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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems"

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Street Object Detection Based on Faster R-CNN

Street Object Detection Based on Faster R-CNN

引用

第37届中国控制会议

作者： Wendi Cai Jiadie Li Zhongzhao Xie Tao Zhao Kang Lu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Library of Wuhan University of Technology

With the increased number of traffic accidents, the research and development of smart cars have been *** detection of street objects has become one of the important research topics. Generic Model detection algorithm based on Convolution Neural Network(CNN) need to design the training model, while the training and testing of the model will take a lot of time. Transfer Learning is used to fine-tune the pre-trained models, using the Image task datasets of COCO, transferring a generic deep learning model to specific one with different weights and outputs. Furthermore, the CNN structure is adjusted to improve overall performance, and the street environment is trained to the special scene. We compare the results of experiments,and the results showed that the network which is fine-tuned is effective.

关键词： Transfer Learning Faster R-CNN Inception-ResNet-v2 Object Detection

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Peak and valley time-of-use price optimization strategy with distributed power supply 8

Peak and valley time-of-use price optimization strategy with...

引用

8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Hu, Bo Zhang, Yu Han, Xin-Yang Jiao, Yu-Qiao Ding, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China State Grid Energy Research Institute Co. LTD. Beijing102200 China

This paper proposes a peak-to-valley time-based electricity price optimization method based on NSGA-II with distributed power supply. First, the curve-fitting method is used to obtain the comprehensive electricity price response curve of users in the whole society. Secondly, based on the use of time-sharing electricity price, the peak-to-valley time-sharing optimization model is established. Then, based on the NSGA-II optimization method, the optimal model is solved, and the optimal electricity price is obtained at different time periods to change the peak-to-valley load and the valley load. Finally, the simulation results verify the effectiveness of the proposed method. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Genetic algorithms

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Multi-Convolution Neural Networks-Based Deep Learning Model for Emotion Understanding

Multi-Convolution Neural Networks-Based Deep Learning Model ...

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Chinese control Conference

作者： Luefeng Chen Min Wu Wanjuan Su Kaoru Hirota Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Tokyo Institute of Technology Yokohama Japan

Multi-convolution neural networks-based deep learning model in combination with multimodal data for emotion understanding is proposed, in which facial expression and body gesture are used to achieve emotional states recognition for emotion understanding. It aims to understand coexistence multimodal information in human-robot interaction by using multi-convolution neural networks, where multilayer convolutions are connected in series and multiple networks are executed in parallel. Moreover, when optimizing the weights of deep neural network by traditional method, it is easy to fall into poor local optimal. To address this problem, a hybrid genetic algorithm with stochastic gradient descent is developed, which has the capacity of inherent implicit parallelism and better global optimization of genetic algorithm so that it can adaptively find the better weights of the network. And in order to speed up the convergence of the proposal, the weights optimized by stochastic gradient descent will be taken as a chromosome of genetic algorithms initial population, and it also can be used as a priori knowledge. To verify the effectiveness of the proposal, experiments on benchmark database of spontaneous emotion expressions are developed, and experimental results show that the proposal outperforms the state-of-the-art methods. Meanwhile, the preliminary application experiments are also carried out and the results indicate that the proposal can be extended to human-robot interaction.

关键词： Feature extraction Genetic algorithms Biological cells Machine learning Sociology Statistics Neural networks

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Optimization of Overhauser magnetometer based on multi-channel frequency measurement algorithm

Optimization of Overhauser magnetometer based on multi-chann...

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第37届中国控制会议

作者： Guanzhong Wang Haobin Dong Jian Ge Wang Luo Huan Liu Zhiwen Yuan Jun Zhu Haiyang Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Systems

Overhauser magnetometer is a weak magnetic measuring instrument based on the dynamic nuclear polarization of free radical *** has the characteristics of high precision,high sensitivity,low power consumption and continuous *** is widely used in geophysics,aeromagnetic surveying,satellite Magnetic measuring,military and various engineering *** at the problem that the measurement accuracy of the magnetometer prototype is low and the measurement effect is poor when the angle between the probe axis and the geomagnetic field is 0°,several optimization methods are proposed and the magnetometer is optimized by adding the frequency measurement channel on the basis of the *** on the standard deviation of GSM-19 measurement data,comparing the experimental data that use the multi-channel frequency measurement algorithm,the standard deviation of prototype data decreases from 0.397 to 0.203 when the angle between probe axial and geomagnetic field is 45°,the standard deviation of the prototype data decreases from 0.631 to 0.371 when the angle between probe axial and geomagnetic field is 0°,which provides an important reference for the follow-up optimization of the magnetometer.

关键词： Overhauser magnetometer optimization standard deviation

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Distributed auction-based coverage motion planning for multiple cooperative robots 8

Distributed auction-based coverage motion planning for multi...

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作者： Gao, Guanqiang Xin, Bin School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

The multi-robot coverage motion planning (MCMP) problem refers to a typical task where every point of the target area must be covered by robots at least once. This paper designs a novel efficient offline algorithm to solve the MCMP problem, which is extended from the spiral-spanning tree coverage algorithm. A distributed auction mechanism is designed for the cooperative task allocation in the proposed algorithm. In this mechanism, each robot will be an auctioneer which chooses a suitable cell as an auction item form its neighbor vertexes and determines a winner robot. According to the connectedness and the balance of each robot’s graph, bidders will submit proper biddings to the auctioneer. After the auction processes, acceptable coverage trajectories can be planned rapidly. Computational experiments validate the effectiveness of the proposed MCMP algorithm. Meanwhile, the proposed algorithm is compared with the state-of-the-art algorithm named DARP. The comparative results show that the auction-based MCMP algorithm has apparent advantages in the running time and the makespans for large crowded configuration spaces. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Multipurpose robots

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Optimal Consensus control of Unknown Nonlinear Multi-Agent systems Using Adaptive Dynamic Programming via MRAC

Optimal Consensus Control of Unknown Nonlinear Multi-Agent S...

引用

第37届中国控制会议

作者： Hao Fu Xin Chen Wei Wang Jinbin Li Yaodong Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems State Grid Hubei Electric Power Research Institute

This paper introduces an optimal consensus control scheme for nonlinear multi-agent systems with completely unknown dynamics. In general, it is difficult to solve the coupled Hamilton-Jacobi-Bellman（HJB） equations, which the optimal consensus control relies on in multi-agent systems, especially unknown nonlinear systems. for the purpose of solving the problem, we propose an optimal consensus control approach based on the model reference adaptive control（MRAC） and adaptive dynamic programming（ADP）. Using the structure of the diagonal recurrent neural network, the identifier and controller are devised to achieve MRAC for every plant of the unknown nonlinear systems, i.e. the reference model serves as a dynamic model of each individual agent. Then, according to reference models of distributed agents, an adaptive dynamic programming（ADP）is introduced to approximate the solution of the coupled HJB equations.

关键词： Multi-agent systems optimal consensus model reference adaptive control adaptive dynamic programming

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Fast Satellite Selection Algorithm Based on Satellite Elevation Angle and Satelte Contribution for Geometry Dilution of Precision in GPS/BEIDOU

Fast Satellite Selection Algorithm Based on Satellite Elevat...

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第37届中国控制会议

作者： Guangjun Wang Jianjin Jiang School of Automation China University of Geosciences China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex System

In order to solve the contradiction between positional accuracy and real-time in satellite navigation system, a fast satellite selection algorithm based on satellite elevation angle and satellite contribution for Geometry Dilution of Precision（GDOP） in GPS/BEIDOU is proposed, which dependents on the high dynamic GPS/BEIDOU receiver developed by our laboratory. Through compared with the existing algorithm by real data simulation, our proposed algorithm has the smaller positional error in the X, Y, Z direction and lower complexity. As a result, we can prove that the proposed method has the feasibility and better real-time performance.

关键词： GPS/BEIDOU elevation angle satellite contribution value satellite selection

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Hexagon-Shaped Screw Recognition and Positioning System Based on Binocular Vision

Hexagon-Shaped Screw Recognition and Positioning System Base...

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第37届中国控制会议

作者： Fang Wang Xin Chen Chang Tan Jinbin Li Yaodong Zhang School of Automation China University of Geoscience Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems State Grid Hubei Electric Power Research Institute

Traditional artificial live work asks for a high standard with operator’s mental state and technical level in high-voltage and strong-magnetic environment,which not only reduces the efficiency of modern production and living but also causes potential threats to the safety of ***,developing robot live work has great significance for both academic research and industrial applications.A key problem of the live work for an industrial robot is recognition and positioning of the hexagonshaped screw in substation with high *** solve this problem,this article designs a hexagon-shaped screw recognition and positioning system based on binocular vision in transformer substation.A method for stereo matching including 3 steps is proposed:edge noise of the target is reduced by median filter at the beginning;then the target can be obtained through the image segmentation method of adjusting threshold;further moments are used to express the centers of hexagons in 2 images which work as stereo matching *** depth information can be obtained due to visual geometric relationships based on stereo model and camera calibration parameters based on camera *** experiment results show that the binocular system designed in this article can accurately identify the target with good stability,and the measurement error is controlled in 4%.

关键词： Binocular stereo vision Image segmentation Stereo matching Depth information

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Calculation Method of Load Distribution for Two-crane Cooperative Lift

Calculation Method of Load Distribution for Two-crane Cooper...

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第37届中国控制会议

作者： Xiaoling Shen Jianqi An Takao Terano School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Cooperative lifting by two cranes is widely used in the current construction site. Since the influence of changeable load in the cooperative lifting process, it is essential to take the load distribution into consideration while planning the lifting path to ensure the safety of the whole lifting process. However, most researches did not consider the reasonable actual load distribution or just used a certain load in the lift process. This paper analyzes the relationship between crane operations and the pose of the lifted object. Then based on this relationship, this paper gives the method calculating the distribution of actual load over each crane that the planning approach is based. This paper also gives calculation methods and constraints for the skew angle of each lifting rope. The results of simulation show the effectiveness of this calculation method.

关键词： Cooperative Lifting Actual Load Calculation

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An intelligent Selection Strategy for Burden Distribution Based on Classification of Blast Furnace Condition

An intelligent Selection Strategy for Burden Distribution Ba...

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第37届中国控制会议

作者： Kexin Zhang Min Wu Jianqi An School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

Burden distribution plays an important role in the optimization of energy-consuming index of a blast furnace(BF).However, due to the low transparency of this process, operators adjust the burden distribution according to their own experiences,which makes it difficult to keep optimal production indexes for a BF. In this paper, an intelligent selection strategy of burden distribution is devised according to the energy-consuming index, where carbon-monoxide utilization rate(CMUR) is taken as the energy-consuming index. First, state variables are chosen based on the calculated Pearson correlation coefficient among each state variable. Then, the chosen state variables are divided into five clusters by k-means clustering algorithm. Finally, the values of CMUR in each condition cluster with different burden distribution are counted. According to the statistics, the burden distribution with the highest CMUR is judged to be the optimal one. Simulation results based on industrial data show that the proposed strategy selects the optimal burden distribution and provides a reasonable guide for the operators.

关键词： Burden distribution blast furnace k-means carbon-monoxide utilization rate

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