential fielden_US
dc.subjectSampling perioden_US
dc.subjectSVM algorithmen_US
dc.subjectSystem functionsen_US
dc.subjectTask allocationen_US
dc.subjectTask assignmenten_US
dc.subjectAlgorithmsen_US
dc.subjectKnowledge based systemsen_US
dc.subjectMagnetic field measurementen_US
dc.subjectMeasurementsen_US
dc.subjectNetworks (circuits)en_US
dc.subjectOptimizationen_US
dc.subjectRobotsen_US
dc.subjectSensor networksen_US
dc.subjectVectorsen_US
dc.subjectSupport vector machinesen_US
dc.titleAutonomous multiple teams establishment for mobile sensor networks by SVMs within a potential fielden_US
dc.typeArticleen_US
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