3D Pose Identification of Micro- and Nanowires in Fluid Suspensions

This paper presents a passive autofocus-based 3D-pose estimation scheme for micro- and nanowires in fluid suspension under bright-field microscopes. The proposed method integrates classic passive auto-focusing (AF) algorithms, rule-based hill-climb methods, and an automatic and efficient scheme to estimate the positions and orientations of multiple micro-and nanowires in 3D. Experimental results validate the performance of the proposed strategy. This work provides the first foundational step toward the automated control of micro-and nanoagents in 3D microfluidic environments.