Overcoming Positioning Uncertainty for AFM-based Nanorobots using Spiral Local Scan in Non-vector Space

Abstract

Atomic force microscopy (AFM) based manipulation technologies have been attractive for decades due to the overwhelming advantages of nanometer spatial resolution, universal working environment, and various mechanical measurement methods. It is noted that though the AFM possesses nanometer imaging resolution, it is hard to achieve nanometer locating precision due to uncertainties, especially the thermal drift which distorts AFM images through relatively long capturing time. Since an AFM image is typically utilized as a reference map for nanomanipulation, the uncertainty induced distorted image will definitely introduce location deviation between the real nano-world and the captured, which usually leads to low efficiency or even failure of tasks. Therefore, to achieve high accuracy for AFM-based manipulation, the positioning uncertainty should be detected and then overcome. In this study, we present a universal approach to quantitatively measure and overcome nanorobot tip locating uncertainty by developing a featureless spiral local scan strategy together with the non-vector space (NVS) navigation approach. Experimental study reveals that variation of the tip locating uncertainty of AFM fast axis is more significant than that of the slow axis with different scan angles.