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

共 373 条记录，以下是151-160 订阅

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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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A fault diagnostic system for a mobile robot

A fault diagnostic system for a mobile robot

引用

conference on intelligent robots and computer vision XVI - algorithms, techniques, Active vision, and Materials Handling

作者： Nikam, U Hall, E Department of Mechanical Industrial and Nuclear Engineering University of Cincinnati Cincinnati OH 45221 United States

ISBN: (纸本)0819426407

This paper describes the development of a Robot Fault Diagnosis System (RFDS). Though designed ostensibly for the University of Cincinnati's autonomous, unmanned, mobile robot for a national competition, it has the flexibility to be adapted for industrial applications as well. Using a top-down approach the robot is sub-divided into different functional units, such as the vision guidance system, the ultrasonic obstacle avoidance system, the steering mechanism, the speed control system, the braking system and the power unit. The techniques of Potential Failure Mode and Effects Analysis (PFMEA) are used to analyze faults, their visible symptoms, and probable causes and remedies. The relationships obtained therefrom are mapped in a database framework. This is then coded in a user-friendly interactive Visual Basic((TM)) program that guides the user to the likely cause(s) of failure through a question-answer format. A provision is made to ensure better accuracy of the system by incorporating historical data on failures as it becomes available. The RFDS thus provides a handy trouble-shooting tool that cuts down the time involved in diagnosing failures in the complex robot consisting of mechanical, electric, electronic and optical systems. This has been of great help in diagnosing failures and ensuring maximum performance from the robot during the contest in the face of pressure of the competition and the outdoor conditions.

关键词： intelligent robot fault diagnosis potential failure modes and effects

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Remotely controlling of mobile robots using gesture captured by the Kinect and recognized by machine learning method

Remotely controlling of mobile robots using gesture captured...

引用

conference on intelligent robots and computer vision XXX - algorithms and techniques

作者： Hsu, Roy Chaoming Jian, Jhih-Wei Lin, Chih-Chuan Lai, Chien-Hung Liu, Cheng-Ting Dept Elect Engn 300 Syuefu Rd Chiayi 60004 Taiwan Dept Comp Sci Informat Engn Chiayi 60004 Taiwan

ISBN: (纸本)9780819494351

The main purpose of this paper is to use machine learning method and Kinect and its body sensation technology to design a simple, convenient, yet effective robot remote control system. In this study, a Kinect sensor is used to capture the human body skeleton with depth information, and a gesture training and identification method is designed using the back propagation neural network to remotely command a mobile robot for certain actions via the Bluetooth. The experimental results show that the designed mobile robots remote control system can achieve, on an average, more than 96% of accurate identification of 7 types of gestures and can effectively control a real e-puck robot for the designed commands.

关键词： Robot remote control Kinect sensor gesture recognition back propagation neural network

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From vision to action: Grasping unmodeled objects from a heap

From vision to action: Grasping unmodeled objects from a hea...

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conference on intelligent robots and computer vision XIV - algorithms, techniques, Active vision, and Materials Handling

作者： Rutishauser, M Ade, F SWISS FED INST TECHNOL IMAGE SCI LABCH-8092 ZURICHSWITZERLAND

ISBN: (纸本)0819419524

We have investigated the problem of removing objects from a heap without having recourse to object models. This capability is useful for `intelligent singulation', i.e., the decomposition of a heap into isolated objects. As we are exclusively relying on geometric information, the use of range data is a natural choice. To ensure that we see opposite patches of the object surfaces, we use up to three range views from different directions. These views are triangulated using the data points as vertices. After merging the views, the resulting surface description is segmented, i.e., partitioned into large sets of contiguous triangles which correspond to objects or object components in the scene. The system then tries to detect grasping opportunities. Two heuristics guide the selection of a `focus of action' which consists of a suitable component. For this component, good grasping point pairs are found by using an intelligent search technique. If no pairs are found due to impending collisions or bad grasping quality another component is checked. Finally the robot performs the grasping. Force sensing allows the correction of inaccuracies of the vision system and the handling of collisions.

关键词： range data segmentation evidence accumulation discrete optimization grasping

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computer vision system for an autonomous mobile robot

Computer vision system for an autonomous mobile robot

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

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

ISBN: (纸本)0819438626

The purpose of this paper is to compare three methods for three-dimensional measurements of line position used for the vision guidance to navigate an autonomous mobile robot. A model is first developed to map three dimensional ground points into image points to be developed using homogeneous coordinates. Then using the ground plane constraint, the inverse transformation that maps image points into three dimensional ground points is determined. And then the system identification problem is solved using a calibration device. Calibration data is used to determine the model parameters by minimizing the mean square error between model and calibration points. A novel simplification is then presented which provides surprisingly accurate results. This method is called the magic matrix approach and uses only the calibration data. A more standard variation of this approach is also considered. The significance of this work is that it shows that three methods that are based on three-dimensional measurements may be used for mobile robot navigation and that a simple method can achieve accuracy to a fraction of an inch which is sufficient in some applications.

关键词： autonomous mobile robot calibration navigation magic matrix

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Digital image based tree measurement for forest inventory

Digital image based tree measurement for forest inventory

引用

conference on intelligent robots and computer vision XVII - algorithms, techniques, and Active vision

作者： Juujarvi, J Heikkonen, J Brandt, S Lampinen, J Helsinki Univ Technol Lab Computat Engn FIN-02015 HUT Finland

ISBN: (纸本)081942983X

In this paper we propose a digital camera based method for estimating the stem diameters of growing trees for forest inventory purposes. The imaging system consists of a single camera, a laser distance measurement device and a calibration stick placed beside the tree to be measured. To carry out the task camera geometry parameters are first;determined using linear pinhole camera and nonlinear lens distortion models. In addition of the accurate camera calibration, the viewing geometry has to be determined for 3-D measurement purpose with the help of the calibration stick. The estimation of the stem diameters is carried out by combining the stem curve information from the image with a priori stem form model. Experimental results reported with Scots pines indicate that this approach provides feasible solutions for the measurement task.

关键词： 3D machine vision camera calibration image segmentation stem form model forest inventory

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Stereo-based registration of LADAR and color imagery

Stereo-based registration of LADAR and color imagery

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conference on intelligent robots and computer vision XVII - algorithms, techniques, and Active vision

作者： Elstrom, MD Smith, PW Abidi, MA Univ Tennessee Dept Elect Engn Imaging Robot & Intelligent Syst Lab Knoxville TN 37996 USA

ISBN: (纸本)081942983X

A major problem in the creation of multi-sensory interfaces for tele-robotics is the development of methods for combining various data sources into one coherent world model for examination by the operator. However, if the images acquired from different sensing modalities can be registered with LADAR range images, texture mapping can be employed for sensor integration. Presented in this paper is a novel stereo-based method for registering color and LADAR images acquired from externally uncalibrated sensors fbr use in a visualization system as described above. In our approach, corresponding features are first extracted from LADAR intensity/color image pairs. Since the computation of Euclidean range using stereoscopic techniques depends on knowledge of the relative sensor orientation, a downhill simplex algorithm is iteratively applied to minimize the sum-squared-error between the stereo and LADAR range estimates of the matched points with respect to the system's relative rotation and translation parameters. Once the system's epipolar geometry has been estimated in this manner, the LADAR range data is employed to re-project the color image to the viewpoint of the scanner for use as a texture map.

关键词： color image processing range imaging registration stereo 3D vision : perception processing and modeling

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techniques for fisheye lens calibration using a minimal number of measurements

Techniques for fisheye lens calibration using a minimal numb...

引用

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

作者： Mundhenk, TN Rivett, MJ Liao, XQ Hall, EL Univ Cincinnati Ctr Robot Res Dept Mech Ind & Nucl Engn Cincinnati OH 45221 USA

ISBN: (纸本)0819438626

A method is discussed describing how different types of Omni-Directional "fisheye" lenses can be calibrated for use in robotic vision. The technique discussed will allow for full calibration and correction of x,y pixel coordinates while only taking two uncalibrated and one calibrated measurement. These are done by finding the observed x,y coordinates of a calibration target. Any Fisheye lens that has a roughly spherical shape can have its distortion corrected with this technique, Two measurements are taken to discover the edges and centroid of the lens. These can be done automatically by the computer and does not require any knowledge about the lens or the location of the calibration target. A third measurement is then taken to discover the degree of spherical distortion, This is done by comparing the expected measurement to the measurement obtained and then plotting a curve that describes the degree of distortion. Once the degree of distortion is known and a simple curve has been fitted to the distortion shape, the equation of that distortion and the simple dimensions of the lens are plugged into an equation that remains the same for all types of lenses. The technique has the advantage of needing only one calibrated measurement to discover the type of lens bring used.

关键词： onmi vision fisheye circular regression correction distortion nikon

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Self-learning, self-broadening knowledge base for calibration-free robot vision

Self-learning, self-broadening knowledge base for calibratio...

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conference on intelligent robots and computer vision XVII - algorithms, techniques, and Active vision

作者： Nguyen, MC Graefe, V Univ Bundeswehr Munchen Inst Messtech D-85577 Neubiberg Germany

ISBN: (纸本)081942983X

A new concept of a self-learning, self-broadening knowledge base that may be used as the long-term memory for a completely calibration-free robot vision to manipulate objects is presented. With this concept the robot automatically acquires during its normal operation the necessary knowledge which can be saved afterwards in the knowledge base and allowing the robot to adapt itself to changing conditions. Thus, the robot presents self-learning characteristics. The robot control using the knowledge base is then based on the human way of solving problems, i.e. new, additional facts (in our case control words) are developed from available facts. Such a control enables improving skills of the robot. The concept has been successfully realized and tested in real-word experiments with an uncalibrated vision-guided manipulator involving the grasping of various objects with nearly any shape and in an arbitrary orientation in horizontal plane.

关键词： self-learning robot calibration-free robot control robot vision machine learning object grasping knowledge based systems

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Improved single-camera stereo system for mobile robotics

Improved single-camera stereo system for mobile robotics

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Lovegrove, William P. McGary, Patrick D. Austin, Kelly Bob Jones Univ Greenville SC 29614 USA

ISBN: (纸本)9780819479327

A single-camera stereo vision system offers a greatly simplified approach to image capture and analysis. In the original study by Lovegrove and Brame, they proposed a novel optical system that uses a single camera to capture two short, wide stereo images that can then be analyzed for real-time obstacle detection. In this paper, further analysis and refinement of the optical design results in two virtual cameras with perfectly parallel central axes. A new prototype camera design provides experimental verification of the analysis and also provides insight into practical construction. The experimental device showed that the virtual cameras' axes possessed a deviation from parallel of less than 12 minutes (or 0.2 degrees). The calculation of distances to objects from the two overlapping images all showed errors smaller than the pixel resolution limitation. In addition, a barrel lens correction was used in processing the image to allow parallax distance determination in the whole horizontal view of the images.

关键词： stereo vision single camera stereo pair mobile robot obstacle detection computer vision

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