# High-Speed Cell Assembly with Piezo-Driven Two-Finger Microhand
## 4 Automated Assembly Strategy for Cells and Experimental Results
### Automated Assembly Experimental Results  
Many researchers have conducted manipulations similar to micro-grasping. [PERSON] manipulated 20 microspheres with diameters ranging from 3 to 4 \(\upmu\)m to construct five two-layered 3D micro-pyramids [39]. The average manipulation time for each microsphere was approximately 48 s. [PERSON] et al. proposed a robotic system based on a MEMS microgripper, using it for high-speed, fully automated pick-and-place operations on borosilicate glass spheres with diameters ranging from 7.5 to 10.9 \(\upmu\)m [36]. The average pick-and-place time  
Figure 6: Automated assembly algorithm flowchart.  
for each sphere was 6 s. These manipulations are targeted towards ideal spherical targets. Manipulating cells is challenging due to their irregular shapes and adhesive membranes, resulting in a slower manipulation speed. [PERSON] proposed a micromanipulation system for the automated pick-place of single cells, which could accurately pick up a single cell, transfer the cell, and deposit it at the target location with a speed of 15-30 s per cell [40]. Based on the research by [PERSON] et al. [41], this paper proposes a micromanipulation method for tissue engineering, enabling rapid pick-and-place. This method combines high speed and high stability when manipulating cells, addressing a previous research gap.  
The cells used in this study are Hela cells, with dimensions of around 10-15 um, smaller than the microspheres mentioned earlier. If the size of the hemispherical end-effector is too small, it may lead to low stiffness, but if it is too large, it may touch the substance's bottom and affect grasping. After multiple experimental tests, we selected a 10 um hemispherical end-effector, achieving a 98% success rate in cell grasping. Another difference between cells and microspheres is their susceptibility to deformation. Experimental tests revealed that when the cell deformation reaches 1 um after grasping, the success rate is only 50%. However, when the deformation is 2 or 3 um, the success rate reaches 95%. When the deformation exceeds 3 um, 100% success in cell grasping can be achieved. However, larger deformations will cause damage to cells, so we chose a grasping deformation of 2 um to balance successful grasping and minimize the risk of cell damage. Under this grasping deformation condition, we conducted 100 cell grasping experiments, achieving a final success rate of 95%. We applied the optimal manipulation parameters for microspheres to cell release, also achieving a success rate of 97% in 100 cell release experiments.  
Finally, the process of automated assembly for the letter 'T' is shown in Figure 7. The average precision of cell assembly is 4.5 um. The average total time of cell grasping and releasing is less than 0.8 s per cell. We conducted 20 experiments of automated assembly of letters, achieving a success rate of 90%. The main reasons for failure were attributed to grasp and release failures during the assembly process. The speed of automatic visual feedback can reach 25 frames per second, meeting our real-time detection needs. Moreover, the algorithm demonstrates robustness against background noise, effectively filtering out cell fragments and impurities in the field of view. By adjusting parameters for specific targets, we can also achieve the assembly of different biological micro-objects, such as cells of different types.