Autonomous multiple teams establishment for mobile sensor networks by SVMs within a potential field
Author
Nazlibilek, S.
Date
2012Source Title
Measurement: Journal of the International Measurement Confederation
Print ISSN
0263-2241
Volume
45
Issue
5
Pages
971 - 987
Language
English
Type
ArticleItem Usage Stats
143
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views
101
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downloads
Abstract
In 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.
Keywords
AlgorithmsMagnetic field measurement
Measurement
Networks
Robots
Vectors
Actual operation
Area-based
Background information
Genetic backgrounds
Inherent structures
Initial values
Knowledge base
Logical gates
Magnetic anomalies
Mobile sensor networks
Mobile units
Multiple teams
Potential field
Sampling period
SVM algorithm
System functions
Task allocation
Task assignment
Algorithms
Knowledge based systems
Magnetic field measurement
Measurements
Networks (circuits)
Optimization
Robots
Sensor networks
Vectors
Support vector machines
Permalink
http://hdl.handle.net/11693/21453Published Version (Please cite this version)
http://dx.doi.org/10.1016/j.measurement.2012.01.046Collections
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