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2008 IEEE Swarm Intelligence Symposium, SIS 2008

作者： Kulkarni, Raghavendra V. Venayagamoorthy, Ganesh K. Miller, Ann Dagli, Cihan H. Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO United States Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO United States Department of Systems Engineering and Engineering Management Missouri University of Science and Technology Rolla MO United States

ISBN: (纸本)9781424427055

There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other alms at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed. ©2008 IEEE.

关键词： Multipurpose robots

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Data mining-driven analysis and decomposition In agent supply chain management networks

Data mining-driven analysis and decomposition In agent suppl...

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2008 IEEE/WIC/ACM International Conference on Web Intelligence and intelligent Agent Technology - Workshops, WI-IAT Workshops 2008

作者： Chatzidimitriou, Kyriakos C. Symeonidis, Andreas L. Mitkas, Pericles A. Department of Electrical and Computer Engineering Aristotle University of Thessaloniki GR541 24 Thessaloniki Greece Intelligent Systems and Software Engineering Laboratory Informatics and Telematics Institute CERTH 57001 Thessaloniki Greece

ISBN: (纸本)9780769534961

In complex and dynamic environments where interdependencies cannot monotonously determine causality, data mining techniques may be employed in order to analyze the problem, extract key features and identify pivotal factors. Typical cases of such complexity and dynamicity are supply chain networks, where a number of involved stakeholders struggle towards their own benefit. These stakeholders may be agents with varying degrees of autonomy and intelligence, in a constant effort to establish beneficiary contracts and maximize own revenue. In this paper, we illustrate the benefits of data mining analysis on a well-established agent supply chain management network. We apply data mining techniques, both at a macro and micro level, analyze the results and discuss them in the context of agent performance improvement. © 2008 IEEE.

关键词： Supply chain management

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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The Third International Conference on human-robot interaction

The Third International Conference on human-robot interactio...

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作者： Fong, Terry Dautenhahn, Kerstin Scheutz, Matthias Demiris, Yiannis Intelligent Robotics Group NASA Ames Research Center Department of Artificial Intelligence School of Computer Science University of Herfordshire Herfordshire United Kingdom Adaptive Systems Research Group University of Herfordshire Herfordshire United Kingdom Department of Cognitive Science Computer Science and Informatics Cognitive Science Program Indiana University Bloomington IN United States Intelligent Robotics Team Department of Electrical Engineering Imperial College London London United Kingdom

The third international conference on Human-Robot Interaction (HRI-2008) was held in Amsterdam, The Netherlands, March 12-15, 2008. The theme of HRI-2008, "living with robots," highlights the importance of the technical and social issues underlying human-robot interaction with companion and assistive robots for long-term use in everyday life and work activities. More than 250 researchers, practitioners, and exhibitors attended the conference, and many more contributed to the conference as authors or reviewers. HRI-2009 will be held in San Diego, California, from March 11-13, 2009. Copyright © 2008, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Camera Handoff with Adaptive Resource Management for Multi-camera Multi-target Surveillance

Camera Handoff with Adaptive Resource Management for Multi-c...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Chung-Hao Chen Yi Yao David Page Besma Abidi Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA GE Global Research Center Niskayuna NY USA

Camera handoff is a crucial step to generate a continuously tracked and consistently labeled trajectory of the object of interest in multi-camera surveillance systems. Most existing camera handoff algorithms concentrate on data association, namely consistent labeling, where images of the same object are matched across different cameras. However, most real-time object tracking systems see a decrease in the system's frame rate as the number of tracked objects increases. To address this issue, we propose to incorporate an adaptive resource management mechanism into camera handoff. In so doing, cameras¿ resources can be dynamically allocated to multiple objects according to their priorities and hence the required minimum frame rate can be maintained. Experimental results illustrate that the proposed camera handoff algorithm is capable of maintaining a constant frame rate and of achieving a substantially improved handoff success rate by approximately 20% in comparison with the algorithm presented by Khan and Shah.

关键词： Resource management Surveillance Labeling Real time systems intelligent robots USA Councils Videoconference Robot vision systems Smart cameras Robot kinematics

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A differential evolution approach to optimal generator maintenance scheduling of the nigerian power system

A differential evolution approach to optimal generator maint...

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IEEE General Meeting Power& Energy Society

作者： Y. Yare G. K. Venayagamoorthy Real-Time and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO USA

The goal of optimal generator maintenance scheduling is to evolve optimal preventive maintenance schedule of generating units for economical and reliable operation of a power system while satisfying system load demand and crew constraints. In this paper, the differential evolution (DE), an evolutionary computation algorithm that utilizes the differential information to guide its further search, is applied to effectively solve the generator maintenance scheduling (GMS) optimization problem. The proposed method can handle mixed integer discrete continuous optimization problems. Results are presented with the DE algorithm on two different case studies for Nigerian power system.

关键词： Maintenance engineering Power systems Optimization Optimal scheduling Power system dynamics Generators Evolution (biology)

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Learning structurally discriminant features in 3D faces

Learning structurally discriminant features in 3D faces

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IEEE International Conference on Image Processing

作者： Sreenivas R. Sukumar Hamparsum Bozdogan David L. Page Andreas F. Koschan Mongi A. Abidi Imaging Robotics and Intelligent Systems Lab Department of Electrical and Computer Engineering University of Tennessee Knoxville USA Department of Statistics University of Tennessee Knoxville USA

In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information complexity criterion to identify discriminant feature-clusters of lower dimensionality. We apply this framework on human face anthropometry data of 32 features collected from each of the 300 3D face mesh models. The feature-subsets that we infer as the output establishes domain knowledge for the challenging problem of 3D face recognition with dense 3D gallery models and sparse or low resolution probes.

关键词： Probes Face recognition Data mining Humans Facial features Feature extraction Principal component analysis Linear discriminant analysis Input variables intelligent robots

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Differential evolution particle swarm optimization for digital filter design

Differential evolution particle swarm optimization for digit...

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Congress on Evolutionary Computation

作者： Bipul Luitel Ganesh K. Venayagamoorthy Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

In this paper, swarm and evolutionary algorithms have been applied for the design of digital filters. Particle swarm optimization (PSO) and differential evolution particle swarm optimization (DEPSO) have been used here for the design of linear phase finite impulse response (FIR) filters. Two different fitness functions have been studied and experimented, each having its own significance. The first study considers a fitness function based on the passband and stopband ripple, while the second study considers a fitness function based on the mean squared error between the actual and the ideal filter response. DEPSO seems to be promising tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance.

关键词： Digital filters Finite impulse response filter IIR filters Filtering algorithms Passband Evolutionary computation Particle swarm optimization

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Localization-oriented coverage based on Bayesian estimation in camera sensor networks

Localization-oriented coverage based on Bayesian estimation ...

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9th IEEE International Symposium on Wireless, Mobile and Multimedia Networks, WoWMoM 2008

作者： Liu, Liang Zhang, Xi Huadong, Ma. Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas A and M University College Station TX 77843 United States Beijing Key Lab. of Intelligent Telecomm Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9781424421008

Target tracking and localization are important applications in camera sensor networks. Although coverage is a very important research topic in wireless sensor networks, and the coverage problem for target detection has been intensively studied, few considers the coverage problem from the perspective of target localization. In this paper, we investigate the coverage problem from the perspective of target localization for camera sensor networks. We first propose a novel localization-oriented sensing model based on the perspective projection of camera. Then, we propose a new notion of Localization-oriented coverage (L-coverage for short). We assume that all camera sensors make the measurements independent of other in the field, and these camera sensors can cooperate to make an accurate estimation for the location of the target. In addition, the relationships among L-coverage, 2-coverage, and the density of camera sensors are also discussed in this paper. The obtained results show that our model can be effectively deployed in many practical scenarios. © 2008 IEEE.

关键词： Target tracking

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Implementation of a PSO based online design of an optimal excitation controller

Implementation of a PSO based online design of an optimal ex...

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IEEE Swarm Intelligence Symposium, SIS

作者： Chuan Yan Ganesh K. Venayagamoorthy Keith A. Corzine Real-time Power and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Real-timePower and Intelligent systems (RTPIS) laboratory in the Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA

The Navypsilas future electric ships will contain a number of pulsed power loads for high-energy applications such as radar, railguns, and advanced weapons. This pulse energy demand has to be provided by the ship energy sources, while not impacting the operation of the rest of the system. It is clear from studies carried out earlier that disturbances are created at the generator ac bus. This paper describes an online design and laboratory hardware implementation of an optimal excitation controller using particle swarm optimization (PSO) to minimize the effects of pulsed loads. The PSO algorithm has been implemented on a digital signal processor. laboratory results show that the PSO designed excitation controller provides an effective control of a generatorpsilas terminal voltage during pulsed loads, restoring and stabilizing it quickly.

关键词： Optimal control Marine vehicles Laboratories Voltage control Radar applications Railguns Weapons AC generators Hardware Particle swarm optimization

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