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OPTIMIZATION OF EYE-IN-HAND CALIBRATION METHODS 10

OPTIMIZATION OF EYE-IN-HAND CALIBRATION METHODS

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Ge, Xiaoliang Zuo, Yunbo Gu, Yuhai Miao, Zhuoran Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

Hand-eye calibration is a vital part in the field of robot vision and motion control, which ensures that the robot system can accurately perceive and operate the surrounding environment. To enhance the accuracy of the hand-eye calibration matrix obtained in the current experimental environment, this paper provides an optimal scheme for the selection of calibration points and hand-eye calibration algorithms on the checkerboard calibration board. The geometric errors, rotation-translation errors and other parameters of Tsai algorithm and Navy algorithm were calculated based on multiple sets of experimental data, and the performance differences between the two algorithms were evaluated. The experimental results show that in the calibration environment of this experiment, the optimal selection number of marker points is about 12, and the optimal calibration algorithm is Tsai algorithm. This study provides a reference for the optimization of robotic hand-eye calibration technology. © The Institution of Engineering & technology 2024.

关键词： Errors

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HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD REGISTRATION METHOD 10

HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD R...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Miao, Zhuoran Zuo, Yunbo Hu, Huan Ge, Xiaoliang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

The objective of this paper is to investigate a hand-eye calibration approach employing an eye-to-hand configuration, focusing on point cloud registration. In the initial segments of the paper, the paper delineate the core principles that underpin hand-eye calibration, as well as the various techniques that are predominantly utilized in this field. Furthermore, the article meticulously analyzes the limitations of the traditional methods and identifies potential areas where improvements can be made. Subsequently, it delves into the hand-eye calibration methodology grounded in 3D point cloud registration. This exploration includes an in-depth analysis of an enhanced version of the Super 4PCS Algorithm-based point cloud registration algorithm, which is a novel and effective method for point cloud registration. Additionally, the article discusses the intricacies of coordinate system transformation and provides a comprehensive explanation of how to solve the hand-eye calibration equation AX=XB using the navy method. Furthermore, the paper empirically validates the efficacy and precision of this method. This validation process involves a comparative analysis with other existing approaches. Lastly, it summarizes the research findings and discusses the strengths and limitations of the proposed method. © The Institution of Engineering & technology 2024.

关键词： Robotic arms

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FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VARIABLE SPEED AND STRONG NOISE 10

FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VAR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qiao, Wan Liu, Xiuli Huang, Jinpeng Wu, Guoxin Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

Aiming at the fault diagnosis of rotating machinery in industrial production, which faces the problems of signal noise, variable speed and other interferences that lead to inconspicuous fault features, and the traditional methods rely on manual experience for feature extraction and lack of robustness, the present study introduces a novel fault diagnosis approach utilizing the TimesNet model. This method takes the temporal multi-periodicity as the starting point, and the one-dimensional original signal is divided into multiple two-dimensional signals by different sizes of the period respectively. Subsequently, Inception-Attention modeling is applied to extract intricate time and space information. The experiments use the planetary gearbox dataset to verify the influence of different parameters and structures of TimesNet on the diagnostic effect, and carry out comparative tests with five time-series classification models, which provide some reference value for the application of TimesNet in fault diagnosis. © The Institution of Engineering & technology 2024.

关键词： Epicyclic gears

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SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT ASSOCIATION 10

SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT A...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Chen, Sai Zuo, Yunbo Hu, Huan Zheng, Yifan Li, Haowei Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

To address the security risks caused by unauthorized individuals smoking in public places, a method for detecting smoking behavior based on an improved YOLOv7 target association is proposed. First, the improved YOLOv7 algorithm is used to detect the people and cigarette targets in the image, and then the distance relationship between the center coordinates of the cigarette target detection frame and the person target detection box is calculated, and the correlation between the two is located to determine whether there is smoking behavior. The improved YOLOv7 algorithm introduces the CBAM attention module to prioritize key areas and diminish background interference. Simultaneously, the SIOU loss function is employed to bolster the precision of the regression outcomes. Experiments conducted on the test dataset reveal that the proposed approach achieves an accuracy of 91.35% and a detection speed of 78 FPS, achieving real-time accurate detection effects. © The Institution of Engineering & technology 2024.

关键词： IMPROVED YOLOV7 OBJECT ASSOCIATION SMOKING BEHAVIOR DETECTION

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DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CROSS-ATTENTION NETWORK 10

DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Liu, Yizheng Su, Qinghua Song, Yue Zhang, Pengbo Xie, Zhihao Wang, Liyong Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

In the field of 3D vision technology, binocular vision technology, as a representative of low-cost and high-efficiency methods, has gained widespread attention and holds superior application prospects in the industrial sector. The current state-of-the-art binocular sparse visual SLAM systems can accurately and reliably estimate camera trajectories and landmark positions. However, these sparse maps are solely used for localization and cannot be employed for other tasks such as obstacle avoidance or scene understanding. To address this, this paper proposes a framework for constructing dense point cloud maps in binocular sparse visual SLAM systems. This framework enhances the traditional ORB-SLAM2 algorithm by incorporating depth estimation using a cross-attention network to complete depth information and build dense point cloud maps based on its localization capabilities. For the first-frame image, the proportion of incorrectly predicted pixels in the KITTI dataset is only 1.77%. The proposed method is effective and robust on common datasets, suitable for constructing dense point cloud maps in outdoor large-scale scenes. The output model is overall comprehensive and detailed, holding significant practical value in various outdoor scenarios. © The Institution of Engineering & technology 2024.

关键词： Binoculars

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THE ADAPTIVE MPC controlLER OF AUTONOMOUS DRIVING FORMULA FOR TRAJECTORY TRACKING 10

THE ADAPTIVE MPC CONTROLLER OF AUTONOMOUS DRIVING FORMULA FO...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Chen, Bowen Su, Qinghua Song, Yue Yin, Zehao Wang, Liyong Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

Autonomous driving technology has gradually been applied in real life, and it has also been improved in the China Collegiate Electric Vehicle Racing. However, as one of the critical components of autonomous driving technology, trajectory tracking control still faces challenges. This paper designs a trajectory tracking controller by building a vehicle's three-degree-of-freedom dynamics model and adopting adaptive model predictive control. It adjusts the prediction horizon of the vehicle's trajectory tracking controller in real-time based on the curvature of the desired trajectory to improve the effect of trajectory tracking. Experimental results show that the tracking effect of the adaptive prediction time-domain trajectory tracking controller in the S-curve is improved by 4.97% and 11.36% compared to the fixed prediction time-domain trajectory tracking controller, respectively. For the formula track conditions, the tracking effect of the controller proposed in this paper is improved by 0.71% compared to the fixed prediction time-domain trajectory tracking controller, with an average tracking error of 5.65%. © The Institution of Engineering & technology 2024.

关键词： Adaptive control systems

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REVIEW OF RESEARCH ON OCCLUSION ISSUES IN RGB-D DYNAMIC SCENE 3D RECONSTRUCTION 10

REVIEW OF RESEARCH ON OCCLUSION ISSUES IN RGB-D DYNAMIC SCEN...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Dong, Yuanqiu Wu, Guoxin Zhang, Guolong Zhou, Linglong Qi, Yinyan The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

As innovation proceeds to advance,3D recreation innovation has ended up a critical portion of the field of computer vision. Among these, 3D reproduction innovation based on RGB-D information sources has ended up a well known approach in later a long time. Right now, the more develop inactive 3D recreation calculations have ended up progressively successful for reproducing stationary objects. Be that as it may, their adequacy lessens when parts of the scene are blocked. This paper briefly presents particular approaches to address impediment issues and the fundamental concepts of energetic 3D remaking innovation based on RGB-D information sources. The points of interest and current investigate status of energetic 3D reproduction focusing on impediment issues utilizing RGB-D information sources are examined. Moreover, the most recent progressions in 3D remaking of energetic scenes are summarized, and proposed future investigate bearings. © The Institution of Engineering & technology 2024.

关键词： 3D reconstruction

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REARCH ON DOUBLE CUBIC INTERPOLATION COMBINED WITH GAUSSIAN FITTING SUB-PIXEL EDGE DETECTION METHOD 10

REARCH ON DOUBLE CUBIC INTERPOLATION COMBINED WITH GAUSSIAN ...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qi, Yinyan Wu, Guoxin Li, Yao Dong, Yuanqiu The Ministry of Education Key Laboratory of Modern Measurement and Control Technology Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

With the rapid advancements in intelligent manufacturing technology, the realization of fast and accurate measurements in aerospace, instrumentation, machinery and equipment, automotive electronics, and other sectors has become a research hotspot. Image positioning technology and edge detection methods, with their advantages of being fast, non-contact, and precise, have been widely employed. How to improve the accuracy of image measurement lies in solving the problem of accurate positioning of image edge detection, based on the problem of inaccurate extraction of directional information and large error in contour size of image edge detection technology proposes an improved sub-pixel edge detection algorithm with Gaussian fitting by double cubic interpolation. Based on preprocessing for pixel-level edge feature extraction, pixel-level edge points are acquired utilizing the least squares fitting algorithm. The normal section is determined by computing the normal intercept line, while the normal isometric line is identified through the Gaussian integration method. Sub-pixel fitting points are obtained via boundary fitting, and the final grey value is derived using an edge detection algorithm that combines double cubic interpolation and Gaussian fitting on the fitted points. The experimental results demonstrate that, through comparative testing of this method, it has been verified that it exhibits the highest image quality and is superior to most current algorithms. An improvement in the algorithm by 0.021%, 0.025%, and 0.031% in edge localization accuracy compared to the Zernike moment algorithm, Gaussian fitting algorithm, and bicubic interpolation algorithm has been achieved, effectively verifying that the image quality detected by this method is relatively high. In comparison with the point cloud method regarding fitting error, it was observed that the error index increased by 0.025% under strong burst light conditions, 0.026% under normal burst light conditions, an

关键词： Interpolation

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APPLICATION OF WAVELET KURTOSIS CONVOLUTIONAL NEURAL NETWORK MODEL IN ROLLING BEARING FAULT DIAGNOSIS 10

APPLICATION OF WAVELET KURTOSIS CONVOLUTIONAL NEURAL NETWORK...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Men, Dachao Jiang, Zhanglei Liu, Xiuli Zheng, Wei Li, Zihan Zha, Zhendong Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

Aiming at the problem of substantial noise in the actual industrial environment, where the intelligent diagnostic model exhibits weak anti-noise performance and the interpretability of the extracted features is not strong, the wavelet kurtosis convolutional neural network model integrating signal processing technology and deep learning neural networks has been proposed. Firstly, the standard CNN convolution kernel has been replaced with a wavelet basis function to form a wavelet convolution layer, and the input signal undergoes decomposition into various frequency components via the wavelet filter in this layer;Secondly, a kurtosis loss layer has been used to filter the high kurtosis value components that contain more fault features, so as to achieve the filtration of the noise and the accurate localisation of the fault signals;Lastly, the efficacy of the proposed model has been verified in the rolling bearing dataset and diagnostic model. The results showed that the model can reach 90% diagnostic accuracy under -4db Gaussian white noise interference, which was higher than other diagnostic models, and had good generalisation and noise resistance. © The Institution of Engineering & technology 2024.

关键词： White noise

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HYBRID-DRIVEN MODEL FOR TEMPERATURE PREDICTION IN WET CLUTCHES 10

HYBRID-DRIVEN MODEL FOR TEMPERATURE PREDICTION IN WET CLUTCH...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Huang, Yuanbin Li, Le Wang, Qian Wang, Liyong Key Laboratory of Modern Measurement and Control Technology in Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

A hybrid-driven model for predicting the temperature at the friction interface of wet clutch friction components was developed, employing a radial basis function neural network algorithm. This model uses temperature data obtained from wet clutch test bench experiments to compensate for the results from a thermo-mechanical coupled numerical simulation model of the friction components. The hybrid model inputs include load pressure, relative speed, radial position of the friction components, and numerically simulated temperatures at the friction interface, to output predicted temperatures under specific operating conditions. The results indicate that the predicted temperatures of the friction components under various conditions align well with experimental values, with a maximum mean relative error of 0.033 and all prediction intervals having a coefficient of determination higher than 0.97. Thus, the hybrid-driven model demonstrates high accuracy and stability in predictions, and possesses strong adaptability and predictive capabilities for different temperature distributions at the friction interface. © The Institution of Engineering & technology 2024.

关键词： Radial basis function networks

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