Neural Network Based Inverse Kinematics Solution for 6-R Robot Using Levenberg-Marquardt Algorithm

The traditional approaches are insufficient to solve the complex kinematics problems of the redundant robotic manipulators. To overcome such intricacy, ANNs are used nowadays. The performance of the neural network is affected by the training algorithm and network topology. There are numerous training algorithms which are used in the training of neural networks. In this paper, Levenberg-Marquardt is used in training algorithm and its effect on the performance of the neural network on the inverse kinematics model learning of a 6-R robot is studied.