Accuracy Calibration Simulation Of General Six Axis Robot

With the rapid upgrading of products,flexible manufacturing has become the basic starting point of manufacturing industry at this stage.Six degree of freedom industrial robot has been widely used in various manufacturing fields because of its advantages such as strong versatility,high flexibility and large working space.However,the general industrial robots generally have the problem of low absolute positioning accuracy,and most of the positioning accuracy is still in millimeter level,which is the main bottleneck limiting the application of robots to higher-end and more precise occasions.Therefore,robot calibration technology has become one of the hot issues in robot research.In this paper,viper650 industrial robot is taken as the research object.According to the classic D-H model,the kinematics model of the robot is established.The forward and inverse kinematics of the robot is deduced and verified by simulation on ACE software.Based on the singularity of the structure and the principle of minimum motion parameters,the model is built by combining D-H and MDH.At the same time,the influence rule of kinematic parameter error on positioning error is analyzed,and MATLAB software is used for simulation verification.Then,the establishment process of kinematic error model is deduced and verified by MATLAB simulation.In the process of parameter identification,a step-by-step adaptive learning parameter identification method is proposed to solve the problem of low accuracy of related parameters and redundant parameters identification.Based on a large number of simulation experiments,the algorithm is improved,and bisection area search is used instead of equal step area search.It solves the problem of equal step area search,and the identification results fall into the local optimal problem,and improves the accuracy of the identification results at the same time.Then,the maximum positioning error compensated by the identification result is taken as the optimization index,which is verified by MATLAB simulation.Finally,aiming at the defects left by the algorithm,the set value of key parameters in the algorithm is optimized,and three optimization strategies are proposed to improve the defects.After the above processing,the accuracy of parameter error identification is effectively improved,and then accurate compensation is realized.The maximum positioning error of robot end in x,y,z axis is basically stable within 0.1mm,which greatly improves the absolute positioning accuracy of robot.