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Model Identification of a Low-Speed UUV

IFAC Proceedings Volumes 2001年第7期34卷 395-400页

作者： P. Ridao J. Battle M. Carreras Computer Vision and Robotics Group University of Girona Edifici Politécnica II Campus Montilivi 17071 Girona Spain

This paper presents a simple and effective model identification method for Unmanned Underwater Vehicles (UUV). The complete process, with 3 different phases, is firstly described and successively applied to the underwater robot GARBI. The identification is aimed at uncoupling the different degrees of freedom (DOF) in low-speed vehicles, and is based completely on low-cost sensors. Least square techniques are used to estimate the UUV dynamics parameters. Experiments in the laboratory and in a real underwater environment were carried out. Numerical and graphical results of the GARBI identification process are included.

关键词： Identification Modelling Marine Systems Robot dynamics Vehicle Simulation

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A system to evaluate the accuracy of a visual mosaicking methodology

A system to evaluate the accuracy of a visual mosaicking met...

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OCEANS

作者： R. Garcia J. Batlle X. Cufi Institute of Informatics and Applications Computer Vision and Robotics Group University of Girona Girona Spain

When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system.

关键词： Image sequences Underwater vehicles Motion estimation Robot vision systems Cameras Navigation Oceans computer vision Laboratories computer errors

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Estimating the motion of an underwater robot from a monocular image sequence

Estimating the motion of an underwater robot from a monocula...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia X. Cufi M. Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot.

关键词： Motion estimation Robots Navigation Underwater vehicles Oceans Floors computer vision Motion detection Vehicle detection Image analysis

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Detection of matchings in a sequence of underwater images through texture analysis

Detection of matchings in a sequence of underwater images th...

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IEEE International Conference on Image Processing

作者： R. Garcia C. Xevi J. Battle Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain Computer Vision and Robotics Group E.P.S. Girona Spain Universitat de Girona Girona Catalunya ES

This paper presents an approach to ameliorate the reliability of the correspondence points relating two consecutive images of a sequence. The images are especially difficult to handle, since they have been acquired by a camera looking at the sea floor while carried by an underwater robot. Underwater images are usually difficult to process due to light absorption, changing image radiance and lack of well-defined features. A new approach based on gray-level region matching and selective texture analysis significantly improves the matching reliability.

关键词： Underwater tracking Image analysis Image sequence analysis Image texture analysis Robot vision systems Cameras Motion detection Vehicle detection Underwater vehicles Testing

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Inverse finite element characterization of soft tissues 4th

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4th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2001

作者： Kauer, M. Vuskovic, V. Dual, J. Szekely, G. Bajka, M. Centre of Mechanics ETH Zurich Zurich8092 Switzerland Institute of Robotics ETH Zurich Zurich8092 Switzerland Computer Vision Group ETH Zurich Zurich8092 Switzerland Department of Gynaecology University Hospital Zurich8091 Switzerland

ISBN: (纸本)3540426973

In this work a tissue aspiration method for the in-vivo determination of biological soft tissue material parameters is presented. An explicit axisymmetric finite element simulation of the aspiration experiment is used together with a Levenberg-Marquardt algorithm to estimate the material model parameters in an inverse parameter determination process. Soft biological tissue is modelled as a viscoelastic, non-linear, nearly incompressible, isotropic continuum. Viscoelasticity is accounted for by a quasi-linear formulation. The aspiration method is validated experimentally with a synthetic material. In-vivo (intra-operatively during surgical interventions) and ex-vivo experiments were performed on human uteri. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Viscoelasticity

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Implementation of a Real-Time Target Tracking Behaviour Using Video Sensors

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IFAC Proceedings Volumes 2001年第7期34卷 517-521页

作者： V. lla P. Ridao J.De La Cruz J. Batlle Computer Vision and Robotics Group Institute of Informatics and Applications. University of Girona Edifici Politecnica ll Campus Montilivi 17071 Girona Spain

Using software OS, real-time operation is constrained by acquisition and preprocessing tasks of input signals. In this way, this paper presents an implementation of a real time target tracking behaviour, from snapped images of the environment, as an example of how to take advantage of real-time hardware devices as a helpful systems for control architectures. A specific board based on FPGA/DSP processors has been used in order to reach this goal. The system has been thought for a marine and underwater environment and it has been tested using GARBI autonomous underwater vehicle. The implemented behaviours allow the robot to navigate autonomously and follow a diver.

关键词： behaviour binary image autonomous vehicle computer control

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Development of a mammographic analysis system using computer vision techniques 2

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2nd International Symposium on Medical Data Analysis, ISMDA 2001

作者： Martí, J. Planiol, P. Freixenet, J. Español, J. Golobardes, E. University of Girona Computer Vision and Robotics Group – IIiA Campus de Montilivi Girona17071 Spain University Hospital of Girona "Dr. Josep Trueta" Department of Oncology Avda. de Fraņca s/n Girona17071 Spain Universitat Ramon Llull Computer Science Department Passeig Bonanova 8 Barcelona08022 Spain

ISBN: (纸本)3540427341

This work presents an application intended to work as a second reader in Radiology Services for digital mammograms, which makes use of several computer vision algorithms. Although the presented prototype basically focuses on the detection and the characterization of microcalcifications, the system has the capability to grow up by adding new abnormalities (e.g. masses) or new classification patterns. Experimental results of the system’s performance have been obtained through digital mammograms of the Regional Health Area of Girona. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Mammography

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Visual attention-based robot navigation using information sampling

Visual attention-based robot navigation using information sa...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： N. Winters J. Santos-Victor Computer Vision and Robotics Group Department of Computer Science University of Dublin-Trinity College Dublin Ireland Instituto de Sistemas e Robótica Instituto Superior Técnico Lisboa Portugal

Presents a method whereby an autonomous mobile robot automatically selects the most informative data from a set of images acquired a priori, using a statistical method termed information sampling. These data could be a single pixel or a number scattered throughout an image. This information is then used to build a topological map of the environment. Our sole input data are omnidirectional images obtained from a catadioptric panoramic camera. Experimental results show that by using only the best data the topological position of a robot, visually maneuvering through a simple indoor environment, can easily be determined.

关键词： Navigation Sampling methods Image sampling robotics and automation Mobile robots Statistical analysis Pixel Scattering Robot vision systems Cameras

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O 2 CA 2 : A New Hybrid Control Architecture for a Low Cost AUV

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IFAC Proceedings Volumes 2001年第7期34卷 311-316页

作者： P. Ridao M. Carreras J. Batlle J. Amat Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Edifici Politècnica II Campus Montilivi 17071 Girona Spain Department of Automatic Control and Computer Engineering Politechnical University of Catalunya. Pau Gargallo n°5 08028 Barcelona (Spain).

The Object Oriented Control Architecture for Autonomy (O 2 CA 2 ) is a control architecture being developed at the University of Girona for the GARBI underwater vehicle. Conceived as a hybrid, it is organised in three layers (Deliberative, Control Execution and Reactive) merging the deliberation mechanisms of planning with reactive behaviours in charge of controlling the robot. The aim of this paper is to provide an overall description of the whole architecture and an in depth description of the Reactive-layer. The concepts of the architecture have been tested with the simulation of a simple mission consisting of navigating through a sequence of way-points while avoiding contact with obstacles.

关键词： Autonomous Vehicles Control architectures behaviour fuzzy systems guidance navigation marine systems

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Positioning an underwater vehicle through image mosaicking

Positioning an underwater vehicle through image mosaicking

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IEEE International Conference on robotics and Automation (ICRA)

作者： R. Garcia J. Batlle X. Cufi J. Amat Computer Vision and Robotics Group IIiA University of Girona E. P. S. P-II Girona Spain Department of Automatic Control and Computer Engineering Polytechnic University of Catalonia Barcelona Spain

ISBN: (纸本)0780365763

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle.

关键词： Underwater vehicles Cameras Motion detection Navigation Oceans Floors Underwater tracking Lighting Optical scattering Feature extraction

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