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International Symposium on Micromechatronics and Human Science (MHS)

作者： Jun Wu Jian Huang Yongji Wang Kexin Xing Qi Xu Key Laboratory of Image Processing and Intelligent Control Department of Control Science & Engineering Huazhong University of Science and Technology Wuhan China

Intensive task-oriented repetitive physical therapies need be provided by individualized interaction between the patients and the rehabilitation specialists to improve hand motor performance for those survived from stroke and traumatic brain injury. The goal of this research is to develop a novel wearable device for robotic assisted hand repetitive therapy. We designed a pneumatic muscle (PM) driven therapeutic device that is wearable and provides assistive forces required for grasping and finger extension. The robot has two distinct degrees of freedom at the thumb and all other fingers. The embedded sensors can feedback position and force information for robot control and quantitative evaluation of task performance. It is potential of providing supplemental at-home therapy in addition to in the clinic treatment. To realize the trajectory tracking control, a fuzzy PID controller is designed for the proposed device. The experimental results show angle tracking control of the robotic hand using the fuzzy PID controller has better performance than that using a conventional PID controller.

关键词： Fuzzy control Three-term control Rehabilitation robotics Muscles Medical treatment Robot sensing systems Fingers Force feedback Robot control Brain injuries

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G-Strong Chain Recurrent Point And G-Chain Equivalent Point of Topological G-Conjugacy On Metric G-Space

G-Strong Chain Recurrent Point And G-Chain Equivalent Point ...

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2019虚拟现实与智能系统国际会议

作者： Ji Zhan-jiang Tu Jing-xian School of Data Science and Software Engineering Wuzhou University Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University

ISBN: (纸本)9781728150505

In this paper,we study the dynamical properties of Gstrong chain recurrent point,G-chain point set and G-chain equivalent point of topological G-conjugacy on metric *** inference,we give the following conclusions that if let f:X→X and f:Y→Y be two continous map of metric G-space X and *** the map h:X→Y is a topogical G-conjugacy from f to f,then（1） h(SCR（f）)=SCR（f）;（2） h(S（x,f）)=S(h（x）,f);（3）h(CE（x,f）)=CE(h（x）,f).These results will enrich the theory of G-strong chain recurrent point,G-chain point and G-chain equivalent point of topological G-conjugacy on metric G-space

关键词： metric G-space topological G-conjugacy G-strong chain recurrent point G-chain point G-chain equivalent point

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Adaptive pinning cluster synchronization of fractional-order complex dynamical networks

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Applied Mathematics and Computation 2014年 231卷 347-356页

作者： Guan-Sheng Wang Jiang-Wen Xiao Yan-Wu Wang Jing-Wen Yi School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China

The problem about cluster synchronization of fractional-order CDNs is studied via a pinning adaptive approach in this paper. Based on the stability theory of fractional differential equations, some sufficient criteria for local and global cluster synchronization of fractional-order CDNs are derived. In this paper, the coupling configuration matrix can be asymmetric as well as reducible and the inner coupling matrix can also be asymmetric. Moreover, the number of pinning nodes in each cluster can be evaluated. Especially, when the coupling strength is large enough and the coupling configuration matrix is symmetric, cluster synchronization can be achieved via pinning a single node in each cluster. Finally, some typical examples are given to illustrate the correctness and effectiveness of our results, a surprising finding is that the synchronization performance will become better as the fractional order decreases in this simulation.

关键词： Complex dynamical networks Cluster synchronization Fractional-order Pinning adaptive control

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Comparison of noninvasive and remote temperature estimation employing magnetic nanoparticles in DC and AC applied fields

Comparison of noninvasive and remote temperature estimation ...

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IEEE Instrumentation and Measurement Technology Conference

作者： Yin Li Wenzhong Liu Jing Zhong Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

This paper examines the advantages and disadvantages of noninvasive and remote temperature estimation employing magnetic nanoparticles (MNPs) in DC and AC applied fields. A Langevin function that describes the magnetization of the MNPs in different applied magnetic fields is investigated to obtain a noninvasive and remote measurement of on-site temperature using MNPs. Several nonlinear functions, in which temperature and concentration are independent variances, are found by discretizing the Langevin function model of the magnetization of MNPs. Then, the temperature estimation range from 310 K to 350 K is transformed to the solution of the nonlinear function using the temperature independence of the saturation magnetization of the MNPs.

关键词： Temperature measurement Estimation Nanoparticles Mathematical model Saturation magnetization Magnetic resonance imaging Magnetization

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NEAT versus PSO for Evolving Autonomous Multi-agents Coordination on Pursuit-Evasion Problem

NEAT versus PSO for Evolving Autonomous Multi-agents Coordin...

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2011 3rd International Asia Conference on Informatics in control, Automation and Robotics(CAR 2011)

作者： Jin Zhao Gang Peng Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry

A method based on multi-agents and ANN(Artificial Neural Network)was proposed to solve the pursuit-evasion task in continuous timevarying *** to this method,several autonomous agents with 8 circular sector sensors and an ANN controller were used to form a coordinated behavior to capture the *** evolve the controller,NEAT(Neuro Evolution of Augmenting Topologies)and PSO(Particle Swarm Optimization)method were used to optimize the *** simulation experiments show that both methods can successfully evolve the controller to capture the evaders,while NEAT requires less swarm members and consume less time comparing to PSO method.

关键词： Pursuit Multi-agents,Artificial Neural Network(ANN),Neuro Evolution of Augmenting Topologies(NEAT),Particle Swarm Optimization(PSO)

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DISCOVERING DISTINCTIVE ACTION PARTS FOR ACTION RECOGNITION

DISCOVERING DISTINCTIVE ACTION PARTS FOR ACTION RECOGNITION

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IEEE International Conference on image processing

作者： Feifei Chen Nong Sang Changxin Gao Xiaoqin Kuang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology

ISBN: (纸本)9781479957521

Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. In this paper, we focus on discovering distinctive action parts for recognition of human actions by learning and selecting a small number of discriminative part detectors directly from training videos. We initially train a large collection of candidate Exemplar-LDA detectors from clusters obtained by clustering spatiotemporal patches in whitened space. A novel Coverage-Entropy curve is proposed as a means of measuring the representative and discriminative capabilities of part detectors, and used to select a set of compact and meaningful detectors out of the vast candidates. By integrating these mined detectors into "bag of parts" representation, our approach demonstrates state-of-the-art performance on the UCF50 dataset.

关键词： Action recognition Action part Exemplar LDA

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control of a rehabilitation robotic exoskeleton based on intentional reaching direction

Control of a rehabilitation robotic exoskeleton based on int...

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International Symposium on Micromechatronics and Human Science (MHS)

作者： Weiguang Huo Jian Huang Yongji Wang Jun Wu Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan China

An upper limb robotic exoskeleton of three degrees of freedom (DOF) is designed for the patients who survived stroke and the elderly who have not enough strength to move their limbs freely. Particular attention is paid to the realization of a intention-driven robotic control approach, by which the robotic exoskeleton can assist the user moving his/her arm freely to where he/she intends to go. A force sensing system made of multiple force sensing resisters (FSRs) is embedded in the robotic exoskeleton. A static force model of the upper limb in a relaxed state is obtained when the user wears the exoskeleton. A hybrid model is proposed to describe the behavior modes of human upper limb motion. Filtering technology is designed to infer the intended moving direction of upper limb based on the measured force information and the static force model. The motion intention of user's upper limb can be online estimated using the filter and a mode transition detector. Guided by the inferred intention, an admittance control strategy is assumed to control the motors of each DOF. The effectiveness of proposed robotic system and control approaches is evaluated by experiments.

关键词： Exoskeletons Joints Robot sensing systems

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Vehicle re-identification by fusing multiple deep neural networks

Vehicle re-identification by fusing multiple deep neural net...

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Workshops on image processing Theory, Tools and Applications, IPTA

作者： Chao Cui Nong Sang Changxin Gao Lei Zou Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Vehicle re-identification has become a fundamental task because of the growing explosion in the use of surveillance cameras in public security. The most widely used solution is based on license plate verification. But when facing the vehicle without a license, deck cars and other license plate information error or missing situation, vehicle searching is still a challenging problem. This paper proposed a vehicle re-identification method based on deep learning which exploit a two-branch Multi-DNN Fusion Siamese Neural Network (MFSNN) to fuses the classification outputs of color, model and pasted marks on the windshield and map them into a Euclidean space where distance can be directly used to measure the similarity of arbitrary two vehicles. In order to achieve this goal, we present a method of vehicle color identification based on Alex net, a method of vehicle model identification based on VGG net, a method of pasted marks detection and identification based on Faster R-CNN. We evaluate our MFSNN method on VehicleID dataset and in the experiment. Experiment results show that our method can achieve promising results.

关键词： image color analysis Feature extraction Neural networks Task analysis Licenses Automobiles Automotive components

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A CSP-based retraining framework for motor imagery based brain-computer interfaces

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Science China(Information Sciences) 2024年第8期67卷 349-350页

作者： Xue JIANG Lubin MENG Xinru CHEN Dongrui WU Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

Motor imagery(MI) is a classic paradigm of electroencephalogram(EEG)-based brain-computer interfaces(BCIs). It entails individuals mentally imagining the movement of a body part without physically performing it. EEG s... 详细信息

关键词： Classification (of information)

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Handling multi-objective in an HTN planner for emergency decision-making

Handling multi-objective in an HTN planner for emergency dec...

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IEEE Conference Anthology

作者： Minglei Li Hongwei Wang Chao Qi Dan Liu Jian Wang Zhe Wang Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science & Technology Wuhan China

There are many multi-objective planning problems in emergency decision-making domain. HTN planners were widely used in emergency decision-making, while they have limited ability to solve optimization, especially multi-objective optimization. Aimed to handling multi-objective in HTN planners, this paper proposes a novel method based on SHOP2, which is a domain-independent state-based forward HTN planner. The method uses a weighted vector to mirror the decision maker's performance for various objectives and an anytime search algorithm to improve the ability to find the best solution plan. Finally, a case of emergency evacuation is given to testify the effectiveness of the method.

关键词： Planning Decision making Floods Optimization Vectors Measurement Search problems

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