Wavelet network solution for the inverse kinematics problem in robotic manipulator

INTRODUCTION The inverse kinematics problem (IKP) for a ro- botic manipulator involves obtaining the required manipulator joint values for a given desired end-point position and orientation. It is usually complex due to lack of a unique solution and closed-form direct ex- pression for the inverse kinematics mapping. The forward kinematics problem (FKP) is to find the po- sition and orientation of the end-effector based on given joint values which can be easily obtained by analyzing the …

Wavelet network solution for the inverse kinematics problem in robotic manipulator

Wavelet network, a class of neural network consisting of wavelets, is proposed to solve the inverse kinematics problem in robotic manipulator. A wavelet network suitable for dealing with multi-input and multi-output system is constructed. The network is optimized by reducing the number of wavelets handling large dimension problem according to the sample data. The algorithms for sparseness analysis of input data and fitting wavelets to the output data with orthogonal method are introduced. Then Levenberg-Marquardt algorithm is used to train the network. Simulation results showed that this method is capable of solving the inverse kinematics problem for PUMA560.