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7th International Conference on Robotics, Control and Automation Engineering, RCAE 2024

作者： Mu, Junqi Zong, Xiaofeng Wei, Yiyang Hou, Xuping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China

ISBN: (纸本)9798350355642

The actuator, serving as the fundamental power source of a soft robot, functions as its central component. The field of soft robotics has garnered increasing research attention since its inception. Pneumatic crawling robots, being an essential branch within the realm of soft robotics, possess notable characteristics such as rapid response time, cost-effectiveness, and human-computer interaction safety. Consequently, they hold significant research value. Among various types of crawling robots that have garnered considerable interest from researchers is the inchworm crawling robot. This paper aims to address the design and development aspects pertaining to inchworm actuators. By utilizing ABAQUS simulation software and taking displacement as the reference parameter, an analysis was conducted to investigate the impact of various geometric parameters on actuator displacement. Additionally, optimization of these geometric parameters was performed. The values of aspect ratio, length-to-width ratio, vertex angle and gap depth suitable for inchworm-like actuator are obtained. These findings are presented for the first time in the field of crawling soft robots and provide a theoretical basis for the development of pneumatic inchworm-like actuators. © 2024 IEEE.

关键词： Aspect ratio

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Automatic Depression Detection Network Based on Facial Images and Facial Landmarks Feature Fusion

Automatic Depression Detection Network Based on Facial Image...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Hu, Min Xu, Lingxiang Liu, Lei Wang, Xiaohua Li, Hongbo Yang, Jiaoyun Hefei University of Technology Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei China Hefei University of Technology National Smart Eldercare International Science and Technology Cooperation Base Hefei China Hefei University of Technology Intelligent Interconnected Systems Laboratory of Anhui Province Hefei China

ISBN: (纸本)9798350386226

Artificial intelligence methods offer objectivity and convenience in automatic depression detection, however, current research often neglects the critical role of facial landmarks. This oversight results in insufficient spatial structure information and a lack of detailed local representation, which fails to capture the nuanced semantic information crucial for identifying depression-related clues. To address these issues, we introduce a novel dual-branch network model comprising the Landmark-Image-Landmark Net (LIL Net) and the Global Context Vision Transformer Net (GCVit Net). Through a dual-stream, multiscale, and cross-fusion strategy, LIL Net is designed to extract original facial image features alongside landmark features, prioritizing the detailed semantic information of potential depression clues. LIL Net employs an innovative LIL Attention approach to jointly learn multiscale features from facial landmarks and images, thereby enhancing the model's ability to capture fine-grained depression-related cues. Furthermore, the Multi-scale Feature Fusion (MSFF) module fuses the obtained multiscale features, augmenting the semantic expression of potential depression clues within facial landmarks via attention mechanisms. Meanwhile, the GCVit Net branch network supplements global information by extracting global facial features. Finally, the features from both branches are concatenated to enhance the accuracy of depression degree predictions. Experimental results demonstrate that our model has superior performance in detecting depression compared to existing methods. We release our code at https://***/xlx777/LIL-Net. © 2024 IEEE.

关键词： Artificial intelligence

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A LESO Based Backstepping Controller Considering Coal Seam Hardness for Rotary Speed in Coal Mine Tunnel Drilling Process

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Journal of systems Science & Complexity 2024年第5期37卷 1789-1808页

作者： CHEN Luefeng LIU Xiao WU Min LU Chengda PEDRYCZ Witold HIROTA Kaoru School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R2G7Canada The Tokyo Institute of Technology Yokohama 226-8502Japan

In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of *** this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary ***,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is *** an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam *** on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary ***,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.

关键词： Backstepping extended state observer hydraulic tunnel drilling machine rotary speed

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Physics and applications of Raman distributed optical fiber sensing

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Light(Science & Applications) 2022年第6期11卷 1059-1087页

作者： Jian Li Mingjiang Zhang College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuanShanxi 030024China Key Laboratory of Advanced Transducers and Intelligent Control Systems(Ministry of Education and Shanxi Province) Taiyuan University of TechnologyTaiyuan 030024China

Raman distributed optical fiber sensing has been demonstrated to be a mature and versatile scheme that presents great flexibility and effectivity for the distributed temperature measurement of a wide range of engineering applications over other established *** past decades have witnessed its rapid development and extensive applicability ranging from scientific researches to industrial ***,there are four theoretical or technical bottlenecks in traditional Raman distributed optical fiber sensing:(ⅰ)The difference in the Raman optical attenuation,a low signal-to-noise ratio(SNR)of the system and the fixed error of the Raman demodulation equation restrict the temperature measurement accuracy of the system.{ⅱ)The sensing distance and spatial resolution cannot be reconciled.(ⅲ)There is a contradiction between the SNR and measurement time of the system.(ⅳ)Raman distributed optical fiber sensing cannot perform dual-parameter *** on the above theoretical and technical bottlenecks,advances in performance enhancements and typical applications of Raman distributed optical fiber sensing are reviewed in this *** of this optical system technology with knowledge based,that is,demodulation technology *** further the performance and accuracy of these systems.

关键词： fiber optical contradiction

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A Deep GRU-Autoencoder for Dimentionality Reduction in Hand Skeleton Data Sequences classification 1

A Deep GRU-Autoencoder for Dimentionality Reduction in Hand ...

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1st IEEE Afro-Mediterranean Conference on Artificial Intelligence, AMCAI 2023

作者： Ameur, Safa Mohamedali, Mahjoub K Hali Fa, Anouar Ben Universite de Sousse Ecole Nationale d'Ingenieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Universite de Jendouba Institut National des Technologies et des Sciences du Kef Le Kef7100 Tunisia

ISBN: (纸本)9798350394689

Hand Gesture Recognition (HGR) has gained significant attention in various fields, including sign language interpretation and human-computer interaction. The classification of hand skeleton data sequences poses a challenge due to the high dimensionality of the input data. In this work, we propound a novel approach for dimensionality reduction in hand skeleton data sequences classification using a Deep Gated Reccurent Unit Autoencoder model (DGRU-AE). Our primary goal in this study is to efficiently decrease the dimensionality of hand gesture data, all the while retaining both the spatial and temporal information to ensure precise classification. We accomplish this by leveraging a DGRU-AE architecture, combining the strengths of recurrent neural networks and autoencoders. Our methodology involves preprocessing the hand skeleton data sequences, including normalization and feature extraction, through training the DGRUAE using suitable loss functions and optimization algorithms. Experimental evaluation on a benchmark datasets demonstrates the effectiveness of our suggested approach. The DGRU-AE achieves significant dimensionality reduction while maintaining high classification accuracy, outperforming existing methods. Our approach not only reduces computational complexity but also facilitates a more compact and meaningful representation of hand gestures. This work contributes to the advancement of HGE techniques by addressing the challenge of dimensionality reduction in classification tasks. © 2023 IEEE.

关键词： Classification (of information)

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Multi-UAV Coverage Path Planning Method Based on Improved Particle Swarm Optimization

Multi-UAV Coverage Path Planning Method Based on Improved Pa...

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2024 China Automation Congress, CAC 2024

作者： Zhou, Yan Xiong, Yonghua School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

The widespread application of unmanned aerial vehicle (UAV) has made the coverage path planning problem for multiple UAV systems a research hotspot. In this paper, we propose a multi-UAV solution to achieve complete coverage of multi-region. Based on this solution, we present an improved particle swarm optimization (PSO) algorithm that combines PSO algorithm, greedy strategy, and back-and-forth (BAF) algorithm. Its purpose is to plan the optimal paths for multi-UAV while achieving the shortest total distance and the highest UAV cooperation efficiency with the minimum number of UAVs, thereby enhancing the multi-UAV coverage cooperation and path optimization capabilities. Simulation results demonstrate the feasibility and superiority of this algorithm. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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3D Geometry Design of the Human Thorax and Forward Calculation for Electrical Impedance Tomography 20

3D Geometry Design of the Human Thorax and Forward Calculati...

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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Alwaz, Youssef Bader, Oumaima Ben Amara, Najoua Essoukri Kanoun, Olfa University of Sousse National Engineering School of Sousse Sousse Tunisia Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Technische Universität Chemnitz Measurement and Sensor Technology Chemnitz09111 Germany

ISBN: (纸本)9798350332568

Electrical Impedance Tomography (EIT) for lung monitoring reflects the internal conductivity distribution of human tissues based on the boundary voltages that are measured through given electrodes. The electrodes are placed around the human chest. A low-amplitude current is injected through driving electrodes, and the boundary voltages are measured through other electrodes. In this context, this work has elaborated a strategy for the design of a 3D geometry of the human thorax based on sequential Computed Tomography (CT) scans. This geometry will be used for the simulation and analysis of the EIT measurement. Image segmentation has been used to extract the contour within different layers of the CT scans to form the final 3D geometry of the chest containing the lungs and the thorax. The generated geometry was later meshed and repaired. Mesh properties were controlled through the Skewness quality metric. A multi-layered design has been elaborated to mimic different human chest layers such as body fluid, muscle, and skin resulting in three models. These models had given the accuracy of 62%, 63%, and 65% of skewed elements relative to the existing volume. Later on, the electrodes were placed on the thorax geometry for EIT forward simulation, and the effect of the multi-layered model has been investigated. © 2023 IEEE.

关键词： Finite element method

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An integrated micromachined flexible ultrasonicinductive sensor for pipe contaminant multiparameter detection

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Microsystems & Nanoengineering 2024年第4期10卷 271-283页

作者： Zheng Yuan Xiaoyu Wu Zhikang Li Jiawei Yuan Yihe Zhao Zixuan Li Shaohui Qin Qi Ma Xuan Shi Zilong Zhao Jiazhu Li Shiwang Zhang Weixuan Jing Xiaozhang Wang Libo Zhao State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China

Pipe contaminant detection holds considerable importance within various industries,such as the aviation,maritime,medicine,and other pertinent *** capability is beneficial for forecasting equipment potential failures,ascertaining operational situations,timely maintenance,and lifespan ***,the majority of existing methods operate offline,and the detectable parameters online are relatively *** constraint hampers real-time on-site detection and comprehensive assessments of equipment *** address these challenges,this paper proposes a sensing method that integrates an ultrasonic unit and an electromagnetic inductive unit for the real-time detection of diverse contaminants and flow rates within a *** ultrasonic unit comprises a flexible transducer patch fabricated through micromachining technology,which can not only make installation easier but also focus the sound ***,the sensing unit incorporates three symmetrical solenoid *** a comprehensive analysis of ultrasonic and induction signals,the proposed method can be used to effectively discriminate magnetic metal particles(e.g.,iron),nonmagnetic metal particles(e.g.,copper),nonmetallic particles(e.g.,ceramics),and *** inclusive categorization encompasses nearly all types of contaminants that may be present in a ***,the fluid velocity can be determined through the ultrasonic Doppler frequency *** efficacy of the proposed detection principle has been validated by mathematical models and finite element *** contaminants with diverse velocities were systematically tested within a 14mm diameter *** experimental results demonstrate that the proposed sensor can effectively detect contaminants within the 0.5−3mm range,accurately distinguish contaminant types,and measure flow velocity.

关键词： inductive holds ultrasonic

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Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

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Engineering 2022年第10期17卷 232-243页

作者： Zihang Gao Guanglu Jia Hongzhao Xie Qiang Huang Toshio Fukuda Qing Shi Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China

Existing biomimetic robots can perform some basic rat-like movement primitives(MPs)and simple behavior with stiff combinations of these *** mimic typical rat behavior with high similarity,we propose parameterizing the behavior using a probabilistic model and movement ***,an analysis of fifteen 10 min video sequences revealed that an actual rat has six typical behaviors in the open field,and each kind of behavior contains different bio-inspired combinations of eight *** used the softmax classifier to obtain the behavior-movement hierarchical probability ***,we specified the MPs using movement parameters that are static and *** obtained the predominant values of the static and dynamic movement parameters using hierarchical clustering and fuzzy C-means clustering,*** predominant parameters were used for fitting the rat spinal joint trajectory using a second-order Fourier series,and the joint trajectory was generalized using a back propagation neural network with two hidden ***,the hierarchical probability model and the generalized joint trajectory were mapped to the robot as control policy and commands,*** implemented the six typical behaviors on the robot,and the results show high similarity when compared with the behaviors of actual rats.

关键词： Biomimetic Bio-inspired robot Neural network learning system Behavior generation

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Improving Energy Quality of a Hybrid Renewable Energy System Wind-Photovoltaic Connected to the Grid

Improving Energy Quality of a Hybrid Renewable Energy System...

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2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Saad, Walid Khemiri, Nihel Khedher, Adel Université de Kairouan Institut Supérieur des Sciences Appliquées et de Techologie de Kairouan Tunisia Université de Sousse Ecole Nationale d'Ingénieurs de Sousse Tunisia LATIS-Laboratory of Advanced Technology and Intelligent Systems Tunisia

ISBN: (纸本)9798350325539

In this study the improvement of the hybrid renewable energy system, HRES (wind/PV), without and with nonlinear three-phase balanced and unbalanced load connected to the grid is proposed. The GSC must be able to compensate harmonics and to compare the power of a nonlinear load. We size the parameters of components upstream and downstream of GSC. The HRES was simulated in Matlab/Simulink without load in order to identify the regions of operation of the DFIG in hypo and hyper synchronous and to ensure the correct operation of the generator, then in the presence of a balanced and an unbalanced three-phase nonlinear load in order to ensure the performance of the control laws developed and the energy quality obtained. © 2023 IEEE.

关键词： Power quality

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