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Springer Tracts in Advanced robotics 2013年 87卷 1-11页

作者： Nicosevici, Tudor Garcia, Rafael Computer Vision and Robotics Group University of Girona EPS-PIV Campus Montilivi Girona17071 Spain

The aim of this book is to provide a complete framework for efficient 3D modeling. More specifically, given an image sequence of a scene, the objective is to provide a high-precision textured 3D reconstruction of the ...

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2D-3D camera fusion for visual odometry in outdoor environments

2D-3D camera fusion for visual odometry in outdoor environme...

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2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Danda Pani Paudel Cédric Demonceaux Adlane Habed Pascal Vasseur In So Kweon Le2i University of Burgundy France ICube University of Strasbourg France LITIS University of Rouen France Robotics and Computer Vision Lab KAIST Korea

Accurate estimation of camera motion is very important for many robotics applications involving SfM and visual SLAM. Such accuracy is attempted by refining the estimated motion through nonlinear optimization. As many modern robots are equipped with both 2D and 3D cameras, it is both highly desirable and challenging to exploit data acquired from both modalities to achieve a better localization. Existing refinement methods, such as Bundle adjustment and loop closing, may be employed only when precise 2D-to-3D correspondences across frames are available. In this paper, we propose a framework for robot localization that benefits from both 2D and 3D information without requiring such accurate correspondences to be established. This is carried out through a 2D-3D based initial motion estimation followed by a constrained nonlinear optimization for motion refinement. The initial motion estimation finds the best possible 2D-to-3D correspondences and localizes the cameras with respect the 3D scene. The refinement step minimizes the projection errors of 3D points while preserving the existing relationships between images. The problems of occlusion and that of missing scene parts are handled by comparing the image-based reconstruction and 3D sensor measurements. The effect of data inaccuracies is minimized using an M-estimator based technique. Our experiments have demonstrated that the proposed framework allows to obtain a good initial motion estimate and a significant improvement through refinement.

关键词： Cameras Three-dimensional displays Image reconstruction Optimization Lasers Robot sensing systems

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Fast Fog Detection for Camera Based Advanced Driver Assistance Systems

Fast Fog Detection for Camera Based Advanced Driver Assistan...

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IEEE International Conference on Intelligent Transportation Systems

作者： Rita Spinneker Carsten Koch Su-Birm Park Jason Jeongsuk Yoon Hochschule Emden/Leer Automation and Robotics (I2AR) Emden Germany LG Electronics Future IT Lab Computer Vision Team Seoul Republic of Korea

In an increasing number of cars, the driver is supported by Advanced Driver Assistance Systems (ADAS). In particular camera based ADAS are a key component for further improvements in safety and driving comfort. While imaging sensors are performing well under good weather conditions, their efficiency suffers under adverse environmental influences such as heavy rain, fog or snow. To handle such optical threats and to estimate information quality of cameras in order to warn the assistance system of possible critical working conditions, a self-diagnosis mechanism is of great importance for reliable operation of an optical ADAS. In this paper an approach of camera based fog detection as part of a self-diagnosis mechanism for ADAS based on the blurring effect of fog is presented. The encouraging results of our experiments have shown that the presented approach of analysing the power spectrum slope (PSS) of a small image block in close proximity to the vanishing point enables a fast discrimination of street scenes with and without fog.

关键词： Cameras Vehicles Roads Integrated optics Optical imaging Optical sensors Automotive components

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Sonar-based Chain Following using an Autonomous Underwater Vehicle

Sonar-based Chain Following using an Autonomous Underwater V...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Natalia Hurtos Narcis Palomeras Arnau Carrera Marc Carreras Charalampos P. Bechlioulis George C. Karras Shahab Hesmati-alamdari Kostas Kyriakopoulos Computer Vision and Robotics Group (VI-COROB) University de Girona 17071 Girona Spain School of Mechanical Engineering National Technical University of Athens Athens 15780 Greece

ISBN: (纸本)9781479969357

Tracking an underwater chain using an autonomous vehicle can be a first step towards more efficient solutions for cleaning and inspecting mooring chains. We propose to use a forward looking sonar as a primary perception sensor to enable the vehicle operation in limited visibility conditions and overcome the turbidity arisen during marine growth removal. Despite its advantages, working with acoustic imagery raises additional challenges to the involved image processing and control methodologies. In this paper we present a robust framework to perform chain following, combining perception, planning and control disciplines. We first introduce a detection system that exploits the sonar's high frame rate and applies local pattern matching to handle the complexity of detecting link chains in acoustic images. Then, a planning system deals with the dispersed detections and determines the link waypoints that the vehicle should reach. Finally, the vehicle is guided through these waypoints using a high level controller that has been tailored to simultaneously traverse the chain and keep track of upcoming links. Experiments on real data demonstrate the capability of autonomously follow a chain with sufficient accuracy to perform subsequent cleaning or inspection tasks.

关键词： Autonomous underwater vehicles Vehicle operations Pattern matching Acoustic imagery Detection systems underwater vehicles sonar Autonomous Vehicles Frame Rate vehicle Underwater

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I-AUV Docking and Intervention in a Subsea Panel

I-AUV Docking and Intervention in a Subsea Panel

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Narcis Palomeras Antonio Penalver Miquel Massot-Campos Guillem Vallicrosa Pep Lluis Negre J. Javier Fernandez Pere Ridao Pedro J. Sanz Gabriel Oliver-Codina Albert Palomer Universitat de Girona Computer Vision and Robotics Institute Centre d'Investigacio en Robotica Submarina (CIRS) 17071 Girona (Spain) Universitat Jaume I Interactive and Robotic Systems Laboratory (IRSLab) 12071 Castello (Spain) Universitat de les Illes Balears Systems Robotics and Vision Group 07122 Palma de Mallorca (Spain)

ISBN: (纸本)9781479969357

While commercially available autonomous underwater vehicles (AUVs) are routinely used in survey missions, a new set of applications exist which clearly demand intervention capabilities: the maintenance of permanent underwater structures as well as the recovery of benthic stations or black-boxes are a few of them. These tasks are addressed nowadays using manned submersibles or work-class remotely operated vehicles (ROVs), equipped with teleoperated arms under human supervision. In the context of the TRITON Spanish funded project, a subsea panel docking and an intervention procedure are proposed. The light-weight intervention AUV (I-AUV) Girona 500 is used to autonomously dock into a subsea panel using a funnel-based docking method for passive accommodation. Once docked, an autonomous fixed-based manipulation system, which uses feedback from a digital camera, is used to turn a valve and plug/unplug a connector. The paper presents the techniques used for the autonomous docking and manipulation as well as how the adapted subsea panel has been designed to facilitate such operations.

关键词： Subsea Intervention Manned submersibles Underwater structures Device Panel Berthing Unmanned vehicles Digital cameras Autonomous underwater vehicles BLACK-BOX

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Coping with stress using social robots as emotion-oriented tool: Potential factors discovered from stress game experiment

Coping with stress using social robots as emotion-oriented t...

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5th International Conference on Social robotics, ICSR 2013

作者： Dang, Thi-Hai-Ha Tapus, Adriana Robotics and Computer Vision Lab. ENSTA-Paristech France

ISBN: (纸本)9783319026749

It is known from psychology that humans cope with stress by either changing stress-induced situations (which is called problemoriented coping strategy) or by changing his/her internal perception about the stress-induced situations (which is called emotion-oriented coping strategy). Social robots, as emerging tools that have abilities to socially interact with humans, can be of great use to help people coping with stress. The paper discusses some recent studies about ways of dealing with stress in stressful situations by using social robots. Moreover, we focus on presenting our experimental design and the discovered factors that can allow social robots to assist humans in dealing with stress in an emotion-oriented manner. © Springer International Publishing 2013.

关键词： Machine design

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Kim, Jungho Choi, Byeongho Kweon, In-So Multimedia IP Research Center KETI Robotics and Computer Vision Lab. KAIST

ISBN: (纸本)9781479903566

Object detection in real images or videos is challenging because the shapes and sizes of objects vary significantly according to their poses, camera viewing direction, and partial occlusion. Previous detection methods employ sliding-window-based schemes that scan windows across an image, requiring many differently shaped windows to capture shape and size variation. In order to solve this problem, we propose an object detection method using hierarchical graph-based segmentation: color-consistent parts are obtained by part-level segmentation and category-consistent regions are found using object-level segmentation. Thus we can avoid scanning a lot of windows across whole images by using part-level segmentation and robustly detect the objects of various shapes and sizes by using object-level segmentation. In addition, we evaluate detection performance using various classifiers with our detection approach.

关键词： Object detection Object classification Graph-based segmentation

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Efficient topology estimation for large scale optical mapping

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Springer Tracts in Advanced robotics 2013年 82卷 1-100页

作者： Elibol, Armaĝan Gracias, Nuno Garcia, Rafael Department of Mathematical Engineering Yildiz Technical University Istanbul Turkey Computer Vision and Robotics Group University of Girona Girona Spain

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Fast Fog Detection for Camera Based Advanced Driver Assistance Systems

Fast Fog Detection for Camera Based Advanced Driver Assistan...

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17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems Engineering Conference 2014

作者： Rita Spinneker Carsten Koch Su-Birm Park Jason Jeongsuk Yoon Hochschule Emden/Leer University of Applied Sciences Institute of InformaticsAutomation and Robotics (I2AR)EmdenGermany LG Electronics Future IT Lab Computer Vision Team SeoulRepublic of Korea

In an increasing number of cars,the driver is supported by Advanced Driver Assistance Systems(ADAS).In particular camera based ADAS are a key component for further improvements in safety and driving *** imaging sensors are performing well under good weather conditions,their efficiency suffers under adverse environmental influences such as heavy rain,fog or *** handle such optical threats and to estimate information quality of cameras in order to warn the assistance system of possible critical working conditions,a self-diagnosis mechanism is of great importance for reliable operation of an optical *** this paper an approach of camera based fog detection as part of a self-diagnosis mechanism for ADAS based on the blurring effect of fog is *** encouraging results of our experiments have shown that the presented approach of analysing the power spectrum slope(PSS) of a small image block in close proximity to the vanishing point enables a fast discrimination of street scenes with and without fog.

关键词： image Fast Fog Detection for Camera Based Advanced Driver Assistance Systems

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