Experimental Study On Error Compensation And Calibration Of An Over-constrained Five-dof Hybrid Robot

The hybrid robot combines the advantages of the serial robot and the parallel robot,and it has the characteristics of high rigidity,large working space and small cumulative error.However,the problem of insufficient precision is still the key factor that affects the inability of the hybrid robot to be put into promotion application.The error at the end of the hybrid robot caused by the errors produced during machining and assembly is not linear and extremely difficult to be measured.The calibration method is one of the effective methods to improve the accuracy of the hybrid robot.In this paper,the 2RPU/UPR+RP hybrid robot is taken as the research object,and the theoretical analysis,simulation verification and experimental research are carried out around the calibration problem of the hybrid robot.Firstly,this paper analysis the kinematics inverse of the 2RPU/UPR+RP hybrid robot.Then the 26 geometric error sources that affect the end precision of the hybrid robot are analyzed,and the method to improve the accuracy of the hybrid robot is studied.In order to facilitate the debugging and analysis error of the hybrid robot,the offline system development of the hybrid robot based on the API interface of Solidworks software provides convenience for the next calibration research.Secondly,through the analysis of the influence coefficient of the hybrid robot,the error parameters which have great influence on the end position of the hybrid robot are obtained,and the zero-position error calibration of the hybrid robot is firstly analyzed.The parallel part adopts the closed-loop vector chain method and the genetic algorithm based on the analysis of the zero position error calibration theory.The series part adopts the plane fitting method to analyze the zero position error calibration theory.According to the calibration principle,the external component laser tracking is selected as the position.The measurement instrument is given and three sets of examples are given to verify that the zero position error identification result based on genetic algorithm is better than the closed-loop vector chain method.Next,in order to further improve the end precision of the hybrid robot,the hybrid robot is fully calibrated,and the parallel part is analyzed based on the closed-loop vector chain method and the genetic algorithm based on the full calibration theory,and the series part adopts the axis fitting method.Perform an analysis of the full calibration theory.Through the exploration of the error compensation principle,the method of correcting the kinematic geometric parameters is used to compensate the error.Computer simulations are then given to verify the correctness of the method.Finally,based on FAGOR CNC8070 controller,the hardware system of the hybrid robot was built,and the adjustment of controller parameters,the embedding of kinematic algorithm and the compensation of backlash were carried out.The hybrid robot was calibrated using the Leica AT901 laser tracker,and the error parameters were identified by genetic algorithm and compensated to kinematics.According to national standards,the accuracy of the X-axis,Y-axis and Z-axis of the hybrid robot was measured using an Agilent 5529 A laser tracker.The measurement results show that after calibration,the positioning accuracy and repeat positioning accuracy of the hybrid robot are improved to different extents,and two sets of test pieces are processed.