This paper presents a functionality that has been developed for the home-made AFM-in-SEM robotic system at the ISIR laboratory. The method allows extending the range of an Atomic Force Microscope (AFM) and dealing with drift issues by fusing multiple individually AFM topography patches. The merging of the patches into a single image is done through a Generalized Procrustes Analysis Iterative Closest Point (GPA-ICP) algorithm. To validate the effectiveness of the approach, an AFM image of a TGX1 calibration grid and a 3.4billion-year-old organic-walled microfossil are reconstructed by automatically merging 50 AFM elementary topography patches of dimension 0.9 µm × 1.2 µm based on feature matching. The overlap between two adjacent patches is 50 % and 33 % in the X and Y axes respectively. The result is a coherent 3.2 µm × 3.0 µm drift-free long range AFM topography without significant artifacts. The method is tested using an AFM-in-SEM system based on a 3-DOF cartesian robot equipped with inertial piezoelectric actuators. This method can be used to extend the range of any type of AFM with a dual XY stage setup. Thus, it opens the door for high-resolution long-range AFM by adding a long-range coarse resolution stage to a preexisting AFM system all without needing to actuate both stages simultaneously.

This article proposes a method for the correction of angular deviations caused during the fixing process of samples prepared for Atomic Force Microscopy (AFM). The correction is done using the angular control of a 6-DOF PPPS parallel platform were the sample is placed, while the AFM scan is performed by a 3-DOF serial cartesian robot with a tuning fork probe designed to perform FM-AFM. The method uses the generic x, y, and z data provided by the AFM after performing a scan on a free surface of the sample substrate. This is used to calculate the plane that closest approximates the points by solving a system of linear equations. This plane is then used to estimate the angular corrections that the 6-DOF parallel robot has to do in order to compensate the deviations. The proposed algorithm can be performed iteratively in order to refine the correction. The method also does not require any special preparation of the substrate. It only requires to have a free surface to scan. Experiments are performed using this algorithm to correct the orientation deviation of a substrate of V1 High-grade mica. The results show that the method is able to correct the angular deviation of the sample relatively to the AFM probe with an error of 0.2° after only two iterations of the algorithm.