intelligent pattern recognition techniques have become important in the fields of computer and robot vision. Our interest focuses on detection of dynamical variables which allows robotic visual units to define object ...
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ISBN:
(纸本)0780358422
intelligent pattern recognition techniques have become important in the fields of computer and robot vision. Our interest focuses on detection of dynamical variables which allows robotic visual units to define object evolution from 2D images. We describe a computational algorithm which predicts the real scene images using spatial Fourier frequency transforms multiplied by transforms of dynamic model integro-differential equations. The theoretical results have been simulated by computer numerical image processing and compared to expected real scenes.
A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle (AGV) robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an...
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ISBN:
(纸本)0819434302
A Neuro-fuzzy control method for navigation of an Autonomous Guided Vehicle (AGV) robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by a terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigate ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its I;igh robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification which are based on the analysis of the classifying neural network and the Neuro-fuzzy algorithm is presented. The significance of this work lies in the development of a new method for mobile robot navigation.
This paper introduces a fast and efficient indexing approach for both 2D & 3D model-based object recognition in the presence of rotation, translation, and scale Variations of objects. The indexing entries are comp...
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ISBN:
(纸本)0819434302
This paper introduces a fast and efficient indexing approach for both 2D & 3D model-based object recognition in the presence of rotation, translation, and scale Variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A Bst of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.
We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and defect regions found on wooden boards. Specifically we present...
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ISBN:
(纸本)0819434302
We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and defect regions found on wooden boards. Specifically we present a method to find an optimal set of parameters for a given two-dimensional object detection method. The method uses banks of Gabor filters to limit the range of spatial frequencies, where mutually distinct textures differ significantly in their dominant characterizing frequencies. By encoding images into multiple narrow spatial frequency and orientation channels a local classification of texture regions can be achieved. Unlike other methods applying Gabor filters, we do not use a full Gabor transform, but use feature selection techniques to maximize discrimination. The selection method uses a genetic algorithm to optimize various parameters of the system including Gabor weights, and the parameters of morphological pre-processing. We demonstrate the applicability of the method to the task of classifying wooden textures, and report experimental results using the proposed method.
In this paper a sequence of algorithms for image feature point detection and tracking as well as Euclidian reconstruction of rigid three-dimensional objects from point correspondences is presented. For fully automatic...
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ISBN:
(纸本)0819434302
In this paper a sequence of algorithms for image feature point detection and tracking as well as Euclidian reconstruction of rigid three-dimensional objects from point correspondences is presented. For fully automatic point feature detection, grayvalue images are processed. High-curvature points on contours, i.e. contour elements with locally maximal curvature, are tracked using a normalized correlation algorithm. High-curvature points that could be tracked in a sequence of more than three images are used as point features that are eligible for reconstruction. Since the general way to obtain the epipolar, projective, and Euclidian geometries from point feature correspondences is already solved, here the emphasis is on the performance of the algorithms in the presense of noise. Kanatani's epipolar geometry estimation method is improved and this is experimentally validated. Regarding Bougnoux's Euclidian geometry estimation method, the initial linear solution is now obtained with less uncertainty and the non-linear minimization does no longer converge to a hidden solution. Experimental results are given to assess the system performance.
Motion control is one of the most critical factors in the design of a robot. The purpose of this paper is to describe the research for applying motion control principles for a mobile robot systems design, which is on ...
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ISBN:
(纸本)0819434302
Motion control is one of the most critical factors in the design of a robot. The purpose of this paper is to describe the research for applying motion control principles for a mobile robot systems design, which is on going at the University of Cincinnati Robotics Center. The mobile robot was constructed during the 1998-1999 academic year, and called BEARCAT II. Its design has inherited many features of its predecessor, BEARCAT I, such as vision guidance, sonar detection and digital control. In addition, BEARCAT II achieved many innovative motion control features as rotating sonar, zero turning radius (ZTR), current control loop, and multi-level controller design (conventional control and fuzzy logic control). This paper will focus on the motion control design, development and programming for the vehicle steering control and rotating sonar systems. The systems have been constructed and tested at the 1999 International Ground Robotics Competition with the Bearcat II running an obstacle course for 153.5 feet and finishing fourth in the competition. The significance of this work is in the increased understanding of robot control and the potential application of autonomous guided vehicle technology for industry, defense and medicine. Keywords: Motion control, motion behavior, compensation, mobile robots.
In the future, interaction between humans and personal robots will become increasingly important as robots will, more and more, operate as assistants in our everyday life. Because of this, there is a need for a conven...
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ISBN:
(纸本)0819434302
In the future, interaction between humans and personal robots will become increasingly important as robots will, more and more, operate as assistants in our everyday life. Because of this, there is a need for a convenient, flexible, and general-purpose technique that we can use to interact with robots. Moreover, the same technique should also be usable when we interact with embedded systems in smart environments. In this paper, we will describe a technique that allows us to use a single simple handheld control device to interact not only with personal robots, but also with ubiquitous embedded systems. When a new system, whether a mobile robot or a VCR, is encountered, the control device downloads a mobile code from the system and executes it. The mobile code then uses the services provided by the control device to create a virtual user interface that we can use to interact with the particular system. Our technique is flexible, simple, adaptive, and open. The technique draws much of its flexibility and simplicity from the mobile code. Adaptivity comes from the fact that the control device only needs minimal knowledge about each particular system. In addition, the technique does not place any restrictions on the type of mobile code that can be used. We will describe the architecture of the CUES system that utilizes our technique. We will also describe the architecture of the SMAF system, our test bed mobile code execution environment used in CUES. In addition, we will present a virtual user interface for a mobile robot that we can use to control the robot and to monitor its status information. The interface also operates as a terminal that we can use to access remote information in the Internet.
This article shows how graph and diagrammatic structures could evolve into the more abstract ones that carry knowledge about the originals in form of relations and hierarchies. They can play a role of context, or &quo...
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ISBN:
(纸本)0819434302
This article shows how graph and diagrammatic structures could evolve into the more abstract ones that carry knowledge about the originals in form of relations and hierarchies. They can play a role of context, or "measurement device", giving the ability to analyze. Such derivative structures can drive processes in distributed networks, like firing a spatio-temporal pattern, creating another structure, etc., therefore, performing top-bottom algorithms. In the mid-80 PDP group came closely to the problem of knowledge representation by distributed graphs called "schemata". Their models were based on the neural networks. I argue that the actual level of problems that neural network can solve is lower than required for knowledge representation. The "hardware unit" of intelligence could rather be a "neural assembly'' that combines both discrete and continuous features, and is able to perform both diagrammatic and graphs operations, being the basis of intelligence. The representation of such "neural assembly" as a fuzzy logic unit with active kernel and less active fuzzy boundaries is proposed. Such units can make logical operations spatially and temporarily, acting on a diagrammatic manner. Connections between the set of such activated units make spatio-temporal pattern really looking like a set of nodes connected via links on more abstract level. The article shows that image understanding is the area where derivative structures play important role, making images and scenes self-describing without any word description, and truly invariant to any transformations. That opens way to the new technologies in computervision and image databases.
Human visual system is properly suited for reliable and adequate volumic perception of natural environment. Volumic data flows coming from the outer physical space are easily acquired, transferred and processed by eye...
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ISBN:
(纸本)0819434302
Human visual system is properly suited for reliable and adequate volumic perception of natural environment. Volumic data flows coming from the outer physical space are easily acquired, transferred and processed by eye-brain system in real time. This relates also to the animals which use different complicated mechanisms of optical volumic data acquisition and can navigate safely at high speeds. Un the contrary machine vision systems utilizing currently the stereoscopic effect in attempt to achieve volumic data presentation are very slow, bulky and in a way inelegantly devised. The stereoscopy itself seems can hardly organize the adequate, real time volumic robot vision. Novel general principles of volumic vision were formulated recently by this author. They can be applied also to machines and used in the future rapidly navigating mobile robots. Volumic approach to vision seems much more logical for handling of volumic data flows. Along the lines of this approach and unified concept of volumic imaging it is quite natural to assume fine stratification in depth both for biological volumic data sensors and the necessity of fine stratification in depth for artificial ones. Volumic data sensors in robotics seem must be organized as finely stratified in depth structures. Finely stratified in depth volumic data sensor operating in real time might incorporate volumic gratings and use a special software to interpret the arriving volumic data flow. While the task is very difficult, success would permit to organize volumic robot vision in a different war and to create principally novel type of robotic system, ie, 'one-eyed robots'. Preliminary experiments were performed in this work. Complicated holographic gratings were obtained which might serve as components of a future volumic data sensor. Microphotographs of such gratings taken as horizontally stratified slices are presented.
An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The current use of these machines in outer space, medicine, hazardous materials, defense applications and industry is bei...
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An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The current use of these machines in outer space, medicine, hazardous materials, defense applications and industry is being pursued with vigor but little funding. In factory automation such robotics machines can improve productivity, increase product quality and improve competitiveness. The computer and the robot have both been developed during recent times. The intelligent robot combines both technologies and requires a thorough understanding and knowledge of mechatronics. In honor of the new millennium, this paper will present a discussion of futuristic trends and predictions. However, in keeping with technical tradition, a new technique for `Follow the Leader' will also be presented in the hope of it becoming a new, useful and non-obvious technique. Today's robotic machines are faster, cheaper, more repeatable, more reliable and safer. The knowledge base of inverse kinematic and dynamic solutions and intelligent controls is increasing. More attention is being given by industry to robots, vision and motion controls. New areas of usage are emerging for service robots, remote manipulators and automated guided vehicles. Economically, the robotics industry now has more than a billion-dollar market in the U.S. and is growing. Feasibility studies show decreasing costs for robots and unaudited healthy rates of return for a variety of robotic applications. However, the road from inspiration to successful application can be long and difficult, often taking decades to achieve a new product. A greater emphasis on mechatronics is needed in our universities. Certainly, more cooperation between government, industry and universities is needed to speed the development of intelligentrobots that will benefit industry and society.
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