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检索条件"任意字段=Conference on Intelligent Robots and Computer Vision XXXII - Algorithms and Techniques"

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Beyond adaptive critic-creative learning for intelligent mobile robots

Beyond adaptive critic-creative learning for intelligent mob...

引用

conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Liao, XQ Cao, M Hall, E Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081944300X

intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new teaming method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning- imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it pe

关键词： reinforcement learning systems adaptive critic intelligent robots heuristic dynamic programming (HDP) dual heuristic programming (DHP) globalized DHP (GDHP)

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Remote hardware reconfigurable robotic camera

Remote hardware reconfigurable robotic camera

引用

conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Arias-Estrada, M Torres-Huitzil, C Maya-Rueda, S Natl Inst Astrophys Opt & Elect Dept Comp Sci Puebla Mexico

ISBN: (纸本)081944300X

In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer, into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software funcionalities that can be exchanged during run-time. The system has been validated with an edge detection and a motion processing architectures, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.

关键词： smart camera FPGA for computer vision reconfigurable architectures

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Boundary extraction in the SEM cross section of LSI

Boundary extraction in the SEM cross section of LSI

引用

conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Nakamae, K Midoh, Y Miura, K Fujioka, H Osaka Univ Grad Sch Engn Dept Informat Syst Engn Suita Osaka 5650871 Japan

ISBN: (纸本)081944300X

We have proposed a boundary extraction algorithm for cross-sectional critical dimension (CD) measurements of the scanning electron microscope (SEM) images in machine/computer vision. Noisy SEM images have the image discontinuity of roof edge with peak. A task is to extract a low contrast boundary or edge with about one pixel width in a noisy cross sectional SEM image. Also CD measurements require that the algorithm locate a boundary or an edge at the correct position. Our policy is to detect the edges with high degree of confidence at first, and then to extract the edges with the high probabilities of edge that are calculated by using gray levels of neighboring pixels. Our proposed algorithm integrates the Gaussian pyramid to suppress noise, morphological operations to detect the edges with high degree of confidence, the relaxation method to recover the gaps in the detected edges, and the hierarchical approach. Application of the proposed algorithm to cross sectional SEM images of DRAMs shows its validity.

关键词： critical dimension measurements cross sectional SEM image boundary extraction morphological operators machine vision

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Interaction of perception and gaze control in autonomous vehicles

Interaction of perception and gaze control in autonomous veh...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Pellkofer, M Lützeler, M Dickmanns, ED UBM Inst Systedynam & Flugmechan Munich Germany

ISBN: (纸本)081944300X

For robust and secure behavior in natural environment an autonomous vehicle needs an elaborate vision sensor as main source of information. The vision sensor must be adaptable to the external situation, the mission, the capabilities of the vehicle and the knowledge about the external world accumulated up to the present time. In the EMS-vision system, this vision sensor consists of four cameras with different focal lengths mounted on a highly dynamic pan-tilt camera head. Image processing, gaze control and behavior decision interact with each other in a closed loop. The image processing experts specify so-called regions of attention (RoAs) for each object in 3D object coordinates. These RoAs should be visible with a resolution as required by the measurement techniques applied. The behavior decision module specifies the relevance of obstacles like road segments, crossings or landmarks in the situation context. The gaze control unit takes all this information in order to plan, optimize and perform a sequence of smooth pursuits, interrupted by saccades. The sequence with the best information gain is performed. ne information gain depends on the relevance of objects or object parts, the duration of smooth pursuit maneuvers, the quality of perception and the number of saccades. The functioning of the EMS-vision system is demonstrated in a complex and scalable autonomous mission with the UBM test vehicle VAMORS.

关键词： active vision autonomous vehicles road recognition

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2D vision in a 3D System

2D vision in a 3D System

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Flinders, M Intelligent Automat Syst Cambridge MA USA

ISBN: (纸本)081944300X

2D vision in a 3D System will be an overview of important software and mechanical issues related to designing and implementing a system with 3-dimensional characteristics constrained by a 2-dimensional vision system. A general methodology for choosing the right components, including cameras, optics, and lighting will be discussed. Some choices for image processing techniques, related in particular to calibration and pattern-matching approaches, will be overviewed. The discussion will involve approaches to auto-focusing and additional mathematical algorithms that may likely be required. These issues will include world-to-camera transformations and considerations to take when dealing with rotational attributes. The presentation is intended primarily for software engineers and/or other engineers that would be involved in the prototyping, design, and implementation phases of such a project. Typical examples of such systems will be cited and a more in-depth overview of a particular example will be made. Some typical pitfalls, both mechanical and software-related, will also be broached.

关键词： machine vision camera calibration image processing robot image distortion geometric pattern match shadow diffuse light

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The effect of different thresholding methods in RGB Imaging

The effect of different thresholding methods in RGB Imaging

引用

conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Miettinen, J Ailisto, H VTT Elect FIN-90571 Oulu Finland

ISBN: (纸本)081944300X

Typical surface inspection tasks using RGB vision require the analysis of tens of megabytes of image data per second, with low false alarm and error escape rates. Although automatic inspection systems have become more common on production lines, for example in sawmills, there are substantial needs to improve their performance and accuracy. Detection is one very important part of image flow before defect recognition. Detection is used in order to find suspicious regions of the image, containing possibly defective areas, since defect detection has to cope with very high data rates. It has to be based on relative simple methods. In this paper we describe the effect of different thresholding methods in RGB defect detection. Threshold values were calculated for R, G and B channels, difference channels \R-G\, \R-B\ and \G-B\ and for mean values from R, G and B channels. The analysis was performed for pine-wood. Error escape rate and false alarm rates were used as evaluation criteria. In this paper, R and G channel thresholding methods were the best ones.

关键词： machine vision detection threshold color wood

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Testing a structural light vision software by genetic algorithms: Estimating the worst case behavior of volume measurement

Testing a structural light vision software by genetic algori...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Mantere, T Alander, JT Turku Ctr Comp Sci TUCS FIN-20520 Turku Finland

ISBN: (纸本)081944300X

In this study we use genetic algorithms to generate test surfaces for a proposed structured light 3-D vision system in order to estimate the worst case behavior of error tolerances. The object software evaluates surface profiles for measuring volumes of small objects attached on surfaces that are highly constrained while somewhat arbitrarily shaped. The test system tries to find, by using genetic algorithm search, the shape that results the highest relative error of volume. The parameters of the object system to be optimized include laser angle, image size, object step size, and the number of scan directions. The preliminary results got seem to indicate that a genetic algorithm based approach is a beneficial aid in optical system design.

关键词： genetic algorithms image processing 3-D imaging 3-D metrology machine vision simulation structured light vision

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Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

Image understanding systems based on the unifying representa...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Kuvychko, I

ISBN: (纸本)081944300X

vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the "cortical software". Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently "unexplainable" results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both "what" and "where" visual pathways. Such systems can open new horizons for robotic and computer vision industries.

关键词： image understanding mid-level and high-level vision computational intelligence knowledge & vision engines

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Real-time computer vision system for mobile robot

Real-time computer vision system for mobile robot

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Persa, S Jonker, P Delft Univ Technol Pattern Recognit Grp NL-2628 CJ Delft Netherlands

ISBN: (纸本)081944300X

The purpose of this paper is to present a real-time vision system for position determination and vision guidance to navigate an autonomous mobile robot in a known environment. We use a digital camera, which provide ten times the video capture bandwidth then a USB, using FireWire interface. In order to achieve real-time image processing we use MMX technology to accelerate vision tasks. Camera calibration is a necessary step in 3D computer vision in order to extract metric information from 2D images. Calibration is used to determine the camera parameters by minimizing the mean square error between model and calibration points. The camera calibration we use here is based on several views of a planar calibration pattern, which is an easy to use and accurate algorithm. For position pose of the robot we use the corner points and lines, features extracted from the image, and matched with the model of the environment. The algorithm is as follows: first we compute an initial pose using the Ganatipathy's four point algorithm and we use this initial estimation as the starting point for the iterative algorithm proposed by Araujo in order to refine our pose.

关键词： real-time vision calibration position estimation navigation mobile robots

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An application of GPS systems on a mobile robot

An application of GPS systems on a mobile robot

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Cao, P Saxena, M Tedder, M Michalske, S Hall, EL Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081944300X

The purpose of this paper is to describe the use of Global Positioning Systems (GPS) as geographic information and navigational system for a ground based mobile robot. Several low cost wireless systems are now available for a variety of innovative automobile applications including location, messaging and tracking and security. Experiments were conducted with a test bed mobile robot, Bearcat II, for point-to-point motion using a Motorola GPS in June 2001. The Motorola M12 Oncore GPS system is connected to the Bearcat U main control computer through a RS232 interface. A mapping program is used to define a desired route. Then GPS information may be displayed for verification. However, the GPS information is also used to update the control points of the mobile robot using a reinforcement learning method. Local position updates are also used when found in the environment. The significance of the method is in extending the use of GPS to local vehicle control that requires more resolution that is available from the raw data using the adaptive control method.

关键词： global positioning systems intelligent robots mobile robots

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