Three-dimensional Localization of Needle Tip Immersed in Medium

Pick and place through micro manipulators has been an indispensable tool for a variety of biomedical applications. In tissue engineering, 3D tissue can be fabricated through the stacking of multiple cells sheets together. To enable precise handling and alignment of cell sheets, accurate detection of a probe tip, which could experience wave distortion from the culture medium during tip manipulation is very important. In this paper, the 3D position of a tip is evaluated using a vision system. Based on 2D images from consecutive frames, the kernel describing the effect from motion is first computed using a motion blur model. Then, an auto regressive (AR) method is employed to extract the scale factor corresponded to the depth of Z coordinate. Parameters in the model are recursively updated using Unscented Kalman Filter (UKF) algorithm. By finding the tip position in the 2D image, its depth information can be found accordingly. Experiments were conducted to examine the performance and accuracy in evaluating the position of a tip immersed in an aqueous environment.