AFM Tip Localization and Efficient Scanning Method for MEMS Inspection
Journal
IEEE Transactions on Instrumentation and Measurement
Journal Volume
71
Date Issued
2022
Author(s)
Abstract
Atomic force microscopy (AFM) is widely used in different fields, such as nanotechnology, semiconductor, microelectromechanical systems (MEMSs), bioscience, and so on. In the case of obtaining the 3-D topography of a large-scale MEMS sample, it is hard to localize the AFM tip position without other auxiliary microscopes in the unknown sample before scanning. Thus, in this article, the relative probe position on the MEMS layout map can be obtained, such that the probe can be moved and placed near the interesting region to start the inspection. However, the AFM scanned images on a MEMS sample typically involve only simple geometries with sparse features, which usually leads to localization difficulty. In this research, an AFM tip localization method was proposed by using the particle filter, referring to the macrorobot simultaneous localization and mapping (SLAM) technique. The AFM scanned images are treated as the unique sensor and the sample layout as the map. The sensor model of the particle filter is based on a feature extraction algorithm. After localization, the interesting area is scanned using a novel efficient scanning method combining online variable speed scan and learning-based feedforward control. In order to verify the effectiveness of the proposed methods, both tremendous simulations and experiments are conducted, and the results of the tip localization and efficient scanning on a MEMS sample are highly promising. © 1963-2012 IEEE.
Subjects
Atomic force microscopy (AFM); efficient scanning method; feedforward control; online variable speed scan; particle filter; tip localization
Other Subjects
Atomic force microscopy; Bandpass filters; MEMS; Online systems; Probes; Robotics; Scanning electron microscopy; Atomic force microscopy; Atomic-force-microscopy; Efficient scanning method; Localisation; Location awareness; Micromechanical device; On-line variables; Online variable speed scan; Particle filter; Scanning methods; Tip localization; Variable speed; Monte Carlo methods
Type
journal article