Kalman Filter-Based Robot Manipulator Five-Degrees of Freedom Uncalibrated Vision Positioning

Abstract

Robot manipulator position and posture control is a popular topic in the field of uncalibrated visual servoing, this paper presents a kalman filter-based robot manipulator five-degrees of freedom uncalibrated vision positioning method. In the case of the fixed binocular cameras and manipulator parameters are unknown; firstly, the specific point and angle image features information in the camera image space were selected in order to describe the relative pose relationship between robot manipulator ends and goals. Then, the kalman filter online estimation algorithm was applied to calculate image Jacobian matrix which is mapping relationship between image space to cartesian mission space, and vision controller was designed in the image plane realized robot manipulator five-degrees of freedom uncalibrated vision positioning control. Finally, Six-degrees of freedom robot manipulator’s five-degrees of freedom uncalibrated visual positioning Simulink model established in the Matlab environment, and the simulation result show that kalman filter online estimation method made the robot manipulator rapid convergence to the desired position and posture with high accuracy.