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A general robot environment understanding approach inspired by biological visual cortex

A general robot environment understanding approach inspired ...

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IEEE International Conference on Robotics and Biomimetics

作者： Xilong Liu Zhiqiang Cao Jile Jiao Kun Ai Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479927456

A general vision approach for environment understanding of mobile robot is proposed, which is inspired by biological visual cortex. Gray level image from robot camera is firstly processed in the selective attention layer, and then in S and C layers for meaningful structure elements. With the help of the Sc layer designed for endpoints detection, the line segments map is generated to serve as the form of environment understanding results. Experiments on mobile robot are implemented by the task of avoiding obstacles with different sizes and shapes, pits, sharp cliffs, et al. The experimental results demonstrate the adaptability and versatility of the proposed approach.

关键词： Visualization Sensors Object segmentation Collision avoidance Image segmentation Mobile robots

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Optimized neural network ensemble by combination of particle swarm optimization and differential evolution

Optimized neural network ensemble by combination of particle...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Zhao, Zeng-Shun Feng, Xiang Wei, Fang Wang, Shi-Ku Cao, Mao-Yong Hou, Zeng-Guang College of Information and Electrical Engineering Shandong University of Science and Technology Qingdao 266590 China School of Control Science and Engineering Shandong University Jinan 250061 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642390647

The Neural-Network Ensemble (NNE) is a very effective method where the outputs of separately trained neural networks are combined to perform the prediction. In this paper, we introduce the improved Neural Network Ensemble (INNE) in which each component forward neural network (FNN) is optimized by particle swarm optimization (PSO) and back-propagation (BP) algorithm. At the same time, the ensemble weights are trained by Particle Swarm Optimization and Differential Evolution cooperative algorithm(PSO-DE). We take two obviously different populations to construct our algorithm, in which one population is trained by PSO and the other is trained by DE. In addition, we incorporate the fitness value from last iteration into the velocity updating to enhance the global searching ability. Our experiments demonstrate that the improved NNE is superior to existing popular NNE. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Iterative methods

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Identifying peer influence in online social networks using transfer entropy

Identifying peer influence in online social networks using t...

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Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2013

作者： He, Saike Zheng, Xiaolong Zeng, Daniel Cui, Kainan Zhang, Zhu Luo, Chuan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Management Information System University of Arizona Tucson AZ 85719 United States School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9783642396922

The past few years have witnessed the rapid growth of online social networks, which have become important hubs of social activity and conduits of information. Identifying social influence in these newly emerging platforms can provide us with significant insights to better understand the interaction behaviors among online users. However, it is difficult for us to measure the influence quantitatively among user peers, since many key factors such as homophily and heterogeneity, can not be observed in our real world conveniently. More recent work mainly focuses on developing theoretical models based on explicit causal knowledge. Nevertheless, such knowledge is usually not available and often needs to be discovered. In this paper, we introduce a model free approach to formulate causal inferences of behaviors among user peers. Experimental results show that influence measured by our approach could successfully reconstruct the underlying networks structure. Furthermore, two additional case studies based on this approach reveal that influentials wield power through specific venues, which constitute a comparatively small portion of the whole channels. © 2013 Springer-Verlag.

关键词： Social networking (online)

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Generalized adaptive dynamic programming algorithm for discrete-time nonlinear systems: Convergence and stability analysis

Generalized adaptive dynamic programming algorithm for discr...

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International Conference on Information Science and Technology (ICIST)

作者： Derong Liu Qinglai Wei State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467327626

This paper is concerned with a generalized iterative adaptive dynamic programming (ADP) algorithm for discrete-time nonlinear systems. The idea is to use iterative ADP algorithm to obtain iterative control laws which make the iterative performance index function reach the optimum. It is proved that for an arbitrary positive semi-definite function, the iterative performance index functions will converge to the optimum. For different initial functions, it shows that the convergence procedures of the iterative performance index functions are different. Stability properties of the system are analyzed in this paper to show that the iterative control can stabilize the system for suitable initial performance index functions. Admissible control properties of the iterative control laws obtained by the present generalized iterative ADP algorithm are also given in this paper.

关键词： ADP Convergence Stability Analysis Stability analysis Automatic data processing Adenosine Diphosphate Converge performance indicators Iterative control law Optimum Nonlinear systems

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The embedded image capture and processing system based on PC104 and FPGA

The embedded image capture and processing system based on PC...

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Chinese control Conference (CCC)

作者： Yu Wang Shuo Wang Chao Zhou State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

In this paper, an image capture and processing system based on PC104 and FPGA is designed. The communication between PC104 and FPGA is achieved by PC104-PLUS bus. The FPGA co-processor accomplishes the image capture of CMOS camera and image pretreatment. The PC104 controller, as an upper computer monitor,realizes feature point detection based on LSD line detector and Camshift target tracking algorithm based on the color. Based on the design of the image capture and processing system, the concrete implementation scheme of the image capture and processing system is proposed. And the practicability of our image capture and processing system is demonstrated by feature point detection of a color mark and target tracking algorithm.

关键词： Field programmable gate arrays CMOS integrated circuits Feature extraction Target tracking SDRAM Electronic mail Process control

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Data-based vehicle adaptive cruise control: A review

Data-based vehicle adaptive cruise control: A review

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Chinese control Conference (CCC)

作者： Dongbin Zhao Bin Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Based on the conventional cruise control, vehicle adaptive cruise control (ACC) measures the distance and the relative velocity to the preceding vehicle real time via distance sensor, computes appropriate control output with respect to throttle or brake pedal, and control the velocity or headway automatically. Under the basically security guarantee, ACC could improve the comfort and reduce fuel consumption. This paper comprehensively investigates the theory and technology for ACC of last decades. We conclude the main approach of modeling, control and optimization of ACC, and note that data-based ACC system which conforms driver character and habit has been a new trend.

关键词： Vehicles Adaptation models control systems Adaptive systems Conferences Predictive models Electronic mail

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An approach to remote update driver system of a robotic fish with two long fins

An approach to remote update driver system of a robotic fish...

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Chinese control Conference (CCC)

作者： Qingping Wei Shuo Wang Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

The robotic fish with two long fins is one kind of underwater robot system imitating stingray's motion. The robotic fish generates thrust by use of two long fins located on both sides of body symmetrically. A driver control system for the motion control of fin rays is designed based on FPGA(Field Programmable Gate Array). Several kinds of motion modes can be achieved through tuning motion parameters. In order to facilitate updating control algorithm, reducing the probability of damaging the robot system and improving debugging efficiency, a solution for remote updating the driver program of the robotic fish wirelessly is proposed in this paper based on the dedicated remote system update circuitry integrated in ALTERA FPGA. In addition, a remote update system is designed in this paper. The designed control program updating system facilitates the debugging and optimization of multi-fin coordination control algorithm for the robotic fish with two long fins greatly.

关键词： Field programmable gate arrays Robot kinematics Light emitting diodes Marine animals control systems Ash

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sEMG based joint angle estimation of lower limbs using LS-SVM

sEMG based joint angle estimation of lower limbs using LS-SV...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Li, Qingling Song, Yu Hou, Zengguang Zhu, Bin Department of Mechanical Engineering China University of Mining and Technology Beijing China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science Beijing China

ISBN: (纸本)9783642420535

In this paper, a new estimation model based on least squares support vector machine (LS-SVM) is proposed to build up the relationship between Surface electromyogram (sEMG) signal and joint angle of the lower limb. The input of the model is 2 channels of preprocessed sEMG signal. The outputs of the model are joint angles of the hip and the knee. sEMG signal is acquired from 7 motion muscles in treadmill exercise. And two channels of them are selected for dynamic angle estimation for their strong correlation with angle data. Angle estimation model is constructed by 2 independent LS-SVM based regression model with radial basis function (RBF). It is trained using part of the sample sets acquired in 10s exercise duration and test by all data. Experimental result shows proposed method has good performance on joint angles estimation based sEMG. Root mean square error (RMSE) of prediction knee and hip joint angles is 3.02° and 2.09° respectively. It provide new human-machine interface for active rehabilitation training of SCI, stroke or neurological injury patients. © Springer-Verlag 2013.

关键词： Patient rehabilitation

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A learning optimal control scheme for robust stabilization of a class of uncertain nonlinear systems

A learning optimal control scheme for robust stabilization o...

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Chinese control Conference (CCC)

作者： Ding Wang Derong Liu Hongliang Li Xiong Yang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

In this paper, a novel learning optimal control scheme is established to design the robust controller of a class of uncertain nonlinear systems. The robust control problem is transformed into the optimal control problem by properly choosing a cost function that reflects the uncertainty, regulation, and control. Then, the online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman (HJB) equation by introducing a critic neural network. The approximate expression of the optimal control policy can be derived directly. Moreover, the closed-loop system is proved to be uniformly ultimately bounded. The equivalence of the neural-network-based HJB solution of the optimal control problem and the solution of the robust control problem is developed as well. Finally, an example is provided to verify the effectiveness of the constructed approach.

关键词： Optimal control Cost function Robust control Equations Approximation methods Nonlinear systems Uncertainty

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Consensus tracking of general linear multi-agent systems: Fast sliding-mode algorithms

Consensus tracking of general linear multi-agent systems: Fa...

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Chinese control Conference (CCC)

作者： Huiyang Liu Long Cheng Min Tan Zengguang Hou Yunpeng Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

This paper solves distributed consensus tracking problems where the task is to make the multi-agent network, with each agent described by a general linear dynamics, to reach consensus with a leader whose control input is nonzero and not available to any followers. A set of sliding mode surfaces are defined and then fast sliding mode controllers are designed for both reduced order and non-reduced order cases. It is shown that all the trajectories exponentially converge to the sliding mode surfaces in a finite time if the leader has a directed path to at least one of the followers in a strongly connected and detailed balanced directed interaction graph and the leader's control input is bounded. The control Lyapunov function for exponential finite time stability, motivated by the fast terminal sliding mode control, is used to prove the reachability of the sliding mode surfaces. Simulation examples are given to illustrate the theoretical results.

关键词： Multi-agent systems Sliding mode control Trajectory Lead Manifolds Lyapunov methods Convergence

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