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Visual Scenes Mining for Agent Awareness Module 1

17th Industrial Conference on Data Mining (ICDM)

作者： Ma, Gang Tang, Zhentao Yang, Xi Shi, Zhongzhi Yang, Kun Chinese Acad Sci Inst Comp Technol Key Lab Intelligent Informat Proc Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Normal Univ Beijing Adv Innovat Ctr Future Educ Beijing Peoples R China Natl Inst Metrol Beijing 100029 Peoples R China

ISBN: (数字)9783319627014

ISBN: (纸本)9783319627014;9783319627007

Most agents obtain knowledges from natural scenes through some single preestablished rules. In practice, those single rules can't achieve the aim to freely awareness the natural scenes, such as the visual scenes. Inspired by biological visual cortex (V1) and higher brain areas perceiving visual features, in this paper we propose an improved visual awareness module, called as visual scenes mining module, for the agent ABGP-CNN in order to directly mine the visual scenes information. Then ABGP-CNN with the visual scenes mining module is deployed on a toy car. The visual information mining from the nature scenes is served as the knowledges of the agent ABGP-CNN to drive the toy car. The toy car deployed the agent ABGP-CNN can easily understand the special natural visual scenes, and has the ability to plan its behaviors according to the visual information mining from the nature scenes. The application of the agent ABGP-CNN with visual scenes mining module enhances the capability of communication between the toy car and the natural visual scenes.

关键词： Agent Visual Scenes Mining ABGP-CNN

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Mixed Iterative Adaptive Dynamic Programming for Optimal Battery Energy control in Smart Residential Microgrids

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2017年第5期64卷 4110-4120页

作者： Wei, Qinglai Liu, Derong Lewis, Frank L. Liu, Yu Zhang, Jie Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Univ Texas Arlington UTA Res Inst Arlington TX 76118 USA Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Shandong Peoples R China

In this paper, a novel mixed iterative adaptive dynamic programming (ADP) algorithm is developed to solve the optimal battery energy management and control problem in smart residential microgrid systems. Based on the data of the load and electricity rate, two iterations are constructed, which are P-iteration and V-iteration, respectively. The V-iteration is implemented based on value iteration, which aims to obtain the iterative control law sequence in each period. The P-iteration is implemented based on policy iteration, which updates the iterative value function according to the iterative control law sequence. Properties of the developed mixed iterative ADP algorithm are analyzed. It is shown that the iterative value function is monotonically nonincreasing and converges to the solution of the Bellman equation. In each iteration, it is proven that the performance index function is finite under the iterative control law sequence. Finally, numerical results and comparisons are given to illustrate the performance of the developed algorithm.

关键词： Adaptive critic designs adaptive dynamic programming (ADP) approximate dynamic programming mixed iteration optimal control policy iteration smart grid value iteration

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-Rao bound

arXiv

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arXiv 2017年

作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. Digital Tech. Center ECE Dept. U. of Minnesota MplsMN55455 United States State Key Lab. of Intelligent Control and Decision of Complex Systems Beijing Inst. of Tech. Beijing100081 China

Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis is a special case of PSSE, and amounts to solving a set of noise-free power flow equations. Physical laws dictate quadratic relationships between availab.e quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradienttype schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming (QCQP) reformulation of the weighted least-squares (WLS) problem. Relative to the prior art, the developed solvers offer superior performance at the cost of higher complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound (CRLB) is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPPbased solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： state estimation

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Coordination of Multiple Robotic Fish With Applications to Underwater Robot Competition

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2016年第2期63卷 1280-1288页

作者： Yu, Junzhi Wang, Chen Xie, Guangming Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Peking Univ Coll Engn Intelligent Control Lab Beijing 100871 Peoples R China

This paper is concerned with the coordination control of multiple biomimetic robotic fish in highly dynamic aquatic environments by building a hybrid centralized system. With the aid of the results of biorobotics and control techniques, a radio-controlled multijoint robotic fish and its locomotion control are developed. To enable a closed control loop, a visual subsystem that is responsible for tracking of multiple moving objects is constructed and implemented in real time. Furthermore, a behavior-based hierarchical architecture in conjunction with fuzzy reinforcement learning is proposed to accomplish effective coordination among multiple swimming robots. Finally, experiments on 2vs2 water polo game are carried out to verify the proposed coordination control scheme. Over the past eight years, this multirobot platform has been successfully applied to international underwater robot competitions to promote innovative research and education in underwater robotics.

关键词： Coordination control multirobot system robotic fish underwater robot competition

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Memetic Algorithm with adaptive Local Search for Capacitated Arc Routing Problem 20

Memetic Algorithm with adaptive Local Search for Capacitated...

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20th IEEE International Conference on intelligent Transportation systems (ITSC)

作者： Yao, Tingting Yao, Xin Han, Shuangshuang Wang, Yingchun Cao, Dongpu Wang, Feiyue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266111 Shandong Peoples R China Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England Qingdao Huituo Intelligent Machine Co Qingdao 266111 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China

ISBN: (纸本)9781538615263

The Capacitated Arc Routing Problem (CARP) is a challenging combinatorial optimization problem with wide real world applications. Since CARP is NP-hard, many heuristic and meta-heuristic approaches have been applied to solve CARP. In this paper, a novel extension memetic approach, named MAENSPls is proposed to improve the state-of-the-art algorithm-Memetic Algorithm with Extended Neighbourhood Search (MAENS) for CARP, in which using an adaptive probability to optimize the frequency and depth of local search. Based on the parameter optimization on all the 8 instances, experimental studies show that the proposed algorithm can significantly improve the average performance of MAENS, and there is an increase in the robust stability and convergence reliability. Furthermore, 4 new best known solutions are found by the proposed algorithm.

关键词： Capacitated Arc Routing Problem (CARP) Memetic Algorithm Extended Neighbourhood Search Adaptive Probability Frequency and Depth of Local Search.

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Design of Low-cost Position Differential Positioning System Based on STM32

Design of Low-cost Position Differential Positioning System ...

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Chinese Automation Congress

作者： Haijun Fu Ming Qiu Xisong Dong Gang Xiong Haonan Xiong Xiang Su Shichao Chen Zhen Shen Xiujiang Guo School of Artificial Intelligence Beijing Union University Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China The Qingdao Academy of Intelligent Industries Macau University of Science and Technology Qingdao China Beijing Union University Beijing China School of Electrical Engineering and Electronic Information Xihua University Chengdu China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Helsinki Fin Finland Measurement Center Station PetroChina Huabei Oilfield Company Renqiu China

There exist some obstacles to realize high-precision positioning with using the position differential technique due to the limiting factors. However, with the advancement of chip performance and the establishment of multiple satellite navigation systems, position differential positioning can be realized to meet the civilian high-precision positioning demand while significantly reducing costs. This paper is to explore the engineering application and propose a new method. Through the experiments and data analysis, we have found the error correlation between two receivers in a small area and designed a set of positioning system, and programmed in the Keil μVision5 in C language. The system consists of the current mainstream low-cost STM32, UBLOX NEO 6M chip, NRF24L01 chip, GPS antenna and power supply module. Each two receivers can form a differential positioning system. At present, the system in the low-speed status is, in the urban environment, basically reaching within 0.5 - 3 m of the positioning error.

关键词： Position differential positioning Low cost Error correlation GPS STM32

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Parallel Imaging: A Unified Theoretical Framework for Image Generation

Parallel Imaging: A Unified Theoretical Framework for Image ...

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Chinese Automation Congress (CAC)

作者： Wang Kunfeng Lu Yue Wang Yutong Wang Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Parallel Vis Innovat Technol Ctr Qingdao 266000 Peoples R China Univ Chinese Acad Sci Sch Comp & Control Engn Beijing 100049 Peoples R China Natl Univ Def Technol Res Ctr Computat Expt & Parallel Syst Technol Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781538635247

In order to build computer vision systems with good generalization capability, one usually needs large-scale, diversified lab.led image data for learning and evaluating the in hand computer vision models. Since it is difficult to obtain satisfactory image data from real scenes, in this paper we propose a unified theoretical framework for image generation, called parallel imaging. The core component of parallel imaging is software-defined artificial imaging systems. Artificial imaging systems receive small-scale image data collected from real scenes, and then generate large amounts of artificial image data. In this paper, we survey the realization methods of parallel imaging, including graphics rendering, image style transfer, generative models, and so on. Furthermore, we compare the properties of artificial images and actual images, and discuss the domain adaptation strategies.

关键词： Parallel Imaging Model Learning Graphics Rendering Image Style Transfer Generative Models

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Training and testing object detectors with virtual images

arXiv

引用

arXiv 2017年

作者： Tian, Yonglin Li, Xuan Wang, Kunfeng Wang, Fei-Yue Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive lab.led data. However, collecting and annotating images from the real world has a great demand for lab.r and money investments and is usually too passive to build datasets with specific characteristics, such as small area of objects and high occlusion level. Under the framework of Parallel Vision, this paper presents a purposeful way to design artificial scenes and automatically generate virtual images with precise annotations. A virtual dataset named ParallelEye is built, which can be used for several computer vision tasks. Then, by training the DPM (Deformable Parts Model) and Faster R-CNN detectors, we prove that the performance of models can be significantly improved by combining ParallelEye with publicly availab.e real-world datasets during the training phase. In addition, we investigate the potential of testing the trained models from a specific aspect using intentionally designed virtual datasets, in order to discover the flaws of trained models. From the experimental results, we conclude that our virtual dataset is viable to train and test the object detectors. Copyright © 2017, The Authors. All rights reserved.

关键词： Object detection

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Solving Large-scale systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow

Solving Large-scale Systems of Random Quadratic Equations vi...

引用

European Signal Processing Conference

作者： Gang Wang Georgios B. Giannakis Jie Chen Dept. of ECE and Digital Tech. Center Univ. of Minnesota Mpls MN USA State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

This work develops a new iterative algorithm, which is called stochastic truncated amplitude flow (STAF), to recover an unknown signal x ∈ R~n from m "phaseless" quadratic equations of the form ψ_i = |a_i~T x|, 1 ≤ i ≤ m. This problem is also known as phase retrieval, which is NP-hard in general. Building on an amplitude-based nonconvex least-squares formulation, STAF proceeds in two stages: s1) Orthogonality-promoting initialization computed using a stochastic variance reduced gradient algorithm;and, s2) Refinements of the initial point through truncated stochastic gradient-type iterations. Both stages handle a single equation per iteration, therefore lending STAF well to Big Data applications. Specifically for independent Gaussian {a_i}_(i=1)~m vectors, STAF recovers exactly any x exponentially fast when there are about as many equations as unknowns. Finally, numerical tests demonstrate that STAF improves upon its competing alternatives.

关键词： Stochastic processes Signal processing algorithms Runtime Mathematical model Computational complexity Europe Signal processing

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Modified K-best Receiver for Multi-antenna Vehicular Networks 20

Modified K-best Receiver for Multi-antenna Vehicular Network...

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20th IEEE International Conference on intelligent Transportation systems (ITSC)

作者： Han, Shuangshuang Zhu, Fenghua Wang, Yingchun Cao, Dongpu Xiong, Gang Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Shandong Peoples R China Chinese Acad Sci Cloud Comp Ctr Dongguan 523808 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China Cranfield Univ Ctr Automot Engn Cranfield MK43 0AL Beds England

ISBN: (纸本)9781538615263

Nowadays, with the fast growth of Internet of Vehicles (IoV), wireless communication techniques for IoV is becoming more and more important for vehicular networks. To achieve more reliable information and reduce the computational complexity, receiver detection is one of the most significant techniques. In this paper, several modified K-best detection algorithms are developed to take advantages of the list decoder, which provide a flexible performance and complexity trade-off. Different from the existing algorithms, the proposed K-best algorithms could make use of the a priori probability to generate the list. Simulation results demonstrate that the proposed low complexity algorithms can achieve a significant performance gain over existing ones, especially for the networks with high order constellations.

关键词： Approximation algorithms complexity theory Decoding MIMO communication Iterative decoding Receivers Transmitting antennas

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