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Hierarchical and Networked Vehicle Surveillance in ITS: A Survey

IEEE TRANSACTIONS ON intelligent TRANSPORTATION systems 2015年第2期16卷 557-580页

作者： Tian, Bin Morris, Brendan Tran Tang, Ming Liu, Yuqiang Yao, Yanjie Gou, Chao Shen, Dayong Tang, Shaohu Inst Automat State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Univ Nevada Dept Elect & Comp Engn Las Vegas NV 89154 USA Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China North China Univ Technol Beijing Key Lab Urban Intelligent Traff Control T Sch Mech & Elect Engn Beijing 100041 Peoples R China

Traffic surveillance has become an important topic in intelligent transportation systems (ITSs), which is aimed at monitoring and managing traffic flow. With the progress in computer vision, video-based surveillance systems have made great advances on traffic surveillance in ITSs. However, the performance of most existing surveillance systems is susceptible to challenging complex traffic scenes (e.g., object occlusion, pose variation, and cluttered background). Moreover, existing related research is mainly on a single video sensor node, which is incapable of addressing the surveillance of traffic road networks. Accordingly, we present a review of the literature on the video-based vehicle surveillance systems in ITSs. We analyze the existing challenges in video-based surveillance systems for the vehicle and present a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques. Then, different methods are reviewed and discussed with respect to each module. Applications and future developments are discussed to provide future needs of ITS services.

关键词： Behavior understanding computer vision networked surveillance system traffic surveillance vehicle detection vehicle tracking

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Coordinated Transportation of a Group of Unmanned Ground Vehicles

Coordinated Transportation of a Group of Unmanned Ground Veh...

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第三十四届中国控制会议

作者： Yunpeng Wang Long Cheng Zeng-Guang Hou Min Tan Hongnian Yu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Faculty of Science and Technology Bournemouth University

ISBN: (纸本)9781467374439

This paper studies a coordinated transportation problem of a group of unmanned ground vehicles(UGVs). These ground vehicles belong to two categories: master vehicles and slave vehicles. A two-step strategy is proposed to solve this problem. First, let the master vehicles move along ideal trajectories. Then, let the slave vehicles move into the area surrounded by master vehicles and move together with them. By the two-step strategy, the coordinated transportation problem is divided into a tracking problem and a containment problem. A P In-type tracking protocol and a P In-type containment protocol(P and I stand for Proportion and Integration, respectively;Inimplies that the protocol includes high-order integral terms) are proposed to solve these two problems. It is proved that the coordinated transportation problem can be solved by two proposed protocols with proper parameters if for each follower there exists at least one leader which has a directed path to this follower. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed algorithms.

关键词： Coordinated transportation,Polynomial trajectory,Containment control,Multi-agent system.

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Obstacle Avoidance for Kinematically Redundant Robot

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IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators System stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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A Method of SMS Spam Filtering Based on AdaBoost Algorithm

A Method of SMS Spam Filtering Based on AdaBoost Algorithm

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World Congress on intelligent control and Automation

作者： Xipeng Zhang Gang Xiong Yuexiang Hu Fenghua Zhu Xisong Dong Timo R. Nyberg State Key Laboratory of Management and Control for Complex Systems Institute of Automation of Chinese Academy of Science Beijing CO 100190 China Cloud Computing Center Chinese Academy of Sciences Dongguan CO 523000 China Hainan Zhongke Flower Ocean Cloud Commerce Technology Co. Ltd Haikou CO570311 Hainan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing CO 100190 China Qingdao Academy of Intelligent Industries Qingdao CO 266061 China Department of Industrial Engineering and Management Aalto University Aalto CO FI-00076 Finland

ISBN: (纸本)9781467384155

Short message is one of the most common communication media for mobile subscribers, so major mobile operators are devoted to improve their Short Message Service (SMS). However, the annoying and undesired messages, also named message spam or simply spam, not only worsen the users' experience, but also cause their complaints on SMS. In this paper, we present a novel Chinese SMS spam filtering framework based on AdaBoost algorithm to provide accurate and effective short messages classification. Three content-based weak filters are introduced to boost the performance of final classification decision. Results from Receiver Operating Characteristics (ROC) analysis prove the proposed method has such advantages as higher efficiency and fewer parameters over those established SMS spam filtering methods. The application of the proposed method is expected to block the most spam for mobile subscribers and improve the service quality of SMS. With simple data processing and few training parameters, the proposed method can be applied into the practice of short text classification.

关键词： Filtering Mobile communication Training Unsolicited electronic mail Classification algorithms Text categorization Bayes methods

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Path Planning and Decision Making for Autonomous Vehicle in Urban Environment

Path Planning and Decision Making for Autonomous Vehicle in ...

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International Conference on intelligent Transportation

作者： Mengyin Fu Wenjie Song Yang Yi Meiling Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Beijing P. R. China State Key Lab. of Intell. Control & Decision of Complex Syst. Beijing Instn. of Technol. China

ISBN: (纸本)9781467365970

In this paper, we focus on the need for autonomous vehicles' path planning and decision making in the urban environment. In our modified method, traffic lanes, road edge and geographic information system(GIS) are integrated to generate three structured road models, which can be used to reduce car's lateral positioning error and guarantee car's driving stably without a precise pre-computed map for localization. Based on these models, car's position, attitude and speed are taken into account to find an optimal guided path and a suitable behavior strategy to keep our car obeying traffic rules. Thus, in the whole architecture, the instability of some modules' detection results and low positioning accuracy of GPS receiver is resolved. Applied to our autonomous vehicle - IN 2 BOT, which has taken part in "Chinese intelligent Vehicle Challenge" for many times, this method is proved more effective than our previous method after experiments under various conditions.

关键词： Path planning Roads Vehicles Decision making Planning Mobile robots Image edge detection

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Time-varying universe based linguistic dynamic analysis of timing design for parallel traffic light

Time-varying universe based linguistic dynamic analysis of t...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Hong Mo Fei-Yue Wang Fenghua Zhu School of Electrical and Information Engineering Changsha University of Science and Technology Changsha CN State Key Lab. of Management and Control for Complex Systems Institute of Automation CN

Reasonable timing design for traffic light can induce and maintain the transportation systems in good order. How to allocate the time are the keys. In the paper, the theory of time-varying universe is used to describe the circle time, and corresponding fuzzy sets on the universe are also discussed to modeling the situation of traffic flow, then the parallel traffic management and control methods which are dynamic with the time change are presented. A simulation example are provided to analyze the linguistic dynamic evolution of timing design of traffic light when the traffic flow is change with time-varying for an intersection.

关键词： Timing Pragmatics Vehicle dynamics Fuzzy sets complex systems Vehicles

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Leader-Following Consensus of Discrete-Time Linear Multi-Agent systems with Communication Noises

Leader-Following Consensus of Discrete-Time Linear Multi-Age...

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第三十四届中国控制会议

作者： Yunpeng Wang Long Cheng Hongming Wang Zeng-Guang Hou Min Tan Hongnian Yu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology China North Vehicle Research Institute Faculty of Science and Technology Bournemouth University

ISBN: (纸本)9781467374439

This paper studies the leader-following consensus problem of discrete-time generic linear multi-agent systems. Agents share their states with their neighbors via a noisy communication network. An algorithm is proposed for the leader-following consensus problem where the time-varying gain is employed to attenuate noises. Different from most previous results where all agents have to use the same time-varying gain, each agent can have its own time-varying gain. Sufficient conditions for solving the mean square leader-following consensus problem are obtained: 1) the communication topology graph has a spanning tree;2) the summation of every time-varying gain from zero to infinite is infinite;3) all time-varying gains are infinitesimal of the same order as time goes to infinity;and 4) all roots of a so-called "parameter polynomial" are inside the unit circle. Finally, a simulation example is given to verify the theoretical results.

关键词： Multi-Agent system,Leader-following consensus,Mean square,Communication noise.

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Large scale online kernel learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Jing Lu Steven C. H. Hoi Jialei Wang Peilin Zhao Zhi-Yong Liu Google MPI for Intelligent Systems School of Information Systems Singapore Management University Singapore Department of Computer Science University of Chicago Chicago IL Institute for Infocomm Research A*STAR Connexis Singapore State Key Lab of Management and Control for Complex System Chinese Academy of Sciences Beijing China

In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalab.e for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalab.e. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.

关键词： kernel approximation large scale machine learning online learning

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Paragraph Vector Based Retrieval Model for Similar Cases Recommendation

Paragraph Vector Based Retrieval Model for Similar Cases Rec...

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第六届全国语言动力系统研讨会

作者： Yifei Zhao Jing Wang Fei-Yue Wang Xiaobo Shi The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chine Institute of Smart Healthcare System Qingdao Academy of Intelligent Industries Qingdao China

Internet inquiry is playing an increasingly important role as the complement of the traditional medical service system,especially the similar cases *** can not only save the patients' waiting time,but also make use of the historical resources,for many cases with the same purpose have been solved ***,because of the diversity and non-standard of the patients' descriptions,the inquiry platform cannot find the cases with similar semantic *** traditional retrieval methods require the overlap of two sentences,and this is not suitable with the diversity and non-standard *** this paper,we try to utilize the sentences' semantic representation in a continuous space to understand the cases,and then recommend the similar *** also incorporate it into query likelihood language models,trying to get better *** experimental data are all collected from a real internet inquiry platform,and the results show that our methods significantly outperform the state-of-the-art translation based methods for similar cases recommendation.

关键词： internet inquiry similar cases recommendation distributed representation data mining

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Shared control for teleoperation enhanced by autonomous obstacle avoidance of robot manipulator

Shared control for teleoperation enhanced by autonomous obst...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Xinyu Wang Chenguang Yang Hongbin Ma Long Cheng Centre for Robotics and Neural Systems Plymouth University Plymouth UK State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Ministry of Education South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effector motion performance. An improved obstacle avoidance strategy based on the joint space redundancy of the manipulator is designed. A dimension reduction method is presented to solve the over defined problem of avoiding velocity to achieve a more efficient use of the redundancy. By employment of an artificial parallel system of the teleoperate manipulator and the task switching weighting factor, the proposed control method enable the robot restoring back to the commanded pose smoothly when the obstacle is removed. By implementing the dimension reduction method, the trajectory of each joint of the manipulator can be controlled at the same time to achieve the restoring task. Thus, the proposed control method can eliminate the impact of the obstacle on the remaining task. Satisfactory experiment results demonstrate the effectiveness of the proposed methods.

关键词： Manipulators Collision avoidance Robot kinematics Trajectory Kinematics Robot sensing systems

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