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42nd Chinese control Conference, CCC 2023

作者： Chen, Jiale Dong, Tao Wang, Shiyun Jiao, Guili Zhang, Rongrong Tian, Xincheng School of Control Science and Engineering Center for Robotics Engineering Research Center of Intelligent Unmanned System Ministry of Education Shandong University Jinan China Jinan China Shandong Tianyong Intelligent Technology Co. Ltd Jinan China Shandong Hydrology Center Jinan China

ISBN: (纸本)9789887581543

With the advent of the rainy season, the chances of urban flooding are increasing, to avoid the risk of flooding people and underground garages, this paper explains our reliance on video surveillance technology and 5G cloud data technology to collect the data of anti-backflow door equipment deployed in various parts of the city, and remote control and command in the management center, which can quickly give flood control measures and early warning to protect the personnel and property of underground garages, and reduced losses. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Remote control

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Improved Extrinsic Calibration of Acoustic Cameras via Batch Optimization

Improved Extrinsic Calibration of Acoustic Cameras via Batch...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhi Li Jiang Wang Xiaoyang Li He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems and the Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Acoustic cameras have found many applications in practice. Accurate and reliable extrinsic calibration of the microphone array and visual sensors within acoustic cameras is crucial for fusing visual and auditory measurements. Existing calibration methods either require prior knowledge of the microphone array geometry or rely on grid search which suffers from slow iteration speed or poor convergence. To overcome these limitations, in this paper, we propose an automatic calibration technique using a calibration board with both visual and acoustic markers to identify each microphone position in the camera frame. We formulate the extrinsic calibration problem (between microphones and the visual sensor) as a nonlinear least squares problem and employ a batch optimization strategy to solve the associated problem. Extensive numerical simulations and real-world experiments show that the proposed method improves both the accuracy and robustness of extrinsic parameter calibration for acoustic cameras, in comparison to existing methods. To benefit the community, we open-source all the codes and data at https://***/AISLAB-sustech/AcousticCamera.

关键词： Visualization Accuracy Cameras Numerical simulation Acoustics Robustness Microphone arrays Calibration Optimization Sensor arrays

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Calibration of Multiple Asynchronous Microphone Arrays using Hybrid TDOA

Calibration of Multiple Asynchronous Microphone Arrays using...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chengjie Zhang Wenda Pan Xinyang Han He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems and the Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Accurate calibration of acoustic sensing systems made of multiple asynchronous microphone arrays is essential for satisfactory performance in sound sour ce localization and tracking. State-of-the-art calibration methods for this type of system rely on the time difference of arrival and direction of arrival measurements among the microphone arrays (denoted as TDOA-M and DOA, respectively). In this paper, to enhance calibration accuracy, we propose to incorporate the time difference of arrival measurements between adjacent sound events (TDOA-S) with respect to the microphone arrays. More specifically, we propose a two-stage calibration approach, including an initial value estimation (IVE) procedure and the final joint optimization step. The IVE stage first initializes all parameters except for microphone array orientations, using hybrid TDOA (i.e., TDOA-M and TDOA-S), odometer data from a moving robot carrying a speaker, and DOA. Subsequently, microphone orientations are estimated through the iterative closest point method. The final joint optimization step estimates multiple microphone array locations, orientations, time offsets, clock drift rates, and sound source locations simultaneously. Both simulation and experiment results show that for scenarios with low or moderate TDOA noise levels, our approach outperforms existing methods in terms of accuracy. All code and data are available at https://***/AISLAB-sustech/Hybrid-TDOA-Multi-Calib.

关键词： Direction-of-arrival estimation Accuracy Time difference of arrival Position measurement Odometers Microphone arrays Calibration Arrays Optimization Noise level

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Research on Synthetic Data Generation and Multi-modal Target Detection

Research on Synthetic Data Generation and Multi-modal Target...

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第34届中国控制与决策会议

作者： Jiexi Liu Chenyu Wang Lei Xu Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

Target Detection is one of the most important tasks in Computer Vision,which has broad application prospects in many *** the past few years,great progress has been made in this field with the rapid development of deep learning ***,it's still a big challenge at complex scenarios such as dim environment for traditional single-modal visible *** address this problem,researchers introduce thermal images as additional modal in consideration of that thermal cameras are less susceptible to interference and explore how to fuse the two modalities information ***,the lack of large labeled and high-quality visible-thermal datasets hampers the usage of convolutional neural networks for ***,we propose to use image-to-image translation model combined with a differentiable data augmentation method to generate fake thermal images from labeled visible images and use multi-modal target detection model to prove the validity of the *** experiment results show that our method can provide us a large labeled dataset of synthetic visible-thermal image pairs with better generalization and the introduction of thermal modality can obtain a better performance than single modality.

关键词： Image-to-image translation Multi-modal target detection Deep learning

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First attempt of barrier functions for Caputo's fractional-order nonlinear dynamical systems

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science China(Information sciences) 2023年第7期66卷 313-314页

作者： Zheren ZHU Pengfei HUANG Xinmin ZHANG Yi CHAI Zhihuan SONG College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology School of Automation Chongqing University Key Laboratory of Complex System Safety and Control(Chongqing University) Ministry of Education

Dear editor, In the past two decades, scholars have begun to use system dynamical models and state motions to study the safety of a system to realize the analysis, diagnosis, and control of system safety. This safety ...

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An error analysis method for attitude estimation system based on epipolar geometry

An error analysis method for attitude estimation system base...

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Luo, Shilin Xu, Cheng Zhang, Lundong Dong, Jing Fu, Wenxing Han, Songlai Central South University School of Aeronautics and Astronautics Changsha China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratary Beijing China

ISBN: (纸本)9781728190037

This paper proposes an error analysis method based on epipolar geometry which is analyzed for improving the accuracy of attitude estimation. The influence of equivalent focal length and principal point coordinates on modeling error was analyzed by simulation and experiment based on a rotary table. The result shows that the influence of the equivalent focal length will increase as the rotation angle increases, the different motion states will lead to different degrees of impact of the principal point coordinates. Besides, we derived that pose measuring accuracy is unrelated to the magnitude of rotation angle and there is no accumulative error under simulation conditions. This proposed method can enhance the measuring accuracy and provide some meaningful advice for engineering applications. © 2021 IEEE.

关键词： Computer vision

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Relative Roughness Measurement Based Real-Time Speed Planning for Autonomous Vehicles on Rugged Road

Relative Roughness Measurement Based Real-Time Speed Plannin...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Liang Wang Tianwei Niu Shoukun Wang Shuai Wang Junzheng Wang Key Laboratory of Drive and Control of Servo Motion System School of Automation Beijing Institute of Technology Beijing China The State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China

In order to guarantee autonomous vehicles' autonomy, mobility, and ride quality in rugged environments, a real-time speed planning method based on the time-frequency transformation of terrain characteristics is designed to achieve adaptive speed planning of autonomous vehicles in rough ground. On the one hand, the vertical profile of the lidar's point cloud data is converted from the time domain to the frequency domain in real time, and the integrated area of the sub-frequency range in the frequency domain is chosen as the relative roughness quantification value to realize the roughness quantification under various terrains. On the other hand, to model the relationship between vehicle speed and relative roughness, iterative search is utilized to create a speed and roughness model, and sliding windows are employed to update the roughness to achieve continuous mapping between speed and roughness. Ultimately, a number of tests were conducted on various rough roads using the oil exploration vehicle EV-56 as the study object. The experimental results show that the proposed method can identify the terrain roughness changes under complex terrain and change their speed within 0.2 m accuracy.

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Cooperative Search Strategy of Multiple UAVs Based on Matrix Game 19

Cooperative Search Strategy of Multiple UAVs Based on Matrix...

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19th International Bhurban Conference on Applied sciences and technology, IBCAST 2022

作者： Song, Dalei Wang, Xiaoqian Dai, Aoliang Ma, Hongjun Wei, Donghui Shenyang University of Technology School of Information Science and Engineering Shenyang China Northeastern University School of Information Science and Engineering Shenyang China South China University of Technology School of Information Science and Engineering Guangdong China Beijing Research Institute of Mechanical & Electrical Technology Key Laboratory of Complex System Control and Intelligent Collaboration Technology Beijing100074 China

ISBN: (数字)9781665460514

ISBN: (纸本)9781665460514

For the regional search problem of multiple unmanned air vehicles (UAVs) ,a cooperative search strategy of multiple UAVs is proposed based on action matrix game (AMG) for intelligent moving targets on the ground in this paper. Based on the proposed AMG, the yaw angle and position information of the target is described in probability matrix, and the matrix is updated by Nash equilibrium and receding horizon control in every control cycle. Simulation results show that this strategy deduces the searching time for revisiting the reference target, and improves the success rate for moving targets searching. © 2022 IEEE.

关键词： Game theory

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Q-Learning for Finite-Horizon H8Tracking control of Unknown Linear Discrete-Time systems 42

Q-Learning for Finite-Horizon H8Tracking Control of Unknown ...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Mingxiang Cai, Qianqian Meng, Wei Li, Dandan Fu, Minyue Han, Zhimin School of Automation Guangdong University of Technology Guangzhou510006 China Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen518055 China School of Automation Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789887581543

In this paper, we present a Q-learning algorithm for finite-horizon H8 tracking control of unknown linear discrete-time systems. Finite horizon control is challenging due to its correspondence with a time-varying Riccati equation. The proposed algorithm can determine the solution of the time-varying Riccati equation with unknown system dynamics. We first establish the time-varying Q-function, then propose a corresponding Q-learning algorithm and prove its convergence. Finally, the proposed algorithm is proved to be effective through numerical examples. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Riccati equations

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Time series generator adversarial network with stochastic process for the degradation generation and prediction

Time series generator adversarial network with stochastic pr...

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Data Driven control and Learning systems (DDCLS)

作者： Anqi Shangguan Nan Feng Lingxia Mu Rong Fei Xinhong Hei Guo Xie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China School of computer science and Engineering Xi'an University of Technology Xi'an China

Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degradation to improve the accuracy of later reliability assessment. Therefore, a degradation generation and prediction method is proposed combining the time series generator adversarial network (TimeGAN) and stochastic process. Firstly, the input degradation is expanded by the sliding window to improve the later training accuracy; Then, the construction of the generator in TimeGAN is linked with the stochastic process to make the generation data more realistic. Finally, the results of degradation prediction by the Gated Recurrent Unit (GRU) can be obtained. Two datasets and different generation methods are adopted to evaluate the effectiveness of the proposed method. The results shows that the Kullback-Leibler(KL) divergence is the smallest, and the prediction error is the smallest compared with the other methods. So, the proposed method is proved that it is valid in the degradation generation and prediction, and can be used for the further reliability assessment of the product in the industrial system.

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