Next Article in Journal
Gabor Transform-Based Deep Learning System Using CNN for Melanoma Detection
Previous Article in Journal
Learning Complementary Representations for Targeted Multimodal Sentiment Analysis
Previous Article in Special Issue
Fair and Energy-Efficient Charging Resource Allocation for Heterogeneous UGV Fleets
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Stereo-Based Single-Shot Hand-to-Eye Calibration for Robot Arms

by
Pushkar Kadam
1,*,
Gu Fang
1,*,
Farshid Amirabdollahian
2,
Ju Jia Zou
1 and
Patrick Holthaus
2
1
Centre for Advanced Manufacturing Technology, School of Engineering, Design and Built Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW 2751, Australia
2
Robotics Research Group, University of Hertfordshire, Hatfield AL10 9AB, UK
*
Authors to whom correspondence should be addressed.
Computers 2026, 15(1), 53; https://doi.org/10.3390/computers15010053
Submission received: 14 December 2025 / Revised: 8 January 2026 / Accepted: 11 January 2026 / Published: 13 January 2026
(This article belongs to the Special Issue Advanced Human–Robot Interaction 2025)

Abstract

Robot hand-to-eye calibration is a necessary process for a robot arm to perceive and interact with its environment. Past approaches required collecting multiple images using a calibration board placed at different locations relative to the robot. When the robot or camera is displaced from its calibrated position, hand–eye calibration must be redone using the same tedious process. In this research, we developed a novel method that uses a semi-automatic process to perform hand-to-eye calibration with a stereo camera, generating a transformation matrix from the world to the camera coordinate frame from a single image. We use a robot-pointer tool attached to the robot’s end-effector to manually establish a relationship between the world and the robot coordinate frame. Then, we establish the relationship between the camera and the robot using a transformation matrix that maps points observed in the stereo image frame from two-dimensional space to the robot’s three-dimensional coordinate frame. Our analysis of the stereo calibration showed a reprojection error of 0.26 pixels. An evaluation metric was developed to test the camera-to-robot transformation matrix, and the experimental results showed median root mean square errors of less than 1 mm in the x and y directions and less than 2 mm in the z directions in the robot coordinate frame. The results show that, with this work, we contribute a hand-to-eye calibration method that uses three non-collinear points in a single stereo image to map camera-to-robot coordinate-frame transformations.
Keywords: robotics; computer vision; stereo calibration; hand-eye calibration robotics; computer vision; stereo calibration; hand-eye calibration

Share and Cite

MDPI and ACS Style

Kadam, P.; Fang, G.; Amirabdollahian, F.; Zou, J.J.; Holthaus, P. Stereo-Based Single-Shot Hand-to-Eye Calibration for Robot Arms. Computers 2026, 15, 53. https://doi.org/10.3390/computers15010053

AMA Style

Kadam P, Fang G, Amirabdollahian F, Zou JJ, Holthaus P. Stereo-Based Single-Shot Hand-to-Eye Calibration for Robot Arms. Computers. 2026; 15(1):53. https://doi.org/10.3390/computers15010053

Chicago/Turabian Style

Kadam, Pushkar, Gu Fang, Farshid Amirabdollahian, Ju Jia Zou, and Patrick Holthaus. 2026. "Stereo-Based Single-Shot Hand-to-Eye Calibration for Robot Arms" Computers 15, no. 1: 53. https://doi.org/10.3390/computers15010053

APA Style

Kadam, P., Fang, G., Amirabdollahian, F., Zou, J. J., & Holthaus, P. (2026). Stereo-Based Single-Shot Hand-to-Eye Calibration for Robot Arms. Computers, 15(1), 53. https://doi.org/10.3390/computers15010053

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop