Research on error analysis and calibration method of 3-PUU parallel robot

Kinematic calibration is necessary for the pose accuracy improvement of the parallel robots. However, difficulties occur in traditional calibration methods, such as exceeding a large number of error parameters and error accumulation. In this paper, a 3-PUU parallel robot is taken as the research object, and the closed-loop vector method and differential theory are employed to establish an error model. Through quantitative analysis of geometric parametric errors, redundant parameters within the calibration algorithm are meticulously eliminated. By treating the dominant error terms as optimization variables for the mechanism’s parameters, the calibration problem is transformed into a nonlinear system optimization challenge, which effectively avoids the problem of multiple error parameters and accumulation of errors in the traditional method. Further, using the particle swarm algorithm to compute the minimum value of the objective function, one can obtain the actual structural parametric errors of the robot. These errors are then utilized to correct the kinematic model, enabling the calibration of the mechanism’s parameters and ultimately enhancing operation accuracy. Lastly, simulation and experimental validation of the algorithm are carried out. The simulation results indicate that the end-effector position error converges to zero infinitely; and the experimental results indicate that the maximum error of the end-effector in the x, y, z directions and the maximum position error are reduced from 8.53, 11.67, 3.29, and 12.56 mm to 1.09, 1.32, 0.98, and 1.75 mm, respectively. The standard deviation of the position error is reduced from 2.43 to 0.32 mm. The mean error is reduced from 7.76 to 1.02 mm. To sum up, the operation accuracy and stability of the robot are greatly improved.