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26th International Conference on Industrial Technology, ICIT 2025

作者： Zhang, Baichao Chen, Xin Chen, Jinge Li, Jinbin Wang, Xiaokai Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan430077 China

ISBN: (纸本)9798331521950

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. Simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications. © 2025 IEEE.

关键词： Motion planning

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Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces

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Computers in Biology and Medicine 2025年第Pt A期192卷 110231-110231页

作者： Li, Xiao Dong, Xianxin Wang, Jun Mao, Haodong Tu, Xikai Li, Wei He, Jiping Li, Qiang Zhang, Peng Hubei Key Laboratory of Modern Manufacturing Quantity Engineering School of Mechanical Engineering Hubei University of Technology Wuhan430068 China Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Science and Technology Hubei Wuhan China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of the iBMI decoder to maintain decoding performance, which requires collecting and labeling a large amount of new data. To address this challenge and minimize the time needed for decoder recalibration, we proposed an active learning domain adversarial neural network (AL-DANN). This model leveraged a substantial volume of historical data alongside a small amount of current data (four samples per category) to calibrate the decoder. By incorporating domain adversarial and active learning strategies, the model effectively transferred knowledge from historical data to new data, reducing the demand for new samples. We validated the proposed method using neural signals recorded from three monkeys performing different movements in a classification task or a regression task. The results showed that the AL-DANN outperformed existing state-of-the-art methods. Impressively, it required only four new samples per category for decoder recalibration, leading to a recalibration time reduction of over 80 %. To our knowledge, this is the first study to incorporate deep transfer learning into iBMI decoder calibration, highlighting the significant potential of applying deep learning technologies in iBMIs. © 2025

关键词： Adversarial machine learning

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Photoinduced Copper-Catalyzed Regio- and Diastereoselective Multicomponent [3 + 2 + 1] Radical Cyclization To Access Tetrahydropyridines

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Organic Letters 2025年第20期27卷 5057-5062页

作者： Li, Sijia Li, Jianye Zhang, He Zhang, Guozhu Guo, Rui CCNU-uOttawa Joint Research Centre State Key Laboratory of Green Pesticide Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction Ministry of Education International Joint Research Center for Intelligent Biosensing Technology and Health College of Chemistry Central China Normal University (CCNU) 152 Luoyu Road Hubei Wuhan 430079 China

The use of simple raw materials to construct complex piperidine scaffolds via multicomponent reactions is highly desirable from the perspectives of atom and step-economy. In this Letter, we present a photoinduced copper-catalyzed three- or four-component [3 + 2 + 1] radical cyclization, utilizing inexpensive and readily available feedstock amines, alkynes, and aldehydes, to synthesize multisubstituted bicyclic or spirocyclic tetrahydropyridines. This method is notable for its mild conditions, atom-economic approach, excellent regio- and diastereoselectivity, and the simultaneous activation of two α-amino C(sp³)-H bonds, resulting in the formation of three C-C bonds and one C-N bond in a single step. Mechanistic studies suggest that the α-aminoalkyl radical is the key intermediate in this reaction, which undergoes sequential radical addition, 1,5-HAT, and 6-exo-trig-type radical cyclization. © 2025 American Chemical Society.

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An automated FBG localization algorithm for distributed strain sensing system using weak FBG array 4

An automated FBG localization algorithm for distributed stra...

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4th International Computational Imaging Conference, CITA 2024

作者： Liang, Changshuo Zhou, Xiaoxu Wang, Yu Bai, Qing Gao, Yan Zhang, Hongjuan Jin, Baoquan Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan China Shanxi Transportation Technology Research & Development Co. Ltd. Shanxi Taiyuan China College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9781510688834

We proposed a Fiber Bragg grating (FBG) localization algorithm for Optical Frequency Domain Reflectometry (OFDR) sensing system with high density weak FBG array. The wavelength selection characteristics of FBG, which are revealed in the distance-wavelength domain spectrum of OFDR signal, are used as the standard for FBG localization. The OFDR system for FBG strain sensing using the proposed method achieved a strain sensing on 45.36 m long FBG array, which is capable of sensing strain up to 3000 μΕ, with spatial resolution of 1 cm, and root mean square error (RMSE) of 0.00192 nm. © 2025 SPIE.

关键词： Fiber Bragg gratings

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

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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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Homochiral carbon nanotube van der Waals crystals

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Science (New York, N.Y.) 2025年第6740期387卷 1310-1316页

作者： Zhang, Zhichun Chen, Yi Shen, Peiyue Chen, Jiajun Wang, Sen Wang, Bo Ma, Saiqun Lyu, Bosai Zhou, Xianliang Lou, Shuo Wu, Zhenghan Xie, Yufeng Zhang, Chengjia Wang, Liguo Xu, Kunqi Li, Haonan Wang, Guohua Watanabe, Kenji Taniguchi, Takashi Qian, Dong Jia, Jinfeng Liang, Qi Wang, Xiaoqun Yang, Wei Zhang, Guangyu Jin, Chuanhong Ouyang, Wengen Shi, Zhiwen Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education) Shanghai Jiao Tong University School of Physics and Astronomy and Tsung-Dao Lee Institute Shanghai China Department of Engineering Mechanics School of Civil Engineering Wuhan University Wuhan Hubei China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan Hubei China State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou Zhejiang China Research Center for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science Tsukuba Japan Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing China School of Physics and Institute for Advanced Studies of Physics Zhejiang University Hangzhou Zhejiang China Beijing National Laboratory for Condensed Matter Physics Key Laboratory for Nanoscale Physics and Devices Institute of Physics Chinese Academy of Sciences Beijing China Songshan Lake Materials Laboratory Dongguan China State Key Laboratory of Micro-Nano Engineering Science Shanghai Jiao Tong University Shanghai China

For applications of single-walled carbon nanotubes (SWNTs) in integrated circuits, it is crucial to have high-tube density arrays of SWNTs that are well aligned and purely semiconducting. In this work, we report on the direct growth of close-packed SWNT arrays on hexagonal boron nitride (hBN) substrates, demonstrating high alignment and uniform chirality within each array. Molecular dynamics simulations suggest that a self-assembly growth mechanism resulted from the intertube van der Waals attraction and the ultralow sliding friction of SWNTs on the atomically flat hBN substrate. Field-effect transistors constructed from the grown SWNT array exhibit high performance at room temperature, with mobilities of up to 2000 square centimeters per volt per second, on/off ratios of ~107, and a maximum current density of ~6 milliamperes per micrometer.

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Distributed multi-timescale algorithm for nonconvex optimization problem: A control perspective

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Neural Networks 2025年 186卷 107257页

作者： Shi, Xiasheng Liu, Jian Sun, Changyin School of Artificial Intelligence Anhui University Hefei230106 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Automation Southeast University Nanjing210096 China

The distributed nonconvex constrained optimization problem with equality and inequality constraints is researched in this paper, where the objective function and the function for constraints are all nonconvex. To solve this problem from a control perspective, a virtual reference-based convex penalty function is added to the augmented Lagrangian function. Then, based on the primal–dual technique, a two-timescale distributed approach is designed based on the consensus scheme. The slower subsystem aims to ensure the optimality, and the faster subsystem intends to guarantee the stability. Finally, three cases are presented to illustrate the approach's effectiveness. © 2025 Elsevier Ltd

关键词： Consensus algorithm

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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Multi-storage, multi-energy, and multi-policy optimization for hybrid green and grey hydrogen production: A regional study in China

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Energy Conversion and Management 2025年 334卷

作者： Yin, Zishan Tang, Xiyun Li, Xi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China Key Laboratory of Imaging Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan430074 China

Green hydrogen is key to global decarbonization. This study optimizes regional green-grey hydrogen production in China, using a multi-storage (hydrogen and battery) and multi-renewable energy model. The focus is on minimizing the levelized cost of hydrogen and carbon emission factor, incorporating carbon reduction policies. The results show that the tradable green certificates policy leads to a lower cost, while the cap-and-trade mechanism accelerates the achievement of grey hydrogen substitution across China's regions by 20 years to 2060. Regions rich in renewable energy achieve $5/kg lower costs and 6 years faster substitution. Hydrogen storage is the most cost-effective solution, hybrid storage is preferable in low renewable energy areas, while battery storage incurs costs that are 25% to 150% higher. The trade-off between carbon emission and cost highlights each region's inflection point, essential for designing incentive policies. © 2025 Elsevier Ltd

关键词： Battery storage

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Innovative Application of Project Integration Technology in the Teaching Mode of Engineering Drawing Course 24

Innovative Application of Project Integration Technology in ...

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7th International Conference on Educational Technology Management, ICETM 2024

作者： Zhang, Runfeng Ming, Yankun Zhang, Guobin Liu, Zhenzhong Wu, Jianguo Tang, Yuxin National Demonstration Center for Exerimenta Mechanica and Electrica Engineering Education Lianin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin Tianjin China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin University of Technology Tianjin Tianjin China

ISBN: (纸本)9798400717468

Taking underwater robots project as an example, this paper discusses the innovation of the teaching mode of engineering drawing courses under the guidance of a project. The traditional engineering drawing course often lacks the link of practice and project application, which leads to the lack of students’ understanding and application ability of the course content. Therefore, this study proposes a teaching mode based on project guidance. By using underwater robots as teaching cases, theoretical knowledge and practical application are combined to promote the cultivation of students’ comprehensive abilities. This paper first reviews the research progress in related fields, then introduces the design and implementation methods of the teaching mode in detail, and analyzes the actual effect of the model through the underwater robot case. The results show that the teaching mode of engineering drawing courses under the guidance of the project has a positive impact on students’ learning interest, practical ability and teamwork ability. The results of this study will provide practical and feasible solutions for the innovation of the teaching mode of engineering drawing courses, and also provide a reference for the reform of undergraduate teaching mode in the construction of "New Engineering Education". © 2024 Copyright held by the owner/author(s).

关键词： Students

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