Error correction based on computer vision method in extrusion-based bioprinting

Abstract

Bioprinting provides a new perspective to solve the problem of organ shortage. Despite recent technological advances, insufficient printing resolution is still one of the reasons that restrain the development of bioprinting. Normally, the machine axes movement cannot be dependably used to predict material placement, and the printing path deviates from the predetermined designed reference trajectory in varying degrees. A computer vision-based method is proposed to correct the trajectory deviation and improve the printing accuracy. The image algorithm calculates the deviation between the printed trajectory and the reference trajectory to generate an error vector. Furthermore, the axes reference trajectory is modified according to the normal vector approach in the second printing to compensate for the deviation error, and the highest correction efficiency could be achieved 91%. More importantly, we found for the first time that the correction results are in a normal distribution instead of a random distribution.