Adaptive Kalman Filter-based Robot 6DOF Uncalibrated Vision Positioning

Abstract

Robot 6 degree of freedom vision positioning is a popular and difficult topic in the field of robot visual servoing for its property of strong coupling and nonlinearity. A robot 6-degree of freedom uncalibrated vision positioning method was proposed using an adaptive kalman filter. Firstly, a set of image moments was designed to represent the relative translation and rotation motion between camera and object. Then, an adaptive kalman filter was designed to estimate the image Jacobian matrix on-line in the uncalibrated hand-eye coordination systems and visual control law was designed to calculate the motion control quantity of the robot. Finally, the Simulink model for a robot 6DOF uncalibrated vision positioning system with eye-to-hand configuration was built using Matlab. After this, the 6-degree of freedom vision positioning of robot was achieved. The experiment results of 6- degree of freedom vision positioning show that the adaptive kalman filter can guide the robot to the desired position with high accuracy under the partial known noises.