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43rd Chinese Control Conference, CCC 2024

作者： Zhang, Zhongyi Xu, Chenyang Jin, Licheng Hou, Huirang Meng, Qinghao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China

ISBN: (纸本)9789887581581

Electroencephalography (EEG) contains a wealth of information, including neuron activity, allowing for a partial understanding of the brain's state. As a reliable tool, EEG, combined with deep neural networks, has been increasingly utilized to assist in the detection of depression and has achieved satisfactory results. However, there are still some limitations in the current models. Firstly, it is worth noting that many existing models are binary classification models. These models can determine whether a subject is depressed or not, but they lack the capability to differentiate the severity of depression. Besides, the variations in EEG signals among various individuals have not been thoroughly taken into account, leading to subpar performance when applying the trained model to new subjects. To address the aforementioned issues, we suggest implementing a multi-classification model that utilizes a graph convolutional neural network (GCN) to identify levels of depression. Additionally, to mitigate the problem of imbalanced samples in multi-classification tasks, we introduce a penalty coefficient for the smaller categories. At the same time, the issue of signal discrepancies among subjects was taken into account, leading to the introduction of the domain generalization module. Finally, the depression level identification task on the MODMA and PRED+CT dataset achieved an accuracy of 75.47% and 77.97% respectively, surpassing the performance of the state-of-the-art (SOTA) model. In addition, numerous ablation experiments were conducted to validate the efficacy of each module. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Convolution

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Flapping-Wing Robot Achieves Multi-Domain Locomotion Using Transformable Wheel Mechanism

Flapping-Wing Robot Achieves Multi-Domain Locomotion Using T...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chai, Xiangxiao Wang, Shihua Pan, Erzhen Xu, Wenfu Shenzhen518055 China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen518055 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

ISBN: (纸本)9781665481090

The difficulty of moving from aquatic to aerial environment is one of the major challenges limiting the development of trans-medium multi-domain locomotion vehicles. In this paper, the concept of the transformable wheel, a feature commonly found in autonomous land vehicles (AL V s), is introduced into the design. Additionally, a flapping-wing robot equipped with multi-domain locomotion capability, which can not only realize aerial flight and surface navigation on water, but also ascend from water to land for subsequent takeoff is presented. The paper first introduces the system design of the robot and proposes the corresponding multi-domain locomotion strategy. Subsequently, the design of the transformable wheel mechanism is described in detail and the force analysis for the water-exit is conducted. The feasibility of the proposed strategy is experimentally validated, confirming the prototype's multi-domain locomotion performance finally. This research explores the feasibility of introducing the transformable wheel mechanism into trans-medium multi-domain vehicle platforms and provides a design example. © 2024 IEEE.

关键词： Machine design

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E-Nose-Based Domain-Generalization Recognition of Ignitable Liquids 43

E-Nose-Based Domain-Generalization Recognition of Ignitable ...

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43rd Chinese Control Conference, CCC 2024

作者： Song, Tian-Shu Chen, Zhen-Peng Hou, Hui-Rang Li, Hong-Yue Meng, Qing-Hao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China

ISBN: (纸本)9789887581581

Detecting ignitable liquids (ILs) at the scene of a fire is crucial for fire investigation. The electronic nose (e-nose) is crucial for detecting ILs due to its affordability and rapid response time. Process limitations and changes in environmental conditions can cause variations in the reactions of multiple e-noses with the same sensor array to the same input gas. This can significantly reduce the accuracy of identifying ILs when deploying a model trained on one e-nose to other e-noses. In order to tackle the issue of cross-platform identification of ILs using e-noses, we developed a feature mute gated network (FMG-Net). This network is capable of maintaining consistency in the shared components of different e-noses at the low-level feature level while effectively muting the distinct low-level features. FMG-Net is comprised of a main network and multiple branch networks that are specific to different domains. Initially, a subsidiary domain-specific convolutional neural network (SDS-CNN) is trained to learn the network parameters on various e-nose platforms with known labels. Additionally, the backbone network generates low-level features of the e-nose responses. Furthermore, the SDS-CNN incorporates random input of low-level features and generates a mask using the gradient. This mask is then used to explicitly remove the non-overlapping parts of the low-level features. At last, the low-level features are sent back to the backbone network for further training once the non-overlapping parts have been removed. Experiments were conducted to identify four types of ILs (diesel, gasoline, ethanol, and thinner) using five self-made e-nose platforms with identical sensor arrays. The results indicated that the proposed FMG-Net consistently outperforms other domain-generalization algorithms in terms of recognition accuracy and parameter sizes. FMG-Net has the ability to detect volatile gases in ILs using an e-nose, even without the need for a dataset. © 2024 Technical Committ

关键词： Convolutional neural networks

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Quantitative analysis of the main components in ceramic raw materials based on the desktop LIBS analyzer

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Plasma Science and Technology 2022年第8期24卷 46-54页

作者： Peng ZHANG Lanxiang SUN Haibin YU Peng ZENG State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016People's Republic of China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016People's Republic of China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110016People's Republic of China

The concentrations of SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiO,and loss on ignition(L.O.I.) are the main inorganic components of geological *** of the eight oxides and *** also the main indicators of concern in the production of building *** analysis of the eight oxides and *** performed using fiber-laserbased laser-induced breakdown spectroscopy(LIBS).A combination of continuous background deduction,full width at half maximum(FWHM) intensity integral and spectral sum normalization was proposed for data *** the data processing combined the continuous background deduction,FWHM intensity integral and spectral sum normalization,the mean absolute errors(MAEs) of the calibration of L.O.I.,SiO,Al2O,KO,NaO,CaO,MgO,Fe2Oand TiOwas reduced from 2.03%,12.06%,4.84%,1.10%,0.69%,0.31%,0.11%,0.20%and 0.10% to 1.80%,9.48%,2.12%,0.36%,0.58%,0.11%,0.08%,0.19% and 0.05%,*** multivariate method was further introduced and discussed to improve the analysis *** MAEs of L.O.I.,SiO,Al2O,KO and NaO were further reduced to1.12%,2.07%,1.38%,0.35% and 0.43%,*** results show that the overall prediction error can meet the requirements for the production of building *** LIBS desktop analyzer has great potential in detection applications on geological samples.

关键词： laser-induced breakdown spectroscopy fiber laser quantitative analysis matrix effects geological samples

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Attitude Tracking Control for Rigid Spacecraft with Arbitrary Convergence Time

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Journal of systems Science & Complexity 2024年第6期37卷 2579-2594页

作者： XU Yu-Tian WU Ai-Guo Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Key University Laboratory of Mechanism&Machine Theory and Intelligent Unmanned Systems of Guangdong Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Department of Automation Harbin Institute of Technology(Shenzhen)Shenzhen 518055China HIT Wuhu Robot Technology Research Institute Wuhu 241060China

In this paper,attitude tracking control with arbitrary convergence time for rigid spacecraft is ***,a novel time-varying sliding function is proposed to achieve free-will arbitrary time convergence when the system states reside on the sliding *** such a sliding function,an attitude tracking controller is designed to guarantee that the states of the closed-loop system converge to the sliding surface within a predetermined time in the presence of external *** free-will arbitrary time convergences of the closed-loop system and sliding function are illustrated by numerical simulations.

关键词： Attitude tracking free-will arbitrary time stability rigid spacecraft sliding mode control

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Additive manufacturing of high-quality tritium breeding pebbles using ceramic precursors

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Journal of the European Ceramic Society 2024年第7期44卷 4719-4730页

作者： Su, Fang Li, Yuzeng Xing, Huanhuan Liu, Yu Liu, Zhiyuan Liu, Changyong Jiang, Cho-Pei Chen, Zhangwei Additive Manufacturing Institute Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robotics Shenzhen University Shenzhen518060 China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an710049 China

In this study, the fabrication of advanced lithium orthosilicate (Li4SiO4) ceramic tritium breeding pebbles through photopolymerization using ceramic precursors (i.e., SiO2 and Li2CO3) is reported for the first time. The pebbles exhibit excellent mechanical and physical properties. Through optimization of manufacturing parameters and a geometrical correction model to compensate printing deviations, the printing accuracy of the pebbles was enhanced. The resulting pebbles had a diameter of approximately 1 mm, a sphericity of 1.01, a uniformly distributed pore structure, a phase purity > 95%, and a satisfying relative density reaching 91.39%. The average crush load 25.7 ± 0.3 N, surpassed that achieved by previously reported methods. Furthermore, the thermal conductivity was enhanced compared to that of solid-phase synthesized Li4SiO4 powder, facilitating the tritium release process for fusion applications. This study may serve as a guidance for designing appropriate ceramic breeders, providing a cost-effective approach applicable to produce other high-precision ceramic components with complex compositions. © 2024 Elsevier Ltd

关键词： Lithium compounds

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OFDM-structure based waveform designs for integrated sensing and communication

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Science China(Information Sciences) 2025年第5期68卷 267-284页

作者： Jiaqi LIU Ping YANG Ke JIANG Jiarong ZHAO Wei XIANG Jianping WEI Ruixiang DUAN Saviour ZAMMIT Tony Q.S.QUEK National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China School of Computing Engineering and Mathematical Sciences La Trobe University Meituan Academy of Robotics Department of Communications and Computer Engineering University of Malta Information Systems Technology and Design Pillar Singapore University of Technology and Design

The future sixth-generation(6G) paradigm aims to seamlessly integrate communication and environmental sensing capabilities into a single radio signal, promising improved efficiency and cost-effectiveness through simultaneous data communications and environmental perception. At the core of this evolution, orthogonal frequency division multiplexing(OFDM) and its advanced waveforms emerge as pivotal for integrated sensing and communications(ISAC). This study introduces a concise and unified ISAC waveform design framework based on orthogonal multicarriers. This framework supports versatile applications of OFDM and its derivative waveforms within a generalized ISAC system, marking a significant leap in integrating communication and sensing capabilities. A distinguishing feature of this framework is its adaptability,allowing users to intelligently select modulation strategies based on their specific environmental needs. This adaptability optimizes performance across diverse scenarios. Central to our innovations is the proposal of discrete Fourier transformspread OFDM with index modulation(DFT-S-OFDM-IM). This framework is paired with newly proposed signal processing methods for single-input single-output and multiple-input multiple-output(MIMO) systems. Extensive evaluations highlight DFT-S-OFDM-IM's superiority, including dramatically reduced peak-to-average power ratios(PAPRs), competitive communication performance, and exceptional sensing capabilities, striking an elegant balance between communication capacity and environmental sensing precision.

关键词： DFT-S-OFDM-IM index modulation integrated sensing and communication OFDM

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Enhancing Ultrasound Scanning Skills in a Leader-Follower Robotic System through Expert Hand Impedance Regulation

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Niu, Baoshan Yang, Dapeng Zhang, Le Ji, Yiming Jiang, Li Liu, Hong Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin150080 China

Traditional breast cancer surgeries require collaboration between ultrasound (US) doctors and surgeons, making the procedure complex and treating physicians prone to fatigue. In leader-follower robotic surgery, a surgeon controls an US robotic arm and an instrument robotic arm with their left and right hands, enabling independent surgical performance. However, the lack of US scanning skills among surgeons, as well as the physical separation in leader-follower operations, can negatively impact both the scanning and surgical outcomes. This paper proposes a robot-assisted scheme based on dynamic arm impedance compensation (IC) that references expert arm stiffness to compensate for novice arm stiffness. The impedance compensator adjusts the compensation strategy according to the scanning area and scanning stage. The impedance force generator estimates the scanning direction via Kalman filtering and applies stiffness and damping forces in the vertical direction to suppress tremors and other involuntary movements. The experimental results revealed that during the coarse and fine scanning phases, the probe position variance decreased by 57.9% and 73.6%, the contact force variance decreased by 55.2% and 42.5%, and the US image confidence increased by 22.0% and 23.8%, respectively. Compared with traditional filtering compensation (FC) schemes, this approach reduces the average position variance and contact force variance by 32.0% and 25.3%, respectively, and increases confidence by 7.3%. In a no-compensation test, the IC training group outperformed the FC group. This scheme can assist leader-follower US scanning and rapidly improve surgical skills. © 2013 IEEE.

关键词： Robotic surgery

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Improved Detection of Transmission Tower Equipment Using YOLOv7 with Saliency Data Augmentation 5

Improved Detection of Transmission Tower Equipment Using YOL...

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5th International Conference on Clean Energy and Electric Power Engineering, ICCEPE 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798350390315

Transmission towers are critical infrastructure for power transmission, and the reliable operation of their equipment is essential to ensure electricity supply. However, the detection of transmission tower equipment faces challenges such as target overlap, large variations in size, small targets, and class imbalance due to the characteristics of the equipment. To tackle the identified issues, this study introduces a method based on YOLOv7 for the detection of transmission tower components, utilizing saliency-based data augmentation. Initially, an approach focusing on importance is employed to augment the sample size in categories with limited numbers, thereby enhancing the effectiveness of detection. Secondly, an adaptive adjustment module is introduced into the multi-head self-attention mechanism to dynamically adjust attention allocation based on the actual size of the targets and integrate contextual information, thus better handling targets with large size variations and overlaps. Finally, incorporating dynamic convolution within the backbone network significantly improves the ability to extract features from small objects. The outcomes of the experiments confirm the efficiency of the suggested approach in the smart surveillance of devices within intricate transmission settings, offering a reliable solution for maintaining power supply dependability. © 2024 IEEE.

关键词： Critical infrastructures

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Industrial Wireless Control Networks:From WIA to the Future

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Engineering 2022年第1期8卷 18-24页

作者： Haibin Yu Peng Zeng Chi Xu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China

*** Industrial automation is undergoing a significant innovation as information,communication,and operation technologies are deeply integrating with each *** this trend,industrial wireless control networks(IWCNs)are becoming increasingly attractive to industrial automation since they can help speed up production efficiency,reduce cost,enhance safety,and finally realize intelligent manufacturing[1].

关键词： attractive integrating becoming

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