Error Identification and Accuracy Compensation Algorithm for Improved 2RPU/UPR+R+P Hybrid Robot

To improve the precision of the 2RPU/UPR+R+P hybrid robot and fulfill production requirements, error compensation was explored. The robot's fixed coordinate system was first used to analyze the workbench error mapping matrix. Next, the correlation between the joint geometric errors and the moving platform kinematic errors of the parallel robot module was examined. The sensitivity of joint geometric errors to the kinematic errors across the entire workspace was determined using statistical methods. Then, a genetic algorithm was employed to identify the joint geometric errors, leading to a kinematic model that accounts for these inaccuracies. Subsequently, the accuracy of the robot was measured, and the results showed that the accuracy of the hybrid robot was improved by 72% in the X-axis direction with poor accuracy. Finally, a sample processing experiment was conducted by the robot. The experiment shows that the surface of the sample parts is good, and the hybrid robot has the ability to stably process complex surfaces.