Neural Network Solution for Forward Kinematics Problem of Cable Robots

作者：Ghasemi Ali; Eghtesad Mohammad^*; Farid Mehrdad

来源：Journal of Intelligent & Robotic Systems, 2010, 60(2): 201-215.

DOI：10.1007/s10846-010-9421-z

• Cable robots
• Forward kinematics
• Neural networks
• MLP
• Back propagation

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.

• 出版日期2010-11