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A Gaze-Guided Human Locomotion Intention Recognition and Volitional control Method for Knee-Ankle Prostheses

IEEE Transactions on Cognitive and Developmental systems 2025年

作者： Chen, Xinxing Chen, Zhaokai Wang, Yuxuan Yin, Shucong Chen, Chuheng Huang, Jian Fu, Chenglong Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen518055 China Shanghai Jiaotong University Shanghai China

This paper presents a novel gaze-guided volitional control method for knee-ankle prostheses, designed to enhance the precision and intuitiveness of prosthetic control in complex locomotion tasks. The method utilizes an eye-tracking system coupled with an RGBD camera to estimate 3D gaze points, which are then used to construct a gaze attention map. This map serves as the basis for predicting human locomotion intentions, enabling the prosthesis to accurately step on the intended foot placement. Experimental validation was conducted with both a healthy subject and an amputee subject, focusing on level-ground walking and stair ascent tasks. The results demonstrated that the prosthesis could achieve precise foot placement, with a mean error of 1.22 cm ± 3.14 cm for the healthy subject and 3.40 cm ± 0.66 cm for the amputee subject during level-ground walking. In stair ascent tasks, the system successfully adapted to various gait patterns, with the prosthetic joint angles closely matching natural human movements. The proposed method also effectively reduced the root mean square error (RMSE) of 3D gaze estimation to 2.70 cm, 2.63 cm, and 1.97 cm along the x, y, and z axes, respectively. These findings indicate that the gaze-guided volitional control method not only enhances the functionality of knee-ankle prostheses but also offers a more intuitive interface for users, aligning prosthetic actions with the user’s visual focus and intentions. © 2016 IEEE.

关键词： Knee prostheses

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Single-Loop Deadbeat Predictive control Framework for Uncertain SPMSM Drives With Disturbance Observation

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IEEE Transactions on Transportation Electrification 2025年

作者： Jiang, Fuxi Wang, Siqi Guo, Yuhao Cheng, Zhe Ye, Jie Cheng, Shanmei Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology School of Optical and Electronic Information Wuhan430074 China

To mitigate the detrimental effects of parameter perturbations and external load torque on the accuracy of speed and current tracking control in surface-mounted permanent magnet synchronous motor (SPMSM) drive systems, while avoiding the complexities inherent in traditional speed-current series control architectures, this paper presents a single-loop deadbeat predictive control (SDPC) framework that incorporates online disturbance observation. The control input voltage vector is directly computed using an SDPC controller in conjunction with a set of discrete-time disturbance observers (DDOBs). This proposed methodology offers two notable advantages over existing research: (i) it substantially reduces the number of adjustable controller parameters, requiring only the tuning of the observer bandwidth and the speed scaling gain, which enhances its practicality for engineering applications;and (ii) the disturbance estimation and compensation mechanism utilizing DDOBs significantly improves the robustness of the SPMSM system. Furthermore, the SDPC framework ensures that the system maintains satisfactory transient and steady-state tracking performance in response to reference signals. Experimental comparisons validate both the effectiveness and superiority of the proposed method. © 2015 IEEE.

关键词： Permanent magnets

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LSU-NET: LIGHTWEIGHT AUTOMATIC ORGANS SEGMENTATION NETWORK FOR MEDICAL IMAGES

arXiv

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arXiv 2025年

作者： Ding, Yujie Teng, Shenghua Li, Zuoyong Chen, Xiao College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control School of Computer and Big Data Minjiang University Fuzhou350121 China

UNet and its variants have widespread applications in medical image segmentation. However, the substantial number of parameters and computational complexity of these models make them less suitable for use in clinical settings with limited computational resources. To address this limitation, we propose a novel Lightweight Shift U-Net (LSU-Net). We integrate the Light Conv Block and the Tokenized Shift Block in a lightweight manner, combining them with a dynamic weight multi-loss design for efficient dynamic weight allocation. The Light Conv Block effectively captures features with a low parameter count by combining standard convolutions with depthwise separable convolutions. The Tokenized Shift Block optimizes feature representation by shifting and capturing deep features through a combination of the Spatial Shift Block and depthwise separable convolutions. Dynamic adjustment of the loss weights at each layer approaches the optimal solution and enhances training stability. We validated LSU-Net on the UWMGI and MSD Colon datasets, and experimental results demonstrate that LSU-Net outperforms most state-of-the-art segmentation architectures. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolution

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Learning to Learn Transferable Generative Attack for Person Re-Identification

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IEEE Transactions on Image processing 2025年 PP卷 PP页

作者： Bian, Yuan Liu, Min Wang, Xueping Ma, Yunfeng Wang, Yaonan Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China

Deep learning-based person re-identification (reid) models are widely employed in surveillance systems and inevitably inherit the vulnerability of deep networks to adversarial attacks. Existing attacks merely consider cross-dataset and cross-model transferability, ignoring the cross-test capability to perturb models trained in different domains. To powerfully examine the robustness of real-world re-id models, the Meta Transferable Generative Attack (MTGA) method is proposed, which adopts meta-learning optimization to promote the generative attacker producing highly transferable adversarial examples by learning comprehensively simulated transfer-based crossmodel&dataset&test black-box meta attack tasks. Specifically, cross-model&dataset black-box attack tasks are first mimicked by selecting different re-id models and datasets for meta-train and meta-test attack processes. As different models may focus on different feature regions, the Perturbation Random Erasing module is further devised to prevent the attacker from learning to only corrupt model-specific features. To boost the attacker learning to possess cross-test transferability, the Normalization Mix strategy is introduced to imitate diverse feature embedding spaces by mixing multi-domain statistics of target models. Extensive experiments show the superiority of MTGA, especially in cross-model&dataset and cross-model&dataset&test attacks, our MTGA outperforms the SOTA methods by 20.0% and 11.3% on mean mAP drop rate, respectively. © 1992-2012 IEEE.

关键词： Generative adversarial networks

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Deep reinforcement learning for path planning of autonomous mobile robots in complicated environments

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Complex and Intelligent systems 2025年第6期11卷 1-15页

作者： Zhang, Zhijie Fu, Hao Yang, Juan Lin, Yunhan School of Computer Science and Technology Wuhan University of Science and Technology No. 947 Heping Avenue Hubei Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System No. 947 Heping Avenue Hubei Wuhan 430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology No. 947 Heping Avenue Hubei Wuhan 430081 China

In complicated environments, which include dynamic and narrow areas, the path planning of Autonomous Mobile Robots (AMRs) encounters challenges, like slow model convergence and limited representational capabilities, often resulting in the robot taking longer, less efficient paths or even colliding with obstacles. To tackle these challenges, the Gated Attention Prioritized Experience Replay Soft Actor-Critic (GAP_ SAC) algorithm is proposed. key improvements include expanding the state space for better perception, designing a dynamic heuristic reward function to more effectively guide the AMR in achieving its path planning objectives and integrating Prioritized Experience Replay (PER) to improve sample efficiency and accelerate convergence. Additionally, a gated attention mechanism is also introduced to focus on critical environmental features, enhancing the models’ perception capability. Comparative experiments validate that the proposed GAP_SAC algorithm outperforms TD3, SAC and SAC’s variant, demonstrating superior robustness and generalization in complicated environments. © The Author(s) 2025.

关键词： Autonomous mobile robot (AMR) Deep reinforcement learning (DRL) Dynamic and narrow areas Gated attention mechanism Path planning

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Corrigendum to "Hyperledger sawtooth based supplychain traceability system for counterfeit drugs" [Comput. Ind. Eng. 190 (2024) 110021] (Computers & Industrial Engineering (2024) 190, (S0360835224001426), (10.1016/***.2024.110021))

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Computers and Industrial Engineering 2025年 204卷

作者： Nawaz, Anum Wang, Liguan Irfan, Muhammad Westerlund, Tomi Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Turku Intelligent and Embedded Robotic Systems Lab Faculty of Technology University of Turku Finland

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An Efficient Phase Noise Elimination Method to Facilitate Cost-effective 100/200G Coherent PON

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Journal of Lightwave Technology 2025年

作者： Chen, Yifan Wang, Chen Yu, Jianjun Long, Jianyu Sang, Bohan Li, Fan Sun Yat-Sen University School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Opto-Electronic Information Processing Chips and Systems Guangzhou 510275 China Fudan University State Key Laboratory of ASIC and System Shanghai 200433 China

In the field of passive optical networks (PONs), coherent sinking has emerged as a significant topic, particularly in the context of cost and complexity improvements. We experimentally demonstrate a cost-effective 100-/200-Gbits/s/λ coherent PON system employing dual-polarization quadrature phase shift keying (DP-QPSK) and 16-ary quadrature amplitude modulation (DP-16QAM). To achieve cost reductions in coherent PON implementations, we employ low-cost distributed feedback lasers (DFBs) as the sole active light sources, replacing the much more expensive external cavity lasers (ECLs) at both the optical line terminal (OLT) and the optical network units (ONUs). To effectively address the performance penalty associated with phase noise (PN) of DFBs characterized by MHz-class linewidths, a straightforward carrier phase recovery (CPR) is proposed via embedding a one-tap carrier phase estimator (CPE) with gradient-descent algorithm into a 4×4 multiple-input multiple-output (MIMO) equalizer following the least-mean square algorithm (LMS). This approach simplifies the structure and enables more precise cancellation of PN. We conduct a transmission performance comparison at 32 Gbaud between our proposed scheme and the blind phase searching algorithm (BPS) for single-carrier (SC) signals, as well as between our method and the frequency-domain pilot-tone carrier phase recovery (FPT-CPR) for two-sub-band digital subcarrier multiplexing (DScM) signals. Experimental results demonstrate the corresponding power budgets of 38.1, 30.8, 36.5, and 29.1 dB for SC-QPSK/16QAM and DScM-QPSK/16QAM at the 20% soft-decision forward error correction (SD-FEC) threshold of 2×10^-2. Furthermore, complexity analysis of these phase noise estimation (PNE) methods reveals the superiority of our proposed scheme in balancing performance and computational complexity. © 1983-2012 IEEE.

关键词： 100/200G PON distributed feedback laser laser phase noise low-cost coherent PON phase noise estimation

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General electronic structure calculation method for twisted systems

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Physical Review B 2025年第7期111卷 075434-075434页

作者： Junxi Yu Shifeng Qian Cheng-Cheng Liu Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) and Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China Anhui Province Key Laboratory for Control and Applications of Optoelectronic Information Materials Department of Physics Anhui Normal University Anhui Wuhu 241000 China

In recent years, two-dimensional twisted systems have gained increasing attention. However, calculating the electronic structures in twisted materials has remained a challenge. To address this, we have developed a general computational methodology that can generate twisted geometries starting from a monolayer structure and obtain a precisely relaxed twisted structure through a machine learning-based method. Then, the electronic structure properties of the twisted material are calculated using the tight-binding (TB) and continuum model methods; thus, the entire process requires minimal computational resources. We introduce the theoretical methods for generating twisted structures and computing their electronic properties, and further provide calculations and brief analyses of the electronic structure properties for several typical two-dimensional materials with different characteristics. This paper serves as a solid foundation for researchers interested in studying twisted systems.

关键词： Electronic properties

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Advanced Software-in-the-Loop Simulation Environment for UAV control Algorithms

Advanced Software-in-the-Loop Simulation Environment for UAV...

引用

Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Ismail Laabousse Mohamed Haidoury Younes El Bouzekri El Idrissi Engineering Sciences Laboratory National School of Applied Sciences Ibn Tofail University Kenitra Morocco Modeling Information Processing and Control Systems National School of Arts and Crafts Moulay Ismail University Meknes Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

The rapid adoption of Unmanned Aerial Vehicles (UAVs) highlights the necessity for a robust testing environment to ensure the reliability, safety, and efficiency of control algorithms. Software-in-the-Loop (SIL) simulation constitutes a critical step in the validation of these systems prior to their deployment in Hardware-in-the-Loop (HIL) simulations or real-world flight trials. This study introduces the design and the implementation of a SIL simulation platform for UAV applications. The proposed environment integrates X-Plane 12 as a high-fidelity flight dynamics simulation engine, Python-based implementation of control algorithms, and a custom-designed Ground control Station (GCS). The simulator enables performance evaluation of control algorithms throughout various trajectories and under diverse scenarios. Simulation outcomes validate the capability of the SIL simulation environment to accurately replicate UAV flight dynamics and generate meaningful insights into the performance and robustness of tested control algorithms.

关键词： Machine learning algorithms Heuristic algorithms Autonomous aerial vehicles Robustness Real-time systems Trajectory Synchronization Vehicle dynamics Engines Testing

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A Novel Wide-Band High-Gain Microstrip Quasi-Yagi Antenna Design for X-Band Applications

A Novel Wide-Band High-Gain Microstrip Quasi-Yagi Antenna De...

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Advances in Electrical, Electronics and Computing Technology (EECT), International Conference on

作者： Xinju Wang Sentao Wang Zhuo Chen Zongsheng Gan Haowei Zhang Yutong Yin Lu Liu Peng Chen School of Ocean Information Engineering Jimei University Xiamen China School of Transportation and Civil Engineering Nantong University Nantong China Fujian Provincial Key Laboratory of Maritime Communication and Intelligent Electronic Systems Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing School of Ocean Information Engineering Jimei University Xiamen China

ISBN: (数字)9798331541545

ISBN: (纸本)9798331541552

A new broadband high-gain microstrip quasi-yagi antenna is proposed. With the aim of designing an end-firing antenna for X-band by utilizing the good directivity of yagi antennas. The main radiating dipole patches of this antenna adopts an additional tapered trapezoidal-like structure to optimize its radiation characteristics. In addition, the operating bandwidth and main beam gain of the antenna are effectively adjusted by placing four identical microstrip metal strip patches on the bottom surface of the dielectric substrate to act as the reflector and the guide, respectively. Simulation results show that the designed antenna operates in the frequency bands of 8.33-13.07 GHz and 13.57-13.95 GHz with relative bandwidths of 44.3% and 2.76%, respectively, and achieves a peak gain of 8.9 dBi. The antenna has a simple structural design and is suitable for X-band wireless communication systems with a wide range of applications.

关键词： Satellite antennas Dipole antennas Simulation Metals Microstrip antennas Bandwidth Radar antennas Reflector antennas Broadband antennas Microstrip

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