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Simulation Winter Conference

作者： Tak-Kuen John Koo Yi Ma G.J. Pappas C. Tomlin Robotics and Intelligent Machines Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA USA

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A Polynomial Function Discovery System — FFS

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International Journal on Artificial Intelligence Tools 1997年第1期6卷 1-13页

作者： Spyros Tzafestas Zhifang Ma Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zografou 15773 Athens Greece On leave from the Department of Computer Science Jilin University Changchun P.R.China

This paper presents a function discovery system FFS that has two core parts: FFS-0-CORE and FFS-1-CORE. Both cores are with polynomial time complexity in discovering functions of either a•f(x)+b form or a 1 f 1 (x)+…+a n f n (x)+b form. FFS-0-CORE allows users to define their own models. FFS-1-CORE uses novel principles to increase information which helps the function discovery procedures. Three computational examples are included.

关键词： Formula discovery machine discovery machine learning artificial intelligence

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Using a robot arm to facilitate the learning in young and mentally development-delayed children

Using a robot arm to facilitate the learning in young and me...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： J. Gu F. Dong M. Meng A. Cook Department of Electrical and Computer Engineering ART (Advanced Robotics and Teleoperation) Laboratory Canada Faculty of Rehabilitation Medicine University of Alberta Edmonton AB Canada

The study is based on two assumptions: 1) the child is an active, goal-oriented participant in his or her own development; and 2) physical manipulation of objects is a major contributing factor in the development of cognitive and language skills in a very young child. The CRS robot arm system is used in our study. All the functions are under the control of a computer based software control algorithm. The training program uses either the teach pedant or a series of text commands to train the arm. With the teach pedant, the operator can move the arm in desired directions by pressing the button on the teach pedant. In the text training mode, the arm moves according to the command set predefined. Another important aspect of the project is how to set up the interface and communication environment between the young children and the robot arm. The final program lets the child to accomplish a series of processing complex tasks through simple operation of certain buttons. The programmed activities have a development sequence, which eventually brings the robot arm under the control of the child; at the same time it facilitates the learning process of the child.

关键词： Robots Medical robotics Rehabilitation robotics Pediatrics Cognitive robotics Pressing Switches computerized monitoring Wrist Grippers

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A fast and accurate 3-D rangefinder using the Biris technology: the TRID sensor

A fast and accurate 3-D rangefinder using the Biris technolo...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： F. Loranger D. Laurendeau R. Houde Computer Vision and Systems Laboratory (CVSL) Electrical and Computer Engineering Department Laval University QUE Canada Robotics Division Hydro-Quebec Research Institute (IREQ) Varennes Canada

In many industrial applications such as autonomous vehicle guidance and robotic manipulations, reliable 3-D informations must be extracted from the scene in order to provide a robust description of the environment in which the system evolves. This paper presents the TRID sensor, a simple, fast, robust and accurate 3-D sensing device based on the Biris technology. TRID is limited to a lateral resolution of one point. Experimental results show that an accuracy better than 0.15% can be obtained for the depth component (Z) of 3-D points at a distance of 1.3 meter from a wooden black painted beam surface with an acquisition rate of 8.5 points/s.

关键词： Robot vision systems Robustness computer vision Application software Robot kinematics Layout Cameras computer industry Costs Geometrical optics

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Determining the skeletal description of sparse shapes

Determining the skeletal description of sparse shapes

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IEEE International Symposium on Computational Intelligence in robotics and Automation (CIRA)

作者： R. Singh V. Cherkassky N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA Department of Electrical Engineering University of Minnesota Minneapolis MN USA

A variety of techniques in machine vision involve representation of objects by using their shape skeleton. In this paper we present a method to obtain the skeletal shape of binary images in the presence of both boundary noise and noise occurring inside object regions. We propose to obtain the skeletal shape of such images by a modified version of the Kohonen self-organizing map, implemented in a batch processing mode. The modifications allow the map to adapt to the input shape distribution. At each iteration, a competitive Hebbian rule is used to progressively compute the Delaunay triangulation of the shape. Information from the triangulation augments the map topology to yield the final skeletal shape. The batch mode implementation of the self-organizing process, allows our approach to compare very favourably, in terms of computational time, with the traditional flowthrough implementations. Encouraging experimental performance has been obtained on a variety of shapes under varying signal to noise ratios.

关键词： Shape Noise shaping Skeleton Intelligent robots Machine vision computer vision Noise level Noise figure Machine intelligence Robot vision systems

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Synthesized passive feedback control of sensor-rich structures

Synthesized passive feedback control of sensor-rich structur...

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American Control Conference (ACC)

作者： P. Akella J.T. Wen Control Laboratory for Mechanical Structures (CLaMS) Center for Advanced Technology in Automation Robotics & Manufacturing Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

The passivity property of dissipative mechanical structures has long been exploited in designing passive controllers that provide robust stability even in the presence of unmodeled dynamics of the system. For an input/output map of a flexible structure to be passive, collocation of the actuators and sensors is required and also the sensors should measure the velocity of the system. The so-called smart structures frequently have more sensors than actuators. Therefore, the passive controller can at best utilize only a subset of the sensors. In this paper we consider the design of a squaring down matrix which would render a system passive subject to some additional performance considerations. The problem of obtaining the synthesized passive output is cast as a set of linear matrix inequalities (LMIs) which can be efficiently solved by the LMI Toolbox in Matlab. We apply this procedure with the assumption that the sensors provide both displacement and velocity information which is generally not true. We show that the passive controllers can be implemented without the use of velocity information. By using synthesized passive outputs in addition to naturally occurring passive outputs, we obtain better system performance. We present experimental results involving a single flexible beam with torque input and hub angular position and strain gage outputs.

关键词： Feedback control Intelligent sensors Control system synthesis Mechanical sensors Sensor systems Linear matrix inequalities Mechanical factors Control systems Robust stability Flexible structures

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Growing region technique in the detection of autonomous structures within X-ray radiographs

Growing region technique in the detection of autonomous stru...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.N. Raptis S.G. Tzafestas S. Pavlopoulos D. Koutsouris S. Kollias Intelligent Robotics and Automation Laboratory National and Technical University of Athens Athens Greece Biomedical Engineering Laboratory National and Technical University of Athens Athens Greece Department of Electrical & Computer Engineering National and Technical University of Athens Athens Greece

Nodule identification is a major issue in chest radiography and cancer prevention and detection. The recognition of cancer nodule characteristics in chest radiographs is a key point to the detection procedure. The method described here is based on the extraction of the major geometrical as well as luminance characteristics that make nodule recognizable and easy to detect. The purpose of the proposed method is to detect within a given block of chest X-ray image any homogeneous and autonomous mass that might means the existence of a nodule or some structure within it. The idea of pixels of interest is introduced which makes the growing a finite steps procedure. The growing of the region around a given point is realized gradually in a finite number of iterations at each one of which a set of criteria is evaluated. These criteria are established in a prior training procedure.

关键词： X-ray detection X-ray detectors X-ray imaging Diagnostic radiography Pixel Laboratories Biomedical engineering Cancer detection Character recognition Shape

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Telemanipulator neurocontrol using multiple RBF networks

Telemanipulator neurocontrol using multiple RBF networks

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IEEE International Symposium on Intelligent Control (ISIC)

作者： S.G. Tzafestas P.A. Prokopiou C.S. Tzafestas Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National and Technical University of Athens Athens Greece Laboratoire de Robotique de Paris CNRS UPMC UVSQ France

This paper addresses the control problem of masterslave systems which involve severe modeling errors and other high-level uncertainties, using neural networks. The solution approach is based on a recent teleoperator control scheme of S. Lee and H.S. Lee (1993, 1994), which is suitably enhanced such that to become capable of compensating the uncertainties. The class of radial-basis functions (RBF) neural networks are employed in a multipartitioned neural network architecture, and a special learning scheme is adopted which distributes the learning error to each subnetwork and allows online learning. The effectiveness of the present RBF neurocontroller was investigated through extensive simulation and compared to that of MLP (multilayer perceptron) neurocontroller and a robust sliding-mode controller representative.

关键词： Radial basis function networks Robot kinematics Error correction Neural networks Teleoperators Master-slave Uncertainty Delay effects robotics and automation Neurocontrollers

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Neural Fault Detection and Accommodation for Interconnected Power Systems

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IFAC Proceedings Volumes 1997年第18期30卷 943-947页

作者： Spyros Tzafestas Yiannis Anthopoulos Efthimios Kyriannakis Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zographou 15773 Athens Greece. Tel: +30-1-7722489 +30-1-772-1527 Fax: +30-1-7722490 +30-1-7722459

Due to increasing safety and reliability demands fault detection and accommodation is a key issue in the design of industrial control systems. This paper presents a neural network based method for fault detection and accommodation, appropriate for interconnected power systems. The simulation results show that the method is very promising.

关键词： fault detection neural networks interconnected systems

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Neural networks based sensorial signal fusion: an application to material identification

Neural networks based sensorial signal fusion: an applicatio...

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International Conference on Digital Signal Processing (DSP)

作者： S.G. Tzaiestas Y. Anthopoulos Dept. of Electr. & Comput. Eng. Nat. Tech. Univ. of Athens Greece Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National and Technical University of Athens Athens Greece

Data acquisition and learning capabilities are necessary for an intelligent system operating in unstructured, dynamically changing environments. For this purpose, a method for the effective use of multiple sensors must be developed. This paper shows how multisensor fusion can be accomplished by neural networks. It first summarizes the conventional fusion techniques and consequently describes the use of neural networks for sensor fusion as well as their advantages. Finally, an application is presented where a neural network is used to fuse the signals of several sensors, of different type, for material identification purposes.

关键词： Neural networks Signal processing Sensor fusion Intelligent sensors Sensor phenomena and characterization Sensor systems Intelligent systems Intelligent robots Costs Recursive estimation

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