Position Control using 2D-to-2D Feature Correspondences in Vision Guided Cell Micromanipulation

Conventional camera calibration that utilizes the extrinsic and intrinsic parameters of the camera and the objects has certain limitations for micro-level cell operations due to the presence of hardware deviations and external disturbances during the experimental process, thereby invalidating the extrinsic parameters. This invalidation is often neglected in macro-world visual servoing and affects the visual image processing quality, causing deviation from the desired position in micro-level cell operations. To increase the success rate of vision guided biological micromanipulations, a novel algorithm monitoring the changing image pattern of the manipulators including the injection micropipette and cell holder is designed and implemented based on 2 dimensional (2D)-to 2D feature correspondences and can adjust the manipulator and perform position control simultaneously. When any deviation is found, the manipulator is retracted to the initial focusing plane before continuing the operation.