Kinematic Calibration Of Industrial Robots Based On Measurement Poses

With the development of science and technology,industrial robots have gradually become the core equipment of modern industry.Due to the extensive use of off-line programming robots,the problem of robots' positional accuracy is increasingly prominent.In this paper,considering the effect of measurement pose on the identification accuracy,the kinematic calibration considering the error of the geometric parameters of the robot from the perspective of kinematic has been studied,aiming to improve the absolute positioning accuracy of industrial robots.Firstly,the kinematic model of robots was built based on D-H method and MD-H model.By setting the error range of each parameter in the model and randomly taking points in the workspace,the influence of geometric parameter errors on the positioning accuracy of the robot endpoint was analyzed.Secondly,combining kinematics model with differential transformation method,the robot position error model considering geometric parameters is established.According to the correlation of the Jacobian matrix column vectors,the redundancy parameters in the position error model were analyzed and the identifiable parameters were determined.The least squares method was used to identify the parameters in the robot tool coordinate and the base coordinate,and then identify the error of the robot's own geometric parameters.By Newton-Raphson compensation method,the endpoint position errors generated by the geometric parameter error were compensated through compensation of the robot's joint angles.The effectiveness of the compensation method is verified by simulation.Then,five observability indexes were obtained by the singular value of the error Jacobian matrix,and the influence of the measurement pose number on the condition number and observability index was analyzed.Thus number of the measurement pose used for identification was determined.By the method of genetic algorithm using observability index as a fitness function,the optimal measurement configuration corresponding to each observability index were found,then comparing the effect of each observability index on identification result and the post-calibration position error through simulation,selecting the best observability index.Finally,the experiment verifies that using the error model to remove redundant parameters and selecting the optimal measurement configuration can effectively improve the robot's terminal accuracy after calibration.In order to further verify the validity of the calibration method proposed in this paper.Calibration experiments were made,and the absolute and repeat positioning accuracy of three different robots ABB,DENSO and FANUC before and after calibration were take into further analysis.The results show that the positioning accuracy of robots has been improved significantly after calibration.