Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate
Point cloud data provides three-dimensional (3D) measurement of the geometric details in the physical world, which relies heavily on the quality of the machine vision system. In this paper, we explore the potentials of a 3D scanner of high quality (15 million points per second), accuracy (up to 0.15...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-05-01
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| Series: | Frontiers in Robotics and AI |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/frobt.2020.00065/full |
| _version_ | 1818515058201722880 |
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| author | Fang Wan Chaoyang Song |
| author_facet | Fang Wan Chaoyang Song |
| author_sort | Fang Wan |
| collection | DOAJ |
| description | Point cloud data provides three-dimensional (3D) measurement of the geometric details in the physical world, which relies heavily on the quality of the machine vision system. In this paper, we explore the potentials of a 3D scanner of high quality (15 million points per second), accuracy (up to 0.150 mm), and frame rate (up to 20 FPS) during static and dynamic measurements of the robot flange for direct hand-eye calibration and trajectory error tracking. With the availability of high-quality point cloud data, we can exploit the standardized geometric features on the robot flange for 3D measurement, which are directly accessible for hand-eye calibration problems. In the meanwhile, we tested the proposed flange-based calibration methods in a dynamic setting to capture point cloud data in a high frame rate. We found that our proposed method works robustly even in dynamic environments, enabling a versatile hand-eye calibration during motion. Furthermore, capturing high-quality point cloud data in real-time opens new doors for the use of 3D scanners, capable of detecting sensitive anomalies of refined details even in motion trajectories. Codes and sample data of this calibration method is provided at Github (https://github.com/ancorasir/flange_handeye_calibration). |
| first_indexed | 2024-12-11T00:24:03Z |
| format | Article |
| id | doaj.art-36bc4426bd7a42a9a6c1d2b38ca76af3 |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-12-11T00:24:03Z |
| publishDate | 2020-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-36bc4426bd7a42a9a6c1d2b38ca76af32022-12-22T01:27:37ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442020-05-01710.3389/frobt.2020.00065537294Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame RateFang Wan0Chaoyang Song1AncoraSpring, Inc. and SUSTech Institute of Robotics, Southern University of Science and Technology, Shenzhen, ChinaDepartment of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, ChinaPoint cloud data provides three-dimensional (3D) measurement of the geometric details in the physical world, which relies heavily on the quality of the machine vision system. In this paper, we explore the potentials of a 3D scanner of high quality (15 million points per second), accuracy (up to 0.150 mm), and frame rate (up to 20 FPS) during static and dynamic measurements of the robot flange for direct hand-eye calibration and trajectory error tracking. With the availability of high-quality point cloud data, we can exploit the standardized geometric features on the robot flange for 3D measurement, which are directly accessible for hand-eye calibration problems. In the meanwhile, we tested the proposed flange-based calibration methods in a dynamic setting to capture point cloud data in a high frame rate. We found that our proposed method works robustly even in dynamic environments, enabling a versatile hand-eye calibration during motion. Furthermore, capturing high-quality point cloud data in real-time opens new doors for the use of 3D scanners, capable of detecting sensitive anomalies of refined details even in motion trajectories. Codes and sample data of this calibration method is provided at Github (https://github.com/ancorasir/flange_handeye_calibration).https://www.frontiersin.org/article/10.3389/frobt.2020.00065/full3D scannerhand-eye calibrationrobustnessflange-based calibrationphotoneo |
| spellingShingle | Fang Wan Chaoyang Song Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate Frontiers in Robotics and AI 3D scanner hand-eye calibration robustness flange-based calibration photoneo |
| title | Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate |
| title_full | Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate |
| title_fullStr | Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate |
| title_full_unstemmed | Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate |
| title_short | Flange-Based Hand-Eye Calibration Using a 3D Camera With High Resolution, Accuracy, and Frame Rate |
| title_sort | flange based hand eye calibration using a 3d camera with high resolution accuracy and frame rate |
| topic | 3D scanner hand-eye calibration robustness flange-based calibration photoneo |
| url | https://www.frontiersin.org/article/10.3389/frobt.2020.00065/full |
| work_keys_str_mv | AT fangwan flangebasedhandeyecalibrationusinga3dcamerawithhighresolutionaccuracyandframerate AT chaoyangsong flangebasedhandeyecalibrationusinga3dcamerawithhighresolutionaccuracyandframerate |