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IEEE International Conference on Robotics and Biomimetics

作者： Giorgio Cannata Marco Maggiali Mechatronics and Automatic Control Laboratory Department of Communication Computer and System Science University of Genova Genoa Italy Mechatronics and Automatic Control Laboratory Italian Institute of Technologies University of Genova Genoa Italy

A fully embedded tactile/force sensor system to be installed on the phalanges of a robot hand is presented in this paper. The sensor consists of a distributed array of analog tactile elements and an integrated three-component force transducer with embedded analog and digital electronics. The tactile sensor is a matrix of electrodes etched on a flexible printed circuit board covered by pressure conductive rubber. The force sensor is an off-the-shelf integrated three components micro-joystick. Communications of the sensors with other control modules are implemented with a CAN bus link. A local processing technique is proposed to enable the transmission of both tactile and force data using a single CAN message. Simulative and experimental tests validate the proposed method.

关键词： Tactile sensors Force sensors Sensor arrays Transmission line matrix methods Robot sensing systems Transducers Electrodes Etching Flexible printed circuits Rubber

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Processing of Tactile/Force Measurements for a Fully Embedded Sensor

Processing of Tactile/Force Measurements for a Fully Embedde...

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International Conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

A new fully embedded tactile/force sensor system to be installed on the phalanges of a robot hand is presented in this paper. Each sensor consists of a distributed array of analog tactile elements and an integrated three-component force transducer with embedded analog and digital electronics. The tactile sensor is a matrix of electrodes etched on a flexible printed circuit board covered by pressure conductive rubber. The force sensor is an off-the-shelf integrated three components micro-joystick. Communications of the sensors with other control modules are implemented with a CAN bus link. A local processing technique is proposed to enable the transmission of both tactile and force data using a single CAN message, and eventually validate through simulative and experimental tests

关键词： Force measurement Tactile sensors Force sensors Sensor arrays Robot sensing systems Transducers Transmission line matrix methods Electrodes Etching Flexible printed circuits

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Implementation of Listing's Law for a Tendon Driven Robot Eye

Implementation of Listing's Law for a Tendon Driven Robot Ey...

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2006 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Giorgio Cannata Marco Maggiali Mechatronics and Automatic Control Laboratory Department of Communications Computer and System Science University of Genova Genoa Italy Mechatronics and Automatic Control Laboratory Italian Institute of Technology University of Genova Genoa Italy

This paper presents a model for a tendon driven robot eye designed to emulate the actual saccadic and smooth pursuit movements performed by human eyes. Physiological saccadic motions obey the so called Listing's law which constrains the admissible eye's angular velocities. The paper discusses conditions making possible to implement the Listing's law on a purely mechanical basis, i.e. without active control

关键词： Tendons Muscles Intelligent robots Mechatronics Automatic generation control Laboratories Pulleys Feedback Motion control Robotics and automation

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Measured disturbance estimation for model predictive controller

Mediterranean Journal of Measurement and Control

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Mediterranean Journal of Measurement and control 2006年第3期2卷 144-151页

作者： Kulcsar, Balazs Bokor, J. Department of Transport Automation Faculty of Transportation Engineering Budapest University of Technology and Economics Budapest Hungary System and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary

This paper presents the Model Predictive controller design process when an unknown input observer provides measured disturbance form unmeasured one. Instead of using an unmeasured disturbance dynamic implemented into the controller, the joint observer-controller uses the estimated measured exogenous disturbance signal. Furthermore the observer can send an alarm sign to the supervisor. The detection and isolation of the unmeasured disturbance is computed by the geometric based strategy called Fundamental Problem in Residual Generation. Better the estimation of the disturbance is, better the rejection of the controller. The measured disturbance could be anticipated. A numerical example explains the effectiveness of the estimation and the usage of the unmeasured disturbance detection. Copyright © 2006 SoftMotor Ltd.

关键词： Predictive control systems

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Integrated information processing and communications: Complexity analysis

Integrated information processing and communications: Comple...

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IASTED International Conference on COMMUNICATION systemS AND APPLICATIONS Part of the Sixth IASTED International Multi-Conference on WIRELESS AND OPTICAL COMMUNICATIONS

作者： Huyu, Qu Le, Yi Wang Yaprak, Ece Hong, Wang Yanlong, Zhao Department of Electrical and Computer Engineering Wayne State University Detroit MI 48202 United States Division of Engineering Technology Wayne State University Detroit MI 48202 United States Department of Anesthesiology Wayne State University Detroit MI 48202 United States Key Laboratory of System and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences China

Accuracy of information transmission when a signal must be transmitted through a communication channel is of essential importance in design of communication systems. When system resources are limited, such as transmission bandwidths assigned to a wireless communication channel, appropriate utility of available resources becomes imperative. This paper investigates fundamental relationships between accuracy of information exchange and communication resources, on a platform of wireless communication channels that involve typical system blocks of data compression, quantization, and stochastic wireless channels. The main complexity relationships developed in this paper provide rigorous trade-off between resource consumptions and information processing errors of each block. When these relationships are integrated, an optimization procedure emerges that allows optimal allocation of resources to each system block, such as compression ratio, quantization levels, and transmission speed, to maximize overall information accuracy. Consequently, the overall errors of the transmitted signal will be minimized at the receiver end.

关键词： Data processing

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New optimization algorithm based on chaos

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Journal of Zhejiang University: Science 2006年第4期7卷 539-542页

作者： Lu, Hui-Juan Zhang, Huo-Ming Ma, Long-Hua Institute of Computer Applications China Jiliang University Hangzhou 310018 China National Laboratory of Ocean and Civil Engineering Shanghai Jiaotong University Shanghai 200030 China National Laboratory of Industrial Control Technology Institute of System Engineering Institute Zhejiang University Hangzhou 310027 China

In this article, some methods are proposed for enhancing the converging velocity of the COA (chaos optimization algorithm) based on using carrier wave two times, which can greatly increase the speed and efficiency of the first carrier wave's search for the optimal point in implementing the sophisticated searching during the second carrier wave is faster and more accurate. In addition, the concept of using the carrier wave three times is proposed and put into practice to tackle the multi-variables optimization problems, where the searching for the optimal point of the last several variables is frequently worse than the first several ones.

关键词： Optimization

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Multiscale Face Detection: A New Approach to Robust Face Detection

Multiscale Face Detection: A New Approach to Robust Face Det...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： M. Aghagolzadeh H. Soltanian-Zadeh B.N. Araabi Department of Electrical and Computer Engineering University of Tehran Tehran Iran Radiologyimageanalaysis laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

This paper presents a novel method for detecting multiple frontal faces in still images using multi-scale processing. The main characteristic of this algorithm is its stability in detecting faces with seldom false detections and a high correct detection rate. The novelty of this work comes from the utilization of multiscale detection and using two classifiers to reduce false detections. The algorithm generally has two stages: in the first stage, a face is detected in a unique scale and in the second stage, only the faces that are located in the neighbor scales are accepted as real faces. Consequently, a still image is first resized and scanned block wise, and then each enhanced block is tested for being face. One dimensional Harr wavelet is used for feature extraction, which gives appropriate discriminating features between the face and nonface classes. Detection results at each scale are accumulated in an internal database, so the ultimate detection is prepared based on the mutual detection information between consequent scales. To parameterize both the Bayesian and the simple proposed classifier, 2,643 faces were congregated from famous face databases and more than 10,000 non-face samples were selected from nature images. Experimental results using images gathered from known databases like MIT-CMU show great ability of the proposed algorithm in detecting faces.

关键词： Face detection Robustness Image databases Bayesian methods Humans Application software Stability Feature extraction Spatial databases computer vision

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Rule-based decision-making framework for knowledge-based anatomical landmark localization (K-BALL)

Rule-based decision-making framework for knowledge-based ana...

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IEEE International Symposium on Biomedical Imaging

作者： M.-R. Siadat H. Soltanian-Zadeh K. Elisevich Henry Ford Health System Radiology Image Analysis Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Neurosurgery Henry Ford Health System Detroit MI USA

K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on information analysis step (2nd step) of K-BALL during which landmarks extracted in its first step are evaluated. We provide a framework in which rules are automatically generated based on estimated and derived models. We show that the rules based on the derived models can improve the overall success rate of K-BALL. Each rule evaluates the extracted points by producing an intermediate confidence factor (ICNF). A total confidence factor is calculated using ICNF's to facilitate the acceptance or rejection of a set of points as landmarks of interest. Using the rules merely based on the estimated models, simulation study produced an overall success rate of 91.8%. Using the rules based on both of the estimated and derived models, this rate increased to 92.5%

关键词： Decision making Hippocampus Information analysis Data mining Humans Radiology Image analysis Radio control Process control control systems

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

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Congress on Evolutionary Computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Fast Prediction of Loadability Margins by Constructing a Small-Signal Stability Boundary Based on Neural Networks

Fast Prediction of Loadability Margins by Constructing a Sma...

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International Conference on Power system Technology (POWERCON)

作者： Xueping Gu Claudio A. Canizares Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control under Ministry of Education North China Electric Power University Baoding Hebei China Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

Determining loadability margins to various security limits is of great importance for the secure operation of a power system. A novel approach is proposed in this paper for fast prediction of loadability margins with respect to small-signal stability based on neural networks. Small-signal stability boundaries are constructed by means of loading the power system until the stability limits are reached from a base operating point along various loading directions. Back-propagation neural networks (BPNN) for different contingencies are trained to approximate these stability boundaries. A search algorithm is then proposed to predict the loadability margins from any stable operating point along arbitrary loading directions through an iterative technique based on the trained BPNNs. The simulation results for the IEEE two-area benchmark system demonstrate the effectiveness of the proposed method for on-line prediction of loadability margins.

关键词： Neural networks Power system stability Power system security Voltage Power system simulation Monitoring National security control systems Operating systems Bifurcation

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