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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Ren, Liang Cao, Zhiqiang Tan, Min Zhao, Peng Chen, Xuechao University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China 21st Research Institute of China Electronics Technology Group Corporation Shanghai China BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China

ISBN: (纸本)9781728163215

The vision-based target recognition and tracking have received much attention in the field of robotics. Existing methods mainly focus on the vision perception of individual robot with a single view, however, the performance is susceptible to illumination and occlusion. Multi-robot collaborative perception provides a potential solution to deal with the limitation of single-view observation, however, the challenging of environmental adaptability for multi-robot collaborative decision still remains unsolved. To solve this problem, this paper proposes a two-level adaptive target recognition and tracking method based on vision for multi-robot system. The problem of multi-robot target recognition and tracking is solved under a two-level framework, which contains the features fusion level of individual robot and the cooperation level of multi-robot system. In the first level, the features measuring results that influence the visual perception of individual robot are fused, while the second level combines the voting of each robot together to determine the target for multi-robot system. Both the features measuring weights and robots voting weights are adaptively updated according to their evaluation, which lead to a beneficial result where the features and robots with higher accuracy play major roles in the first and second levels, respectively. Therefore, a good adaptability to the environments can be guaranteed. The experimental results show that the proposed approach can realize the coordination of multi-robot system in target recognition and tracking with an effective performance. © 2019 IEEE.

关键词： Multipurpose robots

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MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divide-and-conquer Deformation

MatchMesh: Knowledge-based 3D Point Cloud Meshing Using Divi...

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IEEE International Conference on Networking, Sensing and control

作者： Ying Tang Shengtao Sun Ben Wu Rowan University Glassboro USA State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Rowan University Glassboro NJ USA

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

The reconstruction of surface mesh from point cloud is compute-intensive but also very important step in the remanufacturing and personalization industries. With more 3D scanners providing lower cost and higher resolution, further detailed point clouds can be gathered without so much effort as before. In manufacturing, there are databases which contain the origin 3D design models of the products. How to utilize the design model data for swift production of related products remains a problem for remanufacturing and customization. In order to develop a knowledge-based way of handling this problem, editing or deforming an existing mesh to match the target is an effective way of easing the workload. In this paper, we introduce a divide-and -conquer process which segments the depth scan data and then find the best match in the database as its source of deformation. The segmentation is performed on 3D point level using global features extracted by 3D CNN. After that we find best match to our knowledge with the same features to acquire a fast meshing of the target object by deforming the existing parts from the match. The deformation of parts are being done sequentially. For further performance improvement, we present a deformation training method employing transfer learning on segment editing process.

关键词： Training Surface reconstruction Three-dimensional displays Databases Knowledge based systems Feature extraction Strain

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key technologies of GNSS/INS/VO deep integration for UGV navigation in urban canyon 11

Key technologies of GNSS/INS/VO deep integration for UGV nav...

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2017 11th Asian control Conference, ASCC 2017

作者： Meiling, Wang Yafeng, Li Guoqiang, Feng Yi, Yang Tong, Liu Xiao, Xuan School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509015733

As a new emerging integrated navigation technology, the GNSS/INS/VO deep integration system can fully leverage the synergistic and complementary characteristics of the three involved subsystems to achieve cost reduction while improving navigation accuracy, availability, and robustness, by mutual aiding between subsystems. In this paper, firstly, based on a brief review of the technical background and research status of the GNSS/INS/VO deep integration technology, the processing flows of this deep integration mode in both signal and information domains are analyzed, and its performance advantages are summarized. Then, the top-level technology roadmap of the GNSS/INS/VO deep integration for UGV navigation in the urban canyon is presented, and several key technical issues from scheme demonstration to engineering implementation are explored. At last, the short and medium term development prospects of the GNSS/INS/VO deep integration are envisaged. The proposed research ideas and system design concept for GNSS/INS/VO deep integration could be used as a reference for relevant technicians in navigation field. © 2017 IEEE.

关键词： Navigation

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Behavioral Management for Employees based on Blockchain and Smart Contracts

Behavioral Management for Employees based on Blockchain and ...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Ni, Xiaochun Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

With the continuing innovation of information and network technologies, on the one hand, social media has gradually become a necessary tool for internal communication within the organization, resulting in great changes in the behavioral patterns of employees;on the other hand, emerging technologies such as blockchain and smart contracts have enlightened many outstanding issues in organizational management, such as opaque data, tamable information and incomplete execution. Responding to the impact of new media on organizational management model, combined with the emerging technologies - blockchain and smart contracts, this paper aims to explore the behavioral management model of employees for trusted data within virtual cyberspace. It is devoted to the description modeling of employees' behavior and the guidance of employees' behavior based on smart contracts. We also validate our proposed method in a real-world scenario, and the experimental results prove our analysis, as well as the effectiveness of our approach. This paper is a basic research in the new application field, and is expected to offer helpful guidance and reference for future research efforts and industrial applications. © 2019 IEEE.

关键词： Smart contract

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Exploring Optimal Revenue Models for DSPs in Real Time Bidding Advertising

Exploring Optimal Revenue Models for DSPs in Real Time Biddi...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

In RTB advertising, the AdExchange platform (AdX) can be regarded as a bridge connecting the supply side and demand side of advertising, and advertisers buy the ad impressions through the Demand-Side Platforms (DSPs). As such, there is a two-stage auction process for each ad impression, and the first stage is organized by the DSPs, while the second stage is organized by the AdX. In the two-stage auction process, two possible revenue models are available for DSPs, namely commission model and two-stage resale model. In this paper, we first compare the revenues of DSPs under the two models, and then explore the optimal revenue model for a DSP under the condition that the revenue model of other DSPs are given. We also unitize the computational experiments approach to evaluate our proposed method, and our results can help DSPs find their optimal revenue model in RTB advertising. © 2019 IEEE.

关键词： Marketing

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Event-based model predictive control of discrete-time non-linear systems with external disturbances

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IET control Theory & Applications 2019年第1期13卷 27-35页

作者： Mengzhi Wang Jian Sun Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 People's Republic of China

The event-based model predictive control (MPC) problem for discrete-time non-linear control systems with external disturbances is studied. Two triggering conditions are designed based on whether the system state is within the terminal region or not. The first one is triggered outside the terminal region when the difference between the actual system state trajectory and the corresponding optimal state trajectory violates a relative threshold, while the second one is triggered inside the terminal region if the difference between the actual system state trajectory and the predicted nominal state trajectory violates a desired relative threshold. The feasibility analysis and stability analysis are given in detail. Sufficient conditions for feasibility relating to the triggering threshold and disturbance bound are obtained. Sufficient conditions for stability of the event-based control system referring to system parameters, triggering threshold and disturbance bound are given. Besides, the upper bound of the state trajectory is obtained and a robust invariant set that the system state will enter in finite time is given. Finally, simulation examples are given to validate the effectiveness of the proposed method.

关键词： nonlinear control systems robust control stability predictive control control system analysis control system synthesis discrete time systems linear systems discrete-time nonlinear systems external disturbances event-based model predictive control problem discrete-time nonlinear control systems triggering conditions terminal region actual system state trajectory corresponding optimal state trajectory predicted nominal state trajectory desired relative threshold sufficient conditions triggering threshold disturbance event-based control system system parameters

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A Blockchain-based Framework for Central Bank Digital Currency

A Blockchain-based Framework for Central Bank Digital Curren...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Han, Xuan Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

Cryptocurrency and blockchain technologies have developed in parallel in recent years, with technological breakthroughs in currency issuance, payment methods, and currency storage. However, the existing cryptocurrencies cannot replace fiat money. There is a huge gap between decentralized cryptocurrency and central bank digital currency, namely CBDC, in terms of monetary governance and circulation. In this paper, we propose the function and security requirements of CBDC, through a comprehensive analysis of the existing typical cryptocurrency and the prototype of the CBDC scheme. On this basis, we present a blockchain-based framework for CBDC with three layers, including supervisory layer, network layer and user layer, and describe the key business processes of the CBDC's entire lifecycle of issuance-circulation-withdrawal in detail. Finally, we take cross-border payment as an example to explain the transaction process of CBDC. We aim to provide theoretical guidance for CBDC design. © 2019 IEEE.

关键词： Blockchain

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Research on High Precision control of Joint Position Servo System for Hydraulic Quadruped Robot

Research on High Precision Control of Joint Position Servo S...

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第三十八届中国控制会议

作者： CHEN Zhihua WANG Shoukun XU Kang WANG Junzheng ZHAO Jiangbo NIU Shanshuai Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology

Electro-hydraulic servo valve-controlled cylinder(EHSVCC) is a highly integrated and high-performance electrohydraulic servo driving unit(EHSDU), which is the basic driving unit of the leg joint for hydraulic quadruped robot. The robot impedance control mostly adopts control methods based on position inner loop and impedance outer loop, the high precision control of position inner loop is the key to improve impedance control. Therefore, it is of great significance to study a high precision position control method. Firstly, the electro-hydraulic servo drive unit of the foot robot is taken as the research object. The model of the nonlinear system is established, and the feedback linearization of the system is carried out. Secondly, in order to improve the tracking performance and anti-jamming ability of the position inner loop input/output a sliding mode variable structure robust controller(SMVSRC) with switching function, variable structure control rate and improved boundary layer function is designed. Finally, the electro-hydraulic servo drive unit(EHSDU) and the hydraulic foot robot test platform are tested, the influence of the two control algorithms on the position response and tracking error for EHSDU is analyzed and compared under the control of sinusoidal signals with different amplitudes and frequencies and diagonal gait signals. The experimental results show that the improved SMVSRC algorithm is feasible and effective, which provides a theoretical basis for the later study of impedance control based on position inner loop.

关键词： Hydraulic quadruped robot Position control Feedback linearization Sliding mode controller

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Mobile Energy Transfer in Internet of Things

arXiv

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arXiv 2020年

作者： Zhang, Qingqing Wang, Gang Giannakis, Georgios B. Liu, Qingwen Chen, Jie College of Electronic and Information Engineering Tongji University Shanghai201800 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN 55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200092 China

—Internet of things (IoT) is powering up smart cities by connecting all kinds of electronic devices. The power supply problem of IoT devices constitutes a major challenge in current IoT development, due to the poor battery endurance as well as the troublesome cable deployment. The wireless power transfer (WPT) technology has recently emerged as a promising solution. Yet, existing WPT advances cannot support free and mobile charging like Wi-Fi communications. To this end, the concept of mobile energy transfer (MET) is proposed, which relies critically on an resonant beam charging (RBC) technology. The adaptive (A) RBC technology builds on RBC, but aims at improving the charging efficiency by charging devices at device preferred current and voltage levels adaptively. A mobile ARBC scheme is developed relying on an adaptive source power control. Extensive numerical simulations using a 1,000mAh Li-ion battery show that the mobile ARBC outperforms simple charging schemes such as the constant power charging, the profile-adaptive charging, and the distance-adaptive charging in saving energy. Copyright © 2020, The Authors. All rights reserved.

关键词： Energy transfer

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An Enhanced Fault Diagnosis Method with Uncertainty Quantification Using Bayesian Convolutional Neural Network

An Enhanced Fault Diagnosis Method with Uncertainty Quantifi...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Qihang Fang Gang Xiong Xiuqin Shang Sheng Liu Bin Hu Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Fault diagnosis is a vital technique to pinpoint the machine malfunctions in manufacturing systems. In recent years, the deep learning techniques greatly improve the fault detection accuracy, but there still remain some problems. If one fault is absent in the training data or the fault signal is disturbed by severe noise interference, the fault classifier may misjudge the health state. This problem limits the reliability of the fault diagnosis in real applications. In this paper, we enhance the fault diagnosis method by using Bayesian Convolutional Neural Network (BCNN). A Shannon entropy-based method is presented to quantify the prediction uncertainty. The BCNN turns the deterministic predictions to probabilistic distributions and enhances the robustness of the fault diagnosis. The uncertainty quantification method helps to indicate the wrong predictions, detect unknown faults, and discover the strong disturbances. Then, a fine-tuning strategy is applied to enhance the model performance further. The potential usability of the proposed method in monitoring the motors of 3D printers is studied. And the experiment is conducted on a motor bearing dataset provided by Case Western Reserve University. The proposed BCNN achieves 99.82% fault classification accuracy over nine health conditions. Its robustness is verified by comparing the testing accuracy with three other methods on the noisy datasets. And the uncertainty quantification method successfully detects the outlier inputs.

关键词： Fault diagnosis Uncertainty Bayes methods Circuit faults Robustness Predictive models Noise measurement

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