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  • 1.
    Akin, H. Levent
    et al.
    Bogazici University, Turkey.
    Ito, Nobuhiro
    Aichi Institute of Technology, Japan.
    Jacoff, Adam
    National Institute of Standards, USA.
    Kleiner, Alexander
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Pellenz, Johannes
    V&R Vision & Robotics GmbH, Germany.
    Visser, Arnoud
    University of Amsterdam, Holland.
    RoboCup Rescue Robot and Simulation Leagues2013Ingår i: The AI Magazine, ISSN 0738-4602, Vol. 34, nr 1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deploying robots after real disasters (e.g. Fukushima Daiichi nuclear disaster). This article provides an overview of these competitions and highlights the state of the art and the lessons learned.

  • 2.
    Andersson, Olov
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Methods for Scalable and Safe Robot Learning2017Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Robots are increasingly expected to go beyond controlled environments in laboratories and factories, to enter real-world public spaces and homes. However, robot behavior is still usually engineered for narrowly defined scenarios. To manually encode robot behavior that works within complex real world environments, such as busy work places or cluttered homes, can be a daunting task. In addition, such robots may require a high degree of autonomy to be practical, which imposes stringent requirements on safety and robustness. \setlength{\parindent}{2em}\setlength{\parskip}{0em}The aim of this thesis is to examine methods for automatically learning safe robot behavior, lowering the costs of synthesizing behavior for complex real-world situations. To avoid task-specific assumptions, we approach this from a data-driven machine learning perspective. The strength of machine learning is its generality, given sufficient data it can learn to approximate any task. However, being embodied agents in the real-world, robots pose a number of difficulties for machine learning. These include real-time requirements with limited computational resources, the cost and effort of operating and collecting data with real robots, as well as safety issues for both the robot and human bystanders.While machine learning is general by nature, overcoming the difficulties with real-world robots outlined above remains a challenge. In this thesis we look for a middle ground on robot learning, leveraging the strengths of both data-driven machine learning, as well as engineering techniques from robotics and control. This includes combing data-driven world models with fast techniques for planning motions under safety constraints, using machine learning to generalize such techniques to problems with high uncertainty, as well as using machine learning to find computationally efficient approximations for use on small embedded systems.We demonstrate such behavior synthesis techniques with real robots, solving a class of difficult dynamic collision avoidance problems under uncertainty, such as induced by the presence of humans without prior coordination. Initially using online planning offloaded to a desktop CPU, and ultimately as a deep neural network policy embedded on board a 7 quadcopter.

    Delarbeten
    1. Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization
    Öppna denna publikation i ny flik eller fönster >>Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization
    2015 (Engelska)Ingår i: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) / [ed] Blai Bonet and Sven Koenig, AAAI Press, 2015, s. 2497-2503Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Reinforcement learning for robot control tasks in continuous environments is a challenging problem due to the dimensionality of the state and action spaces, time and resource costs for learning with a real robot as well as constraints imposed for its safe operation. In this paper we propose a model-based reinforcement learning approach for continuous environments with constraints. The approach combines model-based reinforcement learning with recent advances in approximate optimal control. This results in a bounded-rationality agent that makes decisions in real-time by efficiently solving a sequence of constrained optimization problems on learned sparse Gaussian process models. Such a combination has several advantages. No high-dimensional policy needs to be computed or stored while the learning problem often reduces to a set of lower-dimensional models of the dynamics. In addition, hard constraints can easily be included and objectives can also be changed in real-time to allow for multiple or dynamic tasks. The efficacy of the approach is demonstrated on both an extended cart pole domain and a challenging quadcopter navigation task using real data.

    Ort, förlag, år, upplaga, sidor
    AAAI Press, 2015
    Nyckelord
    Reinforcement Learning, Gaussian Processes, Optimization, Robotics
    Nationell ämneskategori
    Datavetenskap (datalogi) Datorseende och robotik (autonoma system)
    Identifikatorer
    urn:nbn:se:liu:diva-113385 (URN)978-1-57735-698-1 (ISBN)
    Konferens
    Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 25-30, 2015, Austin, Texas, USA.
    Forskningsfinansiär
    Linnaeus research environment CADICSeLLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsStiftelsen för strategisk forskning (SSF)VINNOVAEU, FP7, Sjunde ramprogrammet
    Tillgänglig från: 2015-01-16 Skapad: 2015-01-16 Senast uppdaterad: 2018-01-11Bibliografiskt granskad
    2. Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization
    Öppna denna publikation i ny flik eller fönster >>Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization
    2016 (Engelska)Ingår i: IEEE International Conference on Robotics and Automation (ICRA), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 4597-4604Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Robots are increasingly expected to move out of the controlled environment of research labs and into populated streets and workplaces. Collision avoidance in such cluttered and dynamic environments is of increasing importance as robots gain more autonomy. However, efficient avoidance is fundamentally difficult since computing safe trajectories may require considering both dynamics and uncertainty. While heuristics are often used in practice, we take a holistic stochastic trajectory optimization perspective that merges both collision avoidance and control. We examine dynamic obstacles moving without prior coordination, like pedestrians or vehicles. We find that common stochastic simplifications lead to poor approximations when obstacle behavior is difficult to predict. We instead compute efficient approximations by drawing upon techniques from machine learning. We propose to combine policy search with model-predictive control. This allows us to use recent fast constrained model-predictive control solvers, while gaining the stochastic properties of policy-based methods. We exploit recent advances in Bayesian optimization to efficiently solve the resulting probabilistically-constrained policy optimization problems. Finally, we present a real-time implementation of an obstacle avoiding controller for a quadcopter. We demonstrate the results in simulation as well as with real flight experiments.

    Ort, förlag, år, upplaga, sidor
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    Serie
    Proceedings of IEEE International Conference on Robotics and Automation, ISSN 1050-4729
    Nyckelord
    Robot Learning, Collision Avoidance, Robotics, Bayesian Optimization, Model Predictive Control
    Nationell ämneskategori
    Robotteknik och automation Datavetenskap (datalogi)
    Identifikatorer
    urn:nbn:se:liu:diva-126769 (URN)10.1109/ICRA.2016.7487661 (DOI)000389516203138 ()
    Konferens
    IEEE International Conference on Robotics and Automation (ICRA), 2016, Stockholm, May 16-21
    Projekt
    CADICSELLIITNFFP6CUASSHERPA
    Forskningsfinansiär
    Linnaeus research environment CADICSELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsEU, FP7, Sjunde ramprogrammetStiftelsen för strategisk forskning (SSF)
    Tillgänglig från: 2016-04-04 Skapad: 2016-04-04 Senast uppdaterad: 2018-01-10Bibliografiskt granskad
    3. Deep Learning Quadcopter Control via Risk-Aware Active Learning
    Öppna denna publikation i ny flik eller fönster >>Deep Learning Quadcopter Control via Risk-Aware Active Learning
    2017 (Engelska)Ingår i: Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI) / [ed] Satinder Singh and Shaul Markovitch, AAAI Press, 2017, Vol. 5, s. 3812-3818Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

    Ort, förlag, år, upplaga, sidor
    AAAI Press, 2017
    Serie
    Proceedings of the AAAI Conference on Artificial Intelligence, ISSN 2159-5399, E-ISSN 2374-3468 ; 5
    Nationell ämneskategori
    Datorseende och robotik (autonoma system) Datavetenskap (datalogi)
    Identifikatorer
    urn:nbn:se:liu:diva-132800 (URN)978-1-57735-784-1 (ISBN)
    Konferens
    Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017, San Francisco, February 4–9.
    Projekt
    ELLIITCADICSNFFP6SYMBICLOUDCUGS
    Forskningsfinansiär
    Linnaeus research environment CADICSELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsEU, FP7, Sjunde ramprogrammetCUGS (National Graduate School in Computer Science)Stiftelsen för strategisk forskning (SSF)
    Tillgänglig från: 2016-11-25 Skapad: 2016-11-25 Senast uppdaterad: 2018-01-13Bibliografiskt granskad
  • 3.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization2015Ingår i: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI) / [ed] Blai Bonet and Sven Koenig, AAAI Press, 2015, s. 2497-2503Konferensbidrag (Refereegranskat)
    Abstract [en]

    Reinforcement learning for robot control tasks in continuous environments is a challenging problem due to the dimensionality of the state and action spaces, time and resource costs for learning with a real robot as well as constraints imposed for its safe operation. In this paper we propose a model-based reinforcement learning approach for continuous environments with constraints. The approach combines model-based reinforcement learning with recent advances in approximate optimal control. This results in a bounded-rationality agent that makes decisions in real-time by efficiently solving a sequence of constrained optimization problems on learned sparse Gaussian process models. Such a combination has several advantages. No high-dimensional policy needs to be computed or stored while the learning problem often reduces to a set of lower-dimensional models of the dynamics. In addition, hard constraints can easily be included and objectives can also be changed in real-time to allow for multiple or dynamic tasks. The efficacy of the approach is demonstrated on both an extended cart pole domain and a challenging quadcopter navigation task using real data.

  • 4.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Ljungqvist, Oskar
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Tiger, Mattias
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Axehill, Daniel
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance2018Ingår i: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, s. 4467-4474Konferensbidrag (Refereegranskat)
    Abstract [en]

    A key requirement of autonomous vehicles is the capability to safely navigate in their environment. However, outside of controlled environments, safe navigation is a very difficult problem. In particular, the real-world often contains both complex 3D structure, and dynamic obstacles such as people or other vehicles. Dynamic obstacles are particularly challenging, as a principled solution requires planning trajectories with regard to both vehicle dynamics, and the motion of the obstacles. Additionally, the real-time requirements imposed by obstacle motion, coupled with real-world computational limitations, make classical optimality and completeness guarantees difficult to satisfy. We present a unified optimization-based motion planning and control solution, that can navigate in the presence of both static and dynamic obstacles. By combining optimal and receding-horizon control, with temporal multi-resolution lattices, we can precompute optimal motion primitives, and allow real-time planning of physically-feasible trajectories in complex environments with dynamic obstacles. We demonstrate the framework by solving difficult indoor 3D quadcopter navigation scenarios, where it is necessary to plan in time. Including waiting on, and taking detours around, the motions of other people and quadcopters.

  • 5.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Sidén, Per
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Filosofiska fakulteten.
    Dahlin, Johan
    Kotte Consulting AB.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Villani, Mattias
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Filosofiska fakulteten. Stockholm University, Stockholm, Sweden.
    Real-Time Robotic Search using Structural Spatial Point Processes2019Konferensbidrag (Refereegranskat)
  • 6.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Deep Learning Quadcopter Control via Risk-Aware Active Learning2017Ingår i: Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI) / [ed] Satinder Singh and Shaul Markovitch, AAAI Press, 2017, Vol. 5, s. 3812-3818Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

  • 7.
    Andersson, Olov
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization2016Ingår i: IEEE International Conference on Robotics and Automation (ICRA), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 4597-4604Konferensbidrag (Refereegranskat)
    Abstract [en]

    Robots are increasingly expected to move out of the controlled environment of research labs and into populated streets and workplaces. Collision avoidance in such cluttered and dynamic environments is of increasing importance as robots gain more autonomy. However, efficient avoidance is fundamentally difficult since computing safe trajectories may require considering both dynamics and uncertainty. While heuristics are often used in practice, we take a holistic stochastic trajectory optimization perspective that merges both collision avoidance and control. We examine dynamic obstacles moving without prior coordination, like pedestrians or vehicles. We find that common stochastic simplifications lead to poor approximations when obstacle behavior is difficult to predict. We instead compute efficient approximations by drawing upon techniques from machine learning. We propose to combine policy search with model-predictive control. This allows us to use recent fast constrained model-predictive control solvers, while gaining the stochastic properties of policy-based methods. We exploit recent advances in Bayesian optimization to efficiently solve the resulting probabilistically-constrained policy optimization problems. Finally, we present a real-time implementation of an obstacle avoiding controller for a quadcopter. We demonstrate the results in simulation as well as with real flight experiments.

  • 8.
    Bergdahl, Christopher
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Modeling Air Combat with Influence Diagrams2013Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Air combat is a complex situation, training for it and analysis of possible tactics are time consuming and expensive. In order to circumvent those problems, mathematical models of air combat can be used. This thesis presents air combat as a one-on-one influence diagram game where the influence diagram allows the dynamics of the aircraft, the preferences of the pilots and the uncertainty of decision making in a structural and transparent way to be taken into account. To obtain the players’ game optimal control sequence with respect to their preferences, the influence diagram has to be solved. This is done by truncating the diagram with a moving horizon technique and determining and implementing the optimal controls for a dynamic game which only lasts a few time steps.

    The result is a working air combat model, where a player estimates the probability that it resides in any of four possible states. The pilot’s preferences are modeled by utility functions, one for each possible state. In each time step, the players are maximizing the cumulative sum of the utilities for each state which each possible action gives. These are weighted with the corresponding probabilities. The model is demonstrated and evaluated in a few interesting aspects. The presented model offers a way of analyzing air combat tactics and maneuvering as well as a way of making autonomous decisions in for example air combat simulators. 

  • 9.
    Berger, Cyrille
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Colour perception graph for characters segmentation2014Ingår i: 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, s. 598-608Konferensbidrag (Refereegranskat)
    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.

  • 10.
    Berger, Cyrille
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Strokes detection for skeletonisation of characters shapes2014Ingår i: 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, s. 510-520Konferensbidrag (Refereegranskat)
    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.

  • 11.
    Berger, Cyrille
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Weak Constraints Network Optimiser2012Ingår i: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE , 2012, s. 1270-1277Konferensbidrag (Refereegranskat)
    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.

  • 12.
    Berger, Cyrille
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Kleiner, Alexander
    iRobot, Pasadena, CA, USA.
    Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter2016Ingår i: Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV), IEEE conference proceedings, 2016, artikel-id Tu31.3Konferensbidrag (Refereegranskat)
    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.

  • 13.
    Berger, Cyrille
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Eriksson, Alexander
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Area Coverage with Heterogeneous UAVs using Scan Patterns2016Ingår i: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR): proceedings, IEEE Robotics and Automation Society, 2016Konferensbidrag (Refereegranskat)
    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.

  • 14.
    Berglund, Aseel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Integrating Soft Skills into Engineering Education for Increased Student Throughput and more Professional Engineers2014Ingår i: Proceedings of LTHs 8:e Pedagogiska Inspirationskonferens (PIK), Lund, Sweden: Lunds university , 2014Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Soft skills are recognized as crucial for engineers as technical work is becoming more and more collaborative and interdisciplinary. Today many engineering educations fail to give appropriate training in soft skills. Linköping University has therefore developed a completely new course “Professionalism for Engineers” for two of its 5-year engineering programs in the area of computer science. The course stretches over the first 3 years with students from the three years taking it together. The purpose of the course is to give engineering students training in soft skills that are of importance during the engineering education as well as during their professional career. The examination is based on the Dialogue Seminar Method developed for learning from experience and through reflection. The organization of the course is innovative in many ways.

  • 15.
    Bergström, David
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Bayesian optimization for selecting training and validation data for supervised machine learning: using Gaussian processes both to learn the relationship between sets of training data and model performance, and to estimate model performance over the entire problem domain2019Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Validation and verification in machine learning is an open problem which becomes increasingly important as its applications becomes more critical. Amongst the applications are autonomous vehicles and medical diagnostics. These systems all needs to be validated before being put into use or else the consequences might be fatal.

    This master’s thesis focuses on improving both learning and validating machine learning models in cases where data can either be generated or collected based on a chosen position. This can for example be taking and labeling photos at the position or running some simulation which generates data from the chosen positions.

    The approach is twofold. The first part concerns modeling the relationship between any fixed-size set of positions and some real valued performance measure. The second part involves calculating such a performance measure by estimating the performance over a region of positions.

    The result is two different algorithms, both variations of Bayesian optimization. The first algorithm models the relationship between a set of points and some performance measure while also optimizing the function and thus finding the set of points which yields the highest performance. The second algorithm uses Bayesian optimization to approximate the integral of performance over the region of interest. The resulting algorithms are validated in two different simulated environments.

    The resulting algorithms are applicable not only to machine learning but can also be used to optimize any function which takes a set of positions and returns a value, but are more suitable when the function is expensive to evaluate.

  • 16.
    Bergström, Patrik
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Automated Setup of Display Protocols2015Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Röntgenläkares arbetsbörda har under flera årtionden ökat. Den digitala sjukvårdsteknologin utvecklas ständigt vilket bidrar till ett förbättrat arbetsflöde och kortare undersökningstider i radiologiavdelningar. Datorsystem används idag överallt inom sjukvården och används bland annat för att visa bilder åt röntgenläkare. För att underlätta visningen används display protocol som automatiskt skapar layouts och hänger bilder åt användaren. För att täcka ett stort antal olika undersökningstyper krävs att användaren skapar hundratals protokoll vilket är en tidskrävande uppgift, och systemet kan ändå misslyckas med att hänga upp bilder om de strikta kraven protokollen ställer inte uppfylls. För att ta bort detta manuella steg föreslår vi att man använder maskininlärning baserat på tidigare sparade presentationer.  Klassificerarna tränas på undersökningens metadata och radiologens preferenser på hängning av serier. Den valda metoden går ut på att skapa klassificerare för olika layout-regler och att sedan använda deras output i en algoritm som placerar ut series-typer till individuella bildplatser enligt kategorier baserade på metadata. Denna metod liknar den process de nuvarande display protokollen utför. De presentationer som skapats visar att systemet kan läras upp, men kräver högre precision om det ska användas kommersiellt. Analys av de olika delarna tyder på att ökad precision tidigt i systemet skulle öka den totala precision.

  • 17.
    Bhatt, Mehul
    et al.
    University of Bremen, Germany.
    Erdem, Esra
    Sabanci University, Turkey.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Spranger, Michael
    Sony Comp Science Labs Inc, Japan.
    Cognitive robotics in JOURNAL OF EXPERIMENTAL and THEORETICAL ARTIFICIAL INTELLIGENCE, vol 28, issue 5, pp 779-7802016Ingår i: Journal of experimental and theoretical artificial intelligence (Print), ISSN 0952-813X, E-ISSN 1362-3079, Vol. 28, nr 5, s. 779-780Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    n/a

  • 18.
    Bialek, Lukasz
    et al.
    Univ Warsaw, Poland.
    Dunin-Keplicz, Barbara
    Univ Warsaw, Poland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. Univ Warsaw, Poland.
    A paraconsistent approach to actions in informationally complex environments2019Ingår i: Annals of Mathematics and Artificial Intelligence, ISSN 1012-2443, E-ISSN 1573-7470, Vol. 86, nr 4, s. 231-255Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Contemporary systems situated in real-world open environments frequently have to cope with incomplete and inconsistent information that typically increases complexity of reasoning and decision processes. Realistic modeling of such informationally complex environments calls for nuanced tools. In particular, incomplete and inconsistent information should neither trivialize nor stop both reasoning or planning. The paper introduces ACTLOG, a rule-based four-valued language designed to specify actions in a paraconsistent and paracomplete manner. ACTLOG is an extension of 4QL(Bel), a language for reasoning with paraconsistent belief bases. Each belief base stores multiple world representations. In this context, ACTLOGs action may be seen as a belief bases transformer. In contrast to other approaches, ACTLOG actions can be executed even when the underlying belief base contents is inconsistent and/or partial. ACTLOG provides a nuanced action specification tools, allowing for subtle interplay among various forms of nonmonotonic, paraconsistent, paracomplete and doxastic reasoning methods applicable in informationally complex environments. Despite its rich modeling possibilities, it remains tractable. ACTLOG permits for composite actions by using sequential and parallel compositions as well as conditional specifications. The framework is illustrated on a decontamination case study known from the literature.

  • 19.
    Bialek, Lukasz
    et al.
    Univ Warsaw, Poland.
    Dunin-Keplicz, Barbara
    Univ Warsaw, Poland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. Univ Warsaw, Poland.
    Rule-Based Reasoning with Belief Structures2017Ingår i: FOUNDATIONS OF INTELLIGENT SYSTEMS, ISMIS 2017, SPRINGER INTERNATIONAL PUBLISHING AG , 2017, Vol. 10352, s. 229-239Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper introduces 4QL(Bel), a four-valued rule language designed for reasoning with paraconsistent and paracomplete belief bases as well as belief structures. Belief bases consist of finite sets of ground literals providing (partial and possibly inconsistent) complementary or alternative views of the world. As introduced earlier, belief structures consist of constituents, epistemic profiles and consequents. Constituents and consequents are belief bases playing different roles. Agents perceive the world forming their constituents, which are further transformed into consequents via the agents or groups epistemic profile. In order to construct 4QL(Bel), we extend 4QL, a four-valued rule language permitting for many forms of reasoning, including doxastic reasoning. Despite the expressiveness of 4QL(Bel), we show that its tractability is retained.

  • 20.
    Bialek, Lukasz
    et al.
    Institute of Informatics, University of Warsaw, Poland.
    Dunin-Keplicz, Barbara
    Institute of Informatics, University of Warsaw, Poland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Towards a Paraconsistent Approach to Actions in Distributed Information-Rich Environments2018Ingår i: Intelligent Distributed Computing XI / [ed] Mirjana Ivanović, Costin Bădică, Jürgen Dix, Zoran Jovanović, Michele Malgeri, Miloš Savić, Cham: Springer, 2018, Vol. 737, s. 49-60Konferensbidrag (Refereegranskat)
    Abstract [en]

    The paper introduces ActLog, a rule-based language capable of specifying actions paraconsistently. ActLog is an extension of 4QL Bel " role="presentation"> Bel , a rule-based language for reasoning with paraconsistent and paracomplete belief bases and belief structures. Actions considered in the paper act on belief bases rather than states represented as sets of ground literals. Each belief base stores multiple world representations which can be though of as a representation of possible states. In this context ActLog’s action may be then seen as a method of transforming one belief base into another. In contrast to other approaches, ActLog permits to execute actions even if the underlying belief base state is partial or inconsistent. Finally, the framework introduced in this paper is tractable.

  • 21.
    Bialek, Lukasz
    et al.
    Institute of Informatics, University of Warsaw, Warsaw, Poland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Lightweight Reasoning with Incomplete and Inconsistent Information: a Case Study2014Ingår i: 2014 IEEE/WIC/ACM International Joint Conferences on  (Volume:3 ) Web Intelligence (WI) and Intelligent Agent Technologies (IAT),, IEEE , 2014, Vol. 3, s. 325-332Konferensbidrag (Refereegranskat)
    Abstract [en]

    Dealing with heterogeneous information sources and reasoning techniques allowing for incomplete and inconsistent information is one of current challenges in the area of knowledge representation and reasoning. We advocate for 4QL, a rule-based query language, as a proper tool allowing one to address these challenges. To justify this point of view we discuss a rescue robotics scenario for which a simulator has been developed and tested. In particular, we present a planner using 4QL and, therefore, capable to deal with lack of knowledge and inconsistencies. Through the case study we show that our approach allows one to use lightweight knowledge representation tools: due to the use of 4QL tractability of modeling and reasoning is guaranteed and high usability is achieved.

  • 22.
    Bock, Alexander
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Kleiner, Alexander
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Lundberg, Jonas
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Ropinski, Timo
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Supporting Urban Search & Rescue Mission Planning through Visualization-Based Analysis2014Ingår i: Proceedings of the Vision, Modeling, and Visualization Conference 2014, Eurographics - European Association for Computer Graphics, 2014Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose a visualization system for incident commanders in urban search~\&~rescue scenarios that supports access path planning for post-disaster structures. Utilizing point cloud data acquired from unmanned robots, we provide methods for assessment of automatically generated paths. As data uncertainty and a priori unknown information make fully automated systems impractical, we present a set of viable access paths, based on varying risk factors, in a 3D environment combined with the visual analysis tools enabling informed decisions and trade-offs. Based on these decisions, a responder is guided along the path by the incident commander, who can interactively annotate and reevaluate the acquired point cloud to react to the dynamics of the situation. We describe design considerations for our system, technical realizations, and discuss the results of an expert evaluation.

  • 23.
    Boyer de la Giroday, Anna
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem.
    Automatic fine tuning of cavity filters2016Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Cavity filters are a necessary component in base stations used for telecommunication. Without these filters it would not be possible for base stations to send and receive signals at the same time. Today these cavity filters require fine tuning by humans before they can be deployed. This thesis have designed and implemented a neural network that can tune cavity filters. Different types of design parameters have been evaluated, such as neural network architecture, data presentation and data preprocessing. While the results was not comparable to human fine tuning, it was shown that there was a relationship between error and number of weights in the neural network. The thesis also presents some rules of thumb for future designs of neural network used for filter tuning.

  • 24.
    Bränd, Stefan
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem.
    Using Rigid Landmarks to Infer Inter-Temporal Spatial Relations in Spatio-Temporal Reasoning2015Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Spatio-temporal reasoning is the area of automated reasoning about space and time and is important in the field of robotics. It is desirable for an autonomous robot to have the ability to reason about both time and space. ST0 is a logic that allows for such reasoning by, among other things, defining a formalism used to describe the relationship between spatial regions and a calculus that allows for deducing further information regarding such spatial relations. An extension of ST0 is ST1 that can be used to describe the relationship between spatial entities across time-points (inter-temporal relations) while ST0 is constrained to doing so within a single time-point. This allows for a better ability of expressing how spatial entities change over time. A major obstacle in using ST1 in practise however, is the fact that any observations made regarding spatial relations between regions is constrained to the time-point in which the observation was made, so we are unable to observe inter-temporal relations. Further complicating things is the fact that deducing such inter-temporal relations is not possible without a frame of reference. This thesis examines one method of overcoming these problems by considering the concept of rigid regions which are assumed to always be unchanging and using them as the frame of reference, or as landmarks. The effectiveness of this method is studied by conducting experiments where a comparison is made between various landmark ratios with respect to the total number of regions under consideration. Results show that when a high degree of intra-temporal relations are fully or partially known, increasing the number of landmark regions will reduce the percentage of inter-temporal relations to be completely unknown. Despite this, very few inter-temporal relations can be fully determined even with a high ratio of landmark regions.

  • 25.
    Burdakov, Oleg
    et al.
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances.   For the hop-constrained DSTP, we propose local search strategies aimed at improving any heuristically produced initial Steiner tree. They are based on solving a sequence of hop-constrained shortest path problems for which we have recently developed ecient label correcting algorithms.   The presented approach is applied to nding suitable 3D locations where unmanned aerial vehicles (UAVs) can be placed to relay information gathered in multi-target monitoring and surveillance. The eciency of our algorithms is illustrated by results of numerical experiments involving problem instances with up to 40 000 nodes and up to 20 million arcs.

  • 26.
    Burdakov, Oleg
    et al.
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance2014Ingår i: Examining Robustness and Vulnerability of Networked Systems / [ed] Butenko, S., Pasiliao, E.L., Shylo, V., IOS Press, 2014, s. 26-50Konferensbidrag (Refereegranskat)
    Abstract [en]

    We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances.For the hop-constrained DSTP, we propose local search strategies aimed at improving any heuristically produced initial Steiner tree. They are based on solving a sequence of hop-constrained shortest path problems for which we have recently developed efficient label correcting algorithms.The presented approach is applied to finding suitable 3D locations where unmanned aerial vehicles (UAVs) can be placed to relay information gathered in multi-target monitoring and surveillance. The efficiency of our algorithms is illustrated by results of numerical experiments involving problem instances with up to 40 000 nodes and up to 20 million arcs.

  • 27.
    Burdakov, Oleg
    et al.
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Optimal Scheduling for Replacing Perimeter Guarding Unmanned Aerial Vehicles2014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Guarding the perimeter of an area in order to detect potential intruders is an important task in a variety of security-related applications. This task can in many circumstances be performed by a set of camera-equipped unmanned aerial vehicles (UAVs). Such UAVs will occasionally require refueling or recharging, in which case they must temporarily be replaced by other UAVs in order to maintain complete surveillance of the perimeter. In this paper we consider the problem of scheduling such replacements. We present optimal replacement strategies and justify their optimality.

  • 28.
    Burdakov, Oleg
    et al.
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska fakulteten.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Optimal scheduling for replacing perimeter guarding unmanned aerial vehicles2017Ingår i: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 249, nr 1, s. 163-174Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Guarding the perimeter of an area in order to detect potential intruders is an important task in a variety of security-related applications. This task can in many circumstances be performed by a set of camera-equipped unmanned aerial vehicles (UAVs). Such UAVs will occasionally require refueling or recharging, in which case they must temporarily be replaced by other UAVs in order to maintain complete surveillance of the perimeter. In this paper we consider the problem of scheduling such replacements. We present optimal replacement strategies and justify their optimality.

  • 29.
    Cao, Son Thanh
    et al.
    Vinh University, Nghe An, Vietnam .
    Nguyen, Linh Anh
    University of Warsaw, Poland; VNU University of Engineering and Technology, Hanoi, Vietnam.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan. University of Warsaw, Poland.
    WORL: a nonmonotonic rule language for the semantic web2014Ingår i: Vietnam Journal of Computer Science, ISSN 2196-8888, Vol. 1, nr 1, s. 57-69Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We develop a new Web ontology rule language, called WORL, which combines a variant of OWL 2 RL with eDatalog ¬ . We allow additional features like negation, the minimal number restriction and unary external checkable predicates to occur at the left-hand side of concept inclusion axioms. Some restrictions are adopted to guarantee a translation into eDatalog ¬ . We also develop the well-founded semantics and the stable model semantics for WORL as well as the standard semantics for stratified WORL (SWORL) via translation into eDatalog ¬ . Both WORL with respect to the well-founded semantics and SWORL with respect to the standard semantics have PTime data complexity. In contrast to the existing combined formalisms, in WORL and SWORL negation in concept inclusion axioms is interpreted using nonmonotonic semantics.

  • 30.
    Cao, S.T.
    et al.
    Faculty of Information Technology, Vinh University, 182 Le Duan street, Vinh Nghe An, Viet Nam; Institute of Informatics, University of of Warsaw, Banacha 2, 02-097 Warsaw, Poland.
    Nguyen, L.A.
    Institute of Informatics, University of of Warsaw, Banacha 2, 02-097 Warsaw, Poland; Faculty of Information Technology, VNU University of of Engineering and Technology, 144 Xuan Thuy, Hanoi, Viet Nam.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan. Institute of Informatics, University of of Warsaw, Banacha 2, 02-097 Warsaw, Poland.
    The web ontology rule language OWL 2 RL+ and its extensions2014Ingår i: Transactions on Computational Collective Intelligence XIII / [ed] Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen, Springer Verlag (Germany) , 2014, Vol. 8342, s. 152-175Konferensbidrag (Refereegranskat)
    Abstract [en]

    It is known that the OWL 2RL Web Ontology Language Profile has PTime data complexity and can be translated into Datalog. However, the result of translation may consist of a Datalog program and a set of constraints in the form of negative clauses. Therefore, a knowledge base in OWL 2RL may be unsatisfiable. In the current paper we first identify a maximal fragment of OWL 2RL, called OWL 2RL+, with the property that every knowledge base expressed in OWL2RL+ can be translated to a Datalog program and hence is satisfiable. We then propose some extensions of OWL 2RL and OWL 2RL + that still have PTime data complexity. © 2014 Springer-Verlag Berlin Heidelberg.

  • 31.
    Conte, Gianpaolo
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kleiner, Alexander
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Korwel, Karol
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Performance evaluation of a light weight multi-echo LIDAR for unmanned rotorcraft applications2013Ingår i: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2, Copernicus Gesellschaft MBH , 2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS) sys- tem consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute the terrain model. Evaluation of the accuracy of the generated 3D model is presented. Additionally, a comparison is provided between the terrain model generated from the developed ALS system and a model generated using a commer- cial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

  • 32.
    Conte, Gianpaolo
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Evaluation of a Light-weight Lidar and a Photogrammetric System for Unmanned Airborne Mapping Applications: [Bewertung eines Lidar-systems mit geringem Gewicht und eines photogrammetrischen Systems für Anwendungen auf einem UAV]2014Ingår i: Photogrammetrie - Fernerkundung - Geoinformation, ISSN 1432-8364, nr 4, s. 287-298Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a comparison of two light-weight and low-cost airborne mapping systems. One is based on a lidar technology and the other on a video camera. The airborne lidar system consists of a high-precision global navigation satellite system (GNSS) receiver, a microelectromechanical system (MEMS) inertial measurement unit, a magnetic compass and a low-cost lidar scanner. The vision system is based on a consumer grade video camera. A commercial photogrammetric software package is used to process the acquired images and generate a digital surface model. The two systems are described and compared in terms of hardware requirements and data processing. The systems are also tested and compared with respect to their application on board of an unmanned aerial vehicle (UAV). An evaluation of the accuracy of the two systems is presented. Additionally, the multi echo capability of the lidar sensor is evaluated in a test site covered with dense vegetation. The lidar and the camera systems were mounted and tested on-board an industrial unmanned helicopter with maximum take-off weight of around 100 kilograms. The presented results are based on real flight-test data.

  • 33.
    Danelljan, Martin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    Khan, Fahad Shahbaz
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.
    Felsberg, Michael
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Granström, Karl
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Kvarnström, Jonas
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Doherty, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems2015Ingår i: COMPUTER VISION - ECCV 2014 WORKSHOPS, PT I / [ed] Lourdes Agapito, Michael M. Bronstein and Carsten Rother, Springer Publishing Company, 2015, Vol. 8925, s. 223-237Konferensbidrag (Refereegranskat)
    Abstract [en]

    Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons.

    In this work, we propose a low-level active vision framework to accomplish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI-based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios

  • 34.
    Danielsson, Tina
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska fakulteten.
    Portering från Google Apps REST API till Microsoft Office 365 REST API2015Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Stress på arbetsplatsen relaterat till många inkommande och utgående kommunikationskanaler är ett reellt problem. Applikationer som samlar alla kanaler i samma verktyg kan hjälpa till på det här området. För att förenkla vid utveckling av en sådan applikation kan ett modulärt system skapas, där varje modul ser liknande ut och enkelt kan kopplas in i en huvudapplikation. Den här studien undersöker de problem som kan uppstå när flera tjänster ska integreras, mer specifikt genom att titta på hur en befintlig modul för e-post via Google Apps kan porteras för att stödja e-post via Microsoft Office 365. Arbetet har skett enligt metoder för testdriven portering och varje steg i porteringen har dokumenterats noggrant. Ett antal problemområden har identifierats och möjliga lösningar föreslås. Utfrån de problem som uppstått dras slutsatsen att de är av en sådan karaktär att de inte utgör något hinder för en portering.

  • 35.
    De Angelis, Francesco Luca
    et al.
    Institute of Services Science, University of Geneva, Switzerland.
    Di Marzo Serugendo, Giovanna
    Institute of Services Science, University of Geneva, Switzerland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. Institute of Informatics, University of Warsaw, Poland.
    Paraconsistent Rule-Based Reasoning with Graded Truth Values2018Ingår i: Journal of Applied Logic, ISSN 2055-3706, Vol. 5, nr 1, s. 185-220Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Modern artificial systems, such as cooperative traffic systems or swarm robotics, are made of multiple autonomous agents, each handling uncertain, partial and potentially inconsistent information, used in their reasoning and decision making. Graded reasoning, being a suitable tool for addressing phenomena related to such circumstances, is investigated in the literature in many contexts – from graded modal logics to various forms of approximate reasoning. In this paper we first introduce a family of many-valued paraconsistent logics parametrised by a number of truth/falsity/inconsistency grades allowing one to handle multiple truth-values at the desired level of accuracy. Second, we define a corresponding family of rule-based languages with graded truth-values as first-class citizens, enjoying tractable query evaluation. In addition, we introduce introspection operators allowing one to resolve inconsistencies and/or lack of information in a non-monotonic manner. We illustrate and discuss the use of the framework in an autonomous robot scenario.

  • 36.
    De Angelis, Francesco Luca
    et al.
    Univ Geneva, Switzerland.
    Serugendo, Giovanna Di Marzo
    Univ Geneva, Switzerland.
    Dunin-Keplicz, Barbara
    Univ Warsaw, Poland.
    Szalas, Andrzej
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. Univ Warsaw, Poland.
    Heterogeneous Approximate Reasoning with Graded Truth Values2017Ingår i: ROUGH SETS, SPRINGER INTERNATIONAL PUBLISHING AG , 2017, Vol. 10313, s. 61-82Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper is devoted to paraconsistent approximate reasoning with graded truth-values. In the previous research we introduced a family of many-valued logics parameterized by a variable number of truth/falsity grades together with a corresponding family of rule languages with tractable query evaluation. Such grades are shown here to be a natural qualitative counterpart of quantitative measures used in various forms of approximate reasoning. The developed methodology allows one to obtain a framework unifying heterogeneous reasoning techniques, providing also the logical machinery to resolve partial and incoherent information that may arise after unification. Finally, we show the introduced framework in action, emphasizing its expressiveness in handling heterogeneous approximate reasoning in realistic scenarios.

  • 37.
    de Leng, Daniel
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Querying Flying Robots and Other Things: Ontology-supported stream reasoning2015Ingår i: XRDS: Crossroads, The ACM Magazine for Students - The Internet of Things, ISSN 1528-4972, Vol. 22, nr 2, s. 44-47Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    A discussion on the role of ontologies and stream reasoning in Internet of Things applications.

  • 38.
    de Leng, Daniel
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Spatio-Temporal Stream Reasoning with Adaptive State Stream Generation2017Licentiatavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    A lot of today's data is generated incrementally over time by a large variety of producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, making sense of these streams of data through reasoning is challenging. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in a physical environment. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and its refinement an important problem.

    Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this thesis, we integrate techniques for logic-based spatio-temporal stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over streaming data and the problem of robustly managing streaming data and its refinement.

    The main contributions of this thesis are (1) a logic-based spatio-temporal reasoning technique that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt in situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in the context of a case study on run-time adaptive reconfiguration. The results show that the proposed system – by combining reasoning over and reasoning about streams – can robustly perform spatio-temporal stream reasoning, even when the availability of streaming resources changes.

  • 39.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty2019Ingår i: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), Palo Alto: AAAI Press, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Stream reasoning can be defined as incremental reasoning over incrementally-available information. The formula progression procedure for Metric Temporal Logic (MTL) makes use of syntactic formula rewritings to incrementally evaluate formulas against incrementally-available states. Progression however assumes complete state information, which can be problematic when not all state information is available or can be observed, such as in qualitative spatial reasoning tasks or in robotics applications. In those cases, there may be uncertainty as to which state out of a set of possible states represents the ‘true’ state. The main contribution of this paper is therefore an extension of the progression procedure that efficiently keeps track of all consistent hypotheses. The resulting procedure is flexible, allowing a trade-off between faster but approximate and slower but precise progression under uncertainty. The proposed approach is empirically evaluated by considering the time and space requirements, as well as the impact of permitting varying degrees of uncertainty.

  • 40.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    DyKnow: A Dynamically Reconfigurable Stream Reasoning Framework as an Extension to the Robot Operating System2016Ingår i: Proceedings of the Fifth IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), IEEE conference proceedings, 2016, s. 55-60Konferensbidrag (Refereegranskat)
    Abstract [en]

    DyKnow is a framework for stream reasoning aimed at robot applications that need to reason over a wide and varying array of sensor data for e.g. situation awareness. The framework extends the Robot Operating System (ROS). This paper presents the architecture and services behind DyKnow's run-time reconfiguration capabilities and offers an analysis of the quantitative and qualitative overhead. Run-time reconfiguration offers interesting advantages, such as fault recovery and the handling of changes to the set of computational and information resources that are available to a robot system. Reconfiguration capabilities are becoming increasingly important with the advances in areas such as the Internet of Things (IoT). We show the effectiveness of the suggested reconfiguration support by considering practical case studies alongside an empirical evaluation of the minimal overhead introduced when compared to standard ROS.

  • 41.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska fakulteten.
    Ontology-Based Introspection in Support of Stream Reasoning2015Ingår i: Thirteenth scandinavian conference on artificial intelligence (SCAI) / [ed] S. Nowaczyk, IOS Press, 2015, s. 78-87Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Building complex systems such as autonomous robots usually require the integration of a wide variety of components including high-level reasoning functionalities. One important challenge is integrating the information in a system by setting up the data flow between the components. This paper extends our earlier work on semantic matching with support for adaptive on-demand semantic information integration based on ontology-based introspection. We take two important standpoints. First, we consider streams of information, to handle the fact that information often becomes continually and incrementally available. Second, we explicitly represent the semantics of the components and the information that can be provided by them in an ontology. Based on the ontology our custom-made stream configuration planner automatically sets up the stream processing needed to generate the streams of information requested. Furthermore, subscribers are notified when properties of a stream changes, which allows them to adapt accordingly. Since the ontology represents both the systems information about the world and its internal stream processing many other powerful forms of introspection are also made possible. The proposed semantic matching functionality is part of the DyKnow stream reasoning framework and has been integrated in the Robot Operating System (ROS).

  • 42.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska fakulteten.
    Ontology-Based Introspection in Support of Stream Reasoning2015Ingår i: Proceedings of the Joint Ontology Workshops (JOWO 2015), Buenos Aires, Argentina, July 25-27, 2015: The Joint Ontology Workshops - Episode 1 / [ed] Odile Papini, Salem Benferhat, Laurent Garcia, Marie-Laure Mugnier, Eduardo Fermé, Thomas Meyer, Renata Wassermann, Torsten Hahmann, Ken Baclawski, Adila Krisnadhi, Pavel Klinov, Stefano Borgo and Oliver Kutz Daniele Porello15, Rheinisch-Westfaelische Technische Hochschule Aachen * Lehrstuhl Informatik V , 2015, Vol. 1517, s. 1-8Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Building complex systems such as autonomous robots usually require the integration of a wide variety of components including high-level reasoning functionalities. One important challenge is integrating the information in a system by setting up the data flow between the components. This paper extends our earlier work on semantic matching with support for adaptive on-demand semantic information integration based on ontology-based introspection.  We take two important stand-points.  First, we consider streams of information, to handle the fact that information often becomes continually and incrementally available.  Second, we explicitly represent the semantics of the components and the information that can be provided by them in an ontology.  Based on the ontology our custom-made stream configuration planner automatically sets up the stream processing needed to generate the streams of information requested. Furthermore, subscribers are notified when properties of a stream changes, which allows them to adapt accordingly. Since the ontology represents both the system's information about the world and its internal stream processing many other powerful forms of introspection are also made possible. The proposed semantic matching functionality is part of the DyKnow stream reasoning framework and has been integrated in the Robot Operating System (ROS).

  • 43.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Partial-State Progression for Stream Reasoning with Metric Temporal Logic2018Ingår i: Proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR) / [ed] Michael Thielscher, Francesca Toni, and Frank Wolter, Palo Alto: AAAI Press, 2018, s. 633-634Konferensbidrag (Refereegranskat)
    Abstract [en]

    The formula progression procedure for Metric Temporal Logic (MTL), originally proposed by Bacchus and Kabanza, makes use of syntactic formula rewritings to incrementally evaluate MTL formulas against incrementally-available states. Progression however assumes complete state information, which can be problematic when not all state information is available or can be observed, such as in qualitative spatial reasoning tasks or in robot applications. Our main contribution is an extension of the progression procedure to handle partial state information. For each missing truth value, we efficiently consider all consistent hypotheses by branching progression for each such hypothesis. The resulting procedure is flexible, allowing a trade-off between faster but approximate and slower but precise partial-state progression.

  • 44.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Qualitative Spatio-Temporal Stream Reasoning With Unobservable Intertemporal Spatial Relations Using Landmarks2016Ingår i: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI) / [ed] Dale Schuurmans, Dale Wellman, AAAI Press, 2016, Vol. 2, s. 957-963Konferensbidrag (Refereegranskat)
    Abstract [en]

    Qualitative spatio-temporal reasoning is an active research area in Artificial Intelligence. In many situations there is a need to reason about intertemporal qualitative spatial relations, i.e. qualitative relations between spatial regions at different time-points. However, these relations can never be explicitly observed since they are between regions at different time-points. In applications where the qualitative spatial relations are partly acquired by for example a robotic system it is therefore necessary to infer these relations. This problem has, to the best of our knowledge, not been explicitly studied before. The contribution presented in this paper is two-fold. First, we present a spatio-temporal logic MSTL, which allows for spatio-temporal stream reasoning. Second, we define the concept of a landmark as a region that does not change between time-points and use these landmarks to infer qualitative spatio-temporal relations between non-landmark regions at different time-points. The qualitative spatial reasoning is done in RCC-8, but the approach is general and can be applied to any similar qualitative spatial formalism.

  • 45.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Towards Adaptive Semantic Subscriptions for Stream Reasoning in the Robot Operating System2017Ingår i: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEEE , 2017, s. 5445-5452Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modern robotic systems often consist of a growing set of information-producing components that need to be appropriately connected for the system to function properly. This is commonly done manually or through relatively simple scripts by specifying explicitly which components to connect. However, this process is cumbersome and error-prone, does not scale well as more components are introduced, and lacks flexibility and robustness at run-time. This paper presents an algorithm for setting up and maintaining implicit subscriptions to information through its semantics rather than its source, which we call semantic subscriptions. The proposed algorithm automatically reconfigures the system when necessary in response to changes at run-time, making the semantic subscriptions adaptive to changing circumstances. To illustrate the effectiveness of adaptive semantic subscriptions, we present a case study with two SoftBank Robotics NAO robots for handling the cases when a component stops working and when new components, in this case a second robot, become available. The solution has been implemented as part of a stream reasoning framework integrated with the Robot Operating System (ROS).

  • 46.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerad datorsystem. Linköpings universitet, Tekniska högskolan.
    Towards On-Demand Semantic Event Processing for Stream Reasoning2014Ingår i: 17th International Conference on Information Fusion, 2014Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    The ability to automatically, on-demand, apply pattern matching over streams of information to infer the occurrence of events is an important fusion functionality. Existing event detection approaches require explicit configuration of what events to detect and what streams to use as input. This paper discusses on-demand semantic event processing, and extends the semantic information integration approach used in the stream processing middleware framework DyKnow to incorporate this new feature. By supporting on-demand semantic event processing, systems can automatically configure what events to detect and what streams to use as input for the event detection. This can also include the detection of lower-level events as well as processing of streams. The semantic stream query language C-SPARQL is used to specify events, which can be seen as transformations over streams. Since semantic streams consist of RDF triples, we suggest a method to convert between RDF streams and DyKnow streams. DyKnow is integrated in the Robot Operating System (ROS) and used for example in collaborative unmanned aircraft systems missions.

  • 47.
    de Leng, Daniel
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Tiger, Mattias
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Almquist, Mathias
    Linköpings universitet, Institutionen för datavetenskap. Linköpings universitet, Tekniska fakulteten.
    Almquist, Viktor
    Linköpings universitet, Institutionen för datavetenskap. Linköpings universitet, Tekniska fakulteten.
    Carlsson, Niklas
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs2018Ingår i: Proceedings of the 2nd Network Traffic Measurement and Analysis Conference (TMA), 2018, s. 1-8Konferensbidrag (Refereegranskat)
    Abstract [en]

    With Twitter and other microblogging services, users can easily express their opinion and ideas in short text messages. A recent trend is that users use the real-time property of these services to share their opinions and thoughts as events unfold on TV or in the real world. In the context of TV broadcasts, Twitter (over a mobile device, for example) is referred to as a second screen. This paper presents the first characterization of the second screen usage over the playoffs of a major sports league. We present both temporal and spatial analysis of the Twitter usage during the end of the National Hockey League (NHL) regular season and the 2015 Stanley Cup playoffs. Our analysis provides insights into the usage patterns over the full 72-day period and with regards to in-game events such as goals, but also with regards to geographic biases. Quantifying these biases and the significance of specific events, we then discuss and provide insights into how the playoff dynamics may impact advertisers and third-party developers that try to provide increased personalization.

  • 48.
    DellAglio, Daniele
    et al.
    Univ Zurich, Switzerland.
    Eiter, Thomas
    TU Vienna, Austria.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Le-Phuoc, Danh
    TU Berlin, Germany.
    Special issue on stream reasoning2019Ingår i: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 10, nr 3, s. 453-455Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    n/a

  • 49.
    Doherty, Patrick
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Heintz, Fredrik
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska högskolan.
    Landén, David
    Linköpings universitet, Institutionen för datavetenskap, KPLAB - Laboratoriet för kunskapsbearbetning. Linköpings universitet, Tekniska högskolan.
    A Distributed Task Specification Language for Mixed-Initiative Delegation2012Ingår i: Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers / [ed] Nirmit Desai, Alan Liu, Michael Winikoff, Springer Berlin/Heidelberg, 2012, Vol. 7057, s. 42-57Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the next decades, practically viable robotic/agent systems are going to be mixed-initiative in nature. Humans will request help from such systems and such systems will request help from humans in achieving the complex mission tasks required. Pragmatically, one requires a distributed task specification language to define tasks and a suitable data structure which satisfies the specification and can be used flexibly by collaborative multi-agent/robotic systems. This paper defines such a task specification language and an abstract data structure called Task Specification Trees which has many of the requisite properties required for mixed-initiative problem solving and adjustable autonomy in a distributed context. A prototype system has been implemented for this delegation framework and has been used practically with collaborative unmanned aircraft systems.

  • 50.
    Doherty, Patrick
    et al.
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Kvarnström, Jonas
    Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem.
    Rudol, Piotr
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Wzorek, Mariusz
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Conte, Gianpaolo
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Berger, Cyrille
    Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten.
    Hinzmann, Timo
    Stastny, Thomas
    A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles2016Ingår i: 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, s. 110-130Konferensbidrag (Refereegranskat)
    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.

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