Neural Network Solution for Forward Kinematics Problem of Cable Robots

被引:0
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作者
Ali Ghasemi
Mohammad Eghtesad
Mehrdad Farid
机构
[1] Shiraz University,Department of Mechanical Engineering, School of Engineering
[2] University of Ottawa,Department of Mechanical Engineering
关键词
Cable robots; Forward kinematics; Neural networks; MLP; Back propagation;
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摘要
Forward kinematics problem of cable robots is very difficult to solve the same as that of parallel robots and in the contrary to the serial manipulators’. This problem is almost impossible to solve analytically because of the nonlinearity and complexity of the robot’s kinematic equations. Numerical methods are the most common solutions for this problem of the parallel and cable robots. But, convergency of these methods is the drawback of using them. In this paper, neural network approach is used to solve the forward kinematics problem of an exemplary 3D cable robot. This problem is solved in the typical workspace of the robot. The neural network used in this paper is of the MLP type and a back propagation procedure is utilized to train the network. A simulation study is performed and the results show the advantages of this method in enhancement of convergency together with very small modeling errors.
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页码:201 / 215
页数:14
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