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Research and design of mobile robot moving object tracking system on hierarchical control

Research and design of mobile robot moving object tracking s...

引用

International Conference on Computer Application and system Modeling (ICCASM)

作者： Liu Wei Tanmin Jian-ping Wang Zhang chongwei Wang Jun School of Electrical Engineering and Automation Hefei University Key Laboratory of Machine Vision and Intelligence Control Technology Hefei China School of Electrical Engineering and Automation Hefei University of Technology Hefei China Hefei University Key Laboratory of Machine Vision and Intelligence Control Technology Hefei China Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei China Hefei University Hefei CN

A intelligent control model structure of double-level-three-stage is presented to deal with the moving robot detecting and tracking system. According to basic ideas of imitation of human intelligence control, it includes Decision-making level and Execution level, each level is decomposed into 3 stages. In the process of tracking, the moving objects state forecast and two-step increment tracking algorithm based on Kalman filter are adopted to drive the mobile robot quickly and smoothly. The robot system to detect and track moving objects with the model structure is designed and its application in automobile stake is illustrated.

关键词： Image segmentation Image recognition Humans Robot kinematics

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An adaptive Differential Evolution algorithm for sewer networks design

An adaptive Differential Evolution algorithm for sewer netwo...

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World Congress on Intelligent control and Automation (WCICA)

作者： Changfen Liu Honggui Han Chao Wang Junfei Qiao Beijing University of Technology Beijing CN College of Electronic and Control Engineering Beijing Key Laboratory of Computational Intelligence and Intelligence System

A newly introduced Self-adaptive Differential Evolution algorithm via Generalized Opposition-Based Learning (SDE-GOBL) is applied to optimal design of two sewer networks. Every chromosome consists of the information of network layout. Select a feasible design which satisfies the constraints of velocity, slope and proportional water depth to get optimal cost through the algorithm. Two sewer optimization problems in which the pipe diameters are considered as the decision variables are solved by the SDE-GOBL algorithm. Comparisons with the previous works are made and the results show that the proposed algorithm performs better in terms of solution quality and efficiency.

关键词： Vectors Algorithm design and analysis Sociology Statistics Optimization Genetic algorithms Pipelines

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Preparation of TiO films by cathode multi arc ion and its performance

Preparation of TiO films by cathode multi arc ion and its pe...

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International Nano-Optoelectronic Workshop, iNOW

作者： Duojin, Fan Duowang, Fan Chenglong, Wang Lingxiao, Ming Lin, Zhao Hongzhong, Liu Lanzhou Dachen Automatic Control System Co. Ltd. Lanzhou 730070 China MOE Key Lab. of Opto-electronic Technology and Intelligence Control Lanzhou Jiaotong University Lanzhou 730070 China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an 710049 China

TiO films were prepared by custom-made Cathode Multi Arc Ion equipment. Experimental test results reveal that our equipment can easly deposite big area scale TIO, particle size is in nanometer scale. © 2007 IEEE.

ISBN: (纸本)1424415918

关键词： Particle size

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Containment control Protocol Design for PDE Agents Subject to External Disturbances

Containment Control Protocol Design for PDE Agents Subject t...

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第42届中国控制会议

作者： Yining Chen School of Artificial Intelligence Tiangong University Key Laboratory of System Control and Information Processing Ministry of Education

This paper mainly solves the containment control issue for a network of infinite-dimensional agents described by wave equations. To eliminate influences caused by external disturbances, observers based on partial differential equations are proposed. A novel interaction protocol is then designed to reach containment control under a fixed directed communication topology. Different from the existing works, disturbances with unbounded derivatives are allowed in this paper. A proper Lyapunov function is constructed and the sufficient condition assuring containment control is obtained. Finally, the theoretical results are verified via numerical examples.

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Research on Boot Problem and Automatic Repair of an Embedded Real-time Operating system 2

Research on Boot Problem and Automatic Repair of an Embedded...

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2nd International Conference on Computer Technologies, ICCTech 2023

作者： Zhou, Haoshang Gao, Zhaoling Wang, Zhongfu Wang, Xiaopeng State Key Laboratory for Traction and Control System of EMU and Locomotive CRRC Dalian Electric Traction R&D Center Co. Ltd China School of Intelligence and Electronic Engineering Dalian Neusoft University of Information China

ISBN: (纸本)9781665455824

At present, in the communication between Electric Multiple Units (EMU) and locomotive network control system, in order to ensure the stability of vehicle control and the accuracy and reliability of data recording, its key components - Central control Unit (CCU) and Event Record machine (ERM) adopt an embedded real-time operation system. In order to facilitate debugging, the system needs to start Microsoft's DOS system before being called to start. Based on the feedback of the embedded real-time operating system startup failure from each locomotive and rolling stock depot, this paper will elaborate on its startup process and propose a solution that can automatically repair the startup problem, which has been tested in the laboratory to prove that this method can effectively avoid the system startup failure. © 2023 IEEE.

关键词： Program debugging

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Image super-resolution based wavelet framework with gradient prior

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Lecture Notes in Computer Science

作者： Xu, Yan Li, Xueming M. Suen, Chingyi Y. Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing 100876 China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9783642236778

A novel super-resolution approach is presented. It is based on the local Lipschitz regularity of wavelet transform along scales to predict the new detailed coefficients and their gradients from the horizontal, vertical and diagonal directions after extrapolation. They form inputs of a synthesis wavelet filter to perform the undecimated inverse wavelet transform without registration error, to obtain the output image and its gradient map respectively. Finally, the gradient descent algorithm is applied to the output image combined with the newly generated gradient map. Experiments show that our method improves in both the objective evaluation of peak signal-to-noise ratio (PSNR) with the greatest improvement of 1.32 dB and the average of 0.56 dB, and the subjective evaluation in the edge pixels and even in the texture regions, compared to the "bicubic" interpolation algorithm. © 2011 Springer-Verlag.

关键词： Wavelet transforms

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Self-Organized Criticality in C. Elegans Neural Network 42

Self-Organized Criticality in C. Elegans Neural Network

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42nd Chinese control Conference, CCC 2023

作者： Gu, Xiao Liu, Jian Yuan, Ye Zhao, Peng Xin, Kuankuan Fang, Tao Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai200240 China Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai200093 China Queensland Brain Institute The University of Queensland BrisbaneQLD4072 Australia

ISBN: (纸本)9789887581543

The self-organized criticality is a fundamental property for organisms to perform normal functional activities. Extensive large-scale biological neural network researches have found the existence of self-organized criticality through avalanche phenomenon, which is typical characteristic of self-organized criticality. However, such research method is not suitable for small-scale biological neural network, because number of neurons in small-scale biological neural network is not large enough to support the emergence of avalanche phenomenon. It has been demonstrated that branching parameter can also be used to describe the propagation of activity in the neural network. Here, in this paper, the C. elegans neural network composed of 302 neurons is selected to investigate the existence of self-organized criticality using branching parameter. Based on the obtained connectome of C. elegans, a directed graph model is constructed to simulate the gradient potential of neurons and the activity of C. elegans, then, the existence of self-organized criticality in the neural network of C. elegans is proved by using branching parameter method. Meanwhile, the result is further confirmed by analyzing the calcium activity data of C. elegans obtained from biological experiments. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Calcium

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Graph Attention Memory for Visual Navigation 4

Graph Attention Memory for Visual Navigation

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4th International Conference on Data-Driven Optimization of Complex systems, DOCS 2022

作者： Li, Dong Zhang, Qichao Zhao, Dongbin Noah's Ark Lab Huawei Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex System China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China

ISBN: (数字)9781665459822

ISBN: (纸本)9781665459822

Visual navigation in complex environments is inefficient with traditional reactive policy or general-purposed recurrent policy due to the long-term memory problem. To address this issue, this paper proposes a graph attention memory (GAM) architecture consisting of memory construction module, graph attention module, and control module. The memory construction module builds the topological graph based on supervised learning by taking the exploration prior. Then, guided attention features to reach the goal are extracted with the graph attention module. Finally, the deep reinforcement learning based control module makes decisions based on visual observations and guided attention features. In addition, the convergence of the proposed GAM module for recurrent attention operation is analyzed in this paper. We evaluate GAM-based navigation system in two complex 3D ViZDoom environments. Experimental results show that the GAM-based navigation system outperforms all baselines in both success rate and navigation efficiency, and significantly improves the generalization. © 2022 IEEE.

关键词： Deep learning

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Time-frequency decomposition-based weighted ensemble learning for motor imagery EEG classification

Time-frequency decomposition-based weighted ensemble learnin...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Zheng, Liangsheng Ma, Yue Li, Mengyao Xiao, Yang Feng, Wei Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781665436786

Motor imagery brain-computer interface system based on Electroencephalogram (EEG) is an effective way to help the disabled recover part of their motor abilities. However, decoding the movement intention contained in the EEG signal accurately presents many challenges. In this paper, we propose a time-frequency decomposition-based weighted ensemble learning (TFDWEL) method, which aims to improve the classification performance of motor imagery EEG signals. The TFDWEL method divides the EEG signal into multiple subsets, and uses four time-frequency processing methods to extract the time-frequency sub-bands of each subset. Then the feature extraction model and classifier model of each subset trained by the common spatial pattern (CSP) algorithm and the support vector machine (SVM) algorithm are used to build a set of base learners. The least square error estimation method is used to learn the weight of each base learner, and finally the weighted summation method is used to obtain the final decision. The classification performance of the TFDWEL method is evaluated on the BCI Competition IV Data Set 2b, and the results show that the classification accuracy of 81.58% can be obtained. Superior classification performance indicates that the TFDWEL method can be used in further research to help the rehabilitation of the disabled. © 2021 IEEE.

关键词： Electroencephalography

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Advances in Swarm intelligence 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Ying Tan Yuhui Shi Zhen Ji

ISBN: (数字)9783642309762

ISBN: (纸本)9783642309755

This book and its companion volume, LNCS vols. 7331 and 7332, constitute the proceedings of the Third International Conference on Swarm intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The 145 revised full papers presented were carefully reviewed and selected from 247 submissions. The papers are organized in 27 cohesive sections covering all major topics of swarm intelligence research and developments.

关键词： Algorithm Analysis and Problem Complexity Information systems Applications (incl. Internet) Artificial intelligence Computation by Abstract Devices Computer Communication Networks Data Mining and Knowledge Discovery

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