Author Description

In this research, firstly, a novel Neural Network (NN) based hand-eye calibration is introduced in PBVS. A MultiLayer Perceptron NN is used to approximate the nonlinear coordinate transform from image coordinates to real world coordinates in visual servoing. The main advantages of NN based hand-eye calibration are that it can solve the hand-eye calibration problem without estimating the hand-eye transformation and can improve the object tracking accuracy as well. The experimental results in an industrial manufacturing robot show that the proposed calibration method outperforms the current solving transformation matrix method and free hand-eye calibration method for 2D object tracking.