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第40届中国控制会议

作者： Le Li Haoyu Liao Yongqiang Bai School of Automation Beijing Institude of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institude of Technology

KCF is an excellent target tracking algorithm with fast computing speed and high ***,it performs poorly in complex tracking situations such as target deformation,motion blur,scale change and *** view of target deformation and motion blur,we designed a feature fusion method,which combines CN feature and HOG feature to enhance the expression ability of the *** view of the change of scale,the scale pool is *** improve the ability of anti occlusion,we improved the model updating mechanism and designed a SVM detector to detect the target after it is *** experiments on OTB-100 showed that the improved method achieves a great improvement compared with KCF,the accuracy increases by 4.2%,the success rate increases by 12.1%,and our algorithm meets the real-time requirements.

关键词： KCF target tracking feature fusion scale pool anti occlusion

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Long-term stable target tracking algorithm based on improved Staple

Long-term stable target tracking algorithm based on improved...

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第40届中国控制会议

作者： Haoyu Liao Le Li Yongqiang Bai School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

Staple algorithm has been widely proven to be an efficient target tracking method, but it is still easy to fail in some tracking scenarios such as target deformation, motion blur, and complete occlusion. This paper makes improvements to the above problems. First of all, we use a binary mask based on spatial reliability to enhance the target information in Staple’s color features, which improves the tracking accuracy of the algorithm in complex scenes. Secondly, we propose a response graph evaluation index based on secondary detection, that is, the least square filter is used for convolution at the original response peak to obtain a more accurate tracking state judgment. Finally, if the current state is judged to be a failure, we use a particle filter-based motion estimation method to relocate the target, thereby improving the algorithm’s tracking success rate when the target is occluded. The test results on the OTB2015 data set show that the overall accuracy of the algorithm in this paper has reached 80%, and the overall success rate has reached 73.2%, which proves the long-term stable tracking performance of the algorithm.

关键词： Target tracking Staple Binary mask Particle filter Anti-occlusion

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Harmonic Disturbance Suppression for High-Performance Nonlinear Repetitive-control systems

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IFAC-PapersOnLine 2023年第2期56卷 4545-4550页

作者： Shengnan Tian Kang-Zhi Liu Manli Zhang Chengda Lu Min Wu Jinhua She School of Automation China University of Geosciences Wuhan 430074 China. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Department of Electrical and Electronic Engineering Chiba University Chiba 263-8522 Japan School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

This study focuses on the performance design issue of nonlinear repetitive control (RC) systems subject to harmonic disturbances. First, a Takagi-Sugeno fuzzy model is used to describe a nonlinear plant. Then, a repetitive controller featuring a harmonic disturbance period is integrated with an EID estimator to form an RC-EID structure. The structure has a learning feature that gradually reduces the harmonic disturbance estimation error by self-learning. The linear inequality matrices guarantee the stability of nonlinear RC systems. A case study with two permanent magnet synchronous motors shows that the presented RC-EID estimator enhances the harmonic disturbance-suppression performance while compensating for the phase lag caused by the conventional EID filter.

关键词： Nonlinear repetitive control systems harmonic disturbance suppression equivalent input disturbance performance enhancement

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Traffic Signal control Using Offline Reinforcement Learning

Traffic Signal Control Using Offline Reinforcement Learning

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2021 China automation Congress, CAC 2021

作者： Dai, Xingyuan Zhao, Chen Li, Xiaoshuang Wang, Xiao Wang, Fei-Yue School of Artificial Intelligence University of Chinese Academy of Sciences China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781665426473

The problem of traffic signal control is essential but remains unsolved. Some researchers use online reinforcement learning, including the off-policy one, to derive an optimal control policy through interaction between agents and environments in simulation. However, it is difficult to deploy the policy in real transportation systems due to the gap between simulated and real traffic data. In this paper, we consider an offline reinforcement learning method to tackle the problem. First, we construct a realistic traffic environment and obtain offline data based on a classic actuated traffic signal controller. Then, we use an offline reinforcement learning algorithm, namely conservative Q-learning, to learn an efficient control policy via offline datasets. We conduct experiments on a typical road intersection and compare the conservative Q-learning policy with the actuated policy and two data-driven policies based on off-policy reinforcement learning and imitation learning. Empirical results indicate that in the offline-learning setting the conservative Q-learning policy performs significantly better than other baselines, including the actuated policy, but the other two data-driven policies perform poorly in test scenarios. © 2021 IEEE

关键词： Reinforcement learning

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements 63

A Multi-Player Potential Game Approach for Sensor Network Lo...

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63rd IEEE Conference on decision and control, CDC 2024

作者： Xu, Gehui Chen, Guanpu Fidan, Baris Hong, Yiguang Qi, Hongsheng Parisini, Thomas Johansson, Karl H. Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Waterloo Department of Mechanical and Mechatronics Engineering WaterlooONN2L 3G1 Canada Tongji University Department of Control Science and Engineering shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China University of Chinese Academy of Sciences School of Mathematical Sciences Beijing China Aalborg University Department of Electronic Systems Denmark Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom University of Trieste Department of Engineering and Architecture Italy

ISBN: (纸本)9798350316339

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies. © 2024 IEEE.

关键词： Nash equilibrium

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Learning to Find Good Correspondences Based on Global and Local Attention Mechanism

Learning to Find Good Correspondences Based on Global and Lo...

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2021 China automation Congress, CAC 2021

作者： Chen, Jun Gu, Yue Luo, Linbo School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (纸本)9781665426473

We are committed to designing a method for establishing a set of reliable correspondences between two images in this paper. Previous work proposes an outlier removal network based on global and local attention mechanism. It normalizes the feature map under the guidance of attention weight, as a result the robustness to outliers is improved and inliers are better preserved. However, element-wise multiplication of these two different attentions makes them unable to perform their original functions. In order to overcome this limitation, a network based on attention mechanism has been designed in our work. Firstly, global attention is employed to compute a global weight which can help normalization focus on inliers and reduce the influence of outliers on context information. Secondly, to extract channel information, we use local attention to learn a channel weight for each correspondence. Finally, the above structures and residual network modules are combined for correspondence establishment. Experimental results show that our method is better than other SOTA methods. © 2021 IEEE

关键词： Computer vision

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An Introduction to Domain Adaptive Object Detection from Synthesis to Reality

An Introduction to Domain Adaptive Object Detection from Syn...

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第40届中国控制会议

作者： Zhijun Xue Wenjie Chen Jing Li State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

In recent years,deep learning based object detection has achieved great *** methods typically assume that large amount of labeled training data is available,meanwhile,training and test data are independent and identically ***,the two assumptions are not always hold in *** many applications,it is prohibitively expensive and time-consuming to obtain large quantities of labeled *** computer graphics technology to generate a large number of labeled data provides a solution to this ***,direct transfer across domains from synthesis to reality often performs poorly due to the presence of domain *** adaptive object detection are concerned with accounting for these types of *** this paper,we present an introduction to these ***,we briefly introduce the object detection and domain ***,the synthetic object detection datasets and related software tools are ***,we present a categorization of approaches,divided into discrepancy-based methods,adversarial discriminative methods,reconstruction-based methods and ***,we also discuss some potential deficiencies of current methods and several open problems which can be explored in future work.

关键词： Deep learning Object detection Synthesis to reality Domain adaptation

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Robotic Intra-Operative Ultrasound:Virtual Environments and Parallel systems

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IEEE/CAA Journal of Automatica Sinica 2021年第5期8卷 1095-1106页

作者： Shuangyi Wang James Housden Tianxiang Bai Hongbin Liu Junghwan Back Davinder Singh Kawal Rhode Zeng-Guang Hou Fei-Yue Wang the State Key Laboratory of Management and Control of Complex Systems Chinese Academy of SciencesInstitute of AutomationBeijing 100190China the School of Biomedical Engineering and Imaging Sciences King’s College LondonLondon SE17EHUK the Xtronics Ltd.Gravesend DA122ADUK

Robotic intra-operative ultrasound has the potential to improve the conventional practice of diagnosis and procedure guidance that are currently performed *** towards automatic or semi-automatic ultrasound,being able to define ultrasound views and the corresponding probe poses via intelligent approaches become *** on the concept of parallel system which incorporates the ingredients of artificial systems,computational experiments,and parallel execution,this paper utilized a recent developed robotic trans-esophageal ultrasound system as the study object to explore the method for developing the corresponding virtual environments and present the potential applications of such *** proposed virtual system includes the use of 3 D slicer as the main workspace and graphic user interface(GUI),Matlab engine to provide robotic control algorithms and customized functions,and PLUS(Public software Library for Ultra Sound imaging research)toolkit to generate simulated ultrasound *** implementation methods were presented and the proposed features of the system were *** on this virtual system,example uses and case studies were presented to demonstrate its capabilities when used together with the physical TEE *** includes standard view definition and customized view optimization for pre-planning and navigation,as well as robotic control algorithm evaluations to facilitate real-time automatic probe pose *** conclude,the proposed virtual system would be a powerful tool to facilitate the further developments and clinical uses of the robotic intra-operative ultrasound systems.

关键词： Medical robots parallel intelligence parallel systems robotic-assisted surgery robotic ultrasound

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Action Recognition Algorithm based on 2D Human Pose Estimation Method

Action Recognition Algorithm based on 2D Human Pose Estimati...

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第40届中国控制会议

作者： Chongkai Yu Wenjie Chen Ye Li Chen Chen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

This paper presents an action recognition method based on 2D human body node data in video. This method uses the pose estimation algorithm to detect the human body node data in each frame of video information. We get the two-dimensional coordinates and confidence data of the nodes, and optimize the arrangement of these data into a 3D array form similar to ***, we use the classical two-dimensional convolutional neural network to carry out classification training. The test on UCF-101 data set shows that this method can indeed improve the accuracy of action recognition based on RGB information to a certain extent, and reduce the training cost.

关键词： Action recognition Pose estimation Two-dimensional convolutional neural network

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Distributed Estimation with Quantized Measurements and Communication over Markovian Switching Topologies

arXiv

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arXiv 2024年

作者： Wang, Ying Guo, Jian Zhao, Yanlong Zhang, Ji-Feng Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm11428 Sweden School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electrical Engineering Zhongyuan University of Technology Zhengzhou450007 China

This paper addresses distributed parameter estimation in stochastic dynamic systems with quantized measurements, constrained by quantized communication and Markovian switching directed topologies. To enable accurate recovery of the original signal from quantized communication signal, a persistent excitation-compliant linear compression encoding method is introduced. Leveraging this encoding, this paper proposes an estimation-fusion type quantized distributed identification algorithm under a stochastic approximation framework. The algorithm operates in two phases: first, it estimates neighboring estimates using quantized communication information, then it creates a fusion estimate by combining these estimates through a consensus-based distributed stochastic approximation approach. To tackle the difficulty caused by the coupling between these two estimates, two combined Lyapunov functions are constructed to analyze the convergence performance. Specifically, the mean-square convergence of the estimates is established under a conditional expectation-type cooperative excitation condition and the union topology containing a spanning tree. Besides, the convergence rate is derived to match the step size’s order under suitable step-size coefficients. Furthermore, the impact of communication uncertainties including stochastic communication noise and Markov-switching rate is analyzed on the convergence rate. A numerical example illustrates the theoretical findings and highlights the joint effect of sensors under quantized communication. Copyright © 2024, The Authors. All rights reserved.

关键词： Encoding (symbols)

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