上海科技大学知识管理系统

The pursuit of 3D reconstruction from 2D images for nanomanipulation under scanning electron microscopy stands as a critical research endeavor. Previous methods either necessitates additional lighting which is difficult in standard SEM devices or relies on feature matching with low resolution and precision, further constraining reconstruction performance. In this paper, we propose a novel robot-assisted nanoscale 360° reconstruction approach, which simplifies SEM setups and maximizes the utilization of robot motion and feedback. By harnessing a nanorobotic system, we capture 360°multi-view images automatically with precise mapping information and camera postures. Sequentially, neural radiance field reconstruct the pixel-wise structure and synthesizing images from diverse perspectives. Experimental results using two real datasets demonstrates our approach’s efficacy, achieving PSNR of 28.1 and SSIM of 0.93 for nanotube reconstruction, and PSNR of 32.8 and SSIM of 0.98 for AFM cantilever reconstruction. These results validate the reliability and robustness of our proposed robot-assisted reconstruction method.