Visual Servoing-Based Depth-Estimation Technique for Manipulation Inside SEM

Abstract

Depth estimation for micronanomanipulation inside a scanning electron microscope (SEM) is always a major concern. So far, in the literature, various methods have been proposed based on stereoscopic imaging. Most of them require external hardware unit or manual interaction during the process. In this paper, solely relying on image sharpness information, we present a new technique to estimate the depth in real time. To improve the accuracy as well as the rapidity of the method, we consider both autofocus and depth estimation as visual servoing paradigms. The major flexibility of the method lies in its ability to compute the focus position and the depth using only the acquired image information, i.e., sharpness. The feasibility of the method is shown by performing various ground truth experiments: autofocus achievements, depth estimation, focus-based nanomanipulator depth control, and sample topographic estimation at different scenarios inside the vacuum chamber of a tungsten gun SEM. The obtained results demonstrate the accuracy, rapidity, and efficiency of the developed method.