Nanomanipulation and nanofabrication with an atomic force microscope (AFM) or other scanning probe microscope (SPM) are a precursor for nanomanufacturing. It is still a challenging task to accomplish nanomanipulation automatically. In ambient conditions without stringent environmental controls, the task of nanomanipulation requires extensive human intervention to compensate for the spatial uncertainties of the SPM. Among these uncertainties, the thermal drift, which affects spatial resolution, is especially hard to solve because it tends to increase with time, and cannot be compensated simultaneously by feedback from the instrument. In this paper, a novel automatic compensation scheme is introduced to measure and estimate the drift one-step ahead. The scheme can be subsequently utilized to compensate for the thermal drift so that a real-time controller for nanomanipulation can be designed, as if the drift did not exist. Experimental results show that the proposed compensation scheme can predict drift with a small error, and therefore, can be embedded in the controller for manipulation tasks.


Electrical and Computer Engineering

Second Department

Computer Science

Third Department


Keywords and Phrases

Nanomanipulation; Neural Network (NN); Phase Correlation Method; Scanning Probe Microscope; Thermal Drift

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version

Final Version

File Type





© 2008 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Mar 2008