3D Pose Identification of Moving Micro- and Nanowires in Fluid Suspensions under Bright-Field Microscopy

Precise manipulation of micro- and nanowires through visual feedback is challenging because of the difficulty of observing their motion along the line-of-sight of microscopes. In this paper, we present a novel auto-focusing and visual posture estimation strategy for identifying three-dimensional (3D) poses for one or more moving micro- and nanowires under bright-field microscopes. The proposed method integrates classic passive auto-focusing algorithms, rule-based hill-climb methods, and an automatic and efficient scheme to estimate the positions and orientations of moving wires. Extensive experimental results demonstrate high accuracy and efficiency of the tracking and 3D pose estimation compared to traditional methods. This work lays the foundation for automated control of micro- and nano-robots in 3D microfluidic environments.