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  • 151.
    Sandewall, Erik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Editorial Material: A perspective on the early history of artificial intelligence in Europe2014In: AI Communications, ISSN 0921-7126, E-ISSN 1875-8452, Vol. 27, no 1, p. 81-86Article in journal (Other academic)
    Abstract [en]

    n/a

  • 152.
    Sandewall, Erik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, Faculty of Science & Engineering.
    Samtal om Sveriges nation2015Book (Other (popular science, discussion, etc.))
    Abstract [sv]

    Demokratin ifrågasätts i dagens värld genom att auktoritära och fundamentalistiska ideologier av flera slag förs fram som alternativ. De tillämpas i praktiken i ett flertal länder, men de sprids också genom aktiv propaganda. Den här boken utgår från föreställningen att detta utgör en utmaning även för vårt land, och den föreslår framförallt två åtgärder för att möta den utmaningen.

    Ett förslag är att precisera samhällets demokratiska grundsatser och att komplettera dem med några ytterligare punkter, såsom följande. En princip om assimilationsfrihet formuleras, alltså en rättighet att byta etnisk, religiös eller politisk tillhörighet om man vill, och samtidigt förstås en rättighet att bevara den man har. I boken föreslås utvidgat skydd för dessa rättigheter. Likaså införs begreppet religionism, alltså hävdandet att en viss religion är överlägsen andra och är förutbestämd att ta över, och det föreslås att religionism ska likställas med rasism.

    Det andra huvudförslaget är att betrakta nationen som bäraren av detta utvidgade demokratibegrepp, men då handlar det om nationen i en annan bemärkelse än vad dagens `nationalister' föreställer sig. Boken anknyter till skillnaden mellan etnisk och samhällelig nationalism (`civic nationalism' på engelska). I den förra sökerman göra en etnisk grupp till en nation, i den senare ses nationen som fundamentet för staten och samhället, och som den samlande faktorn för alla medborgare som ansluter sig till det demokratiska samhällets principer.

    Boken hävdar också att en kunskap om Sveriges historia ur politisk och religiös synpunkt är viktig för att kunna relatera till de främmande ideologierna och för attförstå hur vår samhällsmodell förhåller sig till deras.

  • 153.
    Selin, Magnus
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. Royal Institute of Technology, Stockholm Sweden.
    Tiger, Mattias
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Duberg, Daniel
    Royal Institute of Technology, Stockholm Sweden.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Jensfelt, Patric
    Royal Institute of Technology, Stockholm Sweden.
    Efficient Autonomous Exploration Planning of Large Scale 3D-Environments2019In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045Article in journal (Refereed)
    Abstract [en]

    Exploration is an important aspect of robotics, whether it is for mapping, rescue missions or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this work we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries.

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  • 154.
    Sibelius Parmbäck, Sebastian
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems.
    HMMs and LSTMs for On-line Gesture Recognition on the Stylaero Board: Evaluating and Comparing Two Methods2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis, methods of implementing an online gesture recognition system for the novel Stylaero Board device are investigated. Two methods are evaluated - one based on LSTMs and one based on HMMs - on three kinds of gestures: Tap, circle, and flick motions. A method’s performance was measured in its accuracy in determining both whether any of the above listed gestures were performed and, if so, which gesture, in an online single-pass scenario. Insight was acquired regarding the technical challenges and possible solutions to the online aspect of the problem. Poor performance was, however, observed in both methods, with a likely culprit identified as low quality of training data, due to an arduous and complex gesture performance capturing process. Further research improving on the process of gathering data is suggested.

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  • 155.
    Steinbauer, Gerald
    et al.
    Graz University of Technology, Austria.
    Kleiner, Alexander
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Towards CSP-based mission dispatching in C2/C4I systems2012In: Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR), IEEE , 2012, p. 1-6Conference paper (Refereed)
    Abstract [en]

    One challenging problem in disaster response is to efficiently assign resources such as fire fighters and trucks to local incidents that are spatially distributed on a map. Existing systems for command and control (C2/C4I) are coming with powerful interfaces enabling the manual assignment of resources to the incident commander. However, with increasing number of local incidents over time the performance of manual methods departs arbitrarily from an optimal solution. In this paper we introduce preliminary results of building an interface between existing professional C2/C4I systems and Constraint Satisfaction Problem (CSP)-solvers. We show by using an example the feasibility of scheduling and assigning missions having deadlines and resource constraints.

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    SSRR-2012-Towards-CSP-based-mission-dispatching.pdf
  • 156.
    Strömbäck, Filip
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Mannila, Linda
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Asplund, Mikael
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Kamkar, Mariam
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    A Student's View of Concurrency: A Study of Common Mistakes in Introductory Courses on Concurrency2019In: Proceedings of the 2019 ACM Conference on International Computing Education Research, New York, NY, USA: Association for Computing Machinery (ACM), 2019, p. 229-237Conference paper (Refereed)
    Abstract [en]

    This paper investigates common misconceptions held by students regarding concurrency in order to better understand how concurrency education can be improved in the future. As a part of the exam in two courses on concurrency and operating systems, students were asked to identify and eliminate any concurrency issues in a piece of code as a part of their final exam. Different types of mistakes were identified and the 216 answers were sorted into categories accordingly. The results presented in this paper show that while most students were able to identify the cause of an issue given its symptoms, only approximately half manage to successfully eliminate the concurrency issues. Many of the incorrect solutions fail to associate shared data with a synchronization primitive, e.g. using one lock to protect multiple instances of a data structure, or multiple locks to protect the same instance in different situations. This suggests that students may not only have trouble dealing with concepts related to concurrency, but also more fundamental concepts related to the underlying computational model. Finally, this paper proposes possible explanations for the students' mistakes in terms of improper mental models, and suggests types of problems that highlight the issues with these mental models to improve students' understanding of the subject.

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  • 157.
    Strömbäck, Filip
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Mannila, Linda
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Kamkar, Mariam
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Exploring Students’ Understanding of Concurrency: A Phenomenographic Study2020In: Proceedings of SIGCSE ’20, ACM Publications, 2020Conference paper (Refereed)
    Abstract [en]

    This paper continues previous efforts in understanding the problemsstudents face when learning concurrency. In this paper, weexplore students’ understanding of the subject using phenomenographyin order to gain insights that can aid in explaining the underlyingcauses for common student mistakes in concurrency, whichhas been studied in depth previously. Students’ experience of concurrencyand critical sections were analyzed using a phenomenographicstudy based on interviews with students attending one oftwo courses on concurrency and operating systems. We present6 categories describing students’ experience of concurrency, and4 categories describing students’ experience of critical sections inthis paper. Furthermore, these categories are related to previousresults, both to explore how misconceptions in the categores relateto student mistakes and to estimate how common it is for eachcategory to be discerned.

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  • 158.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    How an agent might think2013In: Logic journal of the IGPL (Print), ISSN 1367-0751, E-ISSN 1368-9894, Vol. 21, no 3, p. 515-535Article in journal (Refereed)
    Abstract [en]

    The current article is devoted to extensions of the rule query language 4QL proposed by Małuszyński and Szałas. 4QL is a Datalog¬¬-like language, allowing one to use rules with negation in heads and bodies of rules. It is based on a simple and intuitive semantics and provides uniform tools for lightweight versions of well-known forms of non-monotonic reasoning. In addition, 4QL is tractable w.r.t. data complexity and captures PTime queries. In the current article we relax most of restrictions of 4QL, obtaining a powerful but still tractable query language 4QL+. In its development we mainly focused on its pragmatic aspects: simplicity, tractability and generality. In the article we discuss our approach and choices made, define a new, more general semantics and investigate properties of 4QL+.

  • 159.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology. University of Warsaw, Poland.
    Symbolic Explanations of Generalized Fuzzy Reasoning2014In: SMART DIGITAL FUTURES 2014, IOS Press , 2014, Vol. 262, p. 7-16Conference paper (Refereed)
    Abstract [en]

    Various generalizations of fuzzy reasoning are frequently used in decision making. While in many application areas it is natural to assume that truth degrees of a property and its complement sum up to 1, such an assumption appears problematic, e.g., in modeling ignorance. Therefore, in some generalizations of fuzzy sets, degrees of membership in a set and in its complement are separated and are no longer required to sum up to 1. In frequent cases, this separation of positive and negative evidences for concept membership is more natural. As we discuss in the current paper, symbolic explanations of results of such forms of reasoning provide additional important information. In the present paper we address two related questions: (i) given generalized fuzzy connectives and a finite set of truth values T, find a finitely-valued logic over T, explaining fuzzy reasoning, and (ii) given a finitely-valued logic, find a fuzzy semantics, explained by the given logic. We also show examples illustrating usefulness of the approach.

  • 160.
    Szklarski, Jacek
    et al.
    Polish Acad Sci, Poland.
    Bialek, Lukasz
    Univ Warsaw, Poland.
    Szalas, Andrzej
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Paraconsistent Reasoning in Cops and Robber Game with Uncertain Information: A Simulation-Based Analysis2019In: International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, ISSN 0218-4885, Vol. 27, no 3, p. 429-455Article in journal (Refereed)
    Abstract [en]

    We apply a non-classical four-valued logic in the process of reasoning regarding strategies for cops in a modified game of "Cops and Robber" played on a graph. We extend the game by introducing uncertainty in a form of random failures of detecting devices. This is realized by allowing that a robber can be detected in a node only with the given probability P-A. Additionally, with the probability P-F, cops can be given a false-positive, i.e., they are informed that the robber is located at some node, whereas it is located somewhere else. Consequently, non-zero P-F introduces a measurement noise into the system. All the cops have access to information provided by the detectors and can communicate with each other, so they can coordinate the search. By adjusting the number of detectors,P-A, and P-F we can achieve a smooth transition between the two well-known variants of the game: "with fully visible robber" and "with invisible robber". We compare a simple probabilistic strategy for cops with the non-parametric strategy based on reasoning with a four-valued paraconsistent logic. It is shown that this novel approach leads to a good performance, as measured by the required mean catch-time. We conclude that this type of reasoning can be applied in real-world applications where there is no knowledge about the underlying source of errors which is particularly useful in robotics.

  • 161.
    Tiger, Mattias
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems. Linköping University, The Institute of Technology.
    Unsupervised Spatio-Temporal Activity Learning and Recognition in a Stream Processing Framework2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Learning to recognize and predict common activities, performed by objects and observed by sensors, is an important and challenging problem related both to artificial intelligence and robotics.In this thesis, the general problem of dynamic adaptive situation awareness is considered and we argue for the need for an on-line bottom-up approach.A candidate for a bottom layer is proposed, which we consider to be capable of future extensions that can bring us closer towards the goal.We present a novel approach to adaptive activity learning, where a mapping between raw data and primitive activity concepts are learned and continuously improved on-line and unsupervised. The approach takes streams of observations of objects as input and learns a probabilistic representation of both the observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using probabilistic graphs.The learned model supports both estimating the most likely activity and predicting the most likely future (and past) activities. Methods and ideas from a wide range of previous work are combined to provide a uniform and efficient way to handle a variety of common problems related to learning, classifying and predicting activities.The framework is evaluated both by learning activities in a simulated traffic monitoring application and by learning the flight patterns of an internally developed autonomous quadcopter system. The conclusion is that our framework is capable of learning the observed activities in real-time with good accuracy.We see this work as a step towards unsupervised learning of activities for robotic systems to adapt to new circumstances autonomously and to learn new activities on the fly that can be detected and predicted immediately.

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  • 162.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Gaussian Process Based Motion Pattern Recognition with Sequential Local Models2018In: 2018 IEEE Intelligent Vehicles Symposium (IV), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1143-1149Conference paper (Refereed)
    Abstract [en]

    Conventional trajectory-based vehicular traffic analysis approaches work well in simple environments such as a single crossing but they do not scale to more structurally complex environments such as networks of interconnected crossings (e.g. urban road networks). Local trajectory models are necessary to cope with the multi-modality of such structures, which in turn introduces new challenges. These larger and more complex environments increase the occurrences of non-consistent lack of motion and self-overlaps in observed trajectories which impose further challenges. In this paper we consider the problem of motion pattern recognition in the setting of sequential local motion pattern models. That is, classifying sub-trajectories from observed trajectories in accordance with which motion pattern that best explains it. We introduce a Gaussian process (GP) based modeling approach which outperforms the state-of-the-art GP based motion pattern approaches at this task. We investigate the impact of varying local model overlap and the length of the observed trajectory trace on the classification quality. We further show that introducing a pre-processing step filtering out stops from the training data significantly improves the classification performance. The approach is evaluated using real GPS position data from city buses driving in urban areas for extended periods of time.

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    Gaussian Process Based Motion Pattern Recognition with Sequential Local Models
  • 163.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Incremental Reasoning in Probabilistic Signal Temporal Logic2020In: International Journal of Approximate Reasoning, ISSN 0888-613X, E-ISSN 1873-4731, Vol. 119, p. 325-352, article id j.ijar.2020.01.009Article in journal (Refereed)
    Abstract [en]

    Robot safety is of growing concern given recent developments in intelligent autonomous systems. For complex agents operating in uncertain, complex and rapidly-changing environments it is difficult to guarantee safety without imposing unrealistic assumptions and restrictions. It is therefore necessary to complement traditional formal verification with monitoring of the running system after deployment. Runtime verification can be used to monitor that an agent behaves according to a formal specification. The specification can contain safety-related requirements and assumptions about the environment, environment-agent interactions and agent-agent interactions. A key problem is the uncertain and changing nature of the environment. This necessitates requirements on how probable a certain outcome is and on predictions of future states. We propose Probabilistic Signal Temporal Logic (ProbSTL) by extending Signal Temporal Logic with a sub-language to allow statements over probabilities, observations and predictions. We further introduce and prove the correctness of the incremental stream reasoning technique progression over well-formed formulas in ProbSTL. Experimental evaluations demonstrate the applicability and benefits of ProbSTL for robot safety.

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  • 164.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Online Sparse Gaussian Process Regression for Trajectory Modeling2015In: 18th International Conference on Information Fusion (Fusion), 2015, IEEE , 2015, p. 782-791Conference paper (Refereed)
    Abstract [en]

    Trajectories are used in many target tracking and other fusion-related applications. In this paper we consider the problem of modeling trajectories as Gaussian processes and learning such models from sets of observed trajectories. We demonstrate that the traditional approach to Gaussian process regression is not suitable when modeling a set of trajectories. Instead we introduce an approach to Gaussian process trajectory regression based on an alternative way of combing two Gaussian process (GP) trajectory models and inverse GP regression. The benefit of our approach is that it works well online and efficiently supports sophisticated trajectory model manipulations such as merging and splitting of trajectory models. Splitting and merging is very useful in spatio-temporal activity modeling and learning where trajectory models are considered discrete objects. The presented method and accompanying approximation algorithm have time and memory complexities comparable to state of the art of regular full and approximative GP regression, while havinga more flexible model suitable for modeling trajectories. The novelty of our approach is in the very flexible and accurate model, especially for trajectories, and the proposed approximative method based on solving the inverse problem of Gaussian process regression.

  • 165.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Stream Reasoning using Temporal Logic and Predictive Probabilistic State Models2016In: 23nd International Symposium on Temporal Representation and Reasoning (TIME), 2016, IEEE Computer Society, 2016, p. 196-205Conference paper (Refereed)
    Abstract [en]

    Integrating logical and probabilistic reasoning and integrating reasoning over observations and predictions are two important challenges in AI. In this paper we propose P-MTL as an extension to Metric Temporal Logic supporting temporal logical reasoning over probabilistic and predicted states. The contributions are (1) reasoning over uncertain states at single time points, (2) reasoning over uncertain states between time points, (3) reasoning over uncertain predictions of future and past states and (4) a computational environment formalism that ground the uncertainty in observations of the physical world. Concrete robot soccer examples are given.

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  • 166.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Towards Learning and Classifying Spatio-Temporal Activities in a Stream Processing Framework2014In: STAIRS 2014: Proceedings of the 7th European Starting AI Researcher Symposium / [ed] Ulle Endriss and João Leite, IOS Press, 2014, p. 280-289Conference paper (Refereed)
    Abstract [en]

    We propose an unsupervised stream processing framework that learns a Bayesian representation of observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using a causal Bayesian graph. This allows the model to be efficient through compactness and sparsity in the causal graph, and to provide probabilities at any level of abstraction for activities or chains of activities. Methods and ideas from a wide range of previous work are combined and interact to provide a uniform way to tackle a variety of common problems related to learning, classifying and predicting activities. We discuss how to use this framework to perform prediction of future activities and to generate events.

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  • 167.
    Tiger, Mattias
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Heintz, Fredrik
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Towards Unsupervised Learning, Classification and Prediction of Activities in a Stream-Based Framework2015In: Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence (SCAI), IOS Press, 2015, Vol. 278, p. 147-156Conference paper (Refereed)
    Abstract [en]

    Learning to recognize common activities such as traffic activities and robot behavior is an important and challenging problem related both to AI and robotics. We propose an unsupervised approach that takes streams of observations of objects as input and learns a probabilistic representation of the observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using a probabilistic graph. The learned model supports in limited form both estimating the most likely current activity and predicting the most likely future activities.  The framework is evaluated by learning activities in a simulated traffic monitoring application and by learning the flight patterns of an autonomous quadcopter.

  • 168.
    Tuna, Gurkan
    et al.
    Trakya University, Edime, Turkey.
    Nefzi, Bilel
    Independent Research, Paris, France.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, The Institute of Technology.
    Unmanned aerial vehicle-aided communications system for disaster recovery2014In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 41, p. 27-36Article in journal (Refereed)
    Abstract [en]

    After natural disasters such as earthquakes, floods, hurricanes, tornados and fires, providing emergency management schemes which mainly rely on communications systems is essential for rescue operations. To establish an emergency communications system during unforeseen events such as natural disasters, we propose the use of a team of unmanned aerial vehicles (UAVs). The proposed system is a post-disaster solution and can be used whenever and wherever required. Each UAV in the team has an onboard computer which runs three main subsystems responsible for end-to-end communication, formation control and autonomous navigation. The onboard computer and the low-level controller of the UAV cooperate to accomplish the objective of providing local communications infrastructure. In this study, the subsystems running on each UAV are explained and evaluated by simulation studies and field tests using an autonomous helicopter. While the simulation studies address the efficiency of the end-to-end communication subsystem, the field tests evaluate the accuracy of the navigation subsystem. The results of the field tests and the simulation studies show that the proposed system can be successfully used in case of disasters to establish an emergency communications system.

  • 169. Order onlineBuy this publication >>
    Warnquist, Håkan
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering. Scania CV AB.
    Troubleshooting Trucks: Automated Planning and Diagnosis2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of which actions to take in order to solve the problem such that the expected cost of restoring the vehicle is low. To achieve this, such a system must be capable of solving two problems: the diagnosis problem of finding which the possible faults are and the decision problem of deciding which action should be taken.

    The diagnosis problem has been approached using Bayesian network models. Frameworks have been developed for the case when the vehicle is in the workshop only and for remote diagnosis when the vehicle is monitored during longer periods of time.

    The decision problem has been solved by creating planners that select actions such that the expected cost of repairing the vehicle is minimized. New methods, algorithms, and models have been developed for improving the performance of the planner.

    The theory developed has been evaluated on models of an auxiliary braking system, a fuel injection system, and an engine temperature control and monitoring system.

    List of papers
    1. Iterative Bounding LAO*
    Open this publication in new window or tab >>Iterative Bounding LAO*
    2010 (English)In: ECAI 2010: 19th European Conference on Artificial Intelligence - Volume 215 Frontiers in Artificial Intelligence and Applications / [ed] Helder Coelho, Rudi Studer and Mike Wooldridge, IOS Press , 2010, p. 341-346Conference paper, Published paper (Refereed)
    Abstract [en]

    Iterative Bounding LAO* is a new algorithm for epsilon- optimal probabilistic planning problems where an absorbing goal state should be reached at a minimum expected cost from a given initial state. The algorithm is based on the LAO* algorithm for finding optimal solutions in cyclic AND/OR graphs. The new algorithm uses two heuristics, one upper bound and one lower bound of the optimal cost. The search is guided by the lower bound as in LAO*, while the upper bound is used to prune search branches. The algorithm has a new mechanism for expanding search nodes, and while maintaining the error bounds, it may use weighted heuristics to reduce the size of the explored search space. In empirical tests on benchmark problems, Iterative Bounding LAO* expands fewer search nodes compared to state of the art RTDP variants that also use two-sided bounds.

    Place, publisher, year, edition, pages
    IOS Press, 2010
    Series
    Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389 ; 215
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-59883 (URN)10.3233/978-1-60750-606-5-341 (DOI)978-1-60750-605-8 (ISBN)978-1-60750-606-5 (ISBN)
    Conference
    The 19th European Conference on Artificial Intelligence (ECAI), August 16-20, Lisbon, Portugal
    Available from: 2010-09-29 Created: 2010-09-29 Last updated: 2018-01-12Bibliographically approved
    2. Modeling and inference for troubleshooting with interventions applied to a heavy truck auxiliary braking system
    Open this publication in new window or tab >>Modeling and inference for troubleshooting with interventions applied to a heavy truck auxiliary braking system
    2012 (English)In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 25, no 4, p. 705-719Article in journal (Refereed) Published
    Abstract [en]

    Computer assisted troubleshooting with external interventions is considered. The work is motivated by the task of repairing an automotive vehicle at lowest possible expected cost. The main contribution is a decision theoretic troubleshooting system that is developed to handle external interventions. In particular, practical issues in modeling for troubleshooting are discussed, the troubleshooting system is described, and a method for the efficient probability computations is developed. The troubleshooting systems consists of two parts; a planner that relies on AO* search and a diagnoser that utilizes Bayesian networks (BN). The work is based on a case study of an auxiliary braking system of a modern truck. Two main challenges in troubleshooting automotive vehicles are the need for disassembling the vehicle during troubleshooting to access parts to repair, and the difficulty to verify that the vehicle is fault free. These facts lead to that probabilities for faults and for future observations must be computed for a system that has been subject to external interventions that cause changes in the dependency structure. The probability computations are further complicated due to the mixture of instantaneous and non-instantaneous dependencies. To compute the probabilities, we develop a method based on an algorithm, updateBN, that updates a static BN to account for the external interventions.

    Place, publisher, year, edition, pages
    Elsevier, 2012
    Keywords
    Automobile industry, Decision support systems, Fault diagnosis, Probabilistic models, Bayesian network
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-77725 (URN)10.1016/j.engappai.2011.02.018 (DOI)000303552100005 ()
    Available from: 2012-05-30 Created: 2012-05-28 Last updated: 2017-12-07
    3. Exploiting Fully Observable and Deterministic Structures in Goal POMDPs
    Open this publication in new window or tab >>Exploiting Fully Observable and Deterministic Structures in Goal POMDPs
    2013 (English)In: Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS) / [ed] Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini, AAAI Press, 2013, p. 242-250Conference paper, Published paper (Refereed)
    Abstract [en]

    When parts of the states in a goal POMDP are fully observable and some actions are deterministic it is possibleto take advantage of these properties to efficiently generate approximate solutions. Actions that deterministically affect the fully observable component of the world state can be abstracted away and combined into macro actions, permitting a planner to converge more quickly. This processing can be separated from the main search procedure, allowing us to leverage existing POMDP solvers. Theoretical results show how a POMDP can be analyzed to identify the exploitable properties and formal guarantees are provided showing that the use of macro actions preserves solvability. The efficiency of the method is demonstrated with examples when used in combination with existing POMDP solvers.

    Place, publisher, year, edition, pages
    AAAI Press, 2013
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-88637 (URN)978-1-57735-609-7 (ISBN)
    Conference
    23rd International Conference on Automated Planning and Scheduling (ICAPS 2013), 10-14 June 2013, Rom, Italy
    Projects
    ELLIITSHERPACUASCADICS
    Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2018-01-11Bibliographically approved
    4. Guided Integrated Remote and Workshop Troubleshooting of Heavy Trucks
    Open this publication in new window or tab >>Guided Integrated Remote and Workshop Troubleshooting of Heavy Trucks
    2014 (English)In: International Journal of Commercial Vehicles, ISSN 1946-391X, Vol. 7, no 1, p. 25-36Article in journal (Refereed) Published
    Abstract [en]

    When a truck or bus suffers from a breakdown it is important that the vehicle comes back on the road as soon as possible. In this paper we present a prototype diagnostic decision support system capable of automatically identifying possible causes of a failure and propose recommended actions on how to get the vehicle back on the road as cost efficiently as possible.

    This troubleshooting system is novel in the way it integrates the remote diagnosis with the workshop diagnosis when providing recommendations. To achieve this integration, a novel planning algorithm has been developed that enables the troubleshooting system to guide the different users (driver, help-desk operator, and mechanic) through the entire troubleshooting process.

    In this paper we formulate the problem of integrated remote and workshop troubleshooting and present a working prototype that has been implemented to demonstrate all parts of the troubleshooting system.

    Place, publisher, year, edition, pages
    Warrendale, PA, USA: SAE International, 2014
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-121498 (URN)10.4271/2014-01-0284 (DOI)
    Available from: 2015-09-22 Created: 2015-09-22 Last updated: 2018-01-11Bibliographically approved
    5. A Modeling Framework for Troubleshooting Automotive Systems
    Open this publication in new window or tab >>A Modeling Framework for Troubleshooting Automotive Systems
    2016 (English)In: Applied Artificial Intelligence, ISSN 0883-9514, E-ISSN 1087-6545, Vol. 30, no 3, p. 257-296Article in journal (Refereed) Published
    Abstract [en]

    This article presents a novel framework for modeling the troubleshooting process for automotive systems such as trucks and buses. We describe how a diagnostic model of the troubleshooting process can be created using event-driven, nonstationary, dynamic Bayesian networks. Exact inference in such a model is in general not practically possible. Therefore, we evaluate different approximate methods for inference based on the Boyen–Koller algorithm. We identify relevant model classes that have particular structure such that inference can be made with linear time complexity. We also show how models created using expert knowledge can be tuned using statistical data. The proposed learning mechanism can use data that is collected from a heterogeneous fleet of modular vehicles that can consist of different components. The proposed framework is evaluated both theoretically and experimentally on an application example of a fuel injection system.

    Place, publisher, year, edition, pages
    Taylor & Francis, 2016
    National Category
    Computer Sciences
    Identifiers
    urn:nbn:se:liu:diva-121499 (URN)10.1080/08839514.2016.1156955 (DOI)000374866700005 ()
    Projects
    ELLIITCADICS
    Funder
    ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
    Note

    The published article is a shorter version than the version in manuscript form. The status of this article was earlier Manuscript.

    Funding agencies: Scania CV AB; FFI - Strategic Vehicle Research and Innovation; Excellence Center at Linkoping and Lund in Information Technology (ELLIIT); Research Council (VR) Linnaeus Center CADICS

    Available from: 2015-09-22 Created: 2015-09-22 Last updated: 2018-01-11Bibliographically approved
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  • 170.
    Warnquist, Håkan
    et al.
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Kvarnström, Jonas
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    A Modeling Framework for Troubleshooting Automotive Systems2016In: Applied Artificial Intelligence, ISSN 0883-9514, E-ISSN 1087-6545, Vol. 30, no 3, p. 257-296Article in journal (Refereed)
    Abstract [en]

    This article presents a novel framework for modeling the troubleshooting process for automotive systems such as trucks and buses. We describe how a diagnostic model of the troubleshooting process can be created using event-driven, nonstationary, dynamic Bayesian networks. Exact inference in such a model is in general not practically possible. Therefore, we evaluate different approximate methods for inference based on the Boyen–Koller algorithm. We identify relevant model classes that have particular structure such that inference can be made with linear time complexity. We also show how models created using expert knowledge can be tuned using statistical data. The proposed learning mechanism can use data that is collected from a heterogeneous fleet of modular vehicles that can consist of different components. The proposed framework is evaluated both theoretically and experimentally on an application example of a fuel injection system.

    Download full text (pdf)
    fulltext
  • 171.
    Wiggberg, M.
    et al.
    Uppsala University.
    Dalenius, Peter
    Linköping University, Department of Computer and Information Science, EIT - Education in Information Technology Group. Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems.
    Bridges and problem solving: Swedish engineering students' conceptions of engineering in 20072009In: Proceedings of the 1st International Conference on Computer Supported Education (CSEDU), 2009, Vol. 2, p. 5-12Conference paper (Refereed)
    Abstract [en]

    Swedish engineering students conceptions of engineering is investigated by a large nation-wide study in ten Swedish higher education institutions. Based on data from surveys and interviews, categories and top-lists, a picture of students conceptions of engineering is presented. Students conceptions of engineering, are somewhat divergent, but dealing with problems and their solutions and creativity are identified as core concepts. The survey data is in general more varied and deals with somewhat different kinds of terms. When explicitly asking for five engineering terms, as in the survey, a broader picture arises including terms, or concepts, denoting how students think of engineering and work in a more personal way. For example, words like hard work, stressful, challenging, interesting, and fun are used. On the other hand, it seems like the interviewed students tried to give more general answers that were not always connected to their personal experiences. Knowledge on students conceptions of engineering is essential for practitioners in engineering education. By information on students conceptions, the teaching can approach students at their particular mindset of the engineering field. Program managers with responsibility for design of engineering programs would also benefit using information on students conceptions of engineering. Courses could be motivated and contextualized in order to connect with the students. Recruitment officers would also have an easier time marketing why people should chose the engineering track.

  • 172.
    Wzorek, Mariusz
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    A Framework for Safe Navigation of Unmanned Aerial Vehicles in Unknown Environments2017In: 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), IEEE , 2017, p. 11-20Conference paper (Refereed)
    Abstract [en]

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

  • 173.
    Wzorek, Mariusz
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Berger, Cyrille
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Deployment of Ad Hoc Network Nodes Using UAVs for Search and Rescue Missions2018In: 2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

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

  • 174.
    Wzorek, Mariusz
    et al.
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Rudol, Piotr
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Conte, Gianpaolo
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    Doherty, Patrick
    Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
    LinkBoard: Advanced Flight Control System for Micro Unmanned Aerial Vehicles2017In: 2017 2ND INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE2017), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    This paper presents the design and development of the LinkBoard, an advanced flight control system for micro Unmanned Aerial Vehicles (UAVs). Both hardware and software architectures are presented. The LinkBoard includes four processing units and a full inertial measurement unit. In the basic configuration, the software architecture includes a fully configurable set of control modes and sensor fusion algorithms for autonomous UAV operation. The system proposed allows for easy integration with new platforms, additional external sensors and a flexibility to trade off computational power, weight and power consumption. Due to the available onboard computational power, it has been used for computationally demanding applications such as the implementation of an autonomous indoor vision-based navigation system with all computations performed onboard. The autopilot has been manufactured and deployed on multiple UAVs. Examples of UAV systems built with the LinkBoard and their applications are presented, as well as an in-flight experimental performance evaluation of a newly developed attitude estimation filter.

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