Enhancing Environmental Sensing Capability of AFM-based Nanorobot Via Spiral Local Scan Strategy

Abstract

Atomic force microscopy (AFM) based nanorobotic technology has been widely implemented in light of the overwhelming advantages, such as nanometer spatial resolution, adaptability to various ambient, and numerous advanced measurement approaches. It is noted that even though the AFM possesses nanometer imaging resolution, it is hard to achieve nanometer tip locating precision due to complicated uncertainties, especially the nonlinearity of tip-environment interaction and the random drift influence. Since an AFM image is typically utilized as a map for nanomanipulation, the uncertainty distorted image will definitely introduce location deviation between the real and the captured nano-world, which typically leads to low efficiency or even failure of tasks. Besides, complicated tip-environment interaction is generally hard to model and to make accurate prediction, which will also lead to task failure. Therefore, to achieve highly accurate operation at the nanoscale, environmental sensing capability of AFM-based nanorobot should be promoted. In this paper, we propose a local environment sensing approach to detect positioning uncertainty between nanorobot tip and its surroundings by developing a multi-functional spiral local scan (MSLS) strategy comprised of structured objects location detection function and local surroundings imaging function. Briefly, sphere/cylinder-like object location detection strategies were proposed; a tip motion predictor was developed to tackle the heavy noise issue of detection tasks at dozens of nanometers scale, based on which a local area imaging approach was established. Efficiency of the MSLS method was verified through experimental study.