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2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Zhang, Jing Miao, Lei Wu, Re-Bing Xi, Ning Li, Chun-Wen Wang, Yue-Chao Tarn, Tzyh-Jong Department of Automation Tsinghua University Beijing 100084 China Center for Quantum Information Science and Technology Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Beijing 110016 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 United States Department of Electrical and Systems Engineering Washington University St. Louis MO 63130 United States

ISBN: (纸本)9781424470334

When a micro cantilever with a nanoscale tip is manipulated on a substrate with atomic roughness, e.g., pushing an atomic-scale sample or etching the surface of the substrate to draw desired patterns, the periodical lateral frictional forces with stochastic fluctuations will induce stick-slip motion of the cantilever tip, which may greatly influence the precision of the nano manipulation. To reduce such a stick-slip motion, we propose a feedback control strategy based on the position estimation of the cantilever tip to compensate the periodical frictional force. Numerical simulations show that the motion of the cantilever tip under feedback control can track the desired trajectory asymptotically. Our proposal can aL be extended to the case when the cantilever tip moves over a Gaussian-shape defection on the substrate and when the stochastic fluctuations in the lateral force are with non-zero correlation time. ©2010 IEEE.

关键词： Feedback control

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Evolutionary Self-learning Scheduling Approach for Wireless Sensor Network

Evolutionary Self-learning Scheduling Approach for Wireless ...

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2010 International Conference on Intelligent Computation Technology and automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

作者： Jianjun Niu State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China Beijing Special Engineering Design and Resear

Energy efficiency is very important for wireless sensor network (WSN). This paper presents an evolutionary self-learning scheduling approach (ESSA) to reduce energy consumption for WSN. The ESSA is based on a new proposed scheme - evolutionary Q-learning with continuousaction (EQC) approach, which combines an extension of Q-learning method with particle swarm optimization (PSO) algorithm. The action space of EQC is partitioned into lots of subintervals. And each endpoint of the subintervals is characterized by a discrete action value and a Q-value. The continuous action value is the weighted average of discrete actions according to their Q values. The PSO algorithm is combined to let an agent profit the experience of other agents. We valid the ESSA in a MAC protocol and simulation results show that the ESSA is an effective method and performs much better than SMAC protocol.

关键词： Wirless Sensor Network Scheduling Q-Learning Particle Swarm Optimization

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Self-learning Scheduling Approach for Wireless Sensor Network

Self-learning Scheduling Approach for Wireless Sensor Networ...

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The 2010 2nd International Conference on Future computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

ISBN: (纸本)9781424458219;9781424458240

Energy efficiency is one of key issues of wireless sensor network (VVSN). In this paper, we propose a self-learning scheduling approach (SSA) to reduce energy consumption for wireless sensor network (WSN). This approach integrates sleep scheduling together with packet transmission scheduling to reduce energy consumption. It enables nodes to learn continuous transmission parameters and sleep parameter through interacting with the WSN. The continuous value of transmission parameter is achieved by our extension of Q-learning method, and the value of sleep parameter can be calculated from the transmission parameter. We valid this approach in a MAC protocol and compare some network performances between the SSA and SMAC protocol. The simulation results show that our SSA performs much better than SMAC protocol in these QoS metrics.

关键词： Wireless sensor network scheduling reinforcement learning

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A swarm intelligence based searching strategy for articulated 3D human body tracking

A swarm intelligence based searching strategy for articulate...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Xiaoqin Zhang Weiming Hu Xiangyang Wang Yu Kong Nianhua Xie Hanzi Wang Haibin Ling Steve Maybank College of Mathematics & Information science Wenzhou University Zhejiang China Institute of Automation National Laboratory of Pattern Recognition Beijing China School of Communication and Information Engineering Shanghai University Shanghai China School of Computer Science Beijing Institute of Technology Beijing China School of Computer Science University of Adelaide Australia Department of Computer and Information Science Temple University Philadelphia USA School of Computer Science and Information Systems Birkbeck College London UK

This paper proposes an annealed particle swarm optimization based particle filter algorithm for articulated 3D human body tracking. In our algorithm, a sampling covariance and an annealing factor are incorporated into the velocity updating equation of particle swarm optimization (PSO). The sampling covariance and the annealing factor are initiated with appropriate values at the beginning of the PSO iteration, and `annealing' is carried out at reasonable steps. Experiments with multi-camera walking sequences from the Brown dataset show that: 1) the proposed tracker can effectively alleviate the problem of inconsistency between the image likelihood and the true model; 2) the tracker is also robust to noise and body self-occlusion.

关键词： Particle swarm optimization Humans Annealing Particle filters Particle tracking Sampling methods Equations Image sampling Legged locomotion Noise robustness

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Grasping simulation of an underactuated finger mechanism for larm hand

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International Journal of Modelling and Simulation 2010年第1期30卷 87-97页

作者： Yao, S. Wu, L. Ceccarelli, M. Carbone, G. Lu, Z. School of Automation Science and Electrical Engineering Beihang University Beijing China College of Information Engineering Central University for Nationalities Beijing China State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China Beijing University of Aeronautics and Astronautics China and University of Cassino Italy LARM: Laboratory of Robotics and Mechatronics Cassino United States

In this paper, the grasp operation of an underactuated finger mechanism is simulated with the aim to characterize and analyze its performance. The design of the proposed mechanism is based on spring systems that give suitable underactuation characteristics. A CAD model is proposed and then it is used in a procedure for numerical simulation. Simulation results show suitable capability for grasping a wide range of objects in size and shape by operating the mechanism inside the finger body. The achieved grasp has been simulated as a human-like functionality with a grasp contact in each phalanx.

关键词： computer aided design

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Equivalence knowledge cumularspharolith and multiple approximate reasoning in R-logic ℂR

Equivalence knowledge cumularspharolith and multiple approxi...

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2009 WRI World Congress on computer science and information Engineering, CSIE 2009

作者： Yalin, Zheng Guang, Yang Research Center of Intelligent Information Technology Department of Computer Science and Technology Dongguan University of Science and Technology Dongguan 523808 China State Key Laboratory for Intelligent Technology and Systems Department of Automation Tsinghua University Beijing 100084 China

ISBN: (纸本)9780769535074

By casting off the direct restriction of topological structure, this paper presents another matching scheme between the input A* and the knowledge A → B based on the equivalence relation on formulae set F(S) and the corresponding equivalence classification F(S)/R = {[A]R |A ∈ F(S)} therefore, obtains another algorithm of approximate reasoning - the IV-type R-algorithm. The paper presents the IV-type R-algorithm for the simple approximate reasoning model and the multiple approximate reasoning model in the frame of R-logic ℂR. © 2008 IEEE.

关键词： Knowledge based systems

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Unsupervised Maximum Margin Feature Selection with manifold regularization

Unsupervised Maximum Margin Feature Selection with manifold ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Bin Zhao James Kwok Fei Wang Changshui Zhang State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing China Department of Computer Science and Engineering HKUST Hong Kong China

Feature selection plays a fundamental role in many pattern recognition problems. However, most efforts have been focused on the supervised scenario, while unsupervised feature selection remains as a rarely touched research topic. In this paper, we propose manifold-based maximum margin feature selection (M3FS) to select the most discriminative features for clustering. M3FS targets to find those features that would result in the maximal separation of different clusters and incorporates manifold information by enforcing smoothness constraint on the clustering function. Specifically, we define scale factor for each feature to measure its relevance to clustering, and irrelevant features are identified by assigning zero weights. Feature selection is then achieved by the sparsity constraints on scale factors. Computationally, M3FS is formulated as an integer programming problem and we propose a cutting plane algorithm to efficiently solve it. Experimental results on both toy and real-world data sets demonstrate its effectiveness.

关键词： Filters Pattern recognition Clustering algorithms Face recognition Laplace equations Laboratories Linear programming Feature extraction Unsupervised learning Supervised learning

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A Structural Health Monitoring System Using Wireless Sensor Network

A Structural Health Monitoring System Using Wireless Sensor ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Jianjun Niu Zhidong Deng Fengguang Zhou Zongsheng Cao Zhanqing Liu Fangzhou Zhu State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory of Information Science and Technology Department of Computer Science and Technology Tsinghua University China Beijing Special Engineering Design and Research Institute China

Wireless sensor network (WSN) based structural health monitoring (SHM) system attracts increasing interest in recent years. However, the restricted bandwidth, memory and energy pose great challenges to the application of SHM in large scale building. Supported by a real engineering project, a WSN based prototype of SHM system is designed in this paper. Acceleration data, synchronously sampled in each sensor node, are transported to a data processing computer through a base station. In order to achieve a high network throughput, a time division multiple access (TDMA) approach is proposed to reduce the packet collision and energy consumption. 17 sensor nodes, one base station and a processing computer are distributed to validate the prototype system. Test results present that the approach, we proposed, can reduce the signal collision and increase data throughput. The prototype is feasible to the SHM project of a large scale building.

关键词： Monitoring Wireless sensor networks Prototypes Large-scale systems Base stations Throughput Time division multiple access Bandwidth Application software Buildings

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Equivalence Knowledge Cumularspharolith and Multiple Approximate Reasoning in R - Logic CR

Equivalence Knowledge Cumularspharolith and Multiple Approxi...

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computer science and information Engineering, CSIE, WRI World Congress on FLAGGED

作者： Yalin Zheng Guang Yang State Key Laboratory of Intelligent Technology and Systems Department of Automation Faculty of Information Science and Technology Tsinghua University Beijing China Research Center of Intelligent Information Technology Department of Computer Science and Technology Faculty of Software Dongguan University of Science and Technology Dongguan China

By casting off the direct restriction of topological structure, this paper presents another matching scheme between the input A * and the knowledge A rarr B based on the equivalence relation R on formulae set F(S) and the corresponding equivalence classification F(S)/R = { [A] R | A isin F(S)} therefore, obtains another algorithm of approximate reasoning - the IV-type R-algorithm. The paper presents the IV-type R-algorithm for the simple approximate reasoning model and the multiple approximate reasoning model in the frame of R-logic C R .

关键词： Logic Chromium computer science Intelligent structures Knowledge engineering information technology Laboratories Intelligent systems automation information science

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Motion planning with obstacle avoidance for kinematically redundant manipulators based on two recurrent neural networks

Motion planning with obstacle avoidance for kinematically re...

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IEEE International Conference on systems, Man and Cybernetics

作者： Xiaolin Hu Jun Wang Bo Zhang Department of Computer Science and Technology Tsinghua University Beijing China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Beijing China Department of Mechanical and Automation Engineering Chinese University of Hong Kong New Territories Hong Kong China

Inverse kinematic motion planning of redundant manipulators by using recurrent neural networks in the presence of obstacles and uncertainties is a real-time nonlinear optimization problem. To tackle this problem, two subproblems should be resolved in real time. One is the determination of critical points on a given manipulator closest to obstacles, and the other is the computation of joint velocities of the manipulator which can direct the manipulator following a desired trajectory and away from obstacles if it is getting close to them. Different from our previous approaches where the critical points on the manipulator were assumed to be known, these points are to be computed by using a recurrent neural network in the paper. A time-varying quadratic programming problem is formulated for avoiding polyhedral obstacles. In view that the problem is not strictly convex, an existing recurrent neural network, general projection neural network, is applied for solving it. By introducing a velocity smoothing technique into our previous quadratic programming formulation of the joint velocity assignment problem, a recently developed recurrent neural network, improved dual neural network, is proposed to solve it, which features lower structural complexity compared with existing neural networks. Moreover, The effectiveness of the proposed neural networks is demonstrated by simulations on the Mitsubishi PA10-7C manipulator.

关键词： Recurrent neural networks Neural networks Quadratic programming Manipulators Laboratories Kinematics Smoothing methods Paper technology information science Technology planning

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