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Communication Dans Un Congrès Année : 2024

Robotic Mosaic Atomic Force Microscopy Through Sequential Imaging and Multiview Iterative Closest Points Method

Résumé

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 3.4-billion-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.
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Dates et versions

hal-04585656 , version 1 (23-05-2024)

Identifiants

  • HAL Id : hal-04585656 , version 1

Citer

Freddy Romero Leiro, Stéphane Régnier, Frédéric Delarue, Mokrane Boudaoud. Robotic Mosaic Atomic Force Microscopy Through Sequential Imaging and Multiview Iterative Closest Points Method. IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2024), YOKOHAMA, JAPAN, May 2024, YOKOHAMA, Japan. ⟨hal-04585656⟩
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