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Chinese Control Conference (CCC)

作者： Yubo Sun Zhenhui Guo Yuxin Feng Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Surface electromyography (sEMG) is a non-invasive technique for recording electrical activity and is extensively employed in gait phase classification. However, the measurement process of the sEMG signal inevitably introduces noise. Consequently, denoising is required for gait analysis from the collected sEMG signal. A novel denoising method ICEEMDAN-DFA-WD has been proposed in this paper. The sEMG signals were decomposed into several intrinsic mode functions (IMF) through an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The Hurst exponents were simulated by detrended fluctuation analysis (DFA) to distinguish noisy IMF and desired IMF. During the walking process, the lower limbs' sEMG exhibits strong periodicity, and the desired IMF yields higher Hurst exponents than the noisy IMF. For the noisy IMF, noise removal was performed through further decomposition by wavelet transform, followed by a hard threshold. The processed IMFs were reconstructed to denoise sEMG. In this study, experiments were conducted to compare with the existing denoising methods WD, EMD-IIT, EEMD-IWT, VMD-SIT. The proposed method can obtain better denoising effect and gait phase classification accuracy. The proposed method provides a more effective way for sEMG denoising.

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Code generation technology and reliability analysis based on structure flow chart 2

Code generation technology and reliability analysis based on...

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2021 2nd International Conference on Machine Learning and Computer Application, ICMLCA 2021

作者： Zhang, Tao Sun, Xuyang Shao, Zhong School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Software College Shenyang University of Technology Liaoning Shenyang China

ISBN: (纸本)9783800757398

With the rapid iterative development of software development technology, the increasing scale of software and the increasing demand for reliability, the research on automatic code generation and reliability prediction technology has increasingly become a hot issue in the field of software engineering. The purpose of this paper is to obtain data from the user modeling process and store it, and then use software metrics to analyze and judge the corresponding data, and obtain a method for optimizing the model, so as to prevent some errors made by users in the modeling phase. And incomplete information, and then iteratively improve and repair the model. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Reliability analysis

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Adaptive position tracking control of the lower limb exoskeleton robot with an uncertain dynamic model

Adaptive position tracking control of the lower limb exoskel...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Ting Yuan Chi Zhang Feng Yi Pingping Lv Shupei Li Meitong Zhang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Instituteof Materials Technology and Engineering Chinese Academy of Sciences Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Ningbo China School of Electrical Engineering Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

In this paper, an adaptive position control method combining proportional-derivative (PD) control, RBF neural network-based sliding mode (SM) control, and feedforward (FF) control, i.e., PD-FF-SM control, is proposed to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot system. The Lagrange method is utilized to establish dynamic models that ignore the uncertainties and disturbances in the swing phase and supporting phase. Then, the PD feedback controller is designed with a sliding surface function, to keep the system stable. The FF controller is adopted to improve the response by using dynamic models. And the RBF neural network-based SM controller is designed to compensate for the uncertainties and disturbances. The system’s stability is verified by Lyapunov’s theorem. The simulation results show that the proposed control method can effectively reduce the error of position tracking and response time with inaccurate dynamic modeling.

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Optimal Landing of Tilt-rotor Aircraft after Engine Failure Considering Pilot Inherent Limitations

Optimal Landing of Tilt-rotor Aircraft after Engine Failure ...

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IEEE International Conference on robotics and Biomimetics

作者： Xufei Yan Renliang Chen Shiqiang Zhu Anhuan Xie Jason Gu Research Center for Intelligent Robotics Zhejiang Lab Hangzhou 311100 China. Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu China Intelligent Robot Research Center Zhejiang Lab Hangzhou Zhejiang China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

An augmented longitudinal rigid-body model is developed with a set of algebra equations describing the controls in the cockpit and the differential equations describing the pilot inherent limitations. The landing procedure after one engine failure is formulated into a nonlinear optimal control problem. XV-15 tilt-rotor aircraft is taken as the sample for the demonstration of landing in one engine failure during short takeoff. The results show that the total power required, thrust coefficient, longitudinal flapping angle and optimal controls are more relatively gentle than the solutions without considering the pilot inherent limitations. Compared with the basic longitudinal rigid-body model, the optimal solutions involve more control information.

关键词： Atmospheric modeling Optimal control Rotors Mathematical models History Aircraft propulsion Aircraft

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The shape optimization design of the guide plate of the modular AUV recovery device

The shape optimization design of the guide plate of the modu...

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作者： Xuhui Wang Wei Zhang Yang Lin Haitao Gu Lingshuai Meng Dongyong Gao School of Mechanical Engineering and Automation Northeastern University Naval Research Academy State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences College of Mechanical Engineering Shenyang University of Technology

At present,the main method of ocean exploration is Autonomous Underwater Vehicle(AUV) in cooperation with manned *** AUV completes its mission,it relies on the operator to retrieve it on the deck of the *** recycling method has shortcomings such as low work efficiency and high personnel *** order to meet the development needs of AUV applications in the future,it is urgent to carry out research on AUV independent recycling *** this paper,a modular AUV autonomous recovery device based on the Unmanned Surface Vehicle(USV) platform is designed in conjunction with the SEA-KET autonomous AUV recovery *** order to improve the success rate and efficiency of AUV docking,reduce recovery time,and optimize the collision force in the docking process,the guide plate in the recovery device is optimized and *** shape of the guide plate is obtained by combination optimization,and the guiding ability of the optimized guide plate is compared with the conventional shape guide plate,which verifies the validity and reliability of the optimization result.

关键词： combinatorial optimization co-simulation docking AUV

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A Textile-Based Pneumatic Soft Suit for Elbow Joint Rehabilitation

A Textile-Based Pneumatic Soft Suit for Elbow Joint Rehabili...

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IEEE International Conference on Cyber technology in Automation, Control, and intelligent Systems

作者： Yan Shen Yu Dang Tianyu Jiang Weiguang Huo Ningbo Yu Jianda Han College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Department of Rehabilitation Medicine The Second Medical Center Chinese PLA General Hospital Beijing China National Clinical Research Center for Geriatric Diseases Beijing China National Key Laboratory of Kidney Diseases Beijing China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Stroke is a disease with a very high mortality rate, and most patients will experience upper limb dysfunction after the disease. Traditional solutions, commonly rigid exoskeletons, have been explored extensively but often fall short due to safety concerns, discomfort, and potential for skin damage owing to their hard attachment mechanisms. To overcome these limitations, this article proposes a textile pneumatic soft suit for elbow joint rehabilitation. This soft suit consists of a modular pneumatic actuator that can help patients with elbow joint flexion and extension rehabilitation training. The design principle is based on the deformation of the textile-based pneumatic bag. The actuator is made of flexible fabric sheets of woven nylon with thermoplastic polyurethane (TPU) coating and 3D printing technology. A mathematical model was developed to describe the relationship between flexion angle and cable length, which could guide the design of the actuator. Experimental validation involved both static and dynamic assessments, confirming the soft suit's capability to meet the requirements of torque and range of the motions. The actuator can provide a starting torque of 7.18 Nm under a pressure of 160 kPa. The suit can provide a range of flexion motion of over 100° for a 1650 g forearm. In the future, we will conduct modeling and further experimental verification of the robot system to complete its control.

关键词： Training Torque Stroke (medical condition) Three-dimensional printing Weaving Skin Safety Elbow Robots Diseases

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Brightness-Enhanced Electroluminescence Driven by Triboelectric Nanogenerators Through Permittivity Manipulation and Impedance Matching

SSRN

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SSRN 2022年

作者： Gu, Mingwei Chen, Yunfeng Gu, Shaoqiang Wang, Can Chen, Liguo Shen, Hao Chen, Guanyu Sun, Xuhui Huang, Haibo Zhou, Yunlei Wen, Zhen Institute of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou215123 China Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices Soochow University Suzhou215123 China College of Chemical Engineering and Technology Hebei University of Technology Tianjin300130 China Key Laboratory of Advanced Technologies of Materials Ministry of Education School of Materials Science and Engineering Southwest Jiaotong University Chengdu610031 China State Key Laboratory of Digital Manufacturing Equipment and Technology Flexible Electronics Research Center Huazhong University of Science and Technology Wuhan430074 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

Triboelectric nanogenerator-driven electroluminescence (TDEL) that can convert human kinetic energy into visible light has attracted extensive attention in wearable electronics. However, the brightness is usually low due to the low electric field strength on the phosphors caused by impedance mismatch. In this work, a TDEL system with optimal brightness has been proposed by adjusting the dielectric constant of nanocomposite and matching impedance with TENG. The circuit model of the TDEL system is established and the voltage at both ends of the EL layer is predicted through simulation, which error is within 4.7%. Finite element simulation is used to simulate the optimal field strength of phosphors under the dual effects of voltage drop and polarization enhancement of EL layer caused by the increase of dielectric constant of nanocomposites in TDEL system. When the volume ratio of ZnS:Cu is 40% and the dielectric constant of the composite increases from 12 to 22.8, the optimal brightness value increases by 172%. Finally, a patterned TDEL system driven by walking or running to realize the functions of night alarm and information exchange is demonstrated. This study opens the window to improve the brightness of TDEL system through permittivity manipulation and impedance matching, which is applicable to different types of TENG, luminescent particles and dielectric nanocomposites. © 2022, The Authors. All rights reserved.

关键词： Nanogenerators

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MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

arXiv

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arXiv 2024年

作者： Zhang, Yaning Wang, Tianyi Yu, Zitong Gao, Zan Shen, Linlin Chen, Shengyong Jinan250353 China Nanyang Technological University 50 Nanyang Ave Block N 4 639798 Singapore School of Computing and Information Technology Great Bay University Dongguan523000 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China Jinan250014 China The Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches mainly capture face forgery patterns using image modality, other modalities like fine-grained noises and texts are not fully explored, which limits the generalization capability of the model. In addition, most FFD methods tend to identify facial images generated by GAN, but struggle to detect unseen diffusion-synthesized ones. To address the limitations, we aim to leverage the cutting-edge foundation model, contrastive language-image pre-training (CLIP), to achieve generalizable diffusion face forgery detection (DFFD). In this paper, we propose a novel multi-modal fine-grained CLIP (MFCLIP) model, which mines comprehensive and fine-grained forgery traces across image-noise modalities via language-guided face forgery representation learning, to facilitate the advancement of DFFD. Specifically, we devise a fine-grained language encoder (FLE) that extracts fine global language features from hierarchical text prompts. We design a multi-modal vision encoder (MVE) to capture global image forgery embeddings as well as fine-grained noise forgery patterns extracted from the richest patch, and integrate them to mine general visual forgery traces. Moreover, we build an innovative plug-and-play sample pair attention (SPA) method to emphasize relevant negative pairs and suppress irrelevant ones, allowing cross-modality sample pairs to conduct more flexible alignment. Extensive experiments and visualizations show that our model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Alignment

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Hair Direction Detection*

Hair Direction Detection*

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WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Peng Ba Pengyi Wang Hongde Wu Qian Yang Yongqiang Feng Junchen Wang Yida David Hu Changsheng Li Wenyong Liu Shaolong Kuang Bai-Quan Su Medical Robotics Laboratory School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China Plastic Surgery Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China Brigham and Women’s Hospital Harvard Medical School Boston MA USA School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China School of Health Science and Environmental Engineering Shenzhen University of Technology Shenzhen China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. The main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. The experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. The experimental results show that the method in this paper can accurately and effectively identify the hair direction. The main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.

关键词： Hair Image segmentation Accuracy Three-dimensional displays Merging Prediction algorithms Stability analysis

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ECA-RetinaNet: A Novel Self-Attention RetinaNet for Environmental Microorganism Image Object Detection

ECA-RetinaNet: A Novel Self-Attention RetinaNet for Environm...

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IEEE International Conference on Big Data

作者： Hechen Yang Jinzhu Yang Tao Jiang Xin Zhao Jinghua Zhang Peng Zhao Ao Chen Qianqing Nie Marcin Grzegorzek Chen Li Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang Liaoning China School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu China International Joint Institute of Robotics and Intelligent Systems Chengdu University of Information Technology Chengdu China Institute of Medical Informatics University of Luebeck Luebeck Germany

The detection of environmental microorganisms is always a difficult task, e specially when the multi-scale environment is complex. For tiny objects in microscopic images, current detection methods face the challenge of accurate identification and localization. In contrast, we propose a convolutional neural network (ECA-RetinaNet) for microscopic object detection of which underlying dataset is a high-quality EMDS-7 dataset. The accuracy of ECA-RetinaNet is high, with a high mean Average Precision (mAP) value of 81.42% in the Environmental Microorganisms (EMS) detection task. Its accuracy has been higher than that of the two-stage object detection network.

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