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2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Wang, Tianyu Miao, Weiwei Zeng, Zeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The ubiquitous power Internet of things (IoT) constructs an intelligent service system with comprehensive perception, efficient response and flexible processing around all departments of the power system and with the support of communication technologies such as mobile Internet and artificial intelligence. With the rapid development of smart IoT perceptual devices and edge computing, it has become possible for perceptual devices and edge IoT agents to cooperate in processing tasks. The task completion time can be greatly reduced through the cooperative processing among multiple entities in the IoT. However, as the scale of the Internet of things and number of to-be-processed tasks expanding year by year, the simple task data interaction between devices can not meet the needs of the completion time. Therefore, it is an urgent problem to optimize data transmission and data interaction in the process of collaborative task processing among IoT devices. Motivated by this point, we propose an optimization method of data interaction in power IoT based on particle swarm algorithm. Evaluation on example IoT networks shows the effectiveness of our method to reduce overall task completion time. © 2022 IEEE.

关键词： Internet of things

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5G1M: Indoor Fingerprint Positioning Using a Single 5G Module

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IEEE Sensors Journal 2024年

作者： Wang, Changhao Jin, Xi Xia, Changqing Xu, Chi Sun, Yiming Duan, Yong Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110169 China Shenyang University of Technology Shenyang110870 China

Many critical applications necessitate indoor positioning, and the implementation of indoor positioning cannot be separated from various wireless signals. Among these, 5G-based indoor positioning is gaining increasing attention due to the wide coverage of 5G base stations and the stability of 5G signals. However, current positioning algorithms based on 5G signals require specialized measuring tools or information from telecommunication operators. Therefore, this paper proposes an indoor positioning algorithm, called 5G1M, that uses only a single 5G module and several commercial base stations already built outdoors. Besides these, 5G1M does not need any further assistance. We design 5G1M based on fingerprint positioning, which is less dependent on the environment and devices. First, 5G1M incorporates a Siamese network model with Ghost modules and squeeze-and-excitation blocks to reduce reliance on the scale of the fingerprint database and computational power while maintaining accuracy. Then, transfer learning is used to adapt to long-term environmental changes, and a trajectory-fitting method is employed to mitigate instantaneous signal fluctuations. The experimental result shows that in such a simplified positioning platform, 5G1M achieves a positioning error of 2.53 meters, improving accuracy by 29.7% compared to existing algorithms, and it also demonstrates faster convergence with fewer model parameters. © 2001-2012 IEEE.

关键词： Base stations

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Improved YOLOv5-based Method for Recognition of Insulator String Pins 12

Improved YOLOv5-based Method for Recognition of Insulator St...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2022

作者： Du, Jingbo Jiang, Yong Shenyang Ligong University Shenyang110158 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problem that the substation insulator replacement robot cannot accurately identify insulator pins in the complex outdoor light environment, an improved YOLOv5-based insulator pin identification method YOLOv5-CBP is proposed. For the substation insulator pin recognition task, the backbone of the network is replaced by the lightweight EfficientNet-lite0;the Neck of the network is optimized and a more efficient feature fusion module BiFPN combined with an attention mechanism is introduced. The bounding box regression loss function was changed to improve the accuracy of inspection frame detection. Finally, the improved algorithm is compared with the original YOLOv5 algorithm on a self-built dataset for experiments. The results show that the insulator pin recognition accuracy is improved by 8.3%, the size of the algorithm model is reduced to 54% of the original, and the number of parameters is reduced by 49.4%. The improved algorithm model more lightweight. © 2022 IEEE.

关键词： Degradation Substations Inspection Insulators control systems Pins Neck

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Design of a Force-controlled End-Effector with Slender Flexible Beams 16th

Design of a Force-Controlled End-Effector with Slender Fl...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Chen, Yin Chen, Genliang Chai, Yuchen Wang, Hao Kong, Lingyu State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiao Tong University Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China Shanghai Key Laboratory of Digital Manufacturing for Thin-Walled Structures Shanghai Jiao Tong University Shanghai200240 China Intelligent Robot Research Center Zhejiang Lab Hangzhou China

ISBN: (纸本)9789819965007

This paper proposes a force-controlled end-effector with slender flexible beams. On the one hand, it can actively control the deformation of slender flexible beams to output a constant force at the end-effector without using a force sensor. On the other hand, it serves as a passive compliant mechanism utilizing the large deformation characteristic of slender flexible beams to prevent structural damage. The kinetostatic modeling of the force-controlled end-effector has been derived to obtain the relationship between the output force and displacement. To conduct experimental tests, a prototype of the force-controlled end-effector has been fabricated. From the experimental results, it can be seen that the error of the force-controlled end-effector is within 0.5N. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Compliant mechanisms

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A graph-based two-stage classification network for mobile screen defect inspection

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Frontiers of Information Technology & Electronic Engineering 2023年第2期24卷 203-216页

作者： Chaofan ZHOU Meiqin LIU Senlin ZHANG Ping WEI Badong CHEN State Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310027China College of Electrical Engineering Zhejiang UniversityHangzhou310027China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong UniversityXi’an710049China

Defect inspection,also known as defect detection,is significant in mobile screen quality *** are some challenging issues brought by the characteristics of screen defects,including the following:(1)the problem of interclass similarity and intraclass variation,(2)the difficulty in distinguishing low contrast,tiny-sized,or incomplete defects,and(3)the modeling of category dependencies for multi-label *** solve these problems,a graph reasoning module,stacked on a classification module,is proposed to expand the feature dimension and improve low-quality image features by exploiting category-wise dependency,image-wise relations,and interactions between *** further improve the classification performance,the classifier of the classification module is redesigned as a cosine similarity *** the help of contrastive learning,the classification module can better initialize the category-wise graph of the reasoning *** on the mobile screen defect dataset show that our two-stage network achieves the following best performances:97.7%accuracy and 97.3%*** proves that the proposed approach is effective in industrial applications.

关键词： Graph-based methods Multi-label classification Mobile screen defects Neural networks

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Research on prefabricated component production line mold platform combination method

Research on prefabricated component production line mold pla...

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2021 International Conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2021

作者： Han, Zhonghua Yu, Lingfeng Li, Bo Qi, Yuanwei School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

In traditional prefabricated component manufacturing enterprises, there are often problems such as low utilization rate of the platform surface due to poor production plans of the enterprise, resulting in waste of production resources and low production capacity of the enterprise. In order to solve the problem of mold platform combination allocation in the production process of prefabricated component manufacturers, a mold platform combination allocation method based on the combination of machine learning and backtracking is proposed. The backtracking method is used to search for the theoretical best fit combination result, and the improved BL is used. The positioning algorithm simulates the placement process of the mold on the platform, and uses the Apriori algorithm to train the obtained data set to obtain the association rules contained in the frequent item set. When the enterprise re-produces, the prefabricated components are combined according to the association rules for production, and the utilization rate of the platform is improved. The simulation test is carried out with the example data of the prefabricated component manufacturing enterprise, which verifies the effectiveness of the combination allocation method of mold and platform combined with the backtracking method and the Apriori algorithm to solve the problem. © Published under licence by IOP Publishing Ltd.

关键词： Production control

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Research on Low Energy Software Defined Industrial Network Time Synchronization Method

Research on Low Energy Software Defined Industrial Network T...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jianmou Li Yongxin Miao Yunxu Zhang Shibo Wang Yongbao Guan Shuai Shao State Grid YingKou Electric Power Supply Company China Yingkou Liaoning Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Industrial control networks are becoming increasingly complex, with various types of networks and devices interconnected, forming a heterogeneous industrial control network environment. In this environment, network time synchronization becomes the key to ensuring the reliable and stable operation of industrial networks and production manufacturing. However, traditional time synchronization algorithms suffer from the problem of frequent broadcasting with fixed cycles, resulting in high communication overhead and hindering the achievement of green and low-carbon production goals. Therefore, studying a low-energy industrial network time synchronization method has important practical significance. This article proposes a low-energy software defined industrial network time synchronization method to solve the communication overhead problem caused by traditional time synchronization algorithms with fixed cycle frequent broadcasts. This method is based on the software defined network concept, constructs a layered network topology, and is compatible with various time synchronization protocols according to application requirements. Considering the impact of dynamic link delay on time synchronization accuracy, low-power synchronous broadcasting was achieved by dynamically adjusting the time synchronization period of each layer of the network, and the time synchronization period was further optimized.

关键词： Energy consumption Accuracy Industrial control Software algorithms Production Broadcasting Software

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A novel robotic visual perception framework for underwater operation

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Frontiers of Information Technology & Electronic Engineering 2022年第11期23卷 1602-1619页

作者： Yue LU Xingyu CHEN Zhengxing WU Junzhi YU Li WEN State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Ytech Kuaishou TechnologyBeijing 100085China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China

Underwater robotic operation usually requires visual perception(e.g.,object detection and tracking),but underwater scenes have poor visual quality and represent a special domain which can affect the accuracy of visual *** addition,detection continuity and stability are important for robotic perception,but the commonly used static accuracy based evaluation(i.e.,average precision)is insufficient to reflect detector performance across *** response to these two problems,we present a design for a novel robotic visual perception ***,we generally investigate the relationship between a quality-diverse data domain and visual restoration in detection *** a result,although domain quality has an ignorable effect on within-domain detection accuracy,visual restoration is beneficial to detection in real sea scenarios by reducing the domain ***,non-reference assessments are proposed for detection continuity and stability based on object ***,online tracklet refinement is developed to improve the temporal performance of ***,combined with visual restoration,an accurate and stable underwater robotic visual perception framework is ***-overlap suppression is proposed to extend video object detection(VID)methods to a single-object tracking task,leading to the flexibility to switch between detection and *** experiments were conducted on the ImageNet VID dataset and real-world robotic tasks to verify the correctness of our analysis and the superiority of our proposed *** codes are available at https://***/yrqs/VisPerception.

关键词： Underwater operation Robotic perception Visual restoration Video object detection

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Single Camera Based Gait Analysis Method with Scaled and Image Coordinate key-points

Single Camera Based Gait Analysis Method with Scaled and Ima...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Xiang, Tian-Yu Zhou, Xiao-Hu Xie, Xiao-Liang Liu, Shi-Qi Wang, Chen Gui, Mei-Jiang Li, Hao Hou, Zeng-Guang University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation School of Artificial Intelligence Beijing100049 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Clinical experiments and scientific evidence show the relations between gait and cognition. Neurological diseases (like stroke and cerebral palsy) distract patients' attention and restrict their executive functions. Furthermore, these diseases impair patients' movement and limit their social participation. Quantitative motion assessment is significant to medical decision-making for neurological disorders but is possible only with expensive motion capture systems and professional medical workers. Here, an end-To-end video-based quantitative gait analysis algorithm is proposed. Unlike previous works, which only focus on image coordinate key-points, our algorithm also utilizes scaled key-points that can depict the size of patients. These two groups of features are sent to other neural networks to extract temporal and spatial characteristics, and then the deep features are fused by the attention mechanism. Finally, a statistic model is used to process the proposed outputs to get a final result. Experiments on the public patients' dataset show the effectiveness and accuracy of our model. Furthermore, the ablation study proves that every step of the proposed method contributes to the whole system's performance. © 2022 IEEE.

关键词： Gait analysis

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Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Trajectory Planning Towards Water-Air Trans-Media Motion for...

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2024 China Automation Congress, CAC 2024

作者： Xiong, Yan Zhang, Pengfei Chen, Di Yu, Junzhi State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Shandong Nuclear Power Company LTD Yantai265116 China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9798350368604

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of trans-media motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions. © 2024 IEEE.

关键词： Trajectories

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