A hybrid artificial neural network inverse kinematic solution for accurate robot path control

被引:7
|
作者
Lou, YF
Brunn, P
机构
[1] Univ Manchester, Inst Sci & Technol, Total Technol Dept, Manchester M60 1QD, Lancs, England
[2] Univ Manchester, Inst Sci & Technol, Dept Mech Engn, Div Mfg, Manchester M60 1QD, Lancs, England
关键词
accurate path control; robots; artificial neural network; inverse kinematics; improved solution;
D O I
10.1243/0959651991540359
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Artificial neural networks (ANNs) have recently become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve highly nonlinear control problems. One of these ANN applications is that of the inverse kinematic problem, which is important in robot path planning. This paper outlines an iterative approach, using the offset error compensation method, to improve the accuracy of the inverse kinematic solution by using an ANN and the forward kinematic model of the robot. The method can be used as a feedforward position controller to generate accurate inverse kinematic information for general-purpose robotic manipulators.
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页码:23 / 32
页数:10
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