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IEEE International Conference on Automation, Quality and Testing, robotics, AQTR

作者： Arnau Oliver Xavier Munoz Joan Batlle Lluis Pacheco Jordi Freixenet Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

关键词： Clustering algorithms Image segmentation Partitioning algorithms Proposals Clustering methods computer vision Robot kinematics Robot vision systems Informatics Application software

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Augmented state Kalman filtering for AUV navigation

Augmented state Kalman filtering for AUV navigation

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IEEE International Conference on robotics and Automation (ICRA)

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

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position.

关键词： Kalman filters Filtering Navigation Motion estimation Underwater vehicles Oceans Remotely operated vehicles Cameras Sea floor State estimation

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Towards a real-time vision-based navigation system for a small-class UUV

Towards a real-time vision-based navigation system for a sma...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia T. Nicosevici P. Ridao D. Ribas Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory.

关键词： Real time systems Motion estimation Underwater vehicles Sea measurements Position measurement Dead reckoning Sonar navigation Robot vision systems Hydrodynamics Costs

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Omnidirectional depth computation from a single image

Omnidirectional depth computation from a single image

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2005 IEEE International Conference on robotics and Automation

作者： Orghidan, Radu Mouaddib, El Mustapha Salvi, Joaquim Centre de Robotique Electrotechnique et d'Automatique Université de Picardie Jules Verne Amiens France Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Catalonia Spain

ISBN: (纸本)078038914X

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications. © 2005 IEEE.

关键词： Cameras

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REAL-TIME vision BASED AUV NAVIGATION SYSTEM USING A COMPLEMENTARY SENSOR SUITE

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IFAC Proceedings Volumes 2007年第17期40卷 373-378页

作者： Jonathan Horgan Daniel Toal Pere Ridao Rafael Garcia Mobile and Marine Robotics Research Centre Department of Electronic and Computer Engineering University of Limerick Ireland Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Spain

This paper proposes a real-time navigation system for an AUV that takes advantage of the complementary performance of a sensor suite including a DVL, a compass, a depth sensor and altimeter sensors with a feature based motion estimator using vision. To allow for real-time performance of the vision based motion estimator a simple but fast correlation algorithm is used for feature matching. The compass and the depth sensors are used to bound the drift of the heading and depth estimations respectively. The altimeter is required in order to translate the feature displacements measured from the images into the metric displacements of the robot. While the robot must rely on DVL navigation above a certain altitude where vision is useless, DVL measurements can be complemented with higher frequency accurate motion estimates from the vision system when navigating close to the seafloor.

关键词： marine robotics robot vision Kalman filtering robot navigation

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Classifying textures when seen from different distances

Classifying textures when seen from different distances

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作者： Lladó, X. Petrou, M. Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH United Kingdom Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona 17071 Girona Spain

The purpose of this work is to analyse what happens to the surface information when the image resolution is modified. We deduce how the same surface appears if seen from different distances. Using 4-source Colour Photometric Stereo, which provides the surface shape and colour information, a method for predicting how surface texture looks like when changing the distance of the camera is presented. We demonstrate this technique by classifying textured surfaces seen from different distances than the textured surfaces in the database. © 2002 IEEE.

关键词： Classification (of information)

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Active regions for colour texture segmentation integrating region and boundary information

Active regions for colour texture segmentation integrating r...

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IEEE International Conference on Image Processing

作者： X. Munoz J. Freixenet X. Cufi J. Marti Computer Vision and Robotics Group. Institute of Informatics and Applications University of Girona Girona Spain

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method.

关键词： Image segmentation Proposals Data mining Image edge detection Pixel computer vision Robot vision systems Informatics Application software Kernel

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ROV-Aided Dam Inspection: Practical Results

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IFAC Proceedings Volumes 2003年第21期36卷 271-274页

作者： Joan Batlle Tudor Nicosevici Rafael Garcia Marc Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona E.P.S. 17071 Girona Spain

Nowadays Unmanned Underwater Vehicles (UUVs) are used in a growing number of underwater missions, mostly inspections of different types of installations such as: telecommunication cables, pipes or oil extraction installations. A field where UUVs are still starting to prove their utility is dam inspection. This paper presents details our first approach in dam inspection. A set of experiments carried out at a dam in Romania is described. Advantages and drawbacks of using a small-class underwater vehicle are analyzed for this type of missions.

关键词： computer vision teleoperation fault detection motion estimation

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Policy Gradient Based Reinforcement Learning for Real Autonomous Underwater Cable Tracking

Policy Gradient Based Reinforcement Learning for Real Autono...

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2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Pages 3133-3660

作者： Andres El-Fakdi Marc Carreras Computer Vision and Robotics Group (VICOROB) Institute of Informatics and Applications University of Girona 17074 Girona Spain

ISBN: (纸本)9781424420575

This paper proposes a field application of a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a Direct Policy Search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU~(AUV).

关键词： Robots Underwater cables Vehicles Power cables Artificial neural networks Surges Robot sensing systems

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Image Mosaicking for Estimating the Motion of an Underwater Vehicle

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IFAC Proceedings Volumes 2000年第21期33卷 147-152页

作者： Rafael García Xevi Cufí Lluís Pacheco Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Edifici Politècnica II Escola Politecnica Superior 17071 Girona Spain

A composite image constructed by combining a set of smaller images is known as mosaic. Mosaics of the ocean floor are very useful in undersea exploration, creation of visual maps, navigation, etc. A feature-based mosaicking method is proposed, based on textural parameters of certain parts of the image. Textures significantly help in the identification of given features of the image. The tracking of these features over time solves the matching problem in consecutive frames. The correspondence is established with the aid of a cross-correlation algorithm, applied to the colour components of the image in the HSI space. Once the correspondence has been found a displacement vector is obtained relating the features of two images of the sequence. The motion parameters between consecutive frames are estimated through an error minimisation technique. Once the best transformation between two frames has been found, images are warped together composing the mosaic, and information about the vehicle motion is recovered. The experimental results on real images show the effectiveness of the proposed method.

关键词： computer vision Motion estimation Autonomous vehicles Image registration Robot navigation Marine Systems

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