Vibration Measurement of Robot End-Effector Based on Improved Optical Flow in Stereo Vision
In the high-precision operation of industrial robotic arms, vibrations can reduce the accuracy of the end-effector trajectory. To achieve vibration suppression, it is essential to accurately measure the vibration characteristics, which makes high-precision vibration measurement particularly importan...
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Published in | International Conference on Automation, Control and Robotics Engineering (Online) pp. 23 - 28 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
16.07.2025
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Subjects | |
Online Access | Get full text |
ISSN | 2997-6278 |
DOI | 10.1109/CACRE66141.2025.11119600 |
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Abstract | In the high-precision operation of industrial robotic arms, vibrations can reduce the accuracy of the end-effector trajectory. To achieve vibration suppression, it is essential to accurately measure the vibration characteristics, which makes high-precision vibration measurement particularly important. Traditional contact sensors suffer from mass loading effects and complex installation, whereas computer vision-based approaches have gained significant attention in research due to their non-contact nature. We present a binocular vision-based approach for measuring the three-dimensional vibration of the robotic arm's end effector. The technique utilizes sub-pixel corner detection technology, a video motion magnification algorithm, and an improved optical flow tracking algorithm that integrates Kalman filtering and the Hungarian algorithm. Through experimental analysis of robotic arm end-effector vibrations, the visual algorithm's output was validated against contact sensor data, confirming its efficacy in detecting microvibrations. The experimental results demonstrate that this method can achieve a high-precision measurement of minute vibrations, with a measurement accuracy of 0.01 mm. Additionally, experimental results under different load conditions indicate that the vibration frequencies of the three axes of the robot arm's end effector are concentrated around a specific frequency, further demonstrating that the end vibration frequency of the robot arm is not directly related to the magnitude of the applied load. |
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AbstractList | In the high-precision operation of industrial robotic arms, vibrations can reduce the accuracy of the end-effector trajectory. To achieve vibration suppression, it is essential to accurately measure the vibration characteristics, which makes high-precision vibration measurement particularly important. Traditional contact sensors suffer from mass loading effects and complex installation, whereas computer vision-based approaches have gained significant attention in research due to their non-contact nature. We present a binocular vision-based approach for measuring the three-dimensional vibration of the robotic arm's end effector. The technique utilizes sub-pixel corner detection technology, a video motion magnification algorithm, and an improved optical flow tracking algorithm that integrates Kalman filtering and the Hungarian algorithm. Through experimental analysis of robotic arm end-effector vibrations, the visual algorithm's output was validated against contact sensor data, confirming its efficacy in detecting microvibrations. The experimental results demonstrate that this method can achieve a high-precision measurement of minute vibrations, with a measurement accuracy of 0.01 mm. Additionally, experimental results under different load conditions indicate that the vibration frequencies of the three axes of the robot arm's end effector are concentrated around a specific frequency, further demonstrating that the end vibration frequency of the robot arm is not directly related to the magnitude of the applied load. |
Author | Fang, Lijin Qian, Yian Zhao, Qiankun Wang, Chao |
Author_xml | – sequence: 1 givenname: Chao surname: Wang fullname: Wang, Chao email: wangchaomail202207@163.com organization: Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China – sequence: 2 givenname: Lijin surname: Fang fullname: Fang, Lijin email: ljfang@mail.neu.edu.cn organization: Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China – sequence: 3 givenname: Qiankun surname: Zhao fullname: Zhao, Qiankun email: robokun@qq.com organization: Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China – sequence: 4 givenname: Yian surname: Qian fullname: Qian, Yian email: qianyian_0315@163.com organization: Northeastern University,Faculty of Robot Science and Engineering,Shenyang,China |
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Snippet | In the high-precision operation of industrial robotic arms, vibrations can reduce the accuracy of the end-effector trajectory. To achieve vibration... |
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SubjectTerms | Accuracy End effectors Frequency measurement high-precision measurements industrial robotic arms Kalman filtering Kalman filters Optical flow Robot sensing systems Service robots sub-pixel corner detection three-dimensional vibration measurement Trajectory Vibration measurement Vibrations |
Title | Vibration Measurement of Robot End-Effector Based on Improved Optical Flow in Stereo Vision |
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