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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Xuan Duan, Haibin Zhang, Hui Wang, Fei-Yue Peng Cheng Laboratory Shenzhen China Beihang University Beijing China Beijing Jiaotong University Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

Learning-based change detection (CD) in water scenarios is a key functionality for unmanned aerial vehicle (UAV). However, computer vision algorithms require large number of labeled datasets. Inspired by parallel intelligence, we propose a systematic framework for data generation. In this work, the framework consists of simulated scene and image generation network. In simulated scene, simulated images with pixel-level annotations are automatically generated. Then, image generation network uses paired images (real and simulated) to generate synthetic images. We use simulated and synthetic images in combination with publicly available real-world images to conduct experiments. The experimental results indicate that: 1) simulated images can be used in change detection research;2) synthetic images effectively improve the performance of supervised change detection model. © 2021 IEEE.

关键词： Change detection

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Design of EL defect detection system for photovoltaic power station modules 4

Design of EL defect detection system for photovoltaic power ...

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2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Li, Na Fan, Tao Yan, Shiqi Wu, Ziang State Grid Electronic Commerce Co.LTD Beijing China State Grid Corporation of China Beijing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

In recent years, the photovoltaic power generation industry has been vigorously promoted and developed, while the solar cell as its core component may have micro-crack defects, which directly affect the power generation efficiency and stability of the photovoltaic system. Therefore, it is necessary to adopt a low-cost, efficient and flexible method to detect defects in solar cells. At present, most of the existing micro-cracks detection is carried out in the laboratory, and there is no EL micro-cracks detection in the actual photovoltaic power station. The main purpose of this paper is to design a set of EL defect detection system that can be used for actual photovoltaic power station modules, which is different from the traditional laboratory-level or module-level defect detection, and to carry the designed detection algorithm to the integrated device to operate. Experiments have shown that the system can perform real-time detection of photovoltaic module defects based on the string level, which improves the detection efficiency while saving time and cost, and shows good performance. © 2022 institute of Physics Publishing. All rights reserved.

关键词： Crack detection

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Accident prediction in mesoscopic view: A CPSS-based social transportation approach 1

Accident prediction in mesoscopic view: A CPSS-based social ...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Sun, Chen Tan, Ruichen Deng, Jie Zhou, Rui Chen, Long Wang, Fei-Yue Cao, Dongpu University of Waterloo Dept. of MME Waterloo Canada Waytous Inc. Qingdao China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665433372

In modern society, traffic accidents are becoming an essential social safety issue that cannot be ignored. Along with the convenience of the high-speed development of modernization, the prosperity of vehicles has also led to severe traffic accidents, which cause massive loss of lives and properties every year. Accident analysis and prediction based on big data have become increasingly important in social transportation. However, the traditional data analysis and prediction methods only focused on either macroscope(transportation) or microscope(vehicle), and the relationships between the two layers are missing. This paper proposes a novel analysis framework by introducing the mesoscopic factors to bridge the transportation and vehicle operation domain under the parallel driving setting. The feature aggregation and mesoscopic factors extraction are included in the proposed prediction strategy to improve the performance of various commonly used decision tree-based classifiers. Methods are compared under the most recent 5-year accident database, which stores over three million records. Insights are discussed based on the future application of connected autonomous vehicles and intelligent road infrastructures. © 2021 IEEE.

关键词： Forecasting

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Full Attention Tracker: A Good Combination of Pixel-Level and Region-Level Cross-Correlation

Full Attention Tracker: A Good Combination of Pixel-Level an...

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第42届中国控制会议

作者： Yuxuan Wang Liping Yan Zihang Feng Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology School of Artificial Intelligence Beijing University of Posts and Telecommunications

The tracker based on Siamese neural network is currently a technical method with high accuracy in the tracking *** the introduction of transformer in the visual tracking field, the attention mechanism has gradually emerged in tracking ***, due to the characteristics of attention operation, Transformer usually has slow convergence speed, and its pixel-level correlation discrimination in tracking is more likely to lead to overfitting, which is not conducive to long-term tracking. A brand new framework FAT was designed, which is the improvement of MixFormer. The operation for simultaneous feature extraction and target information integration in MixFormer is retained, and the Mixing block is introduced to suppress the background as much as possible before the information interaction. In addition, a new operation is designed: the result of region-level crosscorrelation is used as a guidance to help the learning of pixel-level cross-correlation in attention, thereby accelerating the model convergence speed and enhancing the model generalization. Finally, a joint loss function is designed to further improve the accuracy of the model. Experiments show that the presented tracker achieves excellent performance on five benchmark datasets.

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Stable control and Disturbance Rejection Strategy for Planar 2R Underactuated Robot via Intelligent Algorithm 48

Stable Control and Disturbance Rejection Strategy for Planar...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Huang, Zixin Wan, Xiao Zhou, Yaosheng Wang, Lejun Wang, Liheng School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China Wuhan Institute of Technology School of Innovation and Entrepreneurship Wuhan China Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Stable control and active disturbance rejection strategy is proposed for planar 2R underactuated robot via intelligent algorithm in this paper. At first, we build the dynamic model and describe the control characteristic. After that, we design PD controller for the active link. According to the underactuated constraint, we then optimize the parameters of controller by using the differential evolution algorithm (DEA), so that we can ensure the target states of all links could eventually be reached at the identical time. And the simulation results indicate the strategy is effective. © 2022 IEEE.

关键词： Disturbance rejection

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DSNRNet: A Network of LiDAR Data Denoising by Differential Stability in Underground Mine

DSNRNet: A Network of LiDAR Data Denoising by Differential S...

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International Conference on Intelligent Transportation

作者： Dejiang Meng Bin Tian Ziyu Pan Junhui Wang Long Chen The Waytous Inc. Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Data and Computer Science Sun Yat-sen University China

Some sprinklers in underground mines spray water mist to lessen the amount of dust in the air. But water mist causes LiDAR to provide inaccurate point measurements, which are referred to as water mist noise that undermines the effectiveness of LiDAR-based localization and object recognition. Therefore, in order to reduce water mist noise, we have developed a new noise segmentation network that can operate on a CPU in real time-differential stability noise removal network (DSNRNet). This network consists of two sub-networks. The first sub-network is aimed at extracting differential stability features, so we named it the differential stability feature extraction network (sub-network 1). The second sub-network: a fully connected neural network (sub-network 2), is used to segment noise. To evaluate the DSNRNet's performance, we built a LiDAR semantic segmentation dataset of underground mines and run the DSNRNet in an Intel i7-11800H CPU. The experimental results demonstrate that this method is able to strike a better balance between speed (26.3 milliseconds) and accuracy (97.8 % ) compared with the other two most possible methods-DSOR (24.2 milliseconds, 3.2 % ) and WeatherNet (436.8ms, 98.5 % ).

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Blockchain-based consensus study on distributed control systems 1

Blockchain-based consensus study on distributed control syst...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Zhu, Jing Deng, Hongchang Li, Xiang Yuan, Yong Wang, Feiyue College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China School of Mathematics Renmin University of China Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

In this paper, two blockchain-based consensus mechanisms are proposed for distributed control systems, those are the proof-of-work-based (PoW-based) and proof-of-stake-based (PoS-based) consensus mechanisms. The basic idea and process of these blockchain-based consensus mechanisms are introduced, giving rise to the dynamic, impartial and efficient consensus compared with the consensus protocol achieved by traditional control theories. © 2021 IEEE.

关键词： Multi agent systems

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Design of a novel flexible assistive hand exoskeleton 37

Design of a novel flexible assistive hand exoskeleton

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Li, Guotao Cheng, Long Gao, Zhengrun Lu, Jilong Zhao, Yanjiang Institute of Automation State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China Fudan University The National Clinical Research Center for Aging and Medicine Shanghai China Harbin University of Science and Technology Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin150080 China Intelligent Machine Institute Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9781665465366

Hand paralysis caused by stroke, spinal cord injury, or neurological trauma has a significant impact on the independence and quality of life of the patients. The hand exoskeleton can provide hand assistance and improve the patient's grasp. In this article, a novel wearable flexible hand exoskeleton is proposed to assist users in activities of daily life. To create a simple and lightweight assistive hand exoskeleton, 3D printing is used to manufacture most of the components, and a remote drive system is designed to reduce the weight of the hand exoskeleton. A ball pair device and a slider device are used to ensure the freedom of the thumb and the adaptability of the hand exoskeleton to different hand sizes. Finally, the experiments are conducted to verify that the hand exoskeleton can achieve motion assistance. © 2022 IEEE.

关键词： 3D printing

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System Dynamics-Based Analysis on Factors Influencing Comprehensive Competence of Primary and Secondary School Students

System Dynamics-Based Analysis on Factors Influencing Compre...

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Chinese automation Congress (CAC)

作者： Sifeng Jing Xiwei Liu Xiaoyan Gong Hongxia Zhao The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China

With rapid progress of artificial intelligence (AI) , it is urgent to promote educational reform to improve comprehensive competence level of primary and secondary school students (CCLPSSS). However, educational reform is a system engineering involving multiple and intertwined factors. In this research, a system dynamics-based model of education reform is developed. Then, based on this model, a series of simulation experiments are carried out to find main factors affecting improvement of CCLPSSS. Results show that: 1) this model could simulate trends of CCLPSSS under different educational reform measures; 2) Measures including teaching mode reform, development and application of AI-based new teaching method, implementation of Double Reduction in compulsory education, implementation of deepening education evaluation reform policy, and development and application of AI-based education evaluation technology could play significant roles in promoting CCLPSSS and further strengthening cultivation of AI compound talents.

关键词： Analytical models Text analysis System dynamics Education Decision making Predictive models Market research

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MALT: Multi-scale Action Learning Transformer for Online Action Detection

arXiv

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arXiv 2024年

作者： Yang, Zhipeng Wang, Ruoyu Tan, Yang Xie, Liping The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518063 China

Online action detection (OAD) aims to identify ongoing actions from streaming video in real-time, without access to future frames. Since these actions manifest at varying scales of granularity, ranging from coarse to fine, projecting an entire set of action frames to a single latent encoding may result in a lack of local information, necessitating the acquisition of action features across multiple scales. In this paper, we propose a multi-scale action learning transformer (MALT), which includes a novel recurrent decoder (used for feature fusion) that includes fewer parameters and can be trained more efficiently. A hierarchical encoder with multiple encoding branches is further proposed to capture multi-scale action features. The output from the preceding branch is then incrementally input to the subsequent branch as part of a cross-attention calculation. In this way, output features transition from coarse to fine as the branches deepen. We also introduce an explicit frame scoring mechanism employing sparse attention, which filters irrelevant frames more efficiently, without requiring an additional network. The proposed method achieved state-of-the-art performance on two benchmark datasets (THUMOS’14 and TVSeries), outperforming all existing models used for comparison, with an mAP of 0.2% for THUMOS’14 and an mcAP of 0.1% for TVseries. Copyright © 2024, The Authors. All rights reserved.

关键词： Encoding (symbols)

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