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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Elpiniki Papageorgiou Chrysostomos Stylios Peter Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Greece Intelligent Computing Laboratory Department of Informatics and Telecommunications Technology TEI Epirus Greece

Medical problems involve different types of variables and data, which have to be processed, analyzed and synthesized in order to reach a decision and/or conclude to a diagnosis. Usually, information and data set are both symbolic and numeric but most of the well-known data analysis methods deal with only one kind of data. Even when fuzzy approaches are considered, which are not depended on the scales of variables, usually only numeric data is considered. The medical decision support methods usually are accessed in only one type of available data. Thus, sophisticated methods have been proposed such as integrated hybrid learning approaches to process symbolic and numeric data for the decision support tasks. Fuzzy cognitive maps (FCM) is an efficient modelling method, which is based on human knowledge and experience and it can handle with uncertainty and it is constructed by extracted knowledge in the form of fuzzy rules. The FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This rule base could be derived by a number of machine learning and knowledge extraction methods. Here it is introduced a hybrid attempt to handle situations with different types of available medical and /or clinical data and with difficulty to handle them for decision support tasks using soft computing techniques.

关键词： Decision making Fuzzy cognitive maps Medical diagnostic imaging Data mining Decision support systems Learning systems Computational intelligence computer networks Diseases Spatial databases

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MODELING AND CONTROL OF ELEVATORS BY STATECHARTS

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Asian Journal of Control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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A Log-Polar Interpolation Applied to Image Scaling

A Log-Polar Interpolation Applied to Image Scaling

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： A. Amanatiadis I. Andreadis A. Gasteratos Laboratory of Electronics Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece

This paper proposes a bio-inspired interpolation algorithm suitable for image scaling. A log-polar neighbor model is adopted, utilizing the feature of applying larger weights to pixels at the center of the interpolation region and logarithmically decreasing weights to pixels away from the center. The interpolation is performed in the Cartesian plane without requiring the full transformation of the image to the log-polar plane. Experiments show that in both visual comparisons and quantitative analysis, the results extracted by the proposed log-polar neighbor model are better than those extracted from pixel repetition, bilinear and bicubic interpolation.

关键词： Interpolation Pixel Digital images Hardware Retina Photoreceptors Color Conferences Laboratories robotics and automation

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A Rotational and Translational Image Stabilization System for Remotely Operated Robots

A Rotational and Translational Image Stabilization System fo...

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： A. Amanatiadis I. Andreadis A. Gasteratos N. Kyriakoulis Laboratory of Electronics Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece

Remotely operated robots equipped with on board cameras, apart from providing video input to operators, perform optical measurements to assist their navigation as well. Such image processing algorithms require image sequences, free of high frequency unwanted movements, in order to generate their optimal results. Image stabilization is the process which removes the undesirable position fluctuations of a video sequence improving, therefore, its visual quality. In this paper, we introduce the implementation of an image stabilization system that utilizes input from an on board camera and a gyrosensor. The frame sequence is processed by an optic flow algorithm and the inertial data is processed by a discrete Kalman filter. The compensation is performed using two servo motors for the pan and tilt movements and frame shifting for the vertical and horizontal movements. Experimental results of the robot head, have shown fine stabilized image sequences and a system capable of processing 320 times 240 pixel image sequences at approximately 10 frames/sec, with a maximum acceleration of A deg/sec 2 .

关键词： Image sequences Cameras Optical filters Robot vision systems Performance evaluation Navigation Image processing Frequency Fluctuations Video sequences

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Multi-Robot Localization and Mapping Strategy: Utilizing Behavior Based Dynamic Tree Structure and Observer-explorer Routine

Multi-Robot Localization and Mapping Strategy: Utilizing Beh...

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IEEE International Conference on automation Science and engineering (CASE)

作者： Kevin K. Leung Garratt Gallagher Robotics Autonomous Systems and Controls Laboratory (RASCAL) Department of Mechanical and Aeronautical Engineering University of California Davis USA Department of Electrical and Computer Engineering Robotics Autonomus Systems and Control Laboratory (RASCAL) Department of Mechanical and Aeronautical Engineering University of California Davis USA

In this paper, we propose a simultaneous localization and map-building (SLAM) strategy to explore unknown environment. Multiple robots are deployed in unknown area and required to localize each other accurately while exploring. Instead of relying on active obstacle detector, we propose a method of exploration which uses only tactile sensors and inter-robot distance measurements. To avoid dead-reckoning and odometry errors, an observer-explorer based routine is adopted. A dynamic spanning tree structure is implemented for multi-robot coordination. Parent (observer) nodes monitor the distances of their children (explorer) nodes. In order to promote completeness of the map, the reconfigurable spanning tree structure favors unexplored area implicitly. An online behavior-based finite state machine drives the configuration of the structure. Our exploration scheme allows the differentiation between robots and obstacles or boundaries. When an obstacle or boundary is detected, it is recorded on a map that is shared with all other robots. The proposed strategy is simulated and results are presented.

关键词： Tree data structures Robot kinematics Robot sensing systems Simultaneous localization and mapping robotics and automation Distance measurement Automata Service robots Global Positioning System Costs

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Fast Computation of Orthogonal Fourier-Mellin Moments Using Modified Direct Method

Fast Computation of Orthogonal Fourier-Mellin Moments Using ...

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International Conference on systems, Signals and Image Processing, IWSSIP

作者： G. A. Papakostas Y. S. Boutalis D. A. Karras B. G. Mertzios Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Chalkis Institute of Technology Chalkida Greece Department of Automation Laboratory of Control Systems. and Computer Intell Thessaloniki Institute of Technology Thessaloniki Greece

A novel, modified direct method for Orthogonal Fourier-Mellin Moments (OFMMs) computation, which lacks of any factorial terms, is presented. The proposed algorithm is based on the substitution of the factorial terms by their approximate values, according to Stirling's Approximation formula. In this way, a new set of orthogonal moments, which are approximate versions of the original ones, are extracted. The approximation error introduced by the Stirling's Approximation formula is of low order and thus the resulted moments do not significantly differ from their original values. The resulted formulas are factorial free and therefore the time needed to compute the OFMMs is less than this of the conventional direct method.

关键词： Polynomials automation Pattern recognition Kernel Laboratories Automatic control Control systems Feature extraction Approximation algorithms Approximation error

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Highly Compressed Zernike Moments by Smoothing

Highly Compressed Zernike Moments by Smoothing

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International Conference on systems, Signals and Image Processing, IWSSIP

作者： G. A. Papakostas Y. S. Boutalis D. A. Karras B. G. Mertzios Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Chalkis Institute of Technology Chalkida Greece Department of Automation Laboratory of Control Systems. and Computer Intell. Thessaloniki Institute of Technology Thessaloniki Greece

A novel methodology that improves the discrimination capabilities of the compressed feature vectors, used in pattern recognition tasks, is presented in this paper. The Zernike moment signals of some patterns are extracted and are compressed by using a typical wavelet compression technique. In order to increase the compression ratio without loosing a great amount of significant information, the moment signals are smoothed appropriately before the compression. As a result, highly compressed feature vectors that include enough classification information are derived. The resulted improved features are studied for their discriminative power through appropriate experiments.

关键词： Smoothing methods Image coding Polynomials automation Feature extraction Pattern classification Digital images Image reconstruction Laboratories Automatic control

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TRACKING CONTROL IN THE PRESENCE OF NONLINEAR DYNAMIC FRICTIONAL EFFECTS: ROBOT EXTENSION

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Asian Journal of Control 2008年第3期1卷

作者： M. Feemster D.M. Dawson A. Behal W. Dixon Matthew Feemster received the B.S degree in Electrical Engineering from Clemson University Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962 in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no

In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.

关键词： Friction compensation nonlinear control

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A Study On Iterative Learning Control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of Control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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Particle Swarn Optimized Adaptive Dynamic Programming

Particle Swarn Optimized Adaptive Dynamic Programming

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Dongbin Zhao Jianqiang Yi Derong Liu Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Department of Electrical and Computer Engineering University of Illinois Chicago Chicago IL USA

Particle swarm optimization is used for the training of the action network and critic network of the adaptive dynamic programming approach. The typical structures of the adaptive dynamic programming and particle swarm optimization are adopted for comparison to other learning algorithms such as gradient descent method. Besides simulation on the balancing of a cart pole plant, a more complex plant pendulum robot (pendubot) is tested for the learning performance. Compared to traditional adaptive dynamic programming approaches, the proposed evolutionary learning strategy is verified as faster convergence and higher efficiency. Furthermore, the structure becomes simple because the plant model does not need to be identified beforehand

关键词： Dynamic programming Particle swarm optimization Neural networks Robots Backpropagation Adaptive systems Evolutionary computation Learning Cost function Testing

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