Microinjection and cell membrane strain control using vision guided robotic cell micromanipulation system

This dissertation presents methodologies to measure, model and control the cell membrane strain in real-time by using a vision guided robotic cell micromanipulation system. The system includes a motion unit to control the position of the micropipette in six degrees of freedom, a vision unit to process the image information from the camera and a holding unit to immobilize the cell for strain control. An indirect depth estimation method is proposed to place the target cell and the tip of the micropipette on the same focal plane without taking any risk of damaging the fragile tip of the micropipette, which minimizes the position error between the micropipette and the target cell. The cell membrane deformation is estimated by the peripheral and the local deformation and a real-time machine vision algorithm is proposed to track the changes of cell membrane deformation. The proposed method speeds up the sampling rate of the cell strain control system to 10 Hz and no manual adjustment of parameters is required throughout the experiment. A real-time cell strain control system is proposed by employing the knowledge of the strain model through the feedforward input and accounting for errors using the feedback controller. The experimental results show that the maximum error between the desired and the actual cell membrane strain is within 3%.DOCTOR OF PHILOSOPHY (MAE