Image processing based obstacle avoidance control for mobile robot by recurrent fuzzy neural network

被引:7
作者
Mon, Yi-Jen [1 ]
Lin, Chih-Min [2 ]
机构
[1] Taoyuan Innovat Inst Technol, Dept Comp Sci & Informat Engn, Chungli 320, Taoyuan, Taiwan
[2] Yuan Ze Univ, Dept Elect Engn, Taoyuan, Taiwan
关键词
Recurrent fuzzy neural network (RFNN); mobile robot control; e-puck; webots; image processing; SYSTEMS; DESIGN;
D O I
10.3233/IFS-130943
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The e-puck (TM) mobile robot is used and an intelligent obstacle avoidance algorithm is developed in this paper. The image data are processed by edge detection method. By using the recurrent fuzzy neural network (RFNN), the horizontal edge (HE) and vertical edge (VE) are feed into RFNN to train the control rules such as to control the right and left wheels of e-puck robot to avoid obstacles. The good control performances and effectiveness are demonstrated by the simulations of Matlab (TM) and Webots (TM); meanwhile, the empirical tests are also implemented to verify these performances.
引用
收藏
页码:2747 / 2754
页数:8
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