Plug-and-play positioning error compensation model for ripple suppressing in industrial robot polishing

Abstract

The industrial robot-based polisher has wide applications in the field of optical manufacturing due to the advantages of low cost, high degrees of freedom, and high dynamic performance. However, the large positioning error of the industrial robot can lead to surface ripple and seriously restrict the system performance, but this error can only be inefficiently compensated for by measurement before each processing at present. To address this problem, we discovered the period-phase evolution law of the positioning error and established a double sine function compensation model. In the self-developed robotic polishing platform, the results show that the Z-axis error in the whole workspace after compensation can be reduced to ±0.06mm, which reaches the robot repetitive positioning error level; the Spearman correlation coefficients between the measurement and modeling errors are all above 0.88. In the practical polishing experiments, for both figuring and uniform polishing, the ripple error introduced by the positioning error is significantly suppressed by the proposed model under different conditions. Besides, the power spectral density (PSD) analysis has shown a significant suppression in the corresponding frequency error. This model gives an efficient plug-and-play compensation model for the robotic polisher, which provides possibilities for further improving robotic processing accuracy and efficiency.