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Brain‐X 2023年第3期1卷

作者： Weiping Wang Haiyan Zhao Chang He Yuanbo Cui Zhen Wang Alexander Hramov Ping Luan Xiong Luo Jipeng Ouyang Kurths Jürgen School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan Guangdong China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Contribution: Writing - review & editing Department of Neurology Peking University Third Hospital Beijing China Contribution: Resources Zhen Wang The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi 710072 China. Contribution: Writing - original draft The 6th Research Institute of China Electronics Corporation Beijing China The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi China Chang He School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 China. Contribution: Investigation Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Saratov State Medical University Saratov Russia Contribution: Data curation Guangdong Second Provincial General Hospital & Health Science Center Shenzhen Guangdong China Department of Neurology Shunde Hospital Southern Medical University Foshan Guangdong China Institute of Physics Humboldt-University Berlin Germany Potsdam Institute for Climate Impact Research Potsdam Germany

Currently, no specific treatments are available for Alzheimer's disease (AD). Mild cognitive impairment (MCI), the preclinical stage of AD, has a high possibility of reversing symptoms through neural regulation. A state dynamics model for single brain regions was developed to simulate blood oxygen level-dependent signals in a patient with early mild cognitive impairment. Subsequently, the analysis of functional connections was used to comprehensively consider multiple complex network centralities to locate the intervention targets, and a multiple brain region collaborative control scheme was designed. Finally, the reliability and effectiveness of the intervention were verified at the brain region and subnetwork levels. This technique provides a basis for future clinical diagnosis and treatment of AD and MCI.

关键词： adaptive pinning control Alzheimer's disease BOLD signals computational modeling Sub_network

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Steel Surface Defects Recognition Based on Multi-label Classifier with Hyper-sphere Support Vector Machine 29

Steel Surface Defects Recognition Based on Multi-label Class...

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第29届中国控制与决策会议

作者： Maoxiang Chu Jie Zhao Rongfen Gong Liming Liu State Key Laboratory of Robotics and System (HIT) School of Electronic and Information Engineering University of Science and Technology Liaoning

ISBN: (纸本)9781509046584

Aiming at steel surface defects recognition, this paper proposed a multi-label classifier with hyper-sphere support vector machine(HSVM-MC). Firstly, in order to describe steel surface defects well, a new set of edge distance statistical features are proposed. Then, based on twin-hypersphere support vector machine(THSVM), HSVM-MC is built by introducing binary relevance(BR) idea. This novel classifier has merits of THSVM and BR. Moreover, it can make up the shortcomings of BR method. Experimental resuslts show that the novel multi-label classificatin method has superior accuracy and efficiency for steel surface defects recognition.

关键词： Steel Surface Defect Recognition HSVM-MC Edge Distance

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Shape-Memory Polymers: Mechanically Robust and UV-Curable Shape-Memory Polymers for Digital Light Processing Based 4D Printing (Adv. Mater. 27/2021)

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Advanced Materials 2021年第27期33卷

作者： Biao Zhang Honggeng Li Jianxiang Cheng Haitao Ye Amir Hosein Sakhaei Chao Yuan Ping Rao Yuan-Fang Zhang Zhe Chen Rong Wang Xiangnan He Ji Liu Rui Xiao Shaoxing Qu Qi Ge Frontiers Science Center for Flexible Electronics (FSCFE) Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials and Engineering (IBME) Northwestern Polytechnical University 127 West Youyi Road Xi'an 710072 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen 518055 China School of Engineering and Digital Arts University of Kent Canterbury Kent CT2 7NT UK State Key Laboratory for Strength and Vibration of Mechanical Structures Department of Engineering Mechanics Xi'an Jiaotong University Xi'an 710049 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen 518055 China Digital Manufacturing and Design Centre Singapore University of Technology and Design Singapore 487372 Singapore State Key Laboratory of Fluid Power and Mechatronic System Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Department of Engineering Mechanics Zhejiang University Hangzhou 310027 China

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Plantbot: A New ROS-based Robot Platform for Fast Building and Developing

Plantbot: A New ROS-based Robot Platform for Fast Building a...

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IEEE International Conference on mechatronics and Automation

作者： Liulong Ma Yanjie Liu Yibo Gao Chuanming Zhu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang China School of Mechanical Engineering Tongji University Shanghai China

In recent years, the Robot Operating system (ROS) is developing rapidly and has been widely used in robotics research because of its flexible, open source, and easy-to-expand advantages. In scientific research, the corresponding hardware platform is indispensable for the experiment. In the field of mobile robots, PR2, Turtlebot2, and Fetch are commonly used as research platforms. Although these platforms are fully functional and widely used, they are expensive and bulky. What's more, these robots are not easily redesigned and expanded according to requirements. To overcome these limitations, we propose Plantbot, an easy-building, low-cost robot platform that can be redesigned and expanded according to requirements. It can be applied to not only fast algorithm verification, but also simple factory inspection and ROS teaching. This article describes this robot platform from several aspects such as hardware design, kinematics, and control methods. At last two experiments, SLAM and Navigation, on the robot platform are performed. The source code of this platform is available: https://***/marooncn/plantbot.

关键词： Mobile robots Wheels Hardware Simultaneous localization and mapping

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Sparse Kernel Regression with Coefficient-based `q−regularization

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Journal of Machine Learning Research 2019年 20卷

作者： Shi, Lei Huang, Xiaolin Feng, Yunlong Suykens, Johan A.K. Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai China Institute of Image Processing and Pattern Recognition Institute of Medical Robotics Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai China Department of Mathematics and Statistics State University of New York at Albany New York United States Department of Electrical Engineering ESAT-STADIUS KU Leuven Kasteelpark Arenberg 10 LeuvenB-3001 Belgium

In this paper, we consider the `q−regularized kernel regression with 0 q−penalty term over a linear span of features generated by a kernel function. We study the asymptotic behavior of the algorithm under the framework of learning theory. The contribution of this paper is two-fold. First, we derive a tight bound on the `2−empirical covering numbers of the related function space involved in the error analysis. Based on this result, we obtain the convergence rates for the `1−regularized kernel regression which is the best so far. Second, for the case 0 ©c 2019 Lei Shi, Xiaolin Huang, Yunlong Feng, and Johan A.K. Suykens.

关键词： Regression analysis

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Design and Experiments of a Compliant Adaptive Grasper Based on Fish Fin Structure

Design and Experiments of a Compliant Adaptive Grasper Based...

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IEEE International Conference on robotics and Biomimetics

作者： Wenfu Xu Heng Zhang Ningjing Zheng Han Yuan State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9781728103785;9781728103778

Most existing graspers are composed of rigid structures and usually have poor adaptability in capturing objects with irregular shapes. To solve this problem, a compliant two-finger grasper based on bionic fins is proposed, which has extremely simple control but very strong adaptability. In this paper, structure design is firstly detailed, and then contact forces and structure deformations are analyzed by finite element method. Moreover, preliminary tests are made to validate the design. Pressure sensors are used to obtain the capture forces during the whole capturing process. Results show that the proposed compliant grasper could achieve reliable capture for different objects with various shapes and sizes.

关键词： Grasping Strain Force Pressure sensors Resistance Thumb

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Joint learning of discriminative low-dimensional image representations based on dictionary learning and two-layer orthogonal projections

arXiv

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arXiv 2019年

作者： Wei, Xian Shen, Hao Li, Yuanxiang Tang, Xuan Jin, Bo Zhao, Lijun Murphey, Yi Lu Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences China Technical University of Munich Germany and fortiss GmbH Munich Germany Shanghai Key Lab for Trustworthy Computing School of Computer Science and Software Engineering East China Normal University China School of Aeronautics & Astronautics Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China Department of Electrical and Computer Engineering University of Michigan-Dearborn DearbornMI48128 United States

This work investigates the problem of efficiently learning discriminative low-dimensional representations of multi-class large-scale image objects. We propose a generic deep learning approach by taking advantages of Convolutional Neural Networks (CNN), sparse dictionary learning, and orthogonal projections. CNN is not only powerful on feature extraction, but also robust to spatial variance and changes. Sparse dictionary learning is well known for disentangling nonlinear underlying discriminative factors in data. The orthogonal projection is a notable efficient tool to project multi-class data onto low dimensional discriminative subspace. The proposed procedure can be summarized as follows. At first, a CNN is employed to extract high-dimensional (HD) preliminary convolutional features. Secondly, to avoid the high computational cost of direct sparse coding on HD CNN features, we present to learn sparse representation (SR) in an orthogonal projected space over a task-driven sparsifying dictionary. We then exploit the discriminative projection on SR. The whole learning process is treated as a joint optimization problem of trace quotient maximization, which involves the CNN parameters, the orthogonal projection on CNN features, the dictionary and the discriminative projection on sparse codes. The related cost function is well defined on product manifold of the Stiefel manifold, the Oblique manifold, and the Grassmann manifold. It is optimized via a geometrical stochastic gradient descent algorithm. Finally, the quality of dictionary and projections learned by the proposed approach is further investigated in terms of image classification. The experimental results show that the approach can achieve a strongly competitive performance with state-of-the-art image classification methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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Type Synthesis of Fully-Decoupled 3R2T Parallel Mechanisms Based on Driven-Chain Principle

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Journal of Donghua University(English Edition) 2017年第3期34卷 415-423页

作者：周辉陈海秦友蕾葛姝翌曹毅 School of Mechanical Engineering Jiangnan University Wuxi 214122 China Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Wuxi 214122 China State Key Laboratory of Robotics and System Harbin 150080 China State Key Laboratory of Mechanical System and Vibration Shanghai 200240 China

To avoid the existence of nonlinear and strong coupling in parallel mechanisms,it is necessary to address special care to the type synthesis of mechanisms,especially for the type synthesis of fully-decoupled parallel mechanisms. Based on the screw theory and the driven-chain principle,a methodology of structural synthesis for fully-decoupled three-rotational( 3R) and two-translational( 2T)parallel mechanisms was proposed by analyzing the characteristics of the input-output relations for fully-decoupled parallel ***,according to the desired kinematic characteristics of fullydecoupled parallel mechanisms,a method was presented by virtue of screw theory to synthesize the desired forms for both the direct and the inverse Jacobian matrices. Secondly,according to the feature of the direct and the inverse Jacobian matrices,the effective screws,the actuated screws and the mobile un-actuated screws of each leg were established based on the reciprocal screw theory and all possible topology structures fulfilling the requirements were ***,the desired fully-decoupled parallel mechanisms could be synthesized by using the structural synthesis rule and structural synthesis of fully-decoupled 3R2 T parallel mechanisms could be obtained exploiting the abovementioned methodology. Furthermore,the Jacobian matrix of a synthesized 3R2 T parallel mechanism was deduced to demonstrate the decoupling feature of the parallel mechanism,which also validated the correctness of the methodology of the type synthesis for fully-decoupled 3R2 T parallel mechanisms.

关键词： desired kinematic decoupling inverse translational matrices topology Jacobian reciprocal rotation

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Visual Grasping for a Lightweight Aerial Manipulator Based on NSGA-II and Kinematic Compensation

Visual Grasping for a Lightweight Aerial Manipulator Based o...

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IEEE International Conference on robotics and Automation

作者： Linxu Fang Haoyao Chen Yunjiang Lou Yanjie Li Yunhui Liu School of Mechanical Engineering and Automation State Key Laboratory of Robotics and System China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong P. R. China

The grasping control of an aerial manipulator in practical environments is challenging due to its complex kinematics/dynamics and motion constraints. This paper introduces a lightweight aerial manipulator, which is combined with an X8 coaxial octocopter and a 4-DoF manipulator. To address the grasping control problem, we develop an efficient scheme containing trajectory generation, visual trajectory tracking, and kinematic compensation. The NSGA-II method is utilized to implement the multiobjective optimization for trajectory planning. Motion constraints and collision avoidance are also considered in the optimization. A kinematic compensation-based visual trajectory tracking is introduced to address the coupled nature between manipulator and UAV body. No dynamic parameter calibration is needed. Finally, several experiments are performed to verify the stability and feasibility of the proposed approach.

关键词： Manipulator dynamics Trajectory Grasping Kinematics Acceleration Visualization

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system Identification in Adaptive Inverse Control for Electrohydraulic Shaking Table Using Variable Tap-length NLMS Algorithm

System Identification in Adaptive Inverse Control for Electr...

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2017 5th International Conference on Mechanical, Automotive and Materials engineering（CMAME 2017）

作者： Man Wang Dacheng Cong Zhidong Yang Changhong Gao State Key Laboratory of Robotics and System School of Mechatronics EngineeringHarbin Institute of Technology

Adaptive inverse control（AIC） is an advanced control technology which can efficiently learn and control the severely nonlinear and real-time plant,such as the electrohydraulic shaking table（EST）.The foundation of AIC is the system identification of the plant via an adaptive *** traditional adaptive filter theory is known as a fixed tap-length（length of the weight vector） FIR（Finite impulse response） filter whose weights change by adaptive algorithm *** mismatch between plant and the fixed taplength will cause inaccuracy or compute *** paper introduce a variable tap-length NLMS（VTLNLMS） algorithm to find the optimum tap-length（OPTL） of the model of multi-DOF EST,then use AIC to improve the accuracy of time wave *** dynamics response nonlinear model of the EST is built to reflect the experimental *** nonlinear EST model and referred algorithm are simulated in MATLAB/*** show the AIC with OPTL is effective in the EST.

关键词： Adapative Inverse Control Electrohydraulic Shaking Table Variable Tap-length Nl MS Nonliner system system Identification

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