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Multiagent fault‐diagnosis expert system in power systems

European Transactions on electrical Power 1995年第5期5卷 341-347页

作者： Wang, J.P. Trécat, J. Dr. Jianping Wang is a doctor fellow in the Faculte Polytechnique de Mons in Belgium. His current research field is parallel processing applications in power systems. Dr. Wang obtained his BS degree from Southwest Jiaotong University in P.R. Chinain 1982. From 1982 to 1990 he was appointed as an assistant lecturer. lecturer and associate professor respectively in the electrical engineering department of Southwest Jiaotong University. He obtained his Ph.D in the FacultC Polytechnique de Mons in July of 1993. (BD Dolez 3 1 FPMS B-7000 Mons Belgium T +32-65/37 41 87 Fax +32-65/37 43 00) Professor J. Trécat is a director in the power system laboratory in the Faculty Polytechnique de Mons. He obtained his Ph.D in the University of Manchester Institute of Science and Technology(UM1ST) in U.K. in 1970. He has been working in the fields of power system automation artificial intelligence application and computer vision in the Facult6 Polytechnique de Mons since 1970. He is a senior member of IEEE and he has made much contribution both in electrical engineering education and research. (BD Dolez 3 I FPMS B-7000 Mons T +32-651374185. Fax +32-6513743 00)

In order to solve the speed problem and shallow reasoning problem met in current research in fault diagnosis expert system, this paper presents a model based parallel fault diagnosis expert system for energy management systems (EMS). The Petri net model, which corresponds to the relationship between power system components and their protection systems, has been used for the inference in fault diagnosis. A multiagent parallel processing expert system, which is based on five transputers in Sun workstation, has been built for fault diagnosis purposes. The test results show that this expert system is not only fast but also has better performances. Copyright © 1995 John Wiley & Sons, Ltd.

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Motion perception using spatiotemporal frequency analysis

Motion perception using spatiotemporal frequency analysis

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IEEE International Conference on Image Processing

作者： G. Ravichandran M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. We present a new computational framework for motion perception. Our methodology considers spatiotemporal frequency (STF) domain analysis to extract the optical flow information. First, we show that a sequence of image frames can be used to extract the motion parameters for the different regions in a dynamic scene using the basic Fourier transform properties in the STF analysis approach. A detailed analytical description of this model to interchangably extract motion and depth parameters and results to highlight their salient properties are presented.< >

关键词： Motion analysis Spatiotemporal phenomena Image motion analysis Data mining Layout Frequency domain analysis Information analysis Fourier transforms Image analysis Image sequence analysis

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Coordinating motion of cooperative mobile robots through visual observation

Coordinating motion of cooperative mobile robots through vis...

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IEEE International Conference on Systems, Man and Cybernetics

作者： S.B. Marapane M. Holder M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee TN USA

This paper describes the development of an integrated autonomous multi-robot system, where two heterogeneous robots exhibit coordinated convoying behavior. Coordination is accomplished without any communication but by visual observation. An active perception system uses visual servoing to track the leading vehicle to determine its heading and relative distance. A fuzzy logic based real-time motion controller uses the heading to control the steering and relative distance and velocity information to adjust the speed to let the trailing robot smoothly follow the leader. A novel correlation algorithm based on minimum noise and correlation energy (MINACE) filter is used for object tracking. The MINACE based tracker is adaptive and when the tracking degrades due to the change in appearance of the leading robot a new filter is synthesized online to replace the old one. The performance and robustness of the convoying system has been verified in a series of extensive laboratory trials.< >

关键词： Mobile robots Robot kinematics Motion control Velocity control Communication system control Filters Multirobot systems Mobile communication Visual servoing Remotely operated vehicles

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Motion and depth perception using spatiotemporal frequency analysis

Motion and depth perception using spatiotemporal frequency a...

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IEEE International Conference on Systems, Man and Cybernetics

作者： G. Ravichandran M.M. Trivedi Electrical and Computer Engineering Department Computer Vision and Robrics Research Laboratory Computer Vision and Robotics Laboratary University of Tennessee Knoxville TN USA

Motion information is extracted by identifying the temporal signature associated with the textured objects in the scene. In this paper, we present a new computational framework for motion perception. Our methodology considers spatiotemporal frequency (STF) domain analysis to extract the optical flow information. First, we show that a sequence of image frames can be used to extract the motion parameters for the different regions in a dynamic scene using the basic Fourier transform properties in the STF analysis approach. When the observer (or the camera) moves, motion is induced in the scene, and the extracted motion information can then be used to estimate the depth parameters. A detailed analytical description of this model to interchangably extract motion and depth parameters and results to highlight their salient properties are presented.< >

关键词： Motion analysis Spatiotemporal phenomena Data mining Layout Image motion analysis Frequency domain analysis Information analysis Fourier transforms Image analysis Image sequence analysis

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Sensor based obstacle avoidance and mapping for fast mobile robots

Sensor based obstacle avoidance and mapping for fast mobile ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： C. Gourley M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper describes one aspect of a project whose goal is to move a robot in an unknown environment and find pipes to decommission. While moving through the environment a low level map, in the form of an occupancy grid, along with detailed location of pipes in the environment are obtained. This paper deals only with the low level "reflex" of obstacle avoidance that is performed while the robot moves along its path as well as some of the higher level tasks involved in path planning and robot motion in order to negotiate through a hazardous environment. The overall high level interaction with the system is made as simple and user friendly as possible using a graphical interface to control high level tasks. All low level communications and processing are transparent. The robot used for experimentation is a wheeled mobile platform equipped with many different sensors including ultrasonic range sensors and cameras. A quick and efficient obstacle avoidance algorithm has been developed using sixteen ultrasonic range sensor and one infrared proximity sensor.< >

关键词： Mobile robots Infrared sensors Robot sensing systems Path planning Robot motion Communication system control Control systems Mobile communication Robot vision systems Cameras

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Texture segmentation using circular-Mellin operators

Texture segmentation using circular-Mellin operators

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IEEE International Conference on Image Processing

作者： G. Ravichandran M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

Texture is an important preattentive cue in region-based segmentation of images. In this paper, we discuss the use of circular-Mellin features for segmenting an image into homogenous regions. The circular-Mellin operators represent the spectral decomposition of the image scene in the polar-log coordinate system and are invariant to both scale and orientation of the target. Coupled with the unique shift invariance property of the correlator architecture, these circular-Mellin operators can be used for rotation- and scale-invariant feature extraction. We note that while both these feature extractors have similar functional form to the Gabor functions, the distortion-invariant characteristics of the circular-Mellin operators make them preferable for texture segmentation. Segmentation results to demonstrate their salient properties are presented.< >

关键词： Image segmentation Layout computer vision Correlators Feature extraction Maximum likelihood detection Filtering theory Gabor filters Nonlinear filters Pattern recognition

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Simulation and visualization of integrated sensory-motor systems

Simulation and visualization of integrated sensory-motor sys...

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IEEE Workshop on Visualization and Machine vision

作者： S.B. Marapane M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

A binocular robot head, BETH, with ten degrees of freedom (DOF) has been developed for research in active vision. To complement BETH, a graphical simulation and visualization environment has also been developed. The objective of building the graphical system is to create a comprehensive design tool to design and study the dynamic behavior of sensory-motor systems and their interactions with the environment. This environment integrates perception and motor actions and features complete kinematic simulation of BETH, it's sensors and it's workspace. We demonstrate the utility of this environment in systematic and extensive experimental development of computational frameworks and algorithms for 3D active vision systems which utilizes multiple passive depth cues (stereo, vergence, and depth from focusing).< >

关键词： Visualization Head Robot sensing systems Robot vision systems computer vision Computational modeling Buildings Focusing Image analysis Machine vision

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Acquisition of 3D structure of selectable quality from image streams

Acquisition of 3D structure of selectable quality from image...

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IEEE Workshop on Applications of computer vision (WACV)

作者： A.K. Dalmia M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

In this paper we present a computational approach for extracting three-dimensional structure of controllable resolution, depth of field, and accuracy, all made available at real-time speeds. This approach utilizes the spatial and the temporal gradients of the streams of images acquired using an actively controlled camera. Depending on the requirements of a particular task, appropriate parameters such as disparity value sought, the inter-frame camera displacement, and number of frames in a stream, are chosen to control the resolution, depth of field, and accuracy. The acquisition and processing of the image stream are done in real-time on a pipeline architecture based processor. Extensive experiments are presented to demonstrate the accuracy, controllability of depth of field and resolution, and ability to perform successfully in a variety of scenes. The system operated with no latency between the image acquisition and processing. The total acquisition and processing time in these experiments is in the range of 0.27 to 1.56 sec. The depth results have an accuracy of 85% to 92%.< >

关键词： Streaming media computer vision Machine vision Cameras Pipelines Spatial resolution Layout Delay Performance analysis Robot vision systems

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Localized Radon transform-based detection of linear features in noisy images

Localized Radon transform-based detection of linear features...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Copeland Ravichandran Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The algorithm, referred to as the feature space line detector (FSLD) algorithm, is tested on synthetic images of linear features with very high noise levels. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions or that display some curvature.< >

关键词： Feature extraction

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Real-time visual tracking using correlation techniques

Real-time visual tracking using correlation techniques

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IEEE Workshop on Applications of computer vision (WACV)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The Minimum Noise and Correlation Energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3-D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation. The correlation filter-based tracking algorithm has proved to be useful in our research in cooperative mobile robots. A visual servoing system has been implemented using this tracking algorithm for convoying of multiple mobile robots.< >

关键词： Target tracking Cameras Robot vision systems Visual servoing computer vision Adaptive filters Mobile robots Laboratories Power engineering and energy Pipelines

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