Wavelet Based Neural Network Solution for Forward Kinematics Problem of HEXA Parallel Robot

Abstract

Forward kinematics problem of parallel robots is very difficult to solve in comparison to the serial manipulators because of the highly nonlinear relations between joint variables and position and orientation of the end effector. This problem is almost impossible to solve analytically. Numerical methods are one of the common solutions for this problem. But, convergency of these methods is the drawback of using them. In this paper, wavelet based neural network (wave-net) approach is used to solve the forward kinematics problem of the HEXA parallel manipulator. This problem is solved in the typical workspace of this robot. Simulation results show the advantages of employing wavelet neural networks in enhancement of convergency and decreasing modeling errors.