A Microscopic Vision-Based Method for Enhancing the Printing Accuracy of Microfluidic Printer

Microfluidic bioprinter demonstrates significant advantage in controlling the generation of hydrogel microfibers as bioinks, however, precisely controlling the deposition position of the resulting microfibers remains challenging, since a lag is always generated in microfluidic jets, inducing spatial deviation between the laydown pattern of the microfibers and the predefined printing trajectory. This article presents a microscopic vision-based method for automatically compensating for such deviations. In particular, a magnet-embedded reservoir is constructed initially in order to ensure a stable printing process in a solution. Subsequently, an underwater fluorescent imaging method was developed for the purpose of quantitatively investigating the influence of the reservoir movement on the length of jet lag. L. Based on the jet lag feedback, a new microfluidic printing strategy is developed by integrating model predictive control into nonuniform rational B-splines curve-based small-line segment interpolation to control the L-compensated movement of the reservoir. Furthermore, curvature-related velocity planning is utilized in the controlled movement to optimize printing efficiency. The experimental results demonstrate that the printing accuracy is augmented by over 45% and 11% for regular and irregular curly curves, respectively.