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IEEE International Conference on robotics and Biomimetics

作者： Qiuyu Shi Xuan Zhao Haisu Liao Yongji Lin Ruisen Huang Xinyu Wu Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Shatin China

Magnetorheological (MR) fluids-based devices such as MR dampers and brakes can output a continuously controllable damping force via modulating the magnitude of the applied magnetic field. Owing to low energy consumption and fast response, recently vast MR dampers and brakes are widely studied and explored for lower limb prostheses and exoskeletons. This paper proposed a novel MR brake with adjustable interdigitated comb for lower limb prostheses. Through actively adjusting the area the of the comb engagement, the maximum viscous and field-induced damping torque can be increased or decreased. Because of that, the dynamic adjustment interval of the output damping torque can be increased to meet the function requirements of the prosthetic knee in different walking modes. Magnetic analysis via ANSYS is performed to check the magnetic density of the MR fluid under different excitations. Mathematical models of the damping torque are built. Finally, a prototype of the novel MR brake is fabricated.

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Tuning Electrical Conductivity and Ultrafast Optical Nonlinearity of R-Go Films Ablated by Femtosecond Laser Direct Writing

SSRN

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SSRN 2024年

作者： Tao, Youliang Nie, Zhongquan Zhang, Xuefeng Pan, Deng Wang, Han College of Aeronautics and Astronautics Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Institute of New Carbon Materials College of Materials Science and Engineering Taiyuan University of Technology Taiyuan030024 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University 111 Jiu Long Road Hefei230601 China

Carbon-based nanomaterials with excellent electrical and optical properties are highly sought after for a plethora of hybrid applications ranging from advanced opto-electronic components to sustainable energy storage devices. In this contribution, we examine in detail the dependence of electrical conductivity and ultrafast optical nonlinearity of graphene oxide (GO) films on their degrees of reduction, as well as the link between the two properties. The GO films are first synthesized through the vacuum filtration method and then reduced partially controllably by the femtosecond laser direct writing with varying power doses. Subsequently, the 4-point probe measurements of the reduced GO (r-GO) films are demonstrated to exhibit superior resistivity and electrical conductivity compared with the pristine GO counterpart. It was found that the conductivity of the film increases and then decreases with increasing ablation laser power (P), GO was completely reduced at P = 100 mW with resistivity and electrical conductivity of 1.09 × 10-3Ω·m and 9.19 × 102s/m, respectively. GO was over reduced at P = 120 mW with resistivity and electrical conductivity being 3.72 × 10-3Ω·m and 2.69 × 102s/m, respectively. We further test the ultrafast optical nonlinearity (ONL) of the as-prepared pristine and reduced GO with the femtosecond Z-scan technique. The results show that the behavior of ONL is reversed whenever GO is reduced in a controlled manner. More interestingly, the higher the ablation laser power is, the stronger the optical nonlinearity of r-GO is. In particular, the nonlinear absorption and refraction coefficients of the r-GO films reach up to 3.26 × 10-8 m/W and -1.12 × 10-13 m2/W when P = 120 mW. The nonlinear absorption and refraction coefficients reach 1.9 × 10-8 m/W and -3 × 10-13 m2/W, respectively, for P = 70 mW. The GO/r-GO films endowing tunable electro-optical responses are potential building blocks for wide-ranging applications in microelectronic circuits, optoele

关键词： Femtosecond lasers

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3D segmentation guided PET to MR synthesis via deep learning

3D segmentation guided PET to MR synthesis via deep learning

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： H. Y. Tang Z. X. Huang W. B. Li Y. P. Wu J. M. Yuan Y. Yang Y. Zhang H. R. Zheng D. Liang M. Y. Wang Z. L. Hu Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing China Department of Medical Imaging Henan Provincial Peoples Hospital & People’s Hospital of Zhengzhou University Zhengzhou China United Imaging Healthcare Group Central Research Institute Shanghai China Beijing United Imaging Research Institute of Intelligent Imaging Beijing China Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

Multimodal medical images, such as magnetic resonance (MR) and positron emission tomography (PET), have been widely used to diagnose brain diseases such as Alzheimer’s disease due to the variety of information they can provide. PET images can reflect metabolic changes before structural abnormalities are found, which is of great significance for early diagnosis. And the scanning time of PET is shorter than that of MR. Considering the limited clinical applications of PET/MRI systems, we propose a 3D segmentation guided deep learning network to synthesize MR images from PET images. To preserve structural semantic information, we introduce structural semantic loss to guide the network learning. Experiments demonstrate that our method has yielded superior visual and quantitative outcomes with a Peak Signal-to-Noise Ratio (PSNR) of 23.03 dB, a Structural Similarity Index (SSIM) of 0.7911 and a Mean Square Error (MSE) of 0.0052. Compared with methods without introducing structural semantic loss, the PSNR and SSIM have increased by 0.16 dB and 0.0061 respectively, and the MSE has decreased by 0.0001. In addition, we also performed brain segmentation on the synthetic MR images. The MR synthesized by our method obtained an overall Dice score of 0.7313, which is higher than the results of other methods. All experimental results demonstrate the feasibility of our method on PET to MR synthesis tasks.

关键词： Deep learning Image segmentation Visualization Microwave integrated circuits Three-dimensional displays PSNR Semiconductor detectors

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Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning

arXiv

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arXiv 2024年

作者： Zhu, Hongze Xie, Guoyang Hou, Chengbin Dai, Tao Gao, Can Wang, Jinbao Shen, Linlin National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Department of Intelligent Manufacturing CATL Ningde China Fuzhou Fuyao Institute for Advanced Study Fuyao University of Science and Technology Fuzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

High-resolution point clouds (HRPCD) anomaly detection (AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods that have been proposed recently, they still cannot meet the requirements of the HRPCD-AD task. There are several challenges: i) It is difficult to directly capture HRPCD information due to large amounts of points at the sample level;ii) The advanced transformer-based methods usually obtain anisotropic features, leading to degradation of the representation;iii) The proportion of abnormal areas is very small, which makes it difficult to characterize. To address these challenges, we propose a novel group-level feature-based network, called Group3AD, which has a significantly efficient representation ability. First, we design an Intercluster Uniformity Network (IUN) to present the mapping of different groups in the feature space as several clusters, and obtain a more uniform distribution between clusters representing different parts of the point clouds in the feature space. Then, an Intracluster Alignment Network (IAN) is designed to encourage groups within the cluster to be distributed tightly in the feature space. In addition, we propose an Adaptive Group-Center Selection (AGCS) based on geometric information to improve the pixel density of potential anomalous regions during inference. The experimental results verify the effectiveness of our proposed Group3AD, which surpasses Reg3D-AD by the margin of 5% in terms of object-level AUROC on Real3DAD. We provide the code and supplementary information on our website: https://***/M-3LAB/Group3AD. Copyright © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Angle-Of-Arrival Target Tracking Using A Mobile Uav In External Signal-Denied Environment

Angle-Of-Arrival Target Tracking Using A Mobile Uav In Exter...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Bing Zhu Sheng Xu Feng Rice Kutluyıl Doğançay Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China QinetiQ Australia Mawson Lakes SA Australia UniSA STEM University of South Australia Mawson Lakes Australia

This paper focuses on the angle-of-arrival (AOA) target tracking problem using a mobile unmanned aerial vehicle (UAV) equipped with an angle-of-arrival (AOA) sensor to observe targets in an external-denied (no global positioning system, inertial navigation system aid) environment. The mathematical formulations are based on two known anchors. The extended Kalman filter (EKF) is modified to calculate the UAV’s and target’s absolute coordinates. To improve the tracking accuracy, a gradient-based UAV path optimization algorithm using simultaneous perturbation stochastic approximation (SPSA) is developed. The geometry of anchors and UAV impacts the estimation accuracy, especially when the selected anchors are close to the target. The simulations have demonstrated the effectiveness of the proposed scheme.

关键词： Geometry Target tracking Perturbation methods Estimation Signal processing algorithms Signal processing Autonomous aerial vehicles

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Branch-and-cut-and-price for agile earth observation satellite scheduling

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European Journal of Operational Research 2025年

作者： Peng, Guansheng Wang, Jianjiang Song, Guopeng Gunawan, Aldy Xing, Lining Vansteenwegen, Pieter School of Advanced Engineering and Great Bay Institute for Advanced Study Great Bay University Dongguan523000 China Defense Innovation Institute Chinese Academy of Military Science Beijing100071 China College of Systems Engineering National University of Defense Technology Changsha410073 China National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha410073 China School of Computing and Information Systems Singapore Management University Singapore178902 Singapore Research Institute of Intelligent Control and Manufacturing System Jiangsu University of Technology Changzhou213001 China KU Leuven Institute for Mobility - CIB Leuven3001 Belgium

The Agile Earth Observation Satellite scheduling selects and sequences satellite observations of possible targets on the Earth's surface, each with a specific profit and multiple time windows. The objective is to maximize the collected profit of all observations completed under some operational constraints. The problem can be modeled as a variant of the Team Orienteering Problem with Time Windows (TOPTW). The key differences with the regular TOPTW are twofold: first, a time-dependent transition time is required for each pair of consecutive observations to adjust the camera's look angles. Second, the time windows of each target vary during different observation cycles, called "orbits". Some targets are invisible during certain orbits. We call this variant the Time-dependent Team Orienteering Problem with Variable Time Windows. In this paper, we present an efficient branch-and-cut-and-price (BCP) algorithm that exploits the problem's characteristics to solve it to optimality. Some algorithmic enhancements have been implemented, such as a Lagrangian bound, an ng-path relaxation, a primal heuristic, and subset-row inequalities. Extensive experiments on different configurations of benchmark instances demonstrate the superior performance of the proposed BCP algorithm and its algorithmic enhancements. Moreover, the primal heuristic yields a high-quality lower bound and outperforms state-of-the-art heuristics. Finally, we adopt our framework to solve the well-known TOPTW, and our algorithm is much faster than state-of-the-art exact algorithms. © 2025 Elsevier B.V.

关键词： Branch and bound method

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LVRT During-fault-stage Equilibrium Point is Unnecessary for Renewable Grid-tied systems

LVRT During-fault-stage Equilibrium Point is Unnecessary for...

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Power system and Green Energy Conference (PSGEC)

作者： Yayao Zhang Min Cheng Meng Zhan Jiawei Yu Yihua Zhu Mingkang Wu State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Yunnan Power Grid China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid China National Energy Power Grid Technology R&D Centre Electric Power Research Institute China Southern Power Grid China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Electric Power Research Institute China Southern Power Grid China

ISBN: (数字)9798350365573

ISBN: (纸本)9798350365580

Transient synchronous stability of renewable grid- tied systems is of paramount importance. Most of previous studies focused on the grid-tied converter in the low voltage ride through (LVRT) during-fault stage and performed stability analysis based on the belief that if the system has (or has no) a stable equilibrium point in the during-fault stage, the system will be stable (or unstable). Therefore, it has been broadly accepted that the existence and/or stability of equilibrium point in the during-fault stage is necessary. However, the whole LVRT contains four different stages and the during-fault stage is only one among them. The transient synchronous stability of whole system should be determined by the initial state in the late post-fault stage and the attraction basin of its equilibrium point. The late post-fault stage is essential for stability and all four stages are important. Clearly treating the during-fault stage as the whole LVRT stages makes the nonlinear switched dynamics problem be greatly simplified and, certainly, is incomplete. In order to clarify this point, this paper analyzes the influence of existence (or nonexistence) of equilibrium point in the during-fault stage on the transient synchronous stability of permanent magnet synchronous generator grid-tied system. We can find that the existence of an equilibrium point in the during-fault stage is only a sufficient condition, rather than a necessary condition. The theoretical analysis is also verified in the hardware-in-the-loop experiment Therefore, a large number of previous studies and results on the transient synchronous stability of renewable grid-tied systems are incomplete and questionable.

关键词： Sufficient conditions Stability criteria Switches Voltage Power system stability Synchronous generators Permanent magnets Nonlinear dynamical systems Transient analysis Magnetic switching

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Impedance control for a novel composite modular lower-limb hemiplegic exoskeleton

Impedance control for a novel composite modular lower-limb h...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Bao, Ruoyu Li, Pengbo He, Bailin Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

This paper proposes a control scheme based on impedance control for the smoothing control of the operating movements of a lower-limb hemiplegic exoskeleton robot on the basis of a new composite modular lower-limb hemiplegic ex-oskeleton(CMLHE) structure. The CMLHE has good structural performance and can be used in the rehabilitation of patients with hemiplegia caused by stroke and other diseases. At the same time, the smoothing control by means of impedance control ensures that patients with lower limb hemiplegia can use the CMLHE to achieve smooth walking movements without additional injuries caused by the CMLHE during the rehabilitation training. This paper analyses the performance of this CMLHE robot based on walking movements and demonstrates through kinematic and kinetic modelling and simulation that the impedance control scheme of this CMLHE robot is feasible and effective and can be more widely used in the rehabilitation training of patients with lower limb hemiplegia. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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A Deep Siamese Neural Network N-Shot Learning Approach for the Recognition of Chinese Calligraphy

SSRN

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SSRN 2022年

作者： Zhou, Zhaokun Wang, Weijun Ou, Yuhao Che, Qishu Feng, Wei Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangzhou Institute of Advanced Technology Chinese Academy of Sciences Guangdong Guangzhou511458 China University of Chinese Academy of Sciences Guangdong Shenzhen518055 China

The forms of Chinese calligraphic characters vary considerably, posing a challenge even for a typical educated Chinese to read. The total number of characters is in the excess of ten thousand, many of which have small numbers of samples surviving to date. Thus, Chinese calligraphy recognition is a unique challenge for the state-of-the art deep-learning algorithms that require large training datasets to accurately categorize. Here we present a novel deep-convolutional Siamese Neural Network (SNN) based architecture that finishes training in one day on a single RTX 2080 Ti graphics card while reaching an accuracy of 95.0% on a vast set of more than 6000 Chinese characters. We found that, after image pre-processing and setting the optimized SNN parameters, our recognition algorithm (i) is light weight, (ii) trains with small numbers of samples, achieving few-/one-shot learning (iii) recognizes a new character that is not present in the training set and (iv) includes the new character in the dictionary so the dictionary is continually expanded. Further work on the improvement of our method is also proposed including the localization of multiple tokens in an image to further automate detections and word prediction with RNNs to boost categorization accuracy. © 2022, The Authors. All rights reserved.

关键词： Optical character recognition

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A modular rehabilitation lower limb exoskeleton for stroke patients with hemiplegia

A modular rehabilitation lower limb exoskeleton for stroke p...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Li, Pengbo Wei, Wenhao Bao, Ruoyu He, Bailin Su, Zhilong Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering The Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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