Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines

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.

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Publication Details

Journal
EAI Endorsed Transactions on AI and Robotics
Published
2025-09-19
DOI
https://doi.org/10.4108/airo.9898
Primary Topic
Engineering Technology and Methodologies
Type
article
Field-Weighted Citation Impact
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article

Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines

Jorge Duarte-Loera, Claudia Lerma-Hernández, Manuel Meraz Méndez
EAI Endorsed Transactions on AI and Robotics
Engineering Technology and Methodologies
article

Localization of the Work Coordinate System Using Computer Vision and Geometric Transformations on Three-Axis CNC Milling Machines

Jorge Duarte-Loera, Claudia Lerma-Hernández, Manuel Meraz Méndez
article en

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.

EAI Endorsed Transactions on AI and RoboticsVol. 4
Autonomous University of Chihuahua (MX), Jinhua University of Vocational Technology (CN), Universidad Tecnológica de Chihuahua
Openalex Percentile: Top 64%
Engineering Technology and Methodologies
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