Set-based direct visual servoing for nanopositioning

Abstract

Atomic force microscopy (AFM) can be used as an image tool in nanoscale for nanopositioning and other similar works. This problem can be seen as a visual servoing problem. Traditional works for this problem use position-based algorithms, however, the correspondence problem is needed to be solved by feature matching and tracking firstly, as a prerequisite for vision-based control. The correspondence problem refers to the problem of ascertaining which parts of one image correspond to which parts of another image. To solve the problem of AFM based nanomanipulations, we present a novel set-based direct visual servoing controller (SDVSC) for nanopositioning that is based on the whole gray image and does not require feature matching and tracking.