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http://dx.doi.org/10.5391/IJFIS.2009.9.3.213

Intelligent 3D Obstacles Recognition Technique Based on Support Vector Machines for Autonomous Underwater Vehicles  

Mi, Zhen-Shu (Department of Computer Science, Research Institute of Computer and Information Communication, Gyeongsang National University)
Kim, Yong-Gi (Department of Computer Science, Research Institute of Computer and Information Communication, Gyeongsang National University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.9, no.3, 2009 , pp. 213-218 More about this Journal
Abstract
This paper describes a classical algorithm carrying out dynamic 3D obstacle recognition for autonomous underwater vehicles (AUVs), Support Vector Machines (SVMs). SVM is an efficient algorithm that was developed for recognizing 3D object in recent years. A recognition system is designed using Support Vector Machines for applying the capabilities on appearance-based 3D obstacle recognition. All of the test data are taken from OpenGL Simulation. The OpenGL which draws dynamic obstacles environment is used to carry out the experiment for the situation of three-dimension. In order to verify the performance of proposed SVMs, it compares with Back-Propagation algorithm through OpenGL simulation in view of the obstacle recognition accuracy and the time efficiency.
Keywords
SVM; Obstacle Recognition; AUV; BP Algorithm; OpenGL;
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Times Cited By KSCI : 1  (Citation Analysis)
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