Task Space Motion Control for AFM-Based Nanorobot Using Optimal and Ultralimit Archimedean Spiral Local Scan

Abstract

Atomic force microscopy (AFM) based nanorobotic technology provides a unique manner for delicate operations at the nanoscale in various ambient, thanks to its ultrahigh spatial resolution, outstanding environmental adaptability, and numerous measurement approaches. However, one vital challenge behind nanoscale operations is the task space positioning problem, known for its difficulty to realize desirable relative position between the AFM sharp tip and the target. It is noted that although one AFM possesses nanometer imaging resolution, it is hard to achieve nanometer positioning accuracy due to system uncertainties, such as the uncompensated nonlinearity and the thermal drift generated internally/externally. In order to tackle the vital positioning problem in the space, this letter proposes a specific visual servoing control framework using a local ambient image as feedback to overcome positioning uncertainty at the nanoscale. In this letter, we employ the optimal Archimedean spiral scanning strategy and try to exceed the speed criterion to pursue faster and uniform local scan for generating feedback images. To fulfill reliable precise tip locating with the possible non-ideal feedback images, a type of visual servoing control approach i.e., extended non-vector space (ENVS) controller based on the subset projection method, was developed for tackling environmental noise and disturbances. Experimental studies were conducted to verify the effectiveness of the proposed task space tip locating methodology. Testing results demonstrated that the positioning uncertainty was attenuated dramatically, and 1 nm level positioning precision has been achieved for the 500 nm × 500 nm task space.