Yf. Lou et P. Brunn, AN OFFSET ERROR COMPENSATION METHOD FOR IMPROVING ANN ACCURACY WHEN USED FOR POSITION CONTROL OF PRECISION MACHINERY, NEURAL COMPUTING & APPLICATIONS, 7(1), 1998, pp. 90-95
Artificial Neural Networks (ANNs) have recently become the focus of co
nsiderable attention in many disciplines, including robot control, whe
re they can be used as a general class of nonlinear models to solve hi
ghly nonlinear control problems. Feedforward neural networks have been
widely applied for modelling and control purposes. One of the ANN app
lications in robot control is for the solution of the inverse kinemati
c problem, which is important in path planning of robot manipulators.
This paper proposes an iterative approach and an offset error compensa
tion method to improve the accuracy of the inverse kinematic solutions
by using an ANN and a forward kinematic model of a robot. The offset
error compensation method offers potential to generate accurately the
inverse solution for a class of problems which have an easily obtained
forward model and a complicated solution.