Calibration of Robot Manipulator and Hand-eye Using RGB Camera

This paper proposes a robot manipulator and hand–eye kinematic calibration method using an RGB camera attached to an end effector. For in-hand configuration, sensing objects with the camera allows for simultaneous kinematic calibration of the manipulator and hand–eye calibration, which is more effective than performing them separately. Thus, the camera measures the chessboard’s 2D corners at different robot arm postures. These corners are reprojected to all images, and a calibration is performed with a bundle adjustment method by reducing 2D reprojection errors. Additionally, the chessboard is placed at multiple positions so that the manipulator can have any posture without limitation. The transformation between chessboard positions is included in the optimization process. This method is validated through exploratory experiments, with results compared to a laser tracker, demonstrating its effectiveness.

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Publication Details

Journal
Journal of Institute of Control Robotics and Systems
Published
2025-08-01
DOI
https://doi.org/10.5302/j.icros.2025.25.0094
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
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article

Calibration of Robot Manipulator and Hand-eye Using RGB Camera

Ji-Yong Lee, Bum-Jae You
2 links
Journal of Institute of Control Robotics and Systems
Industrial Vision Systems and Defect Detection
article

Calibration of Robot Manipulator and Hand-eye Using RGB Camera

Ji-Yong Lee, Bum-Jae You
article en

Abstract

This paper proposes a robot manipulator and hand–eye kinematic calibration method using an RGB camera attached to an end effector. For in-hand configuration, sensing objects with the camera allows for simultaneous kinematic calibration of the manipulator and hand–eye calibration, which is more effective than performing them separately. Thus, the camera measures the chessboard’s 2D corners at different robot arm postures. These corners are reprojected to all images, and a calibration is performed with a bundle adjustment method by reducing 2D reprojection errors. Additionally, the chessboard is placed at multiple positions so that the manipulator can have any posture without limitation. The transformation between chessboard positions is included in the optimization process. This method is validated through exploratory experiments, with results compared to a laser tracker, demonstrating its effectiveness.

Journal of Institute of Control Robotics and SystemsVol. 31(8)
Affordable and clean energy
Openalex Percentile: Top 71%
Industrial Vision Systems and Defect Detection
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