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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate.

Fang Wan¹, Chaoyang Song²

¹AncoraSpring, Inc. and SUSTech Institute of Robotics, Southern University of Science and Technology, Shenzhen, China.

Frontiers in Robotics and AI

|January 27, 2021

Summary

This study demonstrates a high-quality 3D scanner for robust robot hand-eye calibration. The method accurately tracks dynamic trajectories and detects anomalies in motion, enhancing machine vision applications.

Keywords:

3D scanner flange-based calibration hand-eye calibration photoneo robustness

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Area of Science:

Robotics
Machine Vision
Metrology

Background:

Accurate 3D measurement is crucial for machine vision systems.
Robot hand-eye calibration requires high-quality geometric data.
Dynamic measurements present challenges for traditional calibration methods.

Purpose of the Study:

To explore the potential of a high-performance 3D scanner for robot hand-eye calibration.
To enable direct calibration using standardized geometric features on robot flanges.
To validate calibration methods in dynamic environments with real-time data capture.

Main Methods:

Utilized a 3D scanner with high point rate (15M points/sec), accuracy (0.150 mm), and frame rate (20 FPS).
Employed standardized geometric features on robot flanges for 3D measurement.
Tested flange-based calibration methods in static and dynamic settings, capturing high-frame-rate point cloud data.

Main Results:

Achieved robust and versatile hand-eye calibration in dynamic environments.
Demonstrated accurate trajectory error tracking using real-time 3D data.
Successfully detected sensitive anomalies in refined details during motion trajectories.

Conclusions:

High-quality point cloud data from advanced 3D scanners facilitates robust hand-eye calibration.
Flange-based calibration methods are effective even in dynamic settings.
Real-time 3D scanning opens new possibilities for anomaly detection in moving objects.