Title: Vision and Visual Servoing for Nanomanipulation and Nanocharacterization using Scanning Electron Microscope

Short Abstract: 

With the latest advances in nanotechnology, it became possible to design novel nanoscale devices and systems with increasing efficiency. The consequence of this fact is an increase in the need for developing reliable and cutting edge processes for nanomanipulation and nanocharacterization. Since the human direct sensing is not a feasible option at this particular scale, the tasks are usually performed by an expert human operator using a scanning electron microscope (SEM) equipped with micro-nanorobotic devices. However, due to the lack of effective processes, these tasks are always challenging and often tiresome to perform. Through this work we show that, this problem can be tackled effectively up to an extent using the microscopic vision information. It is concerned about using the SEM vision to develop reliable automated methods in order to perform accurate and  efficient nanomanipulation and nanocharacterization. Since, SEM imaging is affected by the non-linearities and instabilities present in the electron column, real time methods to monitor the imaging quality and to compensate the time varying distortion were developed. Later, these images were used in the development of visual servoing control laws. The developed visual servoing-based autofocusing method ensures a constant focus throughout the process and was used for estimating the inter-object depth that is highly challenging to compute using a SEM. Two visual servoing schemes were developed to perform accurate nanopositioning using a nanorobotic station positioned inside SEM. They are based on the direct use of global pixel intensities and Fourier spectral information respectively. The positioning accuracies achieved by both the methods at different experimental conditions were satisfactory. The achieved results facilitate in developing accurate and reliable applications such as topographic analysis, nanoprobing and sample lift-out using SEM.

Fulltext download: PhD Thesis Marturi 2013

Comments from Jury: Jury report (French and English)