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Swarm-Based Dynamic Coverage of Multi-ASV Systems in the Presence of Measurement Noises

IEEE Transactions on Vehicular technology 2025年第5期74卷 7237-7250页

作者： Liu, Lu Jiao, Shijian Han, Bing Li, Tieshan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China Shanghai Ship and Shipping Research Institute National Engineering Research Center of Ship & Shipping Control System Shanghai200135 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper is concerned with the dynamic coverage of multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles, limited communication distance, and measurement noises. A modular control method including planning, guidance, and control is proposed. At the planning level, a swarm-based dynamic coverage strategy is developed to achieve the coverage of a given domain. Both the collision avoidance and connectivity preservation issues are solved by using artificial potential fields. At the kinematic level, novel adaptive line-of-sight guidance laws are presented based on cascade extended state observers (CESOs), such that accurate guidance signals are given by compensating for time-varying sideslip angle and suppressing measurement noises. At the kinetic level, two CESOs are developed to estimate the internal model uncertainties and external environmental disturbance, and antidisturbance kinetic control laws are designed subsequently. The proposed CESOs overcome the noises sensitivity problem of classical observers, and thus facilitate the practical implementation under measurement noises. The input-to-state stability of the closed-loop system is confirmed by the Lyapunov theory and cascade stability theory. Simulation and hardware-in-the-loop experiment results are provided to demonstrate the effectiveness of the proposed swarm-based dynamic coverage method. © 1967-2012 IEEE.

关键词： Velocity measurement

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Detector-grade perovskite single-crystal wafers via stress-free gel-confined solution growth targeting high-resolution ionizing radiation

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Light(science & Applications) 2023年第5期12卷 754-765页

作者： Yilong Song Lixiang Wang Yongqiang Shi Weihui Bi Jianwu Chen Mingwei Hao Anran Wang Xueying Yang Yuan Sun Fan Yu Liansheng Li Yanjun Fang Deren Yang Qingfeng Dong State Key Laboratory of Supramolecular Structure and Materials College of ChemistryJilin UniversityChangchun 130012China State Key Laboratory of Silicon Materials and School of Materials Science and Engineering Zhejiang UniversityHangzhou 310027China Beijing Institute of Control Engineering Beijing 100190China Science and Technology on Space Intelligent Control Laboratory Beijing 100190China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China

Solution-processed organic‒inorganic halide perovskite(OIHP)single crystals(SCs)have demonstrated great potential in ionizing radiation detection due to their outstanding charge transport properties and low-cost ***,the energy resolution(ER)and stability of OIHP detectors still lag far behind those of melt-grown inorganic perovskite and commercial CdZnTe counterparts due to the absence of detector-grade high-quality OIHP ***,we reveal that the crystallinity and uniformity of OIHP SCs are drastically improved by relieving interfacial stress with a facial gel-confined solution growth strategy,thus enabling the direct preparation of large-area detector-grade SC wafers up to 4 cm with drastically suppressed electronic and ionic *** resultant radiation detectors show both a small dark current below 1 nA and excellent baseline stability of 4.0×10^(-8) nA cm^(-1) s^(-1) V^(-1),which are rarely realized in OIHP ***,a record high ER of 4.9% at 59.5 keV is achieved under a standard 241Am gamma-ray source with an ultralow operating bias of 5 V,representing the best gamma-ray spectroscopy performance among all solution-processed semiconductor radiation detectors ever reported.

关键词： resolution confined stress

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CNS/INS Integrated Navigation Method Based on Improved Adaptive CKF Algorithm 49

CNS/INS Integrated Navigation Method Based on Improved Adapt...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wang, Dong Yang, Jing Xiong, Kai Li, Wenling School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9798350331820

Aiming at the problem that measurement model uncertainty restrains navigation accuracy in the celestial/ inertial (CNS/INS) integrated navigation system, a kind of CNS/INS integrated navigation method based on improved adaptive cubature Kalman filter (CKF) is proposed. In order to mitigate the influence of installation error and axis disturbance error of star camera, angular distance between starlight vector of stars and line of sight vector of space targets is employed to establish the measurement model;the measurement noise covariance matrix (MNCM) is estimated online to lower the model uncertainty;adaptive adjustment coefficient is constructed based on squared Mahalanobis distance (SMD) of measurement innovation to adjust forgetting factor online to further improve robustness and adaptability of the method. Simulation results demonstrate that the proposed method can achieve higher navigation accuracy compared to standard and classical method under measurement model mismatch. © 2023 IEEE.

关键词： Uncertainty analysis

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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Research on lightweight detection algorithm of Infrared Image based on YOLOv5 4

Research on lightweight detection algorithm of Infrared Imag...

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4th International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2024

作者： Zhang, Wenyi Mo, Hongwei Wu, Songling Li, Xiaomin Harbin Engineering University School of Intelligent Science and Engineering Harbin150000 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing100854 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

At present, infrared image can show good detection effect in complex environment because of its unique imaging characteristics, which brings a lot of convenience to people's production and life. However, because the infrared image contains a great lot of unnecessary information, it has great requirements for computing power and memory capacity, so it is challenging to satisfy the demands of real-time detection on resource-constrained portable mobile devices. To solve this problem, this paper proposes a refined lightweight algorithm built upon the YOLOv5, which changes the backbone network of the model to GhostNet network, introduces CA attention mechanism into the model to improve the detection effect of small targets, and changes the loss function of the model to Focal-EIoU loss function to improve the location effect of the boundary box and quicken the model's rate of convergence. Then replace the conventional convolution used in the sampling process of the model with the space-to-depth convolution module, in order to enhance the model's detection performance on low-resolution images and enable the extraction of more feature information. According to the experimental results, the enhanced detection algorithm is just 1% less than the initial YOLOv5 algorithm, and the model volume and floating point calculation are reduced by 31.9% and 36% respectively. This is better suited for deployments that are lightweight. © 2024 SPIE.

关键词： Convolution

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RUL Prediction of Turbo Engine Based on CNN-LSTM and Attention Mechanism 3

RUL Prediction of Turbo Engine Based on CNN-LSTM and Attenti...

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3rd International Symposium on Aerospace engineering and Systems, ISAES 2024

作者： Zhang, Jiarong Lu, Weiquan Jv, Jinli Liu, Ziyu Zhao, Yuxiang Jiang, Haobo Yang, Yongheng Wang, Ziyi School of Intelligent Manufacturing and Control Technology Xi'an Mingde Institute of Technology Xi'an China School of Information Engineering Xi'an Mingde Institute of Technology Xi'an China College of Mechanical and Electrical Engineering Shandong Jianzhu University Jinan China School of Materials Science and Engineering Xi'an University of Technology Xi'an China

ISBN: (纸本)9798350350418

In the process of equipment Remaining Useful Life (RUL), there are often high-dimensional, long-time series of correlation data. The traditional method is difficult to extract the characteristics of such data, and there are often problems such as the disappearance of gradient. For such cases, this article proposes a residual life prediction model for turbo engines based on CNN-LSTM ATTENTION. Preprocess the sensor data such as standardization, extract relevant features through CNN, and introduce attention mechanism to the traditional LSTM for practical feature extraction and prediction. The validation on C-MAPSS data set shows that this method achieves good prediction results. © 2024 IEEE.

关键词： Prediction models

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Accurate modulation of photoprinting under stiffness imaging feedback for engineering ECMs with high-fidelity mechanical properties

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Microsystems & Nanoengineering 2022年第3期8卷 291-301页

作者： Xin Li Huaping Wang Xinyi Dong Qing Shi Tao Sun Shingo Shimoda Qiang Huang Toshio Fukuda Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China The Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China Intelligent Behavior Control Collaboration Unit RIKEN Center of Brain Science463-0003 NagoyaJapan

Engineered extracellular matrices(ECMs)that replicate complex in-vivo features have shown great potential in tissue *** hydrogel microstructures have been widely used to replace these native ECMs for physiologically relevant ***,accurate reproduction of the 3D hierarchical and nonuniform mechanical stffness inside one integrated microstructure to mimic the complex mechanical properties of native ECMs presents a major ***,by using digital holographic microscopy(DHM)-based stffness imaging feedback,we propose a novel closed-loop control algorithm to achieve high-accuracy control of mechanical properties for hydrogel microstructures that recapitulate the physiological properties of native ECMs with high *** photoprinting,the photocuring area of the hydrogel is divided into microscale grid areas to locally control the photocuring *** the assistance of a motorized microfluidic channel,the curing thickness is controlled with layer-by-layer *** DHM-based stiffness imaging feedback allows accurate adjustment of the photocuring degree in every grid area to change the crosslinking network density of the hydrogel,thus enabling large-span and high-resolution modulation of mechanical ***,the gelatin methacrylate was used as a typical biomaterial to construct the highfidelity biomimetic *** Young's modulus could be flexibly modulated in the 10 kPa to 50 kPa ***,the modulus gradient was accurately controlled to within 2.9 *** engineering ECM with locally different mechanical properties,cell spreading along the stff areas was observed *** believe that this method can regenerate complex biomimetic ECMs that closely recapitulate in-vivo mechanical properties for further applications in tissue engineering and biomedical research.

关键词： microstructure ECM curing

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MMLN: Multi-directional and Multi-constraint Learning Network for Remote Sensing Imagery Semantic Segmentation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2024年 1-16页

作者： Sun, Hang Xie, Yongchang Ren, Dong Wen, Fangqing Tong, Lyuyang Chang, Laibin Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China Institute of Vehicle Information Control and Network Technology Hubei University of Automotive Technology Shiyan China School of Computer Science Wuhan University Wuhan China

Recent advances in satellite remote sensing technology and computer technology have significantly impacted practical applications in remote sensing image segmentation. However, the prevalent hybrid segmentation models that combine Convolutional Neural Networks (CNNs) and Transformers, often overlook the critical exploration of local and global feature correlations across various scales. This exploration is essential for learning more representative features and strengthening context modeling capabilities. Additionally, the decoding layers of these models do not effectively exploit the pixel-level semantic relationships within cross-layer feature maps, thereby limiting the models' ability to discern small object features. To address these challenges, this paper introduces a Multi-directional and Multi-constraint Learning Network (MMLN) designed for semantic segmentation of remote sensing imagery. This network features a Multi-directional Dynamic Complement Decoder (MDCD), which enhances the interaction between local and global features in the feature space, and subsequently improves the feature discrimination within the segmentation network. Moreover, a Multi-constraint Saliency Boundary-adaptive Module (MSBM) is implemented to reinforce the spatial constraints on saliency at the edge regions and ensure semantic consistency along the mask boundaries. This, in turn, augments the segmentation model's capability to detect small objects. The evaluation on four datasets reveals that the MMLN outperforms the existing state-of-the-art methods in remote sensing imagery segmentation. The code is available at https://***/zhongyas/MMLN. Authors

关键词： Semantics

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Competitive Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1902-1904页

作者： Boxi Weng Jian Sun Gao Huang Fang Deng Gang Wang Jie Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081 Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China School of Automation Tsinghua UniversityBeijing 100084China Department of Control Science and Engineering Tongji UniversityShanghai 201804 National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China IEEE

Dear Editor,This letter is concerned with developing meta-learning models for fast,stable,and effective few-shot learning across tasks over a few training ***,deep and reinforcement learning(RL)is widely used in auton... 详细信息

关键词： robot autonomous concerned

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