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OPTIMIZING THE SUBDIVISION OF ELEMENTS IN DISCONTINUITY MESHING FOR HIERARCHICAL RADIOSITY

International Journal on Artificial Intelligence Tools 2003年第4期12卷 395-411页

作者： IOANNIS A. PANTAZOPOULOS SPYROS G. TZAFESTAS Intelligent Robotics and Automation Laboratory Signals Control and Robotics Division Electrical and Computer Engineering Department National Technical University of Athens Zographou Athens Greece

This paper presents a new topological structure for use in the context of hierarchical radiosity combined with discontinuity meshing. This is most useful for a new strategy adopted for subdividing the elements of a scene consisting of convex polygons. The subdivision is done in a local optimization manner keeping the aspect ratios of produced polygons low. The generated meshes give high visual accuracy.

关键词： Hierarchical radiosity discontinuity meshing mesh pre(post)-processing multigriding aspect-ratio

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Real-time driver affect analysis and tele-viewing system

Real-time driver affect analysis and tele-viewing system

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IEEE Symposium on Intelligent Vehicle

作者： J.C. McCall S.P. Mallick M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego USA

This paper deals with the development of novel sensory systems and interfaces to enhance the safety of a driver who may be using a cell phone. It describes a system for real time affect analysis and Tele-viewing in order to bring the context of the driver to remote users. The system is divided into two modules. The affect recognition module recognizes six emotional states of the driver. The face-modeling module generates a 3D model of the driver's face using two images and synthesizes the emotions on it. Depending on bandwidth, either a raw video, 3D warped model, or an iconic representation is sent to the remote user.

关键词： Real time systems Cellular phones Face detection Hidden Markov models Tracking loops Safety Emotion recognition Bandwidth Image reconstruction computer vision

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RF CMOS-MEMS capacitor having large tuning range

RF CMOS-MEMS capacitor having large tuning range

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： A. Oz G.K. Fedder Department of Electrical and Computer Engineering MEMS Laboratory Carnegie Mellon University Pittsburgh PA USA Department of Electrical and Computer Engineering MEMS Laboratory Robotics Institute Pittsburgh PA USA

Several CMOS-MEMS tunable capacitors have been designed, fabricated and tested. Large-tuning ranges and high Q values are achieved. The structures were made from the CMOS interconnect stack using a maskless CMOS micromachining process. The 1/sup st/ generation capacitors were fabricated using Austria Microsystems (AMS) 0.6 /spl mu/m and Agilent 0.5 /spl mu/m CMOS process. These devices have a measured nominal capacitance of 209 fF and a measured quality factor 28 at 1.5 GHz. The capacitance change is measured from 209 fF to 294 fF within a 24 V control voltage, and 72.4 mW power at 1.5 GHz. 2/sup nd/-generation tunable capacitors in TSMC 0.35 /spl mu/m CMOS process have larger tuning range and more power efficiency than the 1st generation designs. For these new designs, 3.52 to 1 tuning range has been measured with tuning from 42 fF to 148 fF within a 12 V control voltage, and 34 mW power at 1.5 GHz. This recent design has a measured Q of 52 at 1.5 GHz. Electro-thermal actuation is used for all tunable capacitor designs. The essential differences between this work and prior work are the CMOS compatibility and using a maskless CMOS micromachining process.

关键词： Radio frequency Capacitors CMOS process Capacitance measurement Micromachining Power measurement Voltage control Testing Q factor Power generation

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Telerobotic haptic system to assist the performance of occupational therapy tests by motion-impaired users

Telerobotic haptic system to assist the performance of occup...

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IEEE International Conference on robotics and Automation (ICRA)

作者： N. Pernalete Wentao Yu R. Dubey W.A. Moreno Department of Electrical and Computer Engineering Western Michigan University Rehabilitation Robotics Laboratory University of South Florida USA

This paper describes the development of intelligent mapping from a haptic user interface to a remote manipulator to assist individuals with disabilities performing occupational therapy tasks. This mapping, referred to an assistance function, is determined on the basis of environmental model or sensory data to guide the motion of a telerobotic manipulator while performing a given task. Human input is enhanced rather than superseded by the computer. Three manual dexterity assessment tests, commonly used in the occupational therapy field, were chosen to implement the several forms of assistance functions designed to augment the human performance. The test bed used for these tasks consisted of a six-degree-of-freedom force-reflecting haptic interface device, PHANToM with the GHOST SDK software. This work is the continuation of the authors' previous work at the ICRA'02 [Pernalete, N, et al, 2002], in which only results of fully able individuals were presented. Two motion-impaired users with severe forms of muscular dystrophy and spinal cord injure, volunteered to participate in the experiments and their results are presented in this article. The results demonstrated that the forms of assistance provided reduced the execution times and increased the performance of the chosen tasks for the disabled individuals as well as they did for the fully-able persons. In addition, these results suggest that the introduction of the haptic rendering capabilities, including the force feedback, offers special benefit to motion-impaired users by augmenting their performance on job-related tasks.

关键词： Telerobotics Haptic interfaces Medical treatment System testing Humans Intelligent sensors User interfaces Software testing Imaging phantoms Spinal cord

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Global robust control of feedforward systems: state-feedback and output-feedback

Global robust control of feedforward systems: state-feedback...

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IEEE Conference on Decision and Control

作者： P. Krishnamurthy F. Khorrami Contml/Robotics Researzh Laboratory(CRRL) Department of Electrical and Computer Engineering Polytechnic University Brooklyn NY USA

ISBN: (纸本)0780379241

In this paper, we propose a robust control design technique for feedforward systems based on our recent results on dynamic high-gain scaling techniques for controller design for strict-feedback-type systems. We consider both state-feedback and output-feedback. The designed controllers have a very simple structure being essentially a linear feedback with state-dependent dynamic gains and do not involve any saturations or recursive computations. The observer in the output-feedback case is similar to a Luenberger observer with dynamic observer gains. The Lyapunov functions are quadratic in the states (and the observer errors in the case of output-feedback). The stability analysis is based on our recent results on uniform solvability of coupled state-dependent Lyapunov equations. The controller design provides strong robustness properties both with respect to uncertain parameters in the system model and additive disturbances. This robustness is the key to the output-feedback controller design.

关键词： Robust control Feedforward systems Control systems Signal design Nonlinear dynamical systems Robots Laboratories Design engineering Control design Feedback

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Real-time stereo-based vehicle occupant posture determination for intelligent airbag deployment

Real-time stereo-based vehicle occupant posture determinatio...

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IEEE Symposium on Intelligent Vehicle

作者： T.D. Schoenmackers M.M. Trivedi Department of Electrical and Computer Engineering Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

From 1990 to April 2002, according to the National Highway Traffic Safety Administration (NHTSA), airbag deployment has been responsible for 208 deaths in low-severity crashes. Of these deaths, 107 were children between the ages of 1 and 11, 22 were infants, and 32 were women under the height of five feet two inches. In addition to deaths, airbags are responsible for many more incidental injuries and broken bones. These injuries could be avoided if the system had an accurate model of the actual pose of the occupant. This paper discusses a system we are developing to accurately determine the position of the head, torso, and arms of the front-seat occupant of a vehicle.

关键词： Intelligent vehicles Head Intelligent robots US department of Transportation Pediatrics Injuries Torso Intelligent sensors Road vehicles Vehicle safety

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Kernel snakes: non-parametric active contour models

Kernel snakes: non-parametric active contour models

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IEEE International Conference on Systems, Man and Cybernetics

作者： W. Abd-Almageed C.E. Smith S. Ramadan Robotics Artificial Intelligence and Vision Laboratory Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

In this paper, a new non-parametric generalized formulation to statistical pressure snakes is presented. We discuss the shortcomings of the traditional pressure snakes. We then introduce a new generic pressure model that alleviates these shortcomings, based on the Bayesian decision theory. Non-parametric techniques are used to obtain the statistical models that drive the snake. We discuss the advantages of using the proposed non-parametric model compared to other parametric techniques. Multi-colored-target tracking is used to demonstrate the performance of the proposed approach. Experimental results show enhanced, real-time performance.

关键词： Kernel Active contours Deformable models Image edge detection Intelligent robots Robot vision systems Artificial intelligence Laboratories Bayesian methods Decision theory

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Driver's view and vehicle surround estimation using omnidirectional video stream

Driver's view and vehicle surround estimation using omnidire...

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IEEE Symposium on Intelligent Vehicle

作者： K.S. Huang M.M. Trivedi T. Gandhi Computer Vision and Robotics Research (CVRR) Laboratory Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA

Our research is focused on the development of novel machine vision based telematic systems, which provide non-intrusive probing of the state of the driver and driving conditions. In this paper we present a system which allows simultaneous capture of the driver's head pose, driving view, and surroundings of the vehicle. The integrated machine vision system utilizes a video stream of full 360 degree panoramic field of view. The processing modules include perspective transformation, feature extraction, head detection, head pose estimation, driving view synthesis, and motion segmentation. The paper presents a multi-state statistical decision models with Kalman filtering based tracking for head pose detection and face orientation estimation. The basic feasibility and robustness of the approach is demonstrated with a series of systematic experimental studies.

关键词： Vehicle driving Streaming media Magnetic heads Machine vision Face detection Telematics Feature extraction Motion detection Motion estimation Motion segmentation

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Textual message read by a mobile robot

Textual message read by a mobile robot

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： D. Letourneau F. Michaud J.-M. Valin C. Proulx Department of Electrical Engineering and Computer Engineering Universite de Sherbrooke LABORIUS - Research Laboratory on Mobile Robotics and Intelligent Systems Sherbrooke Quebec CANADA

Giving the ability to read characters and symbols is highly desirable for increased autonomy of mobile robots operating in the real world. The idea is fairly simple: give a robot the ability to acquire an image of a message to read, extract the symbols and recognize them. Image character recognition research has been going on for decades now, with good results. But compared to conventional character recognition systems, the challenge with a mobile robot is to find a textual message to capture in the world and to get a good view of the message, knowing that the viewpoint of the robot depends on its position in relation to the message, which cannot be pre-specified. In this paper we present our approach making it possible for an autonomous mobile robot to read messages. We outline the constraints under which the approach works, and present results obtained using a Pioneer 2 robot equipped with a Pentium 233 MHz and a pan-tilt-zoom camera.

关键词： Mobile robots Robot vision systems Cameras Intelligent robots Character recognition Image recognition Navigation Laboratories Mobile computing Intelligent systems

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Implementation of a neural network based system for estimating the strength of a board using mixed signals

Implementation of a neural network based system for estimati...

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IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： H. Saboksayr A. Saravi P.D. Lawrence F. Lam IEEE Control System Society Vancouver Canada Robotics and Control Laboratoryratory Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Robotics and Control Laboratory Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada Department of Wood Science University of British Columbia Vancouver Canada

An intelligent lumber grading system was developed to provide a new way for estimating the strength of a board by posing the estimation problem as an empirical learning problem. This system processed the X-ray image, extracted geometric features (of 1000 boards that eventually underwent destructive strength testing), and predicted the strength of the lumber by using a neural network. The X-ray image was passed through a threshold filter to separate the knots based on the fact that a denser knot produces a local maximum (as a rounded protrusion in an otherwise almost flat density surface) of the X-ray image. Each knot was modeled by a three-dimensional-cone with seven parameters. Information on all the detected knots such as volume, and knot-area-ratio were fed to a processor to generate 16 geometrical features (such as; the average of knot area ratio, and the number of knots detected in each board), which characterize each board. Then by using back-propagation as the training method, cross correlation as the measure of accuracy, and actual strength of a thousand boards as the empirical data set, a neural network was trained to estimate the strength of each board. The learning system consisted of three layers, with 1, 5, 16 neurons in output, hidden and input layer respectively. Ten-fold cross validation was used to produce an unbiased accuracy of the estimation problem. The learning and testing sets comprised of 900 and 100 boards respectively. By repeating the learning and testing for ten times and averaging the results, a coefficient of determination of 0.4059 was reached in this study for using X-ray images alone. The same methodology was applied to MOE (modulus of elasticity) and a coefficient of determination of 0.56 was reached. The results were improved by fusing the X-ray image and MOE using a learning system consisting of three layers, with 1, 5, 40 neurons in output, hidden and input layer respectively. Ten-Fold cross validation resulted in a coefficient o

关键词： Neural networks X-ray imaging Feature extraction Learning systems Neurons Intelligent systems System testing Filters Character generation Elasticity

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