A hybrid artificial neural network inverse kinematic solution for accurate robot path control

Abstract

Artificial neural networks (ANNs) have recently become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve highly nonlinear control problems. One of these ANN applications is that of the inverse kinematic problem, which is important in robot path planning. This paper outlines an iterative approach, using the offset error compensation method, to improve the accuracy of the inverse kinematic solution by using an ANN and the forward kinematic model of the robot. The method can be used as a feedforward position controller to generate accurate inverse kinematic information for general-purpose robotic manipulators.