Research On Hand-eye Coordination System Of Industrial Robot Based On Jacobian Matrix

The research on the robot hand-eye coordination system is a hot topic at home and abroad.Its research covers many disciplines such as robot kinematics,image processing and recognition,machine vision and control.The research results are widely used in aerospace and industrial automation production fields.It has important significance and value.This paper summarizes the existing research results of the robot hand-eye coordination system,and compares the advantages and disadvantages of image-based,position-based and hybrid vision-based visual servo systems,and describes the feedback control method of the visual servo system.The transformation relations between the camera model and the world coordinate system,camera coordinate system,image physical coordinate system and image pixel coordinate system are analyzed.This article analyzes robot kinematics and builds a robot model The Canny operator is determined to perform the image edge detection scheme and the image moment is used to perform the target feature extraction method.The image Jacobian matrix model and its online identification method are studied.For the on-line identification of image Jacobian matrix has problems such as poor real-time performance,slow convergenceand vulnerability to noise,an improved Kalman filter algorithm is proposed.The recognition results are applied to the robot hand-eye coordination system to establish an eye-hand vision robot.The dynamic target tracking simulation platform completes the dynamic target tracking simulation experiment.Experiments show that the proposed algorithm for online identification of image Jacobian matrix has the advantages of high efficiency,fast convergence speed,and smaller error,and it has good robustness.