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Doherty, P., Kvarnström, J., Rudol, P., Wzorek, M., Conte, G., Berger, C., . . . Stastny, T. (2016). A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles. In: Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P. (Ed.), PRIMA 2016: Principles and Practice of Multi-Agent Systems: . Paper presented at PRIMA 2016: Principles and Practice of Multi-Agent Systems (pp. 110-130). Springer Publishing Company
Open this publication in new window or tab >>A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles
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2016 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer Publishing Company, 2016
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9862
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-130558 (URN)10.1007/978-3-319-44832-9_7 (DOI)000388796200007 ()978-3-319-44831-2 (ISBN)
Conference
PRIMA 2016: Principles and Practice of Multi-Agent Systems
Funder
ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsEU, FP7, Seventh Framework ProgrammeVINNOVASwedish Research Council
Note

Accepted for publication.

Available from: 2016-08-16 Created: 2016-08-16 Last updated: 2018-02-20
Berger, C., Rudol, P., Wzorek, M. & Kleiner, A. (2016). Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter. In: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV): . Paper presented at 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand, November 13-15, 2016. IEEE conference proceedings, Article ID Tu31.3.
Open this publication in new window or tab >>Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter
2016 (English)In: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV), IEEE conference proceedings, 2016, article id Tu31.3Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016
Series
International Conference on Control Automation Robotics and Vision, ISSN 2474-2953
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-130956 (URN)10.1109/ICARCV.2016.7838803 (DOI)000405520900204 ()2-s2.0-85015170851 (Scopus ID)9781509035496 (ISBN)9781509047574 (ISBN)9781509035502 (ISBN)
Conference
14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand, November 13-15, 2016
Note

Funding agencies:This work is partially supported by the Swedish Research Council (VR) Linnaeus Center CADICS, the ELLIIT network organization for Information and Communication Technology, and the Swedish Foundation for Strategic Research (CUAS Project, SymbiKCIoud Project).

Available from: 2016-09-01 Created: 2016-09-01 Last updated: 2018-01-10Bibliographically approved
Berger, C. (2014). Colour perception graph for characters segmentation. In: 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 (Ed.), Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings. Paper presented at ISVC 2014 (pp. 598-608). Springer
Open this publication in new window or tab >>Colour perception graph for characters segmentation
2014 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer, 2014
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 8888
Keywords
characters recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-112541 (URN)10.1007/978-3-319-14364-4_58 (DOI)000354700300058 ()978-3-319-14364-4 (ISBN)978-3-319-14363-7 (ISBN)
Conference
ISVC 2014
Projects
CADICS; ELLIIT; CUAS
Funder
Swedish Research CouncilLinnaeus research environment CADICSELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Foundation for Strategic Research
Available from: 2014-12-01 Created: 2014-12-01 Last updated: 2018-02-07Bibliographically approved
Berger, C. (2014). Strokes detection for skeletonisation of characters shapes. In: 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 (Ed.), Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part II. Paper presented at ISVC 2014 (pp. 510-520). Springer
Open this publication in new window or tab >>Strokes detection for skeletonisation of characters shapes
2014 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Springer, 2014
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 8888
Keywords
Texts recognition
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-112542 (URN)10.1007/978-3-319-14364-4_49 (DOI)000354700300049 ()978-3-319-14364-4 (ISBN)978-3-319-14363-7 (ISBN)
Conference
ISVC 2014
Projects
CADICS; ELLIIT; CUAS
Funder
Swedish Research CouncilLinnaeus research environment CADICSELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Foundation for Strategic Research
Available from: 2014-12-01 Created: 2014-12-01 Last updated: 2018-01-31Bibliographically approved
Berger, C. (2013). Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR. Journal of Automation, Mobile Robotics & Intelligent Systems, 7(1), 35-41
Open this publication in new window or tab >>Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR
2013 (English)In: Journal of Automation, Mobile Robotics & Intelligent Systems, ISSN 1897-8649, E-ISSN 2080-2145, Vol. 7, no 1, p. 35-41Article in journal (Refereed) Published
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.

Keywords
laser scanner, SLAM, LIDAR
National Category
Robotics
Identifiers
urn:nbn:se:liu:diva-90553 (URN)
Funder
eLLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Available from: 2013-04-02 Created: 2013-04-02 Last updated: 2017-12-06
Berger, C. (2012). Toward rich geometric map for SLAM: Online Detection of Planes in 2D LIDAR. In: Proceedings of the International Workshop on Perception for Mobile Robots Autonomy (PEMRA). Paper presented at International Workshop on Perception for Mobile Robots Autonomy (PEMRA).
Open this publication in new window or tab >>Toward rich geometric map for SLAM: Online Detection of Planes in 2D LIDAR
2012 (English)In: Proceedings of the International Workshop on Perception for Mobile Robots Autonomy (PEMRA), 2012Conference paper, Published 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.

Keywords
laser scanner, SLAM, LIDAR
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-84465 (URN)
Conference
International Workshop on Perception for Mobile Robots Autonomy (PEMRA)
Available from: 2012-10-15 Created: 2012-10-09 Last updated: 2018-01-12Bibliographically approved
Berger, C. (2012). Weak Constraints Network Optimiser. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Paper presented at 2012 IEEE International Conference on Robotics and Automation (ICRA), 14-18 May 2012, Saint Paul, MN, USA (pp. 1270-1277). IEEE
Open this publication in new window or tab >>Weak Constraints Network Optimiser
2012 (English)In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE , 2012, p. 1270-1277Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2012
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-87586 (URN)10.1109/ICRA.2012.6225060 (DOI)000309406701043 ()
Conference
2012 IEEE International Conference on Robotics and Automation (ICRA), 14-18 May 2012, Saint Paul, MN, USA
Available from: 2013-01-18 Created: 2013-01-18 Last updated: 2016-09-19
Vidal-Calleja, T., Berger, C., Solà, J. & Lacroix, S. (2011). Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain. Robotics and Autonomous Systems, 59(9), 654-674
Open this publication in new window or tab >>Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain
2011 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 59, no 9, p. 654-674Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2011
Keywords
Multi-robotscooperation, VisualSLAM
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-73413 (URN)10.1016/j.robot.2011.05.008 (DOI)000293804000005 ()
Available from: 2012-01-03 Created: 2012-01-03 Last updated: 2018-01-12Bibliographically approved
Berger, C. & Lacroix, S. (2010). DSeg: Détection directe de segments dans une image. In: 17ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA). Paper presented at Reconnaissance des Formes et Intelligence Artificielle.
Open this publication in new window or tab >>DSeg: Détection directe de segments dans une image
2010 (French)In: 17ème congrès francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA), 2010Conference paper, Published paper (Refereed)
Abstract [fr]

Cet article présente une approche ``model-driven'' pour détecter des segmentsde droite dans une image. L'approche détecte les segments de manièreincrémentale sur la base du gradient de l'image, en exploitant un filtre deKalman linéaire qui estime les paramètres de la droite support des segments etles variances associées. Les algorithmes sont rapides et robustes au bruit etaux variations d'illumination de la scène perçue, ils permettent de détecterdes segments plus longs que les approches existantes guidées par les données(``data-driven''), et ils ne nécessitent pas de délicate détermination deparamètres. Des résultats avec différentes conditions d'éclairage et descomparaisons avec les approches existantes sont présentés.

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.

National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-73242 (URN)
Conference
Reconnaissance des Formes et Intelligence Artificielle
Available from: 2011-12-23 Created: 2011-12-23 Last updated: 2018-01-12
Vidal-Calleja, T., Berger, C., Solà, J. & Lacroix, S. (2009). Environment Modeling for Cooperative Aerial/Ground Robotic Systems. In: Proceedings of the 14th International Symposium on Robotics Research (ISRR): . Paper presented at The 14th International Symposium ISRR (pp. 681-696). Springer
Open this publication in new window or tab >>Environment Modeling for Cooperative Aerial/Ground Robotic Systems
2009 (English)In: Proceedings of the 14th International Symposium on Robotics Research (ISRR), Springer, 2009, p. 681-696Conference paper, Published 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.

Place, publisher, year, edition, pages
Springer, 2009
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 70
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-73415 (URN)10.1007/978-3-642-19457-3_40 (DOI)000309893200040 ()978-3-642-19456-6 (ISBN)
Conference
The 14th International Symposium ISRR
Available from: 2012-01-03 Created: 2012-01-03 Last updated: 2018-01-12
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3011-1505

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