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Chinese control Conference (CCC)

作者： Rong-Ze Huang Yin-Bo Liu Meh Jabeen Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

Indoor layout estimation (ILE) is a challenging research that segments the natural indoor scene image into floor, walls and ceiling, and it has a wide range of application prospects in the fields such as scene understanding, reconstruction, robot positioning, and virtual reality. An ILE method by merging multiple features from a monocular red-green-blue (RGB) image was proposed. Firstly, the High-resolution networks (HRNet) was used to extract the features of indoor corner keypoints (CKs) and informative edges (IEs) in the form of heatmaps. Secondly, the extracted features were then selected through a room type (RT) classification network. Finally, a feature fusion algorithm was proposed, which obtained the initial layout hypothesis through CK features and then continuously optimized the layout hypothesis with IE features. The proposed ILE method was validated on the large scene understanding challenge (LSUN) dataset.

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Joint angle measurement of manipulator and error compensation based on an IMU sensor

Joint angle measurement of manipulator and error compensatio...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Zhang, Tianlin Chen, Sheng Xu, Guozheng Wang, Chao Tan, Caiming School of Automation Nanjing University of Posts and Telecommunications Nanjing210023 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

To detect the joint angle of the manipulator accurately, a measuring method based on an IMU sensor is proposed. The sensor's attitude angles and corresponding rotation matrix are obtained according to the data of three-axis gyroscope and three-axis accelerometer. During the installation, the sensor's Z-axis direction is kept along with the motor's rotation axis direction, so that the angle of the sensor rotating around its Z-axis, which is the rotation angle of the motor, can be calculated by comparing the rotation relationship between the sensor's initial position and the sensor's position after the motor rotating. The largest source of result error derives from the inconsistent between the sensor's Z-axis direction and the motor's rotation axis direction. Consequently, an installation's error compensation method is designed to correct the sensor's Z-axis to the motor's rotation axis by rotating the related motor. The experiments show that the method can measure the joint angle of the manipulator accurately and calibrate the installation error effectively. The measurement result errors are confined © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Manipulators

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Finite-time Consensus for Second-order Multi-agent systems Based on Embedded control

Finite-time Consensus for Second-order Multi-agent Systems B...

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Chinese Automation Congress (CAC)

作者： Quanwei Wu Xiangyu Wang Guodong Wang Chuanlin Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing People’s Republic of China College of Automation Engineering Shanghai University of Electric Power People’s Republic of China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

This paper studies the finite-time consensus problem for both leader-follower and leaderless second-order multi-agent systems. To solve the problem, a nonsmooth embedded control scheme is used, which is made up of two parts. In part one, for each case, based on nonsmooth control theory, a distributed virtual signal generator is designed. For the leaderless case, the outputs of the designed generator reach finite-time consensus and for the leader-follower case, virtual position and velocity signals of the designed generator track the leader's position and velocity in finite time. In part two, for each case, through embedding the generator into the feedback loop and taking its outputs (i.e., outputs for the leaderless case and virtual position and velocity signals for the leader-follower case) as the reference outputs for the agents (i.e., all the agents for the leaderless case and the followers for the leader-follower case), some tracking controllers are designed for the agents to track their reference outputs in finite time. Based on this scheme, some consensus algorithms are proposed. Under the proposed consensus algorithms, leaderless and leader-follower multi-agent systems achieve finite-time consensus. Numerical simulations verify the validity of the proposed consensus algorithms.

关键词： Consensus algorithm Signal generators Multi-agent systems Topology Consensus protocol Generators Automation

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Multi-Home Energy Coordination Scheduling Based on Adaptive Dynamic Programming

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The International Journal of Intelligent control and systems 2024年第1期29卷 30-36页

作者： Kang Xiong Qinglai Wei Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China.

Implementing cooperative scheduling of multi-home microgrid energy and reducing the dependence on the main grid have become the focus of microgrid energy management *** paper proposes a new multi-agent adaptive dynamic programming(MAADP)method for the cooperative control of distributed home *** home is defined as a learning agent that needs to reasonably schedule the energy storage system to meet the respective load demand while accomplishing cooperative scheduling among the individual *** addition,an energy clearing center(ECC)is introduced to complete the energy exchange between each microgrid to protect the benefits of all *** proposed method adopts the learning strategy of“centralized learning and decentralized execution”to avoid the leakage of private *** experimental comparison with the benchmark method verifies that the method can realize the cooperative scheduling of each home and reduce the dependence on the main grid.

关键词： Multi-home scenarios adaptive dynamic programming(ADP) optimal home energy management smart grid

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An Universal control Strategy for Planar 2-DoF Underactuated Manipulator with One Passive Joint

An Universal Control Strategy for Planar 2-DoF Underactuated...

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第40届中国控制会议

作者： Zixin Huang Yaosheng Zhou Zhen Chen Wei Wang Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Innovation and Entrepreneurship Wuhan Institute of Technology School of Information and Safety Engineering Zhongnan University of Economics and Law

This paper presents an unified control strategy based on the trajectory planning and tracking control for the planar 2-Do F underactuated manipulator. The trajectory of the active link is composed of two parts. The first part trajectories are designed according to the initial and target angles of the active link. The second part trajectories are designed based on the constraints between the underactuated link and the active link. Meanwhile, the parameters of the trajectories are optimized by the differential evolution algorithm(DEA) to ensure all links eventually reach to their target values by tracking the designed trajectories. Then,the sliding mode variable structure controller are designed to make the active link track their trajectories. The effectiveness of such strategy is demonstrated through simulation results.

关键词： Planar 2-DoF underactuated manipulator Trajectory planning Tracking control Differential evolution algorithm

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A Parallel Framework for Scene Understanding

A Parallel Framework for Scene Understanding

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wenwen Zhang Jiangong Wang Kunfeng Wang School of Software Engineering Xi'an Jiaotong University Xi'an China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China College of Information Science and Technology Beijing University of Chemical Technology Beijing China

Different related computer vision tasks make it possible to understand and analyze the scene totally. However, there is no useful framework combining different tasks for scene understanding. In this paper, we investigate the current state of scene understanding from different aspects relying on different computer vision tasks and propose an effective framework based on the theory of parallel vision to combine different tasks for scene understanding. With the maintained artificial scene throughout time from the proposed framework, we can understand the scene in an elegant way. To explain our proposed framework, a case study is given.

关键词： Computer vision Digital twin Conferences Task analysis

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An Island Remote Sensing Image Segmentation Algorithm Based on A Fusion Network with Attention Mechanism 3

An Island Remote Sensing Image Segmentation Algorithm Based ...

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2020 3rd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2020

作者： Chen, Tianyuan Wang, Hongfei Liu, Hao Wu, Peng Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing100094 China University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

With the increasing importance of islands in many fields, it has become the focus of research to obtain information from island remote sensing images efficiently by using image semantic segmentation algorithm. In recent years, deep learning methods based on convolutional neural network have been widely used in image segmentation. However, in view of the problems that remote sensing images contain richer ratio information and complex background interference, we propose an island remote sensing image segmentation algorithm based on a fusion network with attention mechanism, called AFU-Net. The network is built on the basis of FC_U-Net [1]. An attention mechanism is added to pre-weight the shallow features before deep-shallow layer feature fusion, in order to enhance the response capability of the target features, suppress the background interference and improve the segmentation accuracy of the network. The testing and comparative experiments on NWPU-RESISC45 dataset show that the quantitative metrics and visual effects of AFU-Net are greatly improved compared to FC_U-Net, and are also superior to other three state-of-the-art methods, U-Net, FCN, SegNet, which indicates the effectiveness of our method. © Published under licence by IOP Publishing Ltd.

关键词： Semantic Segmentation

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An Island Remote Sensing Image Segmentation Algorithm Based on FC_U-Net Network

An Island Remote Sensing Image Segmentation Algorithm Based ...

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2020 International Conference on Computer Vision, Image and Deep Learning, CVIDL 2020

作者： Chen, Tianyuan Wang, Hongfei Liu, Hao Du, Junrong Wu, Peng Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing100094 China University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781728194813

ISBN: (纸本)9781728194813

With the increasing importance of islands in many fields, it has become the focus of research to obtain information from island remote sensing images efficiently by using image semantic segmentation algorithm. In recent years, deep learning methods based on convolutional neural network have been widely used in image segmentation. However, for remote sensing images with rich details and different target scales, there are still some problems such as insufficient segmentation accuracy. To handle these problems, we propose an island remote sensing image segmentation algorithm based on FC_U-Net network. In this network, U-Net and FCN (Fully Convolutional Network) are improved respectively to form two new modules, and then the semantic features and detail features from the two modules are fused by a fusion module. The testing and comparative experiments on NWPU-RESISC45 dataset show that the quantitative metrics and visual effects of FC_U-Net are better than other three state-of-the-art methods, U-Net, FCN (Fully Convolutional Network), SegNet, which indicates the effectiveness of our method. © 2020 IEEE.

关键词： Semantic Segmentation

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A Parallel Education Based Intelligent Tutoring systems Framework

A Parallel Education Based Intelligent Tutoring Systems Fram...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Jing, Sifeng Tang, Ying Liu, Xiwei Gong, Xiaoyan Cui, Wei Liang, Joleen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States Squirrel Ai Learning Shanghai200030 China

ISBN: (纸本)9781728168531

although online education has improved efficiency of learners' access to high-quality educational resources, realtime interaction between instructors and learners have not yet been achieved in online personalized learning. Intelligent Tutoring systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed. © 2020 IEEE.

关键词： Computer aided instruction

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A Self-identifying Checkerboard-like Pattern for Camera Calibration

A Self-identifying Checkerboard-like Pattern for Camera Cali...

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第三十九届中国控制会议

作者： Zhang Gao Mingzhu Zhu Junzhi Yu School of Artificial Intelligence University of Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking University

This paper proposes a new type of planar pattern for camera calibration featuring its checkerboard-like structure and self-identity. White and black blocks are arranged by a novel method to ensure the uniqueness of each local pattern, and meanwhile maintain all checkerboard corners. The pattern is generated by combining identification units based on a random search strategy. Positions of local patterns can be acquired by searching the global pattern, achieving the benefit of self-identity. Because of the checkerboard-like structure, no burden is introduced in sampling compared to traditional calibrations. Experimental results show the effectiveness of the proposed calibration method. The conceived pattern is especially suitable for the calibration of multi-camera system with limited overlapping scope.

关键词： Camera calibration pattern self-identity checkerboard-like

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