
Editorial
Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines
@ARTICLE{10.4108/airo.9898, author={Manuel Meraz Mendez and Jorge Duarte Loera and Claudia Lerma Hern\^{a}ndez}, title={Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines}, journal={EAI Endorsed Transactions on AI and Robotics}, volume={4}, number={1}, publisher={EAI}, journal_a={AIRO}, year={2025}, month={9}, keywords={milling, work coordinate system, repeatability, computer vision, geometric trasnformations, optimization}, doi={10.4108/airo.9898} }
- Manuel Meraz Mendez
Jorge Duarte Loera
Claudia Lerma Hernández
Year: 2025
Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines
AIRO
EAI
DOI: 10.4108/airo.9898
Abstract
This paper presents a novel methodology for the location of the workpiece coordinate system origin (WCS) on three-axis computer numerical control (CNC) milling machines. The proposed approach uses computer vision techniques to detect geometric features on the workpiece and calculates zero-point coordinates through pixel-based adjustment and coordinate transformation matrices. The method includes a calibration process to align the camera system with the machine’s coordinate reference frames and compensates for displacement between the vision sensor and the tool center point. Experimental validation was carried out on a HAAS VF1 CNC milling machine, comparing the proposed method with traditional probing techniques. The results demonstrate improved repeatability and accuracy in the location of the WCS, with deviations maintained within acceptable industrial tolerances. This approach facilitates faster setup times and improves process automation in intelligent manufacturing environments.
Copyright © 2025 MERAZ MÉNDEZ Manuel et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.