Research On Pose Error Modeling And Its Compensation For 6-DOF Robot

With the development of science and technology,industrial robots have been applied more and more widely.Accuracy is an important performance index in various performance indexes of robots,and the accuracy of robots directly affects the application of robots.Improving the pose accuracy of industrial robots has become an urgent problem.In this paper,a 6-DOF robot is taken as the research object.The ODG JLRB20 robot is taken as the prototype.In order to improve the precision of the robot's end-effectors pose,the pose error modeling and its compensation method of the 6-DOF robot is studied.Firstly,the kinematic basis of the robot is introduced.The positive and negative kinematics analysis of the robot and the Jacobian matrix are performed.The source of pose error of the 6-DOF robot is analyzed,and the pose error model of the robot is established based on the modified D-H model(MD-H).In this paper,considering the flexibility of the robot joint,the flexible joint of the robot is simplified moderately.Based on the Lagrange method,the dynamic model of the robot is established,and the dynamic error of the robot joint is obtained.In order to avoid solving the identification equation directly,genetic algorithm is used to identify the error model parameters.Finally,considering the shortcomings of the error compensation based on the error model,this paper uses the mapping ability of the neural network to compensate the pose error by BP neural network.In order to verify the correctness of error modeling and pose compensation,this paper simulates the error model parameter identification and pose error compensation process on MATLAB.The simulation results show that the pose error of robot is greatly reduced after error compensation,which shows that the compensation method is effective.