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Design and Analysis of a 2-DOF Actuator with Variable Stiffness Based on Leaf Springs

Journal of Bionic Engineering 2022年第5期19卷 1392-1404页

作者： ShangKui Yang Peng Chen dongqi wang Yi Yu Yuwang Liu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110000China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110000China Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin UniversityTianjin 300192China University of Chinese Academy of Sciences Beijing 100049China

Variable Stiffness Actuator(VSA)is the core mechanism to achieve physical human–robot interaction,which is an inevitable development trend in robotic.The existing variable stiffness actuators are basically single degree-of-freedom(DOF)rotating joints,which are achieving multi-DOF motion by cascades and resulting in complex robot body structures.In this paper,an integrated 2-DOF actuator with variable stiffness is proposed,which could be used for bionic wrist joints or shoulder joints.The 2-DOF motion is coupling in one universal joint,which is different from the way of single DOF actuators cascade.Based on the 2-DOF orthogonal motion generated by the spherical wrist parallel mechanism,the stiffness could be adjusted by varying the effective length of the springs,which is uniformly distributed in the variable stiffness unit.The variable stiffness principle,the model design,and theoretical analysis of the VSA are discussed in this work.The independence of adjusting the equilibrium position and stiffness of the actuator is validated by experiments.The results show that the measured actuator characteristics are sufficiently matched the theoretical values.In the future,VSA could be used in biped robot or robotic arm,ensuring the safety of human–robot interaction.

关键词： Physical human-robot interaction 2-DOF Bionic wrist joints Variable stiffness actuator Leaf spring

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Community Discovery Algorithm Based on Multi-Relationship Embedding

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Computer Systems Science & Engineering 2023年第9期46卷 2809-2820页

作者： Dongming Chen Mingshuo Nie Jie wang dongqi wang Software College Northeastern UniversityShenyang110169China

Complex systems in the real world often can be modeled as network structures,and community discovery algorithms for complex networks enable researchers to understand the internal structure and implicit information of networks.Existing community discovery algorithms are usually designed for single-layer networks or single-interaction relationships and do not consider the attribute information of nodes.However,many real-world networks consist of multiple types of nodes and edges,and there may be rich semantic information on nodes and edges.The methods for single-layer networks cannot effectively tackle multi-layer information,multi-relationship information,and attribute information.This paper proposes a community discovery algorithm based on multi-relationship embedding.The proposed algorithm first models the nodes in the network to obtain the embedding matrix for each node relationship type and generates the node embedding matrix for each specific relationship type in the network by node encoder.The node embedding matrix is provided as input for aggregating the node embedding matrix of each specific relationship type using a Graph Convolutional Network(GCN)to obtain the final node embedding matrix.This strategy allows capturing of rich structural and attributes information in multi-relational networks.Experiments were conducted on different datasets with baselines,and the results show that the proposed algorithm obtains significant performance improvement in community discovery,node clustering,and similarity search tasks,and compared to the baseline with the best performance,the proposed algorithm achieves an average improvement of 3.1%on Macro-F1 and 4.7%on Micro-F1,which proves the effectiveness of the proposed algorithm.

关键词： Network representation learning multi-relationship node encoder attribute information

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Multi-Agent Deep Reinforcement Learning for Efficient Computation Offloading in Mobile Edge Computing

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Computers, Materials & Continua 2023年第9期76卷 3585-3603页

作者： Tianzhe Jiao Xiaoyue Feng Chaopeng Guo dongqi wang Jie Song Department of Software Engineering Software CollegeNortheastern UniversityShenyang110819China

Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtual reality,mobile devices,and smart cities.In general,these IoT applications always bring higher energy consumption than traditional applications,which are usually energy-constrained.To provide persistent energy,many references have studied the offloading problem to save energy consumption.However,the dynamic environment dramatically increases the optimization difficulty of the offloading decision.In this paper,we aim to minimize the energy consumption of the entireMECsystemunder the latency constraint by fully considering the dynamic environment.UnderMarkov games,we propose amulti-agent deep reinforcement learning approach based on the bi-level actorcritic learning structure to jointly optimize the offloading decision and resource allocation,which can solve the combinatorial optimization problem using an asymmetric method and compute the Stackelberg equilibrium as a better convergence point than Nash equilibrium in terms of Pareto superiority.Our method can better adapt to a dynamic environment during the data transmission than the single-agent strategy and can effectively tackle the coordination problem in the multi-agent environment.The simulation results show that the proposed method could decrease the total computational overhead by 17.8%compared to the actor-critic-based method and reduce the total computational overhead by 31.3%,36.5%,and 44.7%compared with randomoffloading,all local execution,and all offloading execution,respectively.

关键词： Computation offloading multi-agent deep reinforcement learning mobile-edge computing latency energy efficiency

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Design and experiment of a novel pneumatic soft arm based on a deployable origami exoskeleton

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Frontiers of Mechanical Engineering 2023年第4期18卷 119-130页

作者： Yuwang LIU Wenping SHI Peng CHEN Yi YU Dongyang ZHANG dongqi wang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Mechanical Engineering Northeastern UniversityShenyang 110000China University of Chinese Academy of Sciences Beijing 100049China

Soft arms have shown great application potential because of their flexibility and compliance in unstructured environments.However,soft arms made from soft materials exhibit limited cargo-loading capacity,which restricts their ability to manipulate objects.In this research,a novel soft arm was developed by coupling a rigid origami exoskeleton with soft airbags.The joint module of the soft arm was composed of a deployable origami exoskeleton and three soft airbags.The motion and load performance of the soft arm of the eight-joint module was tested.The developed soft arm withstood at least 5 kg of load during extension,contraction,and bending motions;exhibited bistable characteristics in both fully contracted and fully extended states;and achieved a bending angle of more than 240°and a contraction ratio of more than 300%.In addition,the high extension,contraction,bending,and torsional stiffnesses of the soft arm were experimentally demonstrated.A kinematic-based trajectory planning of the soft arm was performed to evaluate its error in repetitive motion.This work will provide new design ideas and methods for flexible manipulation applications of soft arms.

关键词： pneumatic soft arm soft airbag deployable origami exoskeleton bistable characteristics cargoloading capacity

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Influence of anions on the adsorption of uranyl on hydroxylated α-SiO_2(001):A first-principles study

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Green Energy & Environment 2017年第1期2卷 30-41页

作者： Hui wang Zhifang Chai dongqi wang CAS Key Laboratory of Nuclear Radiation and Nuclear Energy Techniques and Multidisciplinary Initiative Center Institute of High Energy Physics Chinese Academy of Sciences CAS Key Laboratory of Nanosystem and Hierarchical Fabrication National Center for Nanoscience and Technology School of Radiation Medicine and Interdisciplinary Sciences (RAD-X) Soochow University

The adsorption of uranyl on hydroxylated α-SiO_2(001) in the presence of a series of anionic ligands, i.e. OH^-, CO_3^(2-), NO_3^-, H_2PO_4^-, HPO_4^(2-),CH_3COO^-(Ac^-), C_6H_5COO^-(PhCO_2^-), C_6H_5O^-(PhO^-), was studied by the periodic density functional theory(DFT) implemented in the Vienna ab initio simulation package(VASP). For the ligands other than OH^-and PhO^-, only the bidentate coordination modes to the uranyl were considered. The excess charge effect of a charged system was first evaluated by constructing models with net charge as is or neutralized by creating defect at the bottom of silica, and the results show that a neutralized model, even with defects, is more realistic than the charged ones.All uranyl species prefer to bind with the deprotonated site(—O^-) rather than the protonated one(—O_H), which suggests that the increase of pH,which leads to the deprotonation of the surface, may enhance the uranyl adsorption. On the other hand, the anionic ligands, which are formed at higher pH, have negative effects. The weaker acidic ligands, such as H_2CO_3, H_3PO_4 and H_2O, whose speciation in solutions is sensitive to the fluctuation of pH, have more complex effect on the uranyl adsorption than strong acids or bases. Humic substances may coordinate with uranyl through carboxyl and phenolic groups, with the carboxyl group bound stronger. The ternary complexes with one bidentate(or monodentate)anion and one(or two) H20 as ligands, which leads to the uranyl penta-coordinated in its equatorial plane, are more favorable than other configurations when bound to the same anionic ligand. Both the charged nature and the coordination behavior of an anionic ligand are relevant to its ability to influence the adsorption of uranyl on the mineral surface. In addition, the uranyl species adsorbed at the surface functionalized by anionic ligands were also addressed, and the functionalized surfaces have weaker interaction with hydrated uranyl dication.

关键词： Density functional theory Adsorption α-SiO2（001） Uranyl Anionic ligands

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Discussion on the Reform of Secure Coding

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计算机教育 2022年第12期 43-48页

作者： Yi Ma Dongming Chen dongqi wang software college Northeastern UniversityShenyang110006China

Secure Coding is an indispensable part of the undergraduate training program for Information Security Major.As a basic course for undergraduates to carry out project engineering,its importance is self-evident.In the actual teaching activities,the program design courses have to be solved in terms of content update,practical ability improvement and scientific research project,so the curriculum reform is imperative.This paper analyses the main problems existing in the Secure Coding course,explores the solution,proposes teaching methods,and gives the evaluation method.The practice shows that the reform exploration can obtain good teaching results.

关键词： Secure coding Case-based teaching method Modern teaching methods Evaluation methods

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Metal release/accumulation during the decomposition of Potamogeton crispus in a shallow macrophytic lake

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Journal of Environmental Sciences 2016年第4期28卷 71-78页

作者： Huanguang Deng Ju Zhang Shiyue Chen Liwei Yang dongqi wang Shiyong Yu School of Environment and Planning Liaocheng University School of Geographical Sciences East China Normal University Institute for Cultural Heritage Shandong University

Changes in metal concentrations in the litter of Potamogeton crispus were monitored during a consecutive 40-day in situ decomposition experiment using the litterbag method.The accumulation index was calculated and used to indicate the changes in the metals in litter.The results showed that the concentrations of Al,Cd,Cr,Fe,Mn,and Pb in litter increased significantly during the decomposition,while Cu and Zn concentrations decreased dramatically.Significant positive correlations were found between the concentrations of Al,Cr,Fe,and Mn and between Cu and Zn.Moreover,Cu and Zn both negatively correlated with Al and Fe.The remaining dry mass was negatively correlated with Al and Fe concentrations but positively correlated with Cu and Zn concentrations.Generally the accumulation index values of metals other than Al were less than one,indicating that the litter of P.crispus acted as a source of metals to the surrounding water body.Al was the only metal that showed continuous net accumulation in litter.The net accumulation of Fe and Mn in litter during the last 10 days of the experiment may indicate the precipitation of Feand Mn-oxides.It was estimated that 160 g/m^2（dry weight）P.crispus was decomposed in40 days.This was equivalent to releasing the following amounts of metals：0.01 mg Cd,0.03 mg Cr,0.71 mg Cu,0.55 mg Mn,0.02 mg Pb and 13.8 mg Zn into surrounding water,and accumulating 149 mg Al and 11 mg Fe,in a 1 m^2 area.

关键词： Litter decomposition Metal release/accumulation Metal stocks Accumulation index Potamogeton crispus Lake Dongping

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硼、硼氮及硼磷纳米材料研究进展

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化工新型材料 2024年第S1期52卷 109-116页

作者：吕超张超王东琪安徽理工大学材料科学与工程学院淮南232001 大连理工大学化学学院大连116024

硼纳米材料有硬度和熔点高、密度低的特点,在高温器件、轻质增强填料等领域应用广泛。种类繁多的硼纳米材料可以成为与其他现有纳米材料、分子、原子或离子结合的基底材料,以设计和创造具有特定功能和特性的新材料。首先介绍了硼纳米材... 详细信息

硼纳米材料有硬度和熔点高、密度低的特点,在高温器件、轻质增强填料等领域应用广泛。种类繁多的硼纳米材料可以成为与其他现有纳米材料、分子、原子或离子结合的基底材料,以设计和创造具有特定功能和特性的新材料。首先介绍了硼纳米材料的研究进展,包括硼团簇、硼纳米线、硼纳米管、硼纳米带和硼纳米片;其次,以硼氮和硼磷材料为例,综述了两种二元含硼纳米材料的研究进展;最后,展望了硼、硼氮及硼磷纳米材料的未来研究方向,为该领域的研究提供启发。

关键词：硼纳米材料氮化硼磷化硼 0维硼材料量子点

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Design and experimental study of a passive power-source-free stiffness-self-adjustable mechanism

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Frontiers of Mechanical Engineering 2021年第1期16卷 32-45页

作者： Yuwang LIU dongqi wang Shangkui YANG Jinguo LIU Guangbo HAO State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Engineering-Electrical and Electronic Engineering University College CorkCorkIreland

Passive variable stiffness joints have unique advantages over active variable stiffness joints and are currently eliciting increased attention.Existing passive variable stiffness joints rely mainly on sensors and special control algorithms,resulting in a bandwidth-limited response speed of the joint.We propose a new passive power-source-free stiffness-self-adjustable mechanism that can be used as the elbow joint of a robot arm.The new mechanism does not require special stiffness regulating motors or sensors and can realize large-range self-adaptive adjustment of stiffness in a purely mechanical manner.The variable stiffness mechanism can automatically adjust joint stiffness in accordance with the magnitude of the payload,and this adjustment is a successful imitation of the stiffness adjustment characteristics of the human elbow.The response speed is high because sensors and control algorithms are not needed.The variable stiffness principle is explained,and the design of the variable stiffness mechanism is analyzed.A prototype is fabricated,and the associated hardware is set up to validate the analytical stiffness model and design experimentally.

关键词： variable stiffness mechanism stiffness self-regulation bionic robot modeling

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机器学习方法预测含硼材料能隙

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化学学报 2024年第4期82卷 387-395页

作者：李珺卿宋千禧刘子义王东琪大连理工大学精细化工国家重点实验室辽宁省碳资源催化转化重点实验室化学学院化工学院大连116024

近年来,含硼材料在新能源、催化等领域日益受到重视,然而,对于高附加值的含硼材料发展还存在很高的技术壁垒.因此,亟需深入研究含硼材料微观性质间的关联关系,推动高端含硼材料的研发.本工作面向材料研究从传统的试错法向数据驱动的研... 详细信息

近年来,含硼材料在新能源、催化等领域日益受到重视,然而,对于高附加值的含硼材料发展还存在很高的技术壁垒.因此,亟需深入研究含硼材料微观性质间的关联关系,推动高端含硼材料的研发.本工作面向材料研究从传统的试错法向数据驱动的研究范式转变的需求,通过特征选择、网格搜索优化以及特征重要性分析,探索了多种重要的机器学习算法在含硼材料能隙预测中的应用.结果表明,采用随机森林算法的能隙预测模型决定系数(R^(2))可达0.84,并发现含硼材料的总磁化强度(total magnetization)特征与能隙存在显著的负相关关系,即材料的总磁化强度越小,其能隙越大.本工作表明机器学习方法可用于定向设计具有特定能隙的含硼材料.同时,结果也表明,作为一种集成学习模型,随机森林具有较好的学习能力与稳定的预测性能,可以应用到其它类型材料体系的能隙以及其它材料属性的预测,加速材料性能的设计与优化过程,对新型功能材料的快速筛选与高性能预测具有重要的科学意义.

关键词：含硼材料能隙总磁化强度机器学习

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