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  • 1.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Colour perception graph for characters segmentation2014In: Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings / [ed] George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Chandra Kambhamettu, Maha El Choubassi, Zhigang Deng, Mark Carlson, Springer, 2014, p. 598-608Conference paper (Refereed)
    Abstract [en]

    Characters recognition in natural images is a challenging problem, asit involves segmenting characters of various colours on various background. Inthis article, we present a method for segmenting images that use a colour percep-tion graph. Our algorithm is inspired by graph cut segmentation techniques andit use an edge detection technique for filtering the graph before the graph-cut aswell as merging segments as a final step. We also present both qualitative andquantitative results, which show that our algorithm perform at slightly better andfaster to a state of the art algorithm.

  • 2.
    Berger, Cyrille
    Laboratoire d'Analyse et d'Architecture des Systèmes (LAAS), l'Université Toulouse, France.
    Perception de la géométrie de l'environment pour la navigation autonome2009Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The goal of the mobile robotic research is to give robots the capability to accomplish missions in an environment that might be unknown. To accomplish his mission, the robot need to execute a given set of elementary actions (movement, manipulation of objects...) which require an accurate localisation of the robot, as well as a the construction of good geometric model of the environment. Thus, a robot will need to take the most out of his own sensors, of external sensors, of information coming from an other robot and of existing model coming from a Geographic Information System. The common information is the geometry of the environment. The first part of the presentation will be about the different methods to extract geometric information. The second part will be about the creation of the geometric model using a graph structure, along with a method to retrieve information in the graph to allow the robot to localise itself in the environment.

  • 3.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Strokes detection for skeletonisation of characters shapes2014In: Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part II / [ed] George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Chandra Kambhamettu, Maha El Choubassi, Zhigang Deng, Mark Carlson, Springer, 2014, p. 510-520Conference paper (Refereed)
    Abstract [en]

    Skeletonisation is a key process in character recognition in natural images. Under the assumption that a character is made of a stroke of uniform colour, with small variation in thickness, the process of recognising characters can be decomposed in the three steps. First the image is segmented, then each segment is transformed into a set of connected strokes (skeletonisation), which are then abstracted in a descriptor that can be used to recognise the character. The main issue with skeletonisation is the sensitivity with noise, and especially, the presence of holes in the masks. In this article, a new method for the extraction of strokes is presented, which address the problem of holes in the mask and does not use any parameters.

  • 4.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Toward rich geometric map for SLAM: Online Detection of Planes in 2D LIDAR2012In: Proceedings of the International Workshop on Perception for Mobile Robots Autonomy (PEMRA), 2012Conference paper (Refereed)
    Abstract [en]

    Rich geometric models of the environment are needed for robots to accomplish their missions. However a robot operatingin a large environment would require a compact representation.

    In this article, we present a method that relies on the idea that a plane appears as a line segment in a 2D scan, andthat by tracking those lines frame after frame, it is possible to estimate the parameters of that plane. The method istherefore divided in three steps: fitting line segments on the points of the 2D scan, tracking those line segments inconsecutive scan and estimating the parameters with a graph based SLAM (Simultaneous Localisation And Mapping)algorithm.

  • 5.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR2013In: Journal of Automation, Mobile Robotics & Intelligent Systems, ISSN 1897-8649, E-ISSN 2080-2145, Vol. 7, no 1, p. 35-41Article in journal (Refereed)
    Abstract [en]

    Rich geometric models of the environment are needed for robots to carry out their missions. However a robot operating in a large environment would require a compact representation. In this article, we present a method that relies on the idea that a plane appears as a line segment in a 2D scan, and that by tracking those lines frame after frame, it is possible to estimate the parameters of that plane. The method is divided in three steps: fitting line segments on the points of the 2D scan, tracking those line segments in consecutive scan and estimating the parameters with a graph based SLAM (Simultaneous Localisation And Mapping) algorithm.

  • 6.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Weak Constraints Network Optimiser2012In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE , 2012, p. 1270-1277Conference paper (Refereed)
    Abstract [en]

    We present a general framework to estimate the parameters of both a robot and landmarks in 3D. It relies on the use of a stochastic gradient descent method for the optimisation of the nodes in a graph of weak constraints where the landmarks and robot poses are the nodes. Then a belief propagation method combined with covariance intersection is used to estimate the uncertainties of the nodes. The first part of the article describes what is needed to define a constraint and a node models, how those models are used to update the parameters and the uncertainties of the nodes. The second part present the models used for robot poses and interest points, as well as simulation results.

  • 7.
    Berger, Cyrille
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Lacroix, Simon
    LAAS.
    DSeg: Détection directe de segments dans une image2010In: 17ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA), 2010Conference paper (Refereed)
    Abstract [en]

    This paper presents a model-driven approach todetect image line segments. The approach incrementally detects segments on thegradient image using a linear Kalman filter that estimates the supporting lineparameters and their associated variances. The algorithms are fast and robustwith respect to image noise and illumination variations, they allow thedetection of longer line segments than data-driven approaches, and do notrequire any tedious parameters tuning. Results with varying scene illuminationand comparisons to classic existing approaches are presented.

  • 8.
    Berger, Cyrille
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Lacroix, Simon
    LAAS.
    Modélisation de l'environnement par facettes planes pour la Cartographie et la Localisation Simultanées par stéréovision2008In: Reconnaissance des Formes et Intelligence Artificielle (RFIA), 2008Conference paper (Refereed)
  • 9.
    Berger, Cyrille
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Lacroix, Simon
    LAAS/CNRS, Univ. of Toulouse, Toulouse, France.
    Using planar facets for stereovision SLAM2008In: Proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), IEEE conference proceedings, 2008, p. 1606-1611Conference paper (Refereed)
    Abstract [en]

    In the context of stereovision SLAM, we propose a way to enrich the landmark models. Vision-based SLAM approaches usually rely on interest points associated to a point in the Cartesian space: by adjoining oriented planar patches (if they are present in the environment), we augment the landmark description with an oriented frame. Thanks to this additional information, the robot pose is fully observable with the perception of a single landmark, and the knowledge of the patches orientation helps the matching of landmarks. The paper depicts the chosen landmark model, the way to extract and match them, and presents some SLAM results obtained with such landmarks.

  • 10.
    Berger, Cyrille
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Wzorek, Mariusz
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kleiner, Alexander
    iRobot, Pasadena, CA, USA.
    Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter2016In: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV), IEEE conference proceedings, 2016, article id Tu31.3Conference paper (Refereed)
    Abstract [en]

    In this work we are investigating reactive avoidance techniques which can be used on board of a small quadcopter and which do not require absolute localisation. We propose a local map representation which can be updated with proprioceptive sensors. The local map is centred around the robot and uses spherical coordinates to represent a point cloud. The local map is updated using a depth sensor, the Inertial Measurement Unit and a registration algorithm. We propose an extension of the Dynamic Window Approach to compute a velocity vector based on the current local map. We propose to use an OctoMap structure to compute a 2-pass A* which provide a path which is converted to a velocity vector. Both approaches are reactive as they only make use of local information. The algorithms were evaluated in a simulator which offers a realistic environment, both in terms of control and sensors. The results obtained were also validated by running the algorithms on a real platform.

  • 11.
    Berger, Cyrille
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Wzorek, Mariusz
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Eriksson, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Area Coverage with Heterogeneous UAVs using Scan Patterns2016In: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR): proceedings, IEEE Robotics and Automation Society, 2016Conference paper (Refereed)
    Abstract [en]

    In this paper we consider a problem of scanningan outdoor area with a team of heterogeneous Unmanned AirVehicles (UAVs) equipped with different sensors (e.g. LIDARs).Depending on the availability of the UAV platforms and themission requirements there is a need to either minimise thetotal mission time or to maximise certain properties of thescan output, such as the point cloud density. The key challengeis to divide the scanning task among UAVs while taking intoaccount the differences in capabilities between platforms andsensors. Additionally, the system should be able to ensure thatconstraints such as limit on the flight time are not violated.We present an approach that uses an optimisation techniqueto find a solution by dividing the area between platforms,generating efficient scan trajectories and selecting flight andscanning parameters, such as velocity and flight altitude. Thismethod has been extensively tested on a large set of randomlygenerated scanning missions covering a wide range of realisticscenarios as well as in real flights.

  • 12.
    Doherty, Patrick
    et al.
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Kvarnström, Jonas
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Wzorek, Mariusz
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Hinzmann, Timo
    Stastny, Thomas
    A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles2016In: PRIMA 2016: Principles and Practice of Multi-Agent Systems / [ed] Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P., Springer Publishing Company, 2016, p. 110-130Conference paper (Refereed)
    Abstract [en]

    This paper describes an overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act. The system used contains a complex set of integrated software modules that include delegation managers for each platform, a task specification language for characterizing distributed tasks, a task planner, a multi-agent scan trajectory generation and region partitioning module, and a system infrastructure used to distributively instantiate any number of robotic systems and user interfaces in a collaborative team. The application focusses on 3D reconstruction in alpine environments intended to be used by alpine rescue teams. Two complex UAV systems used in the experiments are described. A fully autonomous collaborative mission executed in the Italian Alps using the framework is also described.

  • 13.
    Lemaire, Thomas
    et al.
    LAAS/CNRS 7, Toulouse, France.
    Berger, Cyrille
    LAAS/CNRS 7, Toulouse, France.
    Jung, Il-Kyun
    LAAS/CNRS 7, Toulouse, France.
    Lacroix, Simon
    LAAS/CNRS 7, Toulouse, France.
    Vision-Based SLAM: Stereo and Monocular Approaches2007In: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 74, no 3, p. 343-364Article in journal (Refereed)
    Abstract [en]

    Building a spatially consistent model is a key functionality to endow a mobile robot with autonomy. Without an initial map or an absolute localization means, it requires to concurrently solve the localization and mapping problems. For this purpose, vision is a powerful sensor, because it provides data from which stable features can be extracted and matched as the robot moves. But it does not directly provide 3D information, which is a difficulty for estimating the geometry of the environment. This article presents two approaches to the SLAM problem using vision: one with stereovision, and one with monocular images. Both approaches rely on a robust interest point matching algorithm that works in very diverse environments. The stereovision based approach is a classic SLAM implementation, whereas the monocular approach introduces a new way to initialize landmarks. Both approaches are analyzed and compared with extensive experimental results, with a rover and a blimp.

  • 14.
    Vidal-Calleja, Teresa
    et al.
    University of Sydney, Australia.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Lacroix, Simon
    Robotics and InterationS group, LAAS, France.
    Event-driven loop closure in multi-robot mapping2009In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE conference proceedings, 2009, p. 1535-1540Conference paper (Refereed)
    Abstract [en]

    A large-scale mapping approach is combined with multiple robots events to achieve cooperative mapping. The mapping approach used is based on hierarchical SLAM -global level and local maps-, which is generalized for the multi-robot case. In particular, the consequences of multi-robot loop closing events (common landmarks detection and relative pose measurement between robots) are analyzed and managed at a global level. We present simulation results for each of these events using aerial and ground robots, and experimental results obtained with ground robots.

  • 15.
    Vidal-Calleja, Teresa
    et al.
    LAAS/CNRS, University of Toulouse, Toulouse, France.
    Berger, Cyrille
    LAAS/CNRS, University of Toulouse, Toulouse, France.
    Solà, Joan
    LAAS/CNRS, University of Toulouse, Toulouse, France.
    Lacroix, Simon
    LAAS/CNRS, University of Toulouse, Toulouse, France.
    Environment Modeling for Cooperative Aerial/Ground Robotic Systems2009In: Proceedings of the 14th International Symposium on Robotics Research (ISRR), Springer, 2009, p. 681-696Conference paper (Refereed)
    Abstract [en]

    This paper addresses the cooperative localization and visual mapping problem for multiple aerial and ground robots.We propose the use of heterogeneous visual landmarks, points and line segments. A large-scale SLAM algorithm is generalized to manage multiple robots, in which a global graph maintains the topological relationships between a series of local sub-maps built by the different robots. Only single camera setups are considered: in order to achieve undelayed initialization, we present a novel parametrization for lines based on anchored Plücker coordinates, to which we add extensible endpoints to enhance their representativeness. The built maps combine such lines with 3D points parametrized in inverse-depth. The overall approach is evaluated with real-data taken with a helicopter and a ground rover in an abandoned village.

  • 16.
    Vidal-Calleja, Teresa
    et al.
    Australian Centre for Field Robotics, University of Sydney, NSW, Australia.
    Berger, Cyrille
    CNRS; LAAS; Toulouse, France and Université de Toulouse; UPS, INSA, INP, ISAE; LAAS; Toulouse, France.
    Solà, Joan
    CNRS; LAAS; Toulouse, France and Université de Toulouse; UPS, INSA, INP, ISAE; LAAS; Toulouse, France.
    Lacroix, Simon
    CNRS; LAAS; Toulouse, France and Université de Toulouse; UPS, INSA, INP, ISAE; LAAS; Toulouse, France.
    Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain2011In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 59, no 9, p. 654-674Article in journal (Refereed)
    Abstract [en]

    This paper addresses the cooperative localization and visual mapping problem with multiple heterogeneous robots. The approach is designed to deal with the challenging large semi-structured outdoors environments in which aerial/ground ensembles are to evolve. We propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in such environments. A large-scale SLAM algorithm is generalized to handle multiple robots, in which a global graph maintains the relative relationships between a series of local sub-maps built by the different robots. The key issue when dealing with multiple robots is to find the link between them, and to integrate these relations to maintain the overall geometric consistency; the events that introduce these links on the global graph are described in detail. Monocular cameras are considered as the primary extereoceptive sensor. In order to achieve the undelayed initialization required by the bearing-only observations, the well-known inverse-depth parametrization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parametrization based on anchored Plücker coordinates, to which extensible endpoints are added. Extensive simulations show the proposed developments, and the overall approach is illustrated using real-data taken with a helicopter and a ground rover.

  • 17.
    Wzorek, Mariusz
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    A Framework for Safe Navigation of Unmanned Aerial Vehicles in Unknown Environments2017In: 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), IEEE , 2017, p. 11-20Conference paper (Refereed)
    Abstract [en]

    This paper presents a software framework which combines reactive collision avoidance control approach with path planning techniques for the purpose of safe navigation of multiple Unmanned Aerial Vehicles (UAVs) operating in unknown environments. The system proposed leverages advantages of using a fast local sense-and-react type control which guarantees real-time execution with computationally demanding path planning algorithms which generate globally optimal plans. A number of probabilistic path planning algorithms based on Probabilistic Roadmaps and Rapidly-Exploring Random Trees have been integrated. Additionally, the system uses a reactive controller based on Optimal Reciprocal Collision Avoidance (ORCA) for path execution and fast sense-and-avoid behavior. During the mission execution a 3D map representation of the environment is build incrementally and used for path planning. A prototype implementation on a small scale quad-rotor platform has been developed. The UAV used in the experiments was equipped with a structured-light depth sensor to obtain information about the environment in form of occupancy grid map. The system has been tested in a number of simulated missions as well as in real flights and the results of the evaluations are presented.

  • 18.
    Wzorek, Mariusz
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Deployment of Ad Hoc Network Nodes Using UAVs for Search and Rescue Missions2018In: 2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

    Due to the maturity of technological development, widespread use of Unmanned Aerial Vehicles (UAVs) is becoming prevalent in the civil and commercial sectors. One promising area of application is in emergency rescue support. As recently seen in a number of natural catastrophes such as the hurricanes in Texas, Florida and Puerto Rico, major communication and electrical infrastructure is knocked out, leading to an inability to communicate between the victims and rescuers on the ground as well as between rescuers themselves. This paper studies the feasibility of using heterogeneous teams of UAVs to rapidly deliver and establish ad hoc communication networks in operational environments through autonomous in-air delivery of CommKits that serve as nodes in local ad hoc networks. Hardware and software infrastructures for autonomous CommKit delivery in addition to CommKit specification and construction is considered. The results of initial evaluation of two design alternatives for CommKits are presented based on more than 25 real flight tests in different weather conditions using a commercial small-scale UAV platform.

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