A Micro-Robotic Approach for The Correction of Angular Deviations in AFM Samples From Generic Topographic Data
- Resource Type
- Conference
- Authors
- Leiro, Freddy Romero; Bazaei, Ali; Regnier, Stephane; Boudaoud, Mokrane
- Source
- 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2022 IEEE/RSJ International Conference on. :1055-1061 Oct, 2022
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Vibrations
Linear systems
Parallel robots
Shape
Scanning probe microscopy
3-DOF
Mathematical models
- Language
- ISSN
- 2153-0866
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.