Control Research For Robot Adaptive Servo System Based On Image

Vision sensors are used to get the image as the feedback information to construct theclosed loop control system of robot, namely visual servoing. In recent years, with thedevelopment of scientific technology, the robot has played an increasingly important rolein the industrial production. In order to improve the environmental adaptability andintelligent of robot, people pay more and more attention to the research of robot visualservo system. In view of the depth information of the binocular vision model, this paperstudies the image-based robot visual servo control, can be achieved on stationary targetpositioning function. In this paper, the main research contents can be summarized as thefollowing several aspects:First of all, the vision model of the system, the kinematics model and dynamic modelof the robot is established for the binocular hand-eye robot system. Through this processof establishing these models can make us have a deep understand of the relevant conceptsof the robotic visual servoing for the next study.Secondly, the uncalibrated visual servoing is studied. This paper proposes a newadaptive controller under both of the inside and outside parameters of the cameras areunknown. This adaptive algorithm combined the Slotine-Li with online minimization oferror to estimate unknown parameters, for making the robot localization task more quicklyand effectively. And the Lyapunov stability theorem was used to prove the stability of thedesigned system.Again, the PID neural network was introduced into the control of the robot forimage-based binocular visual servo control system with hand-eye model, and a controllerwas designed which combined the PI motion controller with the PID neural networkcontroller in this paper. PI motion controller gives the desired velocity of the robot jointsbased on the image errors, and obtains the joint torque from the neural network PIDcontroller. And the torque drives the robot reaching a desired position and orientation. TheLyapunov theory is used to prove asymptotic stability of the PI motion controller.Finally, MATLAB/Simulink software is used to simulate the designed controller, the results of the simulation objectively discussed the effectiveness of the designed controller.