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Inverse Origami Design Model for Soft Robotic Development

Soft robotics 2024年第1期11卷 131-139页

作者： Hu, Qiqiang Li, Junyang Tao, Jian Dong, Erbao Sun, Dong Department of Biomedical Engineering City University of Hong Kong Hong Kong Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China Hefei China Department of Electronic Engineering Ocean University of China Qingdao China CAS Key Laboratory of Mechanical Behavior and Design of Materials School of Engineering Science University of Science and Technology of China Hefei China Centre for Robotics and Automation Shenzhen Research Institute of City University of Hong Kong Shenzhen China

Origami provides an opportunity to construct a wide range of 3D functional structures by folding a flat sheet. It can be used to develop various soft functional robots by combining soft smart actuators. However, a simple and an effective model that can address the challenging problem of designing origami patterns to connect origami design with robotics is lacking, thereby greatly increasing the threshold of soft origami robots and hindering its development. This study proposes an easy-to-use inverse origami design model to generate the flat crease pattern from the desired folded shape automatically while simulating origami morphing by simply providing the shape parameters or 2D shape graphics. This method overcomes the difficulty of origami design and enables a close connection between origami and robotics. Through this method, various soft origami robots can be developed with low design complexity and time cost to achieve different functions, thereby promoting the development of soft origami robots. © 2024 Mary Ann Liebert Inc.. All rights reserved.

关键词： Robots

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Operation Cost Optimization Method of Regional Integrated Energy System in Electricity Market Environment Considering Uncertainty

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 368-380页

作者： Peng Li Fan Zhang Xiyuan Ma Senjing Yao Yuhang Wu Ping Yang Zhuoli Zhao Loi Lei Lai Digital Grid Research Institute of China Southern Power Grid Guangzhou 510663China Guangdong Key Laboratory of Clean Energy Technology South China University of TechnologyGuangzhou 510640China Department of Electrical Engineering School of AutomationGuangdong University of TechnologyGuangzhou 510006China IEEE

In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market ***,the RIES will face the risk of load and electricity price uncertainties,which may make its operation cost higher than *** paper proposes a method to optimize the operation cost of the RIES in the electricity market environment considering ***,based on the operation cost structure of the RIES in the electricity market environment,the energy flow relationship of the RIES is analyzed,and the operation cost model of the RIES is ***,the electricity purchase costs of the RIES in the medium-and long-term electricity markets,the spot electricity market,and the retail electricity market are ***,considering the risk of load and electricity price uncertainties,the operation cost optimization model of the RIES is established based on conditional *** it is solved to obtain the operation cost optimization strategy of the *** results show that the proposed operation cost optimization method can reduce the operation cost of high electricity price scenario by optimizing the energy purchase and distribution strategy,constrain the risk of load and electricity price uncertainties,and help balance the risks and benefits.

关键词： Conditional value-at-risk electricity market uncertainty operation cost regional integrated energy system(RIES).

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Experimental implementation of chaos-based video encryption using visible light communication technology

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Applied Optics 2025年第9期64卷 C101-C118页

作者： Fotso, Sorel Bagio Nono Mbé, Jimmi Hervé Talla Takotue, Jean Ernest Takougang, Armand Cyrille Nzeukou Ndjiongue, Alain Richard Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang P.O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer Department of Electrical Engineering IUT-FV Bandjoun University of Dschang P.O. Box: 134 Bandjoun Cameroon Laboratory of Industrial Systems and Environmental Engineering Fotso Victor University Institute of Technology University of Dschang P.O. Box 134 Bandjoun Cameroon School of Electrical and Information Engineering Faculty of Engineering and the Built Environment University of the Witwatersrand Johannesburg South Africa

Simulations are commonly used to develop and evaluate video encryption algorithms. Although these approaches are useful for demonstrating theoretical feasibility and algorithm performance, they neglect practical challenges and real-world communication conditions. This oversight creates a critical gap in evaluating their effectiveness and security in practical applications. In this paper, we describe a novel, to the best of our knowledge, video encryption scheme that employs a modified chaotic Colpitts oscillator, a customized Josephus problem, and ribonucleic acid (RNA) operations, and is implemented in visible light communication (VLC) environment. The modified Colpitts oscillator reveals significant phenomena, the most prominent for this study being chaos. The encryption scheme involves block scrambling and pixel-level permutation employing a customized Josephus problem and a column and row shifting technique. Diffusion is then achieved through a custom Josephus problem-oriented RNA operation combined with basic RNA operations and cipher block chaining (CBC). Based on the results, we found that the customized Josephus problem-based permutation performed more efficiently than traditional methods, whereas the column and row shifting permutation was more robust. By eliminating key sequence coding and item-to-item operations, the proposed RNA operation reduces computational overhead. This video encryption scheme is proven to be effective and resilient at securing video data transmitted over the VLC channel, and it constitutes a significant advancement in areas such as surveillance, medical imaging, and military communication requiring robust secured video data. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Medical imaging

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THÖR-Magni: Comparative Analysis of Deep Learning Models for Role-conditioned Human Mtion Prediction

THÖR-Magni: Comparative Analysis of Deep Learning Models fo...

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2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023

作者： De Almeida, Tiago Rodrigues Rudenko, Andrey Schreiter, Tim Zhu, Yufei Maestro, Eduardo Gutierrez Morillo-Mendez, Lucas Kucner, Tomasz P. Martinez Mozos, Oscar Magnusson, Martin Palmieri, Luigi Arras, Kai O. Lilienthal, Achim J. Örebro University Sweden Corporate Research Robert Bosch GmbH Stuttgart Germany Aalto University Mobile Robotics Group Department of Electrical Engineering and Automation Finland Finnish Center for Artificial Intelligence Fcai Finland

ISBN: (纸本)9798350307443

Autonomous systems, that need to operate in human environments and interact with the users, rely on understanding and anticipating human activity and motion. Among the many factors which influence human motion, semantic attributes, such as the roles and ongoing activities of the detected people, provide a powerful cue on their future motion, actions, and intentions. In this work we adapt several popular deep learning models for trajectory prediction with labels corresponding to the roles of the people. To this end we use the novel THÖR-Magni dataset, which captures human activity in industrial settings and includes the relevant semantic labels for people who navigate complex environments, interact with objects and robots, work alone and in groups. In qualitative and quantitative experiments we show that the role-conditioned LSTM, Transformer, GAN and VAE methods can effectively incorporate the semantic categories, better capture the underlying input distribution and therefore produce more accurate motion predictions in terms of Top-K ADE/FDE and log-likelihood metrics. © 2023 IEEE.

关键词： deep learning human motion dataset human trajectory prediction

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A Manta Ray-Inspired Biosyncretic Robot with Stable Controllability by Dynamic Electric Stimulation

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Cyborg and Bionic Systems 2022年第1期2022卷 314-326页

作者： Chuang Zhang Yiwei Zhang Wenxue Wang Ning Xi Lianqing Liu State Key Laboratory of Robotics Shenyang Inst itute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang 110159China Emerging Technologies Institute Department of Industrial Manufacturing Systems Engineering University of Hong KongPokfulamChina

Biosyncretic robots,which are new nature-based robots in addition to bionic robots,that utilize biological materials to realize their core function,have been supposed to further promote the progress in *** as the main operation mechanism relates to the robotic overall ***,biosyncretic robots actuated by living biological actuators have attracted increasing ***,innovative propelling modes and control methods are still necessary for the further development of controllable motion performance of biosyncretic *** this work,a muscle tissue-based biosyncretic swimmer with a manta *** propelling mode has been *** is more,to improve the stable controllability of the biosyncretic swimmer,a dynamic control method based on circularly distributed multiple electrodes(CDME)has been *** this method,the direction of the electric field generated by the CDME could be real-time controlled to be parallel with the adtuation tissue of the dynamic ***,the instability of the tissue actuation induced by the dynamic included angle between the tissue axis and electric field direction could be ***,the biosyncretic robot has demonstrated stable,controllable,and efective swimming,by adjusting the electric stimulation pulse direction,amplitude,and *** work may be beneficial for not only the development of biosyncretic robots but also other related studies including bionic design of soft robots and muscle tissue engineering.

关键词： Robot robot Dynamic

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An Economic Dispatch Method for Power System Based on Distributed Mutual-Fed-Consensus

An Economic Dispatch Method for Power System Based on Distri...

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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： Li, Xiangjun Zhang, Panpan Li, Bo China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Energy Storage and Electrical Engineering Department Beijing China Northeast Electric Power University School of Automation Engineering China

ISBN: (纸本)9798350366204

This paper presents a distributed algorithm based on mutual feedback mechanism for economic dispatch problem of power system. In such a mutual feedback mechanism, the average of the load demand and power generated are estimated, respectively. Simulation results on standard test cases show the convergence and effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Consensus algorithm

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Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

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Defence Technology（防务技术） 2024年第3期33卷 573-587页

作者： Qu Wang Meixia Fu Jianquan Wang Lei Sun Rong Huang Xianda Li Zhuqing Jiang Yan Huang Changhui Jiang School of Automation Science and Electrical Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFo Shan528399China Research Institute of China Unicom Beijing100190China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing100876China Department of Automation Tsinghua University Beijing100084China GEOLOC Laboratory Universite Gustave EiffelParis77454France

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time ***,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with *** paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual *** at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent *** at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding *** at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude *** conduct extensive and well-designed experiments to evaluate the performance of the proposed *** experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

关键词： Indoor positioning Inertial navigation system(INS) Zero-velocity update(ZUPT) Internet of things(IoTs) Location-based service(LBS)

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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 146-159页

作者： Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang Key Laboratory of Networked Control Systems Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Computing Wichita State UniversityWichita 67260 USA Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeTN 37996 USA Department of Automation Technology ABB Corporate Research SwedenVasteras 72178Sweden Department of Intelligent Systems Royal Institute of Technology(KTH)Stockholm 11428Sweden

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment ***,traditional calibrations suffer inaccuracy and *** address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying *** our method,the spatial relationship is geometrically correlated between the sensing units and robotic *** decoupled estimations on rotation and translation could reduce the coupled errors during the ***,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and *** calibration has been evaluated on our developed *** the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,*** comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

关键词： Calibration inertial measurement unit(IMU) monocular camera robotic arm spiral moving trajectory

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Rock Climbing‑Inspired Electrohydrodynamic Cryoprinting of Micropatterned Porous Fiber Scaffolds with Improved MSC Therapy for Wound Healing

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Advanced Fiber Materials 2023年第1期5卷 312-326页

作者： Jinjian Huang Jie Wu Jiahang Wang Mengjia Xu Jiao Jiao Yuhao Qiang Feng Zhang Zongan Li Research Institute of General Surgery Jinling HospitalSchool of MedicineSoutheast UniversityNanjing 210009China Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing NARI School of Electrical and Automation EngineeringNanjing Normal UniversityNanjing 210042China Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridge 02139USA

Impaired wound healing imposes great health risks to ***,mesenchymal stem cell(MSC)therapy has shown potential to improve the healing process,but approaches to employ MSCs in the treatment of wounds remain *** this study,we reported a novel electrohydrodynamic(EHD)cyroprinting method to fabricate micropatterned fiber scaffolds with polycaprolactone(PCL)dissolved in glacial acetic acid(GAC).Cyroprinting ensured the formation of a porous struc-ture of PCL fibers by preventing the evaporation of GAC,thus increasing the surface roughness parameter Ra from 11 to 130 *** to how rough rocks facilitate easy climbing,the rough surface of fibers was able to increase the adhesion of adipose-derived MSCs(AMSCs)by providing more binding sites;therefore,the cell paracrine action of secreting growth factors and chemokines was enhanced,promoting fibroblast migration and vascular endothelial cell tube *** rat models with one-centimeter wound defects,enhanced MSC therapy based on porous PCL fiber scaffolds improved wound healing by augmenting scarless collagen deposition and angiogenesis and reducing proinflammatory ***,this study offers a new and feasible strategy to modulate the surface topography of polymeric scaffolds to strengthen MSC therapy for wound healing.

关键词： Electrohydrodynamic cryoprinting Porous fiber scaffolds Mesenchymal stem cell Wound healing

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A Fully Test-Time Adaptation Method for Motor Imagery

SSRN

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SSRN 2024年

作者： Peng, Yiheng Luo, Jingjing Wang, Hongbo Chen, Li Guo, Shijie Guo, Yuzhu Li, Yang The Institute of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai200433 China Engineering Research Center of AI and Robotics Ministry of Education Shanghai200043 China Department of Automation Sciences and Electrical Engineering Beihang University Beijing100191 China School of Automation Science and Electrical Engineering China

Transfer learning offers a promising solution to the annotation and calibration challenges associated with motor imagery (MI) electroencephalogram (EEG) decoding during neural-feedback rehabilitation. In this study, we address the challenge of online unsupervised cross-subject adaptation in MI-EEG classification, where target samples arrive sequentially, and we should adapt the model online with limited target data. We focus on the testing stage and propose a MI Fully Test-Time Adaptation (MI-FTTA) method that essentially enables online training using limited and unlabeled target data. MI-FTTA effectively alleviates the influence of noisy pseudo labels with teacher-student mutual learning and time-constrained sample selection. Through recalculating normalization statistics with limited accessible source and target information and prototype-based cross-domain contrastive learning, MI-FTTA adaptively enhances the representational capability of models. It thoroughly harnesses the limited online target samples to enhance adaptation performance. Experimental evaluations are conducted using three classification datasets , including two-class (BCI-IV2b), three-class (High-Gamma), and four-class (BCI-IV2a) scenarios. MI-FTTA demonstrates its superiority by surpassing direct source model deployment with an average performance gain of 4.11\% across different scenarios. Notably, our proposed approach also achieves a significant improvement over 12 different online test-time adaptation algorithms at three different backbones, thus affirming its *** work represents early endeavor in source-free fully test-time adaptation for cross-subject MI-EEG decoding. © 2024, The Authors. All rights reserved.

关键词： Transfer learning

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