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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Jinrong Li, Ruixuan Xu, Yaoyuan Li, Shishi Meng, Xianghe Xie, Hui State key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781665481090

This paper presents a novel magnetic-field-assisted LCD stereolithography technique for fabricating centipede-inspired magnetic soft robots. Unlike previous DLP-based methods, our approach leverages Liquid Crystal Display (LCD) technology, offering a simpler optical path, comparable resolution, and cost-effectiveness. The method integrates LCD photo-polymerization with a permanent magnet orienting system possessing 5-DOF in motion, enabling precise control over the direction of magnetization patterns during manufacturing. We demonstrate the technique by designing and fabricating a biomimetic centipede robot with programmable deformation capabilities. Finite element analysis was used to simulate the robot's deformation behavior, which was subsequently validated through experimental locomotion tests. The fabricated robot exhibited complex deformation and efficient locomotion in response to external magnetic fields. This approach advances the creation of intricate magnetic arrangements for planar soft robots, potentially expanding their application in fields such as biomedicine and microfluidics. The proposed method provides a new pathway for manufacturing biologically inspired magnetic soft robots with complex programmable behaviors. © 2024 IEEE.

关键词： Liquid crystal displays

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Deep Learning-Enhanced Super-Resolution Ultrasound for Efficient Brain Vascular Mapping

Deep Learning-Enhanced Super-Resolution Ultrasound for Effic...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Sun, Andi Shen, Xingjian Meng, Xianghe Xie, Hui Harbin Institute of Technology State key Laboratory of Robotics and Systems Harbin150080 China

ISBN: (纸本)9781665481090

Robotic implantation of neural electrodes for in-vasive brain-computer interface(BCI) requires precise vascular mapping to avoid major blood vessels. While super-resolution ultrasound imaging offers superior resolution compared to traditional methods, it typically requires probes with numer-ous elements, demanding substantial hardware resources. This paper presents a novel approach combining deep learning with reduced-element probes for high-resolution vascular imaging. The proposed method employs a transformer-based neural network to accurately localize high-density microbubbles while reducing the required number of probe elements. Simulations reveal that a 32-element linear probe with deep learning outper-forms a 64-element probe using 2D normalized cross-correlation for microbubble concentrations below 1.95 microbubbles/mm2. The overall localization precision and Jaccard index demon-strate superior performance of the deep learning approach, particularly at lower microbubble densities. In vivo experiments on a mouse brain model using a 64-element probe (15 MHz) and deep learning achieved vascular network reconstruction with 21 um resolution, distinguishing vessels 26 um apart. This technique significantly lowers the hardware requirements for constructing high-resolution vascular networks, thereby providing detailed cerebrovascular distribution maps. These maps have the potential to enable more precise planning and safer execution of neural electrode implantation for BCI research, while reducing overall system complexity. © 2024 IEEE.

关键词： Brain mapping

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A Study of Prototypical Network Techniques for Cross-Subject EEG Analysis 27

A Study of Prototypical Network Techniques for Cross-Subject...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Liu, Wenchao Wang, Guagnyu He, Yuhong Bo, Hongjian Ma, Lin Li, Haifeng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Faculty of Computing Harbin Institute of Technology Harbin China Shenzhen Academy of Aerospace Technology Shenzhen China

ISBN: (纸本)9781643685489

Electroencephalography (EEG), a technique that uses electrodes on the scalp to record changes in cerebral electrical potentials, plays a key role in various brain-computer interface applications. However, due to the large differences in EEG distribution across subjects, how to accurately classify cross-subject EEG is still a challenge. In practice, it is unavoidable to collect data for each subject to perform calibration, which is cumbersome and expensive. In this paper, we propose a Cross Subject EEG Prototypical Network (CS-EEGPNet) for accurate few-shot EEG classification. To the best of our knowledge, we are the first to eliminate inter-subject distribution shift in few-shot EEG classification through multiple feature layers computation. Specifically, to avoid the effect of individual differences, we propose a few-shot feature normalization (FSFN) method, which uses the mean and variance of the same subject’s support set features to normalize the query set features. Meanwhile, we design a prototypical module based on auxiliary factors. This module utilizes learnable vectors to store category-related information for assisting the construction of prototypes, thus mitigating the effects of EEG’s randomness and non-stationary characteristics on cross-subject few shot classification. To validate the effectiveness of the method, we selecte the motor imagery paradigm, which is relatively complex in brain-computer interfaces, and test our method on the BCIC IV 2a and HGD datasets. The results demonstrate that our method significantly enhances EEG classification performance, achieving the state-of-the-art accuracies. © 2024 The Authors.

关键词： Electroencephalography

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Layer-controlled 2D Sn_(4)P_(3) via space-confined topochemical transformation for enhanced lithium cycling performance

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Nano Research 2024年第11期17卷 9697-9703页

作者： Jianan Gu Yongzheng Zhang Bingbing Fan Yanlong Lv Yanhong Wang Ruohan Yu Meicheng Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of New Energy North China Electric Power University Beijing 100096 China State Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China Wuhan University of Technology Sanya 572000 China

Topochemical transformation has emerged as a promising method for fabricating two-dimensional (2D) materials with precise control over their composition and morphology. However, the large-scale synthesis of ultrathin 2D materials with controllable thickness remains a tremendous challenge. Herein, we adopt an efficient topochemical synthesis strategy, employing a confined reaction space to fabricate ultrathin 2D Sn_(4)P_(3) nanosheets in large-scale. By carefully adjusting the rolling number during the processing of Sn/Al foils, we have successfully fabricated Sn_(4)P_(3) nanosheets with varied layer thicknesses, achieving a remarkable minimum thickness of two layers (~ 2.2 nm). Remarkably, the bilayer Sn_(4)P_(3) nanosheets display an exceptional initial capacity of 1088 mAh·g^(−1), nearing the theoretical value of 1230 mAh·g^(−1). Furthermore, we reveal their high-rate property as well as outstanding cyclic stability, maintaining capacity without fading more than 3000 cycles. By precisely controlling the layer thickness and ensuring nanoscale uniformity, we enhance the lithium cycling performance of Sn_(4)P_(3), marking a significant advancement in developing high-performance energy storage systems.

关键词： topochemical transformation 2D materials confined reaction layer-controlled Sn_(4)P_(3)nanosheets lithium storage

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Damage evolution and removal behaviors of GaN crystals involved in double-grits grinding

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International Journal of Extreme Manufacturing 2024年第2期6卷 469-484页

作者： Chen Li Yuxiu Hu Zongze Wei Chongjun Wu Yunfeng Peng Feihu Zhang Yanquan Geng State Key Laboratory of Robotics and System(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China Key Laboratory of Microsystems and Microstructures Manufacturing(HIT) Harbin Institute of TechnologyHarbin 150001People’s Republic of China College of Mechanical Engineering Donghua UniversityShanghai 201620People’s Republic of China Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005People’s Republic of China

Elucidating the complex interactions between the work material and abrasives during grinding of gallium nitride(GaN)single crystals is an active and challenging research *** this study,molecular dynamics simulations were performed on double-grits interacted grinding of GaN crystals;and the grinding force,coefficient of friction,stress distribution,plastic damage behaviors,and abrasive damage were systematically *** results demonstrated that the interacted distance in both radial and transverse directions achieved better grinding quality than that in only one *** grinding force,grinding induced stress,subsurface damage depth,and abrasive wear increase as the transverse interacted distance ***,there was no clear correlation between the interaction distance and the number of atoms in the phase transition and dislocation *** interacted distances between abrasives can decrease grinding force,coefficient of friction,grinding induced stress,subsurface damage depth,and abrasive wear during the grinding *** results of grinding tests combined with cross-sectional transmission electron micrographs validated the simulated damage results,*** atoms,high-pressure phase transition,dislocations,stacking faults,and lattice *** results of this study will deepen our understanding of damage accumulation and material removal resulting from coupling between abrasives during grinding and can be used to develop a feasible approach to the wheel design of ordered abrasives.

关键词： grinding double-grits molecular dynamics damage material removal gallium nitride

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A Unified Trajectory Optimization Approach for Long-Term and Reactive Motion Planning of Legged Locomotion

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Journal of Bionic Engineering 2023年第5期20卷 2108-2122页

作者： Yapeng Shi Bin Yu Kaixian Ba Mantian Li School of Mechanical Engineering Yanshan UniversityNo.438 West Hebei AvenueQinhuangdao066004HebeiPeople’s Republic of China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001People’s Republic of China

This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged *** on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target *** unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned *** effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.

关键词： Legged locomotion Motion planning Trajectory optimization Bionic robot

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Multi-area Frequency-constrained Unit Commitment for Power systems with High Penetration of Renewable Energy Sources and Induction Machine Load

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Journal of Modern Power systems and Clean Energy 2024年第3期12卷 754-766页

作者： Leibao Wang Hui Fan Jifeng Liang Longxun Xu Tiecheng Li Peng Luo Bo Hu Kaigui Xie the State Grid Hebei Electric Power Research Institute Shijiazhuang 050021China State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqing 400044China

The increasing penetration of renewable energy sources(RESs)brings great challenges to the frequency security of power *** traditional frequency-constrained unit commitment(FCUC)analyzes frequency by simplifying the average system frequency and ignoring numerous induction machines(IMs)in load,which may underestimate the risk and increase the operational *** this paper,we consider a multiarea frequency response(MAFR)model to capture the frequency dynamics in the unit scheduling problem,in which regional frequency security and the inertia of IM load are modeled with high-dimension differential algebraic equations.A multi-area FCUC(MFCUC)is formulated as mixed-integer nonlinear programming(MINLP)on the basis of the MAFR ***,we develop a multi-direction decomposition algorithm to solve the MFCUC *** original MINLP is decomposed into a master problem and *** subproblems check the nonlinear frequency dynamics and generate linear optimization cuts for the master problem to improve the frequency security in its optimal *** studies on the modified IEEE 39-bus system and IEEE 118-bus system show a great reduction in operational ***,simulation results verify the ability of the proposed MAFR model to reflect regional frequency security and the available inertia of IMs in unit scheduling.

关键词： Decomposition algorithm frequency response frequency-constrained unit commitment induction machine multi-area mixed-integer nonlinear programming(MINLP)

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Mechanical design and analysis of a novel variable stiffness actuator with symmetrical pivot adjustment

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Frontiers of Mechanical Engineering 2021年第4期16卷 711-725页

作者： Yiwei LIU Shipeng CUI Yongjun SUN State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

The safety of human-robot interaction is an essential requirement for designing collaborative ***,this paper aims to design a novel variable stiffiiess actuator(VSA)that can provide safer physical human-robot interaction for collaborative *** A follows the idea of modular design,mainly including a variable stiffiiess module and a drive *** variable stiffiiess module transmits the motion from the drive module in a roundabout maimer,making the modularization of VS A *** the key component of the variable stiffiiess module,a stiffness adjustment mechanism with a symmetrical structure is applied to change the positions of a pair of pivots in two levers linearly and simultaneously,which can eliminate the additional bending moment caused by the asymmetric *** design of the doubledeck grooves in the lever allows the pivot to move freely in the groove,avoiding the geometric constraint between the ***,the VSA stiffiiess can change from zero to infinity as the pivot moves from one end of the groove to the *** facilitate building a manipulator in the future,an expandable electrical system with a distributed structure is also *** calibration and control experiments are performed to evaluate the physical performance of the designed *** results show that the VSA stiffiiess is close to the theoretical design ***,the VSA with a proportional-derivative feedback plus feedforward controller exhibits a fast response for stiffiiess regulation and a good performance for position tracking.

关键词： variable stiffiiess actuator variable stiffness module drive module symmetrical structure doubledeck grooves expandable electrical system

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An Autonomous Obstacle Avoidance Path Planning Method Involving PSO for Dual-Arm Surgical Robot 5

An Autonomous Obstacle Avoidance Path Planning Method Involv...

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5th International Conference on Mechatronics, robotics and Automation, ICMRA 2022

作者： Chen, Qiao Liu, Yiwei Chen, Zhuo Zhou, Yangjunjian Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781665472654

Currently, motion planning and reasonable obstacle avoidance of surgical robots are essential research directions. Most surgical robots adopt a simple master-slave control strategy and cannot avoid obstacles autonomously. To this end, we propose an autonomous obstacle avoidance method for the dual-arm surgical robot. Firstly, the obstacle avoidance path planning is based on the artificial potential field method. We propose the splicing algorithm to make the manipulator jump out of the local minimum and improve the planning efficiency. And using the adaptive step to stable motion. Secondly, for collision detection, we use the Gilbert-Johnson-Keerthi (GJK) algorithm to calculate the distance between the obstacle and the equivalent convex body of the manipulator. A warning appears when there is a collision. Because the artificial potential field method lacks time planning, we use the time-optimized 3-5-3 polynomial interpolation based on the Particle Swarm optimization (PSO) to the obtained path. And make manipulators perform the surgery without collision for a suitable period. Finally, we carry out the system simulation, physical experiments, and dual-arm obstacle avoidance experiments based on the above autonomous obstacle avoidance algorithm. Experiments show that this study can make the dual-arm surgical robot move quickly and smoothly on the premise of avoiding obstacles, which provides a reference for the automation of surgical robots. © 2022 IEEE.

关键词： Motion planning

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Integral Real-time Locomotion Mode Recognition Based on GA-CNN for Lower Limb Exoskeleton

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Journal of Bionic Engineering 2022年第5期19卷 1359-1373页

作者： Jiaqi Wang Dongmei Wu Yongzhuo Gao Xinrui Wang Xiaoqi Li Guoqiang Xu Wei Dong State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Weapon Equipment Research Institute China South Industries Group CorporationBeijing 102202China

The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion *** subject-specific training is the main challenge of the existing approaches,and most methods have the problem of insufficient *** paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition(LMR)method based on GA-CNN for a lower limb exoskeleton *** LMR method is a combination of Convolutional Neural Networks(CNN)and Genetic Algorithm(GA)-based multi-sensor information *** improve network performance,the hyper-parameters are optimized by Bayesian *** exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed *** locomotion modes,which composed an integral locomotion system for the daily application of the exoskeleton,can be recognized by the proposed *** to a series of experiments,the recognizer shows strong comprehensive abilities including high accuracy,low delay,and sufficient adaption to different subjects.

关键词： Locomotion mode recognition Gait mode detection Lower limb exoskeleton Convolutional neural network Genetic algorithm Bionic design

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