Visual servoing control based on fuzzy behavior and neural networks

被引：0
|
作者：
Liu, Xiaoyu [1 ]
Fang, Kangling [1 ]
机构：
[1] Wuhan Univ Sci & Technol, Coll Informat Sci & Engn, Wuhan 430081, Huabei, Peoples R China
来源：
2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2 | 2006年
关键词：
fuzzy logic; neural networks; visual servoing;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposed a visual servoing control scheme for positioning a robot manipulator. Similar to the behaviour of human, this scheme is divided into two steps: firstly a fuzzy logic-based visual servoing controller is used to guide the gripper into the neighbourhood of the object, and then one local neural network is applied to position the gripper in a desired pose. The whole control needs no calibration of the robot and the cameras and can utilize humans' experience and has high precision. Simulation results on a 6 DOF industrial robot show the validity and effectiveness of the proposed control scheme.
引用
收藏
页码：1792 / +
页数：2
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