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  • 1.
    Bianco, Giuseppe
    et al.
    Lund University, Sweden.
    Ilieva, Mihaela
    Lund University, Sweden; Bulgarian Academic Science, Bulgaria.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Öfjäll, Kristoffer
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Gadomska, Alicja
    Lund University, Sweden.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Felsberg, Michael
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Åkesson, Susanne
    Lund University, Sweden.
    Emlen funnel experiments revisited: methods update for studying compass orientation in songbirds2016In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 6, no 19, p. 6930-6942Article in journal (Refereed)
    Abstract [en]

    1 Migratory songbirds carry an inherited capacity to migrate several thousand kilometers each year crossing continental landmasses and barriers between distant breeding sites and wintering areas. How individual songbirds manage with extreme precision to find their way is still largely unknown. The functional characteristics of biological compasses used by songbird migrants has mainly been investigated by recording the birds directed migratory activity in circular cages, so-called Emlen funnels. This method is 50 years old and has not received major updates over the past decades. The aim of this work was to compare the results from newly developed digital methods with the established manual methods to evaluate songbird migratory activity and orientation in circular cages. 2 We performed orientation experiments using the European robin (Erithacus rubecula) using modified Emlen funnels equipped with thermal paper and simultaneously recorded the songbird movements from above. We evaluated and compared the results obtained with five different methods. Two methods have been commonly used in songbirds orientation experiments; the other three methods were developed for this study and were based either on evaluation of the thermal paper using automated image analysis, or on the analysis of videos recorded during the experiment. 3 The methods used to evaluate scratches produced by the claws of birds on the thermal papers presented some differences compared with the video analyses. These differences were caused mainly by differences in scatter, as any movement of the bird along the sloping walls of the funnel was recorded on the thermal paper, whereas video evaluations allowed us to detect single takeoff attempts by the birds and to consider only this behavior in the orientation analyses. Using computer vision, we were also able to identify and separately evaluate different behaviors that were impossible to record by the thermal paper. 4 The traditional Emlen funnel is still the most used method to investigate compass orientation in songbirds under controlled conditions. However, new numerical image analysis techniques provide a much higher level of detail of songbirds migratory behavior and will provide an increasing number of possibilities to evaluate and quantify specific behaviors as new algorithms will be developed.

  • 2.
    Ceragioli, Francesca
    et al.
    Politécnico di Torino, Dip. di Mathematica.
    Lindmark, Gustav
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Wahlström, Niklas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Lindfors, Martin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Altafini, Claudio
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    A bounded confidence model that preserves the signs of the opinions2016In: Proceedings of the 2016 European Control Conference, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 543-548Conference paper (Refereed)
    Abstract [en]

    The aim of this paper is to suggest a modification to the usual bounded confidence model of opinion dynamics, so that “changes of opinion” (intended as changes of the sign of the initial state) of an agent are never induced by the dynamics. In order to do so, a bipartite consensus model is used, endowing it with a confidence range. The resulting signed bounded confidence model has a state-dependent connectivity and a behavior similar to its standard counterpart, but in addition it preserves the sign of the opinions by “repelling away” opinions localized near the origin but on different sides with respect to 0.

  • 3.
    Gunnarsson, Svante
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Jung, Ylva
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Glad, Torkel
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    IO (Implement and Operate) First in an Automatic Control Context2016In: Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016 / [ed] Jerker Björkqvist, Kristina Edström, Ronald J. Hugo, Juha Kontio, Janne Roslöf, Rick Sellens & Seppo Virtanen, CDIO , 2016, p. 238-249Conference paper (Refereed)
    Abstract [en]

    A first course in Automatic control is presented.  A main objective of the course is to put most of the emphasis on the Implement and Operate phases in the process of developing a control system for a process. The course is built around a large amount of student active learning based on three extensive laboratory exercises, where each laboratory exercise can have duration of up to two weeks. For each of the laboratory exercises there is a sequence of learning activities supporting the students’ learning: Introductory lecture, problem solving session, preparation work, help-desk session, independent work in the laboratory, and a final demonstration of the control system. In addition there is a small project where the task is to write a manual for a process operator. The laboratory tasks involve implementation of a control system in an industrial PLC (Programmable Logic Controller) and development of an operator interface.

  • 4. Olofsson, Jonatan
    et al.
    Lindahl Flåten, Andreas
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Lauknes, Tom Rune
    Gaussian Field Current Estimation from Drift Sea Ice Tracking with the Labeled Multi-Bernoulli Filter2017In: Proceedings of the 2017 OCEANS 17 conference, 2017Conference paper (Refereed)
    Abstract [en]

    In polar region operations, drift sea ice positioning and tracking is useful for both scientific and safety reasons. Modeling ice movements has proven difficult, not least due to the lack of information of currents and winds of high enough resolution. Thus, observations of drift ice is essential to an up-to-date ice-tracking estimate.

    As an inverse problem, it is possible to extract current and wind estimates from the tracked objects of a Multi-Target Tracking (MTT) filter. By inserting the track estimates into a Gaussian field, we obtain a two-dimensional current estimate over a region of interest.

    The algorithm is applied to a Terrestrial Radar Interferometer (TRI) dataset from Kongsfjorden, Svalbard, to show the practical application of the current estimation.

  • 5.
    Olofsson, Jonatan
    et al.
    Norwegian University of Science and Technology, Norway.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Sea Ice Tracking with a Spatially Indexed Labeled Multi-Bernoulli Filter2017In: Proceedings of the 2017 20th International Conference on Information Fusion, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 376-383Conference paper (Refereed)
    Abstract [en]

    In polar region operations, drift ice positioning and tracking is useful for both scientific and safety reasons. At its core is a Multi-Target Tracking (MTT) problem in which currents and winds make motion modeling difficult. One recent algorithm in the MTT field, employed in this paper, is the Labeled Multi-Bernoulli (LMB) filter. In particular, a proposed reformulation of the LMB equations exposes a structure which is exploited to propose a compact algorithm for the generation of the filter's posterior distribution. Further, spatial indexing is applied to the clustering process of the filter, allowing efficient separation of the filter into smaller, independent parts with lesser total complexity than that of an unclustered filter. Many types of sensors can be employed to generate detections of sea ice, and in this paper a recorded dataset from a Terrestrial Radar Interferometer (TRI) is used to demonstrate the application of the Spatially Indexed Labeled Multi-Bernoulli filter to estimate the currents of an observed area in Kongsfjorden, Svalbard.

  • 6. Olofsson, Jonatan
    et al.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Johansen, Tor Arne
    Outline of a System for Integrated Adaptive Ice Tracking and Multi-Agent Path Planning2017In: Proceedings of the 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), IEEE, 2017, p. 13-18Conference paper (Refereed)
    Abstract [en]

    In polar region operations, drift sea ice positioning and tracking is useful for both scientific and safety reasons. Modeling ice movements has proven difficult, not least due to the lack of information of currents and winds of high enough resolution. Thus, observations of drift ice is essential to an up-to-date ice-tracking estimate.

    Recent years have seen the rise of Unmanned Aerial Systems (UAS) as a platform for geoobservation, and so too for the tracking of sea ice. Being a mobile platform, the research on UAS path-planning is extensive and usually involves an objective-function to minimize. For the purpose of observation however, the objective-function typically changes as observations are made along the path.

    Further, the general problem involves multiple UAS and—in the case of sea ice tracking—vast geographical areas.

    In this paper we discuss the architectural outline of a system capable of fusing data from multiple sources—UAS’s and others—as well as incorporating that data for both path-planning, sea ice movement prediction and target initialization. The system contains tracking of sea ice objects, situation map logic and is expandable as discussed with path-planning capabilities for closing the loop of optimizing paths for information acquisition.

  • 7.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Tracking of Animals Using Airborne Cameras2016Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The various elements of a modern target tracking framework are covered. Background theory on pre-processing, modelling and estimation is presented as well as some novel ideas on the topic by the author. In addition, a few applications are posed as target tracking problems for which solutions are gradually constructed as relevant theory is covered.

    Among considered problems are how to constrain targets to a region, use state-independent measurements to improve estimation in jump Markov models and how to incorporate observations sampled at an uncertain time into a state-space model.

    A framework is developed for tracking dolphins constrained to a basin using an overhead camera that suffers from occlusions. In this scenario, conventional motion models would suffer from infeasible predictions outside the basin. A motion model is developed for the dolphins where collisions with nearby walls are avoided by turning. The basin is modelled as a polygon where each point along the edge influences the turn rate of the dolphin. The proposed model results in predictions inside the basin, increasing robustness against occlusions. An extension to a Gaussian mixture background model providing a degree of confidence for detections is used to improve tracking in the presence of shadows. A probabilistic data association filter is also modified to estimate the dolphin extension as an ellipse. The proposed framework is able to maintain tracks through occlusions and poor light conditions.

    A framework is developed for estimating takeoff times and directions of birds in circular cages using an overhead camera. A jump Markov model is used to model the stationary and flight behaviours of the birds. A proposed extension also incorporates state-independent measurements, such as blurriness, to improve mode estimation. Takeoff times and directions are estimated from mode transitions and results are compared to manually annotated data.

    The cameras are inaccessible in both applications, disallowing proper calibrations. As an alternative, a method is proposed to estimate stationary camera models from available data and known features in the scene. A map of the basin and the funnel dimensions are used respectively. The method estimates a homography and distortion parameters in an invertible mapping function.

    An extension to the linear Gaussian state-space models is proposed, incorporating an additional observation with an uncertain timestamp. The posterior distribution of the states is derived for the model, which is shown to be a mixture of Gaussians, as well as some estimators for the distribution. The effects of incorporating the observation with an uncertain timestamp into the model are analysed for a one-dimensional scenario. The model is also applied to improve the GPS position of an orienteering sprinter by using the control position as an observation with an uncertain timestamp.

  • 8.
    Veibäck, Clas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Tracking the Wanders of Nature2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Target tracking is a mature topic with over half a century of mainly military and aviation research. The field has lately expanded into a range of civilian applications due to the development of cheap sensors and improved computational power. With the rise of new applications, new challenges emerge, and with better hardware there is an opportunity to employ more elaborated algorithms.

    There are five main contributions to the field of target tracking in this thesis. Contributions I-IV concern the development of non-conventional models for target tracking and the resulting estimation methods. Contribution V concerns a reformulation for improved performance. To show the functionality and applicability of the contributions, all proposed methods are applied to and verified on experimental data related to tracking of animals or other objects in nature.

    In Contribution I, sparse Gaussian processes are proposed to model behaviours of targets that are caused by influences from the environment, such as wind or obstacles. The influences are learned online as a part of the state estimation using an extended Kalman filter. The method is also adapted to handle time-varying influences and to identify dynamic systems. It is shown to improve accuracy over the nearly constant velocity and acceleration models in simulation. The method is also evaluated in a sea ice tracking application using data from a radar on Svalbard.

    In Contribution II, a state-space model is derived that incorporates observations with uncertain timestamps. An example of such observations could be traces left by a target. Estimation accuracy is shown to be better than the alternative of disregarding the observation. The position of an orienteering sprinter is improved using the control points as additional observations.

    In Contribution III, targets that are confined to a certain space, such as animals in captivity, are modelled to avoid collision with the boundaries by turning. The proposed model forces the predictions to remain inside the confined space compared to conventional models that may suffer from infeasible predictions. In particular the model improves robustness against occlusions. The model is successfully used to track dolphins in a dolphinarium as they swim in a basin with occluded sections.

    In Contribution IV, an extension to the jump Markov model is proposed that incorporates observations of the mode that are state-independent. Normally, the mode is estimated by comparing actual and predicted observations of the state. However, sensor signals may provide additional information directly dependent on the mode. Such information from a video recorded by biologists is used to estimate take-off times and directions of birds captured in circular cages. The method is shown to compare well with a more time-consuming manual method.

    In Contribution V, a reformulation of the labelled multi-Bernoulli filter is used to exploit a structure of the algorithm to attain a more efficient implementation.Modern target tracking algorithms are often very demanding, so sound approximations and clever implementations are needed to obtain reasonable computational performance. The filter is integrated in a full framework for tracking sea ice, from pre-processing to presentation of results.

  • 9.
    Veibäck, Clas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    On Fusion of Sensor Measurements and Observation with Uncertain Timestamp for Target Tracking2016In: Proceedings of the 19th International Conference on Information Fusion, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1268-1275Conference paper (Refereed)
    Abstract [en]

    We consider a target tracking problem where, in addition to the usual sensor measurements, accurate observations with uncertain timestamps are available. Such observations could, \eg, come from traces left by a target or from witnesses of an event, and have the potential in some scenarios to improve the accuracy of an estimate significantly. The Bayesian solution to the smoothing problem for one observation with uncertain timestamp is derived for a linear Gaussian state space model. The joint and marginal distributions of the states and uncertain time are derived, as well as the minimum mean squared error (MMSE) and maximum a posteriori (MAP) estimators. To attain an intuition for the problem in consideration a simple first-order example is presented and its posterior distributions and point estimators are compared and examined in some depth.

  • 10.
    Veibäck, Clas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Tracking of Dolphins in a Basin Using a Constrained Motion Model2015In: Proceedings of the 18th International Conference of Information Fusion, Institute of Electrical and Electronics Engineers (IEEE), 2015Conference paper (Refereed)
    Abstract [en]

    Visual animal tracking is a challenging problem generally requiring extended target models, group tracking and handling of clutter and missed detections. Furthermore, the dolphin tracking problem we consider includes basin constraints, shadows, limited field of view and rapidly changing light conditions. We describe the whole pipeline of a solution based on a ceiling-mounted fisheye camera that includes foreground segmentation and observation extraction in each image, followed by a target tracking framework. A novel contribution is a potential field model of the basin edges as a part of the motion model, that provides a robust prediction of the dolphin trajectories in phases with long segments of missed detections. The overall performance on real data is quite promising.

  • 11.
    Veibäck, Clas
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Uncertain Timestamps in Linear State Estimation2019In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 55, no 3, p. 1334-1346Article in journal (Refereed)
    Abstract [en]

    We consider a linear state estimation problem, where, in addition to the usual timestamped measurements, observations with uncertain timestamps are available. Such observations could, e.g., come from traces left by a target in a tracking scenario or from witnesses of an event and have the potential to improve the estimation accuracy significantly. We derive the posterior distribution and point estimators for a linear Gaussian smoothing formulation of this problem and illustrate with two numerical examples.

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