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International Conference on Micro/Nano Sensors for AI, Healthcare, and robotics (NSENS)

作者： Hao Sun Zhikun Zhan Hongyu Zhang Junshan Liu Xiaopeng Sha Xiaodong Yu Jianing Yu Yuliang Zhao Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

Rail fasteners, a key component of a railway track, are used to connect the rail and the sub-rail foundation together with the required degree of elasticity. Severely loose or failed fasteners may lead to serious safety hazards for rail transportation. However, current strategies for determining fastener looseness are mainly implemented manually, which is labor-intensive, inefficient and less-than-objective. In this paper, we propose a system that uses a MEMS acceleration meter and a wireless data transmission technique to detect railway fasteners. Vibration was generated by hitting the rail with a hammer. Then the acceleration data was transmitted to the cloud by the Global System for Mobile Communications (GSM) technique. The fastener looseness was analyzed using power spectrum entropy and frequency domain analysis. Results from the field experiments show that our method can identify the fastener's loosening state accurately and automatically. This wireless, low-cost fastener inspection system is expected to provide an effective approach to improving the efficiency of regular railway maintenance..

关键词： Conferences Artificial intelligence Medical services Robot sensing systems IP networks

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Electrochemical Detection of Insulin Based on Screen Printed Electrode Modified by Nickel Hydroxide

Electrochemical Detection of Insulin Based on Screen Printed...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and robotics (NSENS)

作者： Hongyu Zhang Zhikun Zhan Yuliang Zhao Xiaopeng Sha Xiaodong Yu Hui Sun Lijia Gu Jiali Liu Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

This paper reports a novel electrochemical method for the detection of insulin in ultra-pure water. A screen printed electrode (SPE) modified by Nickel hydroxide was used as the working electrode, one with good activity of electro-catalytic oxidation-reduction for insulin. The SPE was modified by Nickel hydroxide using the electrodeposition method. The results showed that Nickel hydroxide was homogeneously electrodeposited on the surface of the working electrode. A coin-size electrolytic tank was fabricated with PDMS, which only requires 0.3ml of sample for the detection. The concentration of insulin was analyzed using the methods of Cyclic voltammetry (CV), Electrochemical impedance spectroscopy (EIS) and Chronoamperometry (i-t). The Nickel hydroxide used for detecting insulin showed good analytical characteristics, such as a high sensitivity of 14.797μA·μM -1 , a good linear detection range of 100nM-5μM, and a low detection limit of 93nM. This nickel hydroxide modified SPE electrode has a much smaller size and is easier to fabricate than traditional electrodes, making it a much more promising candidate for an insulin sensor.

关键词： Electrodes Insulin Nickel Oxidation Sensitivity Surface treatment Diabetes

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Parallel Learning:a Perspective and a Framework

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 389-395页

作者： Li Li Yilun Lin Nanning Zheng Fei-Yue Wang Department of Automation TNListTsinghua University IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Institute of Artificial Intelligence and Robotics(IAIR) Xi'an Jiaotong University Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

The development of machine learning in complex system is hindered by two problems *** first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven *** second problem is the lack of a general theory which can be used to analyze and implement a complex learning *** this paper,we proposed a general methods that can address both two *** combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by *** a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.

关键词： Descriptive learning machine learning parallel learning parallel systems predictive learning prescriptive learning

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Algorithms Analysis of Mobile Robot SLAM based on Kalman and Particle Filter 9th

Algorithms Analysis of Mobile Robot SLAM based on Kalman and...

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2017 9th International Conference on Modelling, Identification and control (ICMIC 2017)

作者： Feng Zhang Siqi Li Shuai Yuan Enze Sun Languang Zhao Information & Control Engineering Faculty Shenyang Jianzhu University State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509065769;9781509065752

Many algorithms of mobile robot SLAM(Simultaneous Localization and Mapping) have been researched at present,however,the SLAM algorithm of mobile robot based on probability is often used in the unknown *** this paper,two kinds of SLAM algorithms based on probability are analyzed and *** kind is the SLAM algorithm based on Kalman filter: extended Kalman filter SLAM(EKF-SLAM)and unscented Kalman filter SLAM algorithm(UKF-SLAM).Another kind is the SLAM algorithm based on Particle filter:Fast SLAM and unscented Fast SLAM(UFast SLAM) *** difference from the four algorithms of SLAM is illustrated in terms of principle and calculation ***,the simulation results show that the UFast SLAM algorithm is superior to other algorithms in robot path and landmark estimation.

关键词： mobile robot Simultaneous Localization and Mapping EKF-SLAM UKF-SLAM Fast SLAM UFast SLAM

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Robustness of Itô stochastic nonlinear networked control systems 13

Robustness of Itô stochastic nonlinear networked control sy...

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13th IEEE International Conference on control and Automation, ICCA 2017

作者： Wang, Tong Ma, Min Ji, Wenqiang Qiu, Jianbin Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150080 China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9781538626795

This paper investigates the robustness issue of stochastic nonlinear network control systems (NCSs) with network-induced delays and packet dropouts. Firstly, the controller for the nominal system (without network-induced delays and packet dropouts) is designed to guarantee its globally asymptotic stability. Then, by choosing parameters which satisfy associated conditions, the ultimately globally asymptotic stability (UGAS) of corresponding stochastic nonlinear NCS is guaranteed. Finally, a simulation example is given to demonstrate the effectiveness of the proposed stability conditions. © 2017 IEEE.

关键词： networked control systems

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An all-solid-state ion-selective electrode for dopamine determination

An all-solid-state ion-selective electrode for dopamine dete...

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IET Doctoral Forum on Biomedical Engineering, Healthcare, robotics and Artificial Intelligence 2018, BRAIN 2018

作者： Ma, Siyuan He, Cheng Wang, You Luo, Zhiyuan Li, Guang State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and Control Zhejiang University Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Computer Learning Research Centre Royal Holloway University of London Egham Hill Egham SurreyTW200EX United Kingdom

ISBN: (纸本)9781839530838

An all-solid-state ion-selective electrode (ISE) was developed for potentiometric detection of dopamine. A gold disk covered by poly(3, 4-ethylenedioxythiophene) doped with poly(styrenesulfonate) (PEDOT/PSS) was used as the work electrode, a polymeric membrane containing β-cyclodextrin as an ionophore and potassium tetrakis(4-chlorophenyl) borate as ionic additive was immobilized on the conduct polymer layer as the dopamine selective membrane. The ISE was sensitive to dopamine linearly from 3×10-5 to 10-1M with a slope of 56.60±1.28mV/decade. And the detection limit was 2.2×10-5M. It performed stably in a pH range of 6-8 and a temperature range of 35-41°C. The dynamic response, reproducibility and stability as well as the sensitivity were investigated. © 2018 Institution of Engineering and Technology. All rights reserved.

关键词： Ion selective electrodes

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Development of a Tetris Playing Robot controlled by KNR

Development of a Tetris Playing Robot Controlled by KNR

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IEEE International Conference on Mechatronics and Automation

作者： Ming Wang Yanlu Zhang Huifang Dong Xu Li Junzhi Yu Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system.

关键词： Mobile robots Cameras Robot sensing systems Image color analysis Servomotors Robot kinematics

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Target tracking based on neural network depth feature and texture fusion

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IOP Conference Series: Earth and Environmental Science 2020年第1期461卷

作者： Yongzhan Cao Meiju Liu Shanykui Yang Guodong Yang Peng Chen Shuyun Zhu Zhuang Ge Yuwang Liu Information and Control Engineering Faculty Shenyang Jianzhu University Shenyang Liaoning 110168 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China School of Mechanical Engineering and Automation Northeastern University 3 Wenhua Street Shenyang 110819 China

This paper presents a method of target tracking based on convolution neural network and texture feature fusion. The lower layer of the convolutional neural network can extract some spatial structure, shape and other features of the target. High-level level can extract relatively abstract semantic information. In this paper, vgg-m convolutional neural network is adopted to realize tracking by adaptive fusion of the extracted depth features of Conv2 and Conv5 with the texture features extracted by two-dimensional Gabor filtering. In this paper, the experimental analysis of this method is carried out on the OTB2013 data set, and the results show that this method can achieve more accurate positioning of the target and has a strong timeliness.

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Incremental Adaptive EEG Classification of Motor Imagery-based BCI

Incremental Adaptive EEG Classification of Motor Imagery-bas...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hai-Jun Rong Changjun Li Rong-Jing Bao Badong Chen State Key Laboratory for Strength and Vibration of Mechanical Structures Shaanxi Key Laboratory of Environment and Control for Flight Vehicle School of Aerospace Engineering Xi’an Jiaotong University China Institute of Artificial Intelligence and Robotics School of the Electronic and Information Engineering Xi’an Jiaotong University China

Generally, electroencephalogram (EEG) signals recorded from the brain computer interface (BCI) systems are very noisy and non-stationary, which may affect the online performance of classifiers established from the prior session heavily. In order to address such problems, the classifiers should also be capable of adapting the change of EEG automatically during the processing of evaluation. In this paper, we propose an incremental adaptive EEG classification scheme. In this scheme, an extended sequential adaptive fuzzy inference system (ESAFIS) is used to evolve its structure dynamically and adapts the classifier automatically online to address the non-stationarity of the EEG signals. ESAFIS is an evolving system, wherein the fuzzy rules are evolved based on the modified influence of the rule. This paper presents the classification of 2-class motor imagery EEG based on ESAFIS with adaptive strategy. Simulations are conducted based on two datasets: one is the BCI Competition IV dataset 2b and the other one is recorded from our own BCI experiments. Compared to other methods such as ELM and LDA, the simulation results demonstrate that the proposed scheme produces better classification results.

关键词： Electroencephalography Feature extraction Training Image segmentation Windows Adaptive systems Brain modeling

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Artificial Intelligence Course Design: ISTREAM-based Visual Cognitive Smart Vehicles

Artificial Intelligence Course Design: ISTREAM-based Visual ...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Gong, Xiaoyan Wu, Yilin Ye, Zifan Liu, Xiwei State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Intelligent Education Institute Qingdao Academy of Intelligent Industries Qingdao266071 China Beijing NO. 13 School Beijing100088 China NO.2 High School Beijing Normal University Beijing100088 China

ISBN: (纸本)9781538644522

New intelligent era calls for new learners and thus urgently needs a series of artificial intelligence. As a good educational platform for teaching artificial intelligence, smart cars have aroused concern and practices of all parties. However, at present, most courses and training pay more attention to basic knowledge and technology of smart cars, seldom to training based on artificial intelligence curriculum system and comprehensive competency integrating science, technology, art and management. Therefore, based on concept of iSTREAM (intelligence for Science, Technology, robotics, Engineering, Art, and Management) and Raspberry intelligent vehicle teaching platform, this paper introduced a smart car-themed artificial intelligence courses including basic courses, specialized courses, specialized technical courses and elective courses. This course can guide learners to develop smart cars based on visual cognition, in-depth learning, VR and 3D printing integrated artistic creativity. It combines disciplines such as science, technology, art, games and management to upgrade a single knowledge and technology course into a comprehensive competency course that integrates knowledge, skills, emotion and management. Practice in Beijing NO.13 and NO.101 High School shows that this course allows students to experience scientific research process, learn artificial intelligence related knowledge and skills, understand scientific way of thinking and scientific research methods, stimulate learners' responsibility and scientific passion, and cultivate leadership skills through self-learning and partly project management. © 2018 IEEE.

关键词： Project management

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