An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The use of these machines in factory automation can improve productivity, increase product quality and improve competitiv...
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ISBN:
(纸本)081944300X
An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The use of these machines in factory automation can improve productivity, increase product quality and improve competitiveness. This paper presents a discussion of recent and future technical and economic trends. During the past twenty years the use of industrial robots that are equipped not only with precise motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. intelligent robot products have been developed in many cases for factory automation and for some hospital and home applications. To reach an even higher degree of applications, the addition of learning may be required. Recently, learning theories such as the adaptive critic have been proposed. In this type of learning, a critic provides a grade to the controller of an action module such as a robot. The adaptive critic is a good model for human learning. In general, the critic may be considered to be the human with the teach pendant, plant manager, line supervisor, quality inspector or the consumer. If the ultimate critic is the consumer, then the quality inspector must model the consumer's decision-making process and use this model in the design and manufacturing operations. Can the "adaptive critic" be used to advance intelligentrobots? intelligentrobots have historically taken decades to be developed and reduced to practice. Methods for speeding this development include technology such as rapid prototyping and product development and government, industry and university cooperation.
A model of an object is an image consisting of features of die object. The input is a gray scale image from which features are computed. In his doctoral thesis [7] J. L. Chen used a model based approach for object rec...
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ISBN:
(纸本)081944300X
A model of an object is an image consisting of features of die object. The input is a gray scale image from which features are computed. In his doctoral thesis [7] J. L. Chen used a model based approach for object recognition. His method is based on Rosin's work [26] for extraction of parts. Both model and scene features are contour based properties. Properties of each part such as area, compactness, convexity etc. are computed and used to match the scene image to the model. This paper extends the algorithm in several directions. The contours are improved using two passes over the initial input image. The notion of internal part or base of an object is introduced and used to normalize the part areas. Insignificant parts are merged with neighboring parts to provide a better segmentation of the scene. Interpretation trees are used to match scene to object. The algorithm is tested on simple hand drawn images and also images of buildings obtained from architectural databases.
The analysis of the prenatal engineering of the human brain and more specifically that of the human eye may encourage new interpretations and better understanding of 'cortical' processors and lead to better id...
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ISBN:
(纸本)081944300X
The analysis of the prenatal engineering of the human brain and more specifically that of the human eye may encourage new interpretations and better understanding of 'cortical' processors and lead to better ideas about how to built optical sensors. What human vision at its first processing stages realizes is an adaptive transformation of physical parameters from an 'outer' 4D-spatiotemporal into an 'inner' psychological world or its reciprocal projection and construction of an illusionary (inner or outer) world. The description of some of the most remarkable steps in the development of the human eye before birth, very critical for the optical functionalities in vision, will illustrate the new interpretations.
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 bel...
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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
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-tim...
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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 computervision 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.
We have proposed a boundary extraction algorithm for cross-sectional critical dimension (CD) measurements of the scanning electron microscope (SEM) images in machine/computervision. Noisy SEM images have the image di...
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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/computervision. 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.
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, t...
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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.
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. ...
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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.
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...
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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.
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 surfa...
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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.
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