Fast Specimen Boundary Tracking and Local Imaging with Scanning Probe Microscopy

An efficient and adaptive boundary tracking method is developed to confine area of interest for high-efficiency local scanning. By using a boundary point determination criterion, the scanning tip is steered with a sinusoidal waveform while estimating azimuth angle and radius ratio of each boundary point to accurately track the boundary of targets. A local scan region and path are subsequently planned based on the prior knowledge of boundary tracking to reduce the scan time. Boundary tracking and local scanning methods have great potential not only for fast dimension measurement but also for sample surface topography and physical characterization, with only scanning region of interest. The performance of the proposed methods was verified by using the alternate current mode scanning ion-conductance microscopy, tapping, and PeakForce modulation atomic force microscopy. Experimental results of single/multitarget boundary tracking and local scanning of target structures with complex boundaries demonstrate the flexibility and validity of the proposed method.

Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey

We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given certain assumptions about the system). This topic continues to be an active area of research, and we highlight some directions in which available approaches may be improved. The paper discusses models of the sensors and vehicle kinematics, assumptions about the environment, and performance criteria. Methods applicable to stationary obstacles, moving obstacles and multiple vehicles scenarios are all reviewed. In preference to global approaches based on full knowledge of the environment, particular attention is given to reactive methods based on local sensory data, with a special focus on recently proposed navigation laws based on model predictive and sliding mode control.

Local raster scanning for high-speed imaging of biopolymers in atomic force microscopy

A novel algorithm is described and illustrated for high speed imaging of biopolymers and other stringlike samples using atomic force microscopy. The method uses the measurements in real-time to steer the tip of the instrument to localize the scanning area over the sample of interest. Depending on the sample, the scan time can be reduced by an order of magnitude or more while maintaining image resolution. Images are generated by interpolating the non-raster data using a modified Kriging algorithm. The method is demonstrated using physical simulations that include actuator and cantilever dynamics, nonlinear tip-sample interactions, and measurement noise as well as through scanning experiments in which a two-axis nanopositioning stage is steered by the algorithm using simulated height data.

Modeling scanning probe microscope lateral dynamics using the probe-surface interaction signal

In this paper, a novel scanning probe microscope (SPM) modeling technique is presented. The novelty of this technique is that it exploits the SPM's probe-surface interaction measurement capabilities [e.g., the topography signal in atomic force microscopy (AFM)] to determine the SPM's lateral positioning dynamics. SPM operation speed is limited due to mechanical vibrations induced by movement of the SPM nanopositioner. In order to facilitate high-speed SPM operation, the dynamics of the SPM can be modeled and used to design feedforward and feedback controllers that reduce nanopositioner vibrations. The proposed technique seeks to develop a transfer function model of the SPM dynamics using only the SPM probe-surface interaction signal obtained while scanning a calibration sample. The technique is presented in the context of an AFM example, errors associated with the method are analyzed, and the method is experimentally verified using a commercial AFM. Experimental modeling results show that the method is capable of modeling the dynamics of SPM systems.