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4th International Conference on robotics and Computer Vision, ICRCV 2022

作者： Yu, Zhenghong Wang, Hao Yang, Hang Zhou, Huabing Guangdong Polytechnic of Science and Technology School of Robotics Zhuhai China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology College of Computer Science and Engineering Wuhan Institute of Technology Wuhan China

ISBN: (数字)9781665481700

ISBN: (纸本)9781665481700

As computer vision and human-computer interaction technologies are getting mature, vision-based auxiliary text reading has become the mainstream method to optimize learning and reading experience. To overcome the drawbacks of the common multi-step detection way and further improve the text reading experience, we propose a new human-centered fast text-locating method, named HTD. It transforms the relatively time-consuming serial procedure to a hybrid object detection problem, utilizing the hand-text hybrid object detection model to instantly locate the text of interest to readers. Considering the particularity of this task, we choose to perform the weighted NMS to infer final predicted bounding box. To verify the effectiveness of the proposed method, we tested the performance on the homemade hand-text hybrid object detection dataset HTDD. The experiment indicated that our proposed method is more efficiency and can produce satisfying results, which could meet the needs of human-computer interactive auxiliary reading in text reading scenarios. © 2022 IEEE.

关键词： Object detection

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Simulation research on trajectory tracking control system of manipulator based on fuzzy PID control

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International Journal of Innovative Computing and Applications 2022年第5-6期13卷 269-277页

作者： Ma, Ruyi Li, Zeshen Jiang, Du Yun, Juntong Liu, Ying Liu, Yibo Bai, Dongxu Li, Gongfa Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan430081 China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Institute of Precision Manufacturing Wuhan University of Science and Technology Wuhan430081 China

In view of the influence of external environment interference, parameter changing and random noise in the process of manipulator trajectory tracking, as well as the problems of fuzzy PID control, such as fuzzy rules are not easy to set, quantisation interval and parameters are affected by subjective consciousness, which leads to the problem of insufficient performance of manipulator system. In this paper, firstly, in the MATLAB simulation environment, based on the D-H parameter model, the linkage model of the four degree of freedom manipulator is established, and the homogeneous transformation matrix of the manipulator is calculated. Then, through the application of fuzzy PID control in the Simulink toolbox, the optimal parameters of the controller are found by using the proportion factor self-adjusting strategy, and the corresponding trajectory tracking and forward inverse kinematics simulation are studied. The trajectory tracking curve of the manipulator is obtained. The research method and experimental results in the paper are of great significance for the simulation of articulated manipulator. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Simulink

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Building layover detection in SAR images via image translation 2

Building layover detection in SAR images via image translati...

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2nd International Conference on Signal Image Processing and Communication, ICSIPC 2022

作者： Wang, Haixia Yuan, Shuo Wang, Dongji Dong, Qiulei Hu, Zhanyi Key Laboratory for Robot and Intelligent Technology Shandong University of Science and Technology Shandong Province Qingdao City China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Haidian District Beijing China

ISBN: (纸本)9781510657694

Conventionally image translation is used to convert synthetic aperture radar (SAR) images to optical ones to increase interpretability. Due to the different imaging natures of SAR range sensing and optical directional projection, it is within the expectation that some kinds of SAR images could be reasonably translated into optical ones, while others not. Arguably, less good patches in the translated image could act as a potential indicator of salient differences of the two imaging mechanisms. Following this line of thought, considering in urban SAR images, the layover is mainly caused by buildings, we proposed a method to detect building layovers in SAR images by evaluating the correlation of the original SAR image and the translated one by the cycle-translation, that is, from SAR to optical to SAR translation. Because the presence of building is the main factor of the layover phenomenon in urban SAR images, building layover areas in SAR images are expected to be less correlated, or they should have a low correlation coefficient. Preliminary experiments validate our underlying principle and method. © 2022 SPIE.

关键词： Synthetic aperture radar

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Targetless Extrinsic Calibration for LiDAR and Camera Systems with Intensity Information

Targetless Extrinsic Calibration for LiDAR and Camera System...

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IEEE International Conference on Mechatronics, robotics and Automation (ICMRA)

作者： Weiyang Jiang Yanduo Zhang Tao Lu Yunxiao Hu Jiaming Wang Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China Guangyu Jingye(Wuhan) Intelligent Technology Co. Ltd Wuhan China Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

Accurate and efficient external calibration, available in real-time within a targetless environment, remains a significant challenge due to the inherent inhomogeneous reflectance, density distribution, and small FOV of Non-Repeat Scanning (NRS) LiDAR system data, these issues bring difficulties for subsequent applications in areas such as simultaneously localization and mapping (SLAM) and autonomous driving. To address these issues, this paper proposes a targetless method for the automatic calibration of LiDAR and camera systems. Initially, we analyzed the complexity and variability of LiDAR point cloud information and developed a feature extraction method that integrates geometric and intensity data. Subsequently, we optimized the intensity data within the point cloud to extract reliable intensity information. Finally, we matched and iteratively optimized the sensor system data to obtain the final extrinsic parameters. Through extensive experimental analysis, we verified the effectiveness and accuracy of our algorithm.

关键词： Point cloud compression Laser radar Accuracy Simultaneous localization and mapping robot vision systems Feature extraction Cameras Sensor systems Calibration robotics and automation

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Study on a Two-layer Path Planning Method of Spherical Multi-robot 20

Study on a Two-layer Path Planning Method of Spherical Multi...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Li, Chenqi Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory BinshuiXidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Key Laboratory of Convergence Medical Engineering Systems and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

A path planning method based on a two-layer coordination system is proposed for the compatibility requirement of path planning global optimum and local coordination in a spherical multi-robot system. In the first layer of the algorithm, the global path quality is improved by proposing a nonlinear sine factor and a sparrow search algorithm with improved levy flight strategy to plan the global collision-free optimal path for each robot. In the second layer, a rolling window method is used to determine the possible collision positions of each robot in the system, and a priority-based conflict resolution strategy is proposed to complete the local coordination of the path near the corresponding position. The experimental results show that the path planning method enables the robots to drive along the global optimal path, but still can carry out flexible and orderly local path coordination, which effectively improves the path planning performance of the system. © 2023 IEEE.

关键词： Multipurpose robots

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Two-Stage Hand-Eye Calibration based on Variance Minimization Principle

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Ding, Tao Tian, Dazhuang Wu, Hao Zhu, Dahu Li, Wenlog Wuhan University of Technology Hubei Key Laboratory of Advanced Technology for Automotive Components School of Automotive Engineering Wuhan430070 China Wuhan University of Technology Hubei Digital Manufacturing Key Laboratory School of Mechanical and Electronic Engineering Wuhan430070 China Wuhan University of Technology Hubei Key Laboratory of Advanced Technology for Automotive Components Hubei Provincial Engineering Research Center of Robot and Intelligent Manufacturing Wuhan430070 China Huazhong University of Science and Technology State Key Laboratory of Intelligent Manufacturing Equipment and Technology Wuhan430074 China

Hand-eye calibration in industrial scenarios greatly determines the efficiency and effectiveness of 3D vision-guided robotic tasks. Most of the existing hand-eye calibration methods, however, rely on collecting large-scale point cloud samples to guarantee high measurement accuracy, which is time-consuming and particularly influenced by measurement defects such as local missing, noise, and uneven density. To overcome this challenging problem, we present a novel two-stage hand-eye calibration method based on the variance minimization principle. In the first stage, a robust function weighted variance minimization (RFWVM) registration algorithm is proposed for fine registration of defective point clouds, aiming at solving the coarse hand-eye calibration matrix with few-shot point clouds. In the second stage, an objective function of the calibration error correction algorithm is established via the point-to-plane distance variance minimization, which is intended to suppress the influence of measurement defects. Through these two stages, the globally optimal hand-eye matrix is solved by iteratively correcting the coarse hand-eye calibration matrix. A series of experiments validate the universality, accuracy, and robustness of the proposed method. © 1963-2012 IEEE.

关键词： Error correction

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Design and Control for WLR-3P:A Hydraulic Wheel-Legged robot

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Cyborg and Bionic Systems 2023年第1期4卷 243-259页

作者： Xu Li Haoyang Yu Haibo Feng Songyuan Zhang Yili Fu State Key Laboratory of Robotics and System College of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Intelligent Robot Research Center Zhejiang LaboratoryHangzhou 311100China

The robot used for disaster rescue or field exploration requires the ability of fast moving on flat road and adaptability on complex *** hybrid wheel-legged robot(WLR-3P,prototype of the third-generation hydraulic wheel-legged robot)has the characteristics of fast and efficient mobility on flat surfaces and high environmental adaptability on rough *** this paper,3 design requirements are proposed to improve the mobility and environmental adaptability of the *** meet these 3 requirements,2 design principles for each requirement are put ***,for light weight and low inertia with high stiffness,3-dimensional printing technology and lightweight material are ***,the integrated hydraulically driven unit is used for high power density and fast response ***,the microhydraulic power unit achieves power autonomy,adopting the hoseless design to strengthen the reliability of the hydraulic *** is more,the control system including hierarchical distributed electrical system and control strategy is *** mobility and adaptability of WLR-3P are demonstrated with a series of ***,the robot can achieve a speed of 13.6 km/h and a jumping height of 0.2 m.

关键词： robot robot terrain

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PDAOD: An Unsupervised Domain Adaptation Method for Orchard Apple

PDAOD: An Unsupervised Domain Adaptation Method for Orchard ...

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IEEE International Conference on Mechatronics, robotics and Automation (ICMRA)

作者： Zhiyu Yang Yanan Li School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

Traditional unsupervised domain adaptation methods are limited in agricultural object detection due to small target sizes and cluttered backgrounds. The PDAOD-Net model is introduced, offering the capability to dynamically distribute attention between localization and classification tasks in a flexible manner. By utilizing point confidence matrix alignment to achieve precise domain adaptation, experiments show that PDAOD-Net achieves superior performance on apple orchard datasets, outperforming existing methods by approximately 5.8% in AP.

关键词： Location awareness Adaptation models Mechatronics Object detection robotics and automation

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Graph Convolutional Networks for Malicious URLs Detection

Graph Convolutional Networks for Malicious URLs Detection

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IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)

作者： Huanyu Yang Gengsheng Zheng School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

This study aims to explore the application of graph convolutional networks in the task of malicious domain detection, integrating it with cybersecurity issues. By leveraging graph convolutional networks to model the relationships between domains, we can more accurately capture semantic information and structural features among domains, thereby improving detection accuracy and generalization ability. The model achieves an average prediction accuracy of over 91.27% on two different datasets, malicious-url and CSIC. Experimental results demonstrate significant performance improvement in the task of malicious domain detection, validating the effectiveness of combining graph convolutional networks with cybersecurity problems.

关键词： Accuracy Automation Semantics Predictive models Feature extraction Information management Task analysis

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Median Filter Helps Lymph Node Segmentation in Deep Learning via PET/CT 4

Median Filter Helps Lymph Node Segmentation in Deep Learning...

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4th International Conference on Digital Medicine and Image Processing, DMIP 2021

作者： Zhang, Xuan Liao, WenTao Xu, Guoping School of Computer ScienceandEngineering Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology China

ISBN: (纸本)9781450386487

Pathological lymph node segmentation plays a vital role in clinical practice. Yet it is still a challenging problem owing to low contrast to surrounding structures on images. In this paper, we investigate the problem whether the classical median filter helps lymph node segmentation in deep learning via PET/CT. Specifically, we design a median filter layer and integrate it into two types of deep convolution neural networks: SegNet and DeepLabv3+, which takes the encoder and decoder structure that has the advantage to segment objects in a multi-scale way. Meanwhile, we adopt three various objective functions, which are cross entropy loss, generalized Dice loss and focal loss, to study which is the best choice for pathological lymph node segmentation with median filter. Four-fold cross validation has been done on 63 volumes containing 214 malignant lymph nodes, and the experiments demonstrate that median filter could help improve the lymph segmentation performance with cross entropy as loss function, which has 3% and 2% improvements with SegNet and 4% and 3% improvements with DeepLabv3+ in terms of Sensitivity and Dice Similarity Coefficient (DSC). © 2021 ACM.

关键词： Convolutional neural networks

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