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  • 1.
    Alirezaie, Marjan
    et al.
    Örebro University, School of Science and Technology.
    Renoux, Jennifer
    Örebro University, School of Science and Technology.
    Köckemann, Uwe
    Örebro University, School of Science and Technology.
    Kristoffersson, Annica
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Blomqvist, Eva
    RISE SICS East, Linköping, Sweden.
    Tsiftes, Nicolas
    RISE SICS, Stockholm, Sweden.
    Voigt, Thiemo
    RISE SICS, Stockholm, Sweden.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    An Ontology-based Context-aware System for Smart Homes: E-care@home2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 7, article id 1586Article in journal (Refereed)
    Abstract [en]

    Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.

  • 2.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Bouguerra, Abdelbaki
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar Nikolaev
    INRIA - Grenoble, Meylan, France.
    Driankov, Dimiter
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Saarinen, Jari Pekka
    Örebro University, School of Science and Technology. Aalto University, Espo, Finland .
    Sherikov, Aleksander
    Centre de recherche Grenoble Rhône-Alpes, Grenoble, France .
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Autonomous transport vehicles: where we are and what is missing2015In: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223X, Vol. 22, no 1, p. 64-75Article in journal (Refereed)
    Abstract [en]

    In this article, we address the problem of realizing a complete efficient system for automated management of fleets of autonomous ground vehicles in industrial sites. We elicit from current industrial practice and the scientific state of the art the key challenges related to autonomous transport vehicles in industrial environments and relate them to enabling techniques in perception, task allocation, motion planning, coordination, collision prediction, and control. We propose a modular approach based on least commitment, which integrates all modules through a uniform constraint-based paradigm. We describe an instantiation of this system and present a summary of the results, showing evidence of increased flexibility at the control level to adapt to contingencies.

  • 3. Bidot, Julien
    et al.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Lagriffoul, Fabien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Geometric backtracking for combined task and motion planning in robotic systems2017In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 247, p. 229-265Article in journal (Refereed)
    Abstract [en]

    Planners for real robotic systems should not only reason about abstract actions, but also about aspects related to physical execution such as kinematics and geometry. We present an approach to hybrid task and motion planning, in which state-based forward-chaining task planning is tightly coupled with motion planning and other forms of geometric reasoning. Our approach is centered around the problem of geometric backtracking that arises in hybrid task and motion planning: in order to satisfy the geometric preconditions of the current action, a planner may need to reconsider geometric choices, such as grasps and poses, that were made for previous actions. Geometric backtracking is a necessary condition for completeness, but it may lead to a dramatic computational explosion due to the large size of the space of geometric states. We explore two avenues to deal with this issue: the use of heuristics based on different geometric conditions to guide the search, and the use of geometric constraints to prune the search space. We empirically evaluate these different approaches, and demonstrate that they improve the performance of hybrid task and motion planning. We demonstrate our hybrid planning approach in two domains: a real, humanoid robotic platform, the DLR Justin robot, performing object manipulation tasks; and a simulated autonomous forklift operating in a warehouse.

  • 4.
    Bidot, Julien
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Lagriffoul, Fabien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Geometric backtracking for combined task and path planning in robotic systemsManuscript (preprint) (Other academic)
    Abstract [en]

    Planners for real, possibly complex, robotic systems should not only reason about abstract actions, but also about aspects related to physical execution such as kinematics and geometry. We present an approach in which state-based forward-chaining task planning is tightly coupled with sampling-based motion planning and other forms of geometric reasoning. We focus on the problem of geometric backtracking which arises when a planner needs to reconsider geometric choices, like grasps and poses, that were made for previous actions, in order to satisfy geometric preconditions of the current action. Geometric backtracking is a necessary condition for completeness, but it may lead to a dramatic computational explosion due to the systematic exploration of the space of geometric states. In order to deal with that, we introduce heuristics based on the collisions between the robot and movable objects detected during geometric backtracking and on kinematic relations between actions. We also present a complementary approach based on propagating explicit constraints which are automatically generated from the symbolic actions to be evaluated and from the kinematic model of the robot. We empirically evaluate these dierent approaches. We demonstrate our planner on a real advanced robot, the DLR Justin robot, and on a simulated autonomous forklift. 

  • 5.
    Bouguerra, Abdel
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    PC-SHOP: a probabilstic-conditional hierarchical task planner2005In: Intelligenza Artificiale, ISSN 1724-8035, Vol. 2, no 4, p. 44-50Article in journal (Refereed)
    Abstract [en]

    In this paper we report on the extension of the classical HTN planner SHOP to plan in partially observable domains with uncertainty. Our algorithm PC-SHOP uses belief states to handle situations involving incomplete and uncertain information about the state of the world. Sensing and acting are integrated in the primitive actions through the use of a stochastic model. PC-SHOP is showed to scale up well compared to some of the state-of-the-art planners. We outline the main characteristics of the algorithm, and present performance results on some problems found in the literature.

  • 6.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Hierarchical task planning under uncertainty2004Conference paper (Refereed)
    Abstract [en]

    In this paper we present an algorithm for planning in non-deterministic domains. Our algorithm C-SHOP extends the successful classical HTN planner SHOP, by introducing new mechanisms to handle situations where there is incomplete and uncertain information about the state of the environment. Being an HTN planner, C-SHOP supports coding domain-dependent knowledge in a powerful way that describes how to solve the planning problem.

    To handle uncertainty, belief states are used to represent incomplete information about the state of the world, and actions are allowed to have stochastic outcomes. This allows our algorithm to solve problems involving partial observability through feedback at execution time. We outline the main characteristics of the algorithm, and present performance results on some problems found in literature.

  • 7.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Symbolic probabilistic-conditional plans execution by a mobile robot2005Conference paper (Refereed)
    Abstract [en]

    In this paper we report on the integration of a high-level plan executor with a behavior-based architecture. The executor is designed to execute plans that solve problems in partially observable domains. We discuss the different modules of the overall architecture and how we made the different modules interact using a shared representation. We also give a detailed description of the hierarchical architecture of the executor and how execution-time failures are handled.

  • 8.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Synthesizing plans for multiple domains2005In: Abstraction, reformulation and approximation: Proceedings of the 6th international symposium, SARA 2005 / [ed] Jean-Daniel Zucker, Lorenza Saitta, Springer Berlin/Heidelberg, 2005, p. 30-43Conference paper (Refereed)
    Abstract [en]

    Intelligent agents acting in real world environments need to synthesize their course of action based on multiple sources of knowledge. They also need to generate plans that smoothly integrate actions from different domains. In this paper we present a generic approach to synthesize plans for solving planning problems involving multiple domains. The proposed approach performs search hierarchically by starting planning in one domain and considering subgoals related to the other domains as abstract tasks to be planned for later when their respective domains are considered. To plan in each domain, a domain-dependent planner can be used, making it possible to integrate different planners, possibly with different specializations. We outline the algorithm, and the assumptions underlying its functionality. We also demonstrate through a detailed example, how the proposed framework compares to planning in one global domain.

  • 9.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Active execution monitoring using planning and semantic knowledge2007In: Proc. of the ICAPS Workshop on Planning and Plan Execution for Real-World Systems, Providence, RI, 2007, 2007, p. 9-15Conference paper (Other academic)
    Abstract [en]

    To cope with the dynamics and uncertainty inherent in real world environments, autonomous mobile robots need to perform execution monitoring for verifying that their plans are executed as expected. Domain semantic knowledge has lately been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when the robot moves into an office, it would expect to see a desk and a chair. Such expectations are checked using the immediately available perceptual information. We propose to extend the semantic knowledge-based execution monitoring to handle situations where some of the required information is missing. To this end, we use AI sensor-based planning to actively search for such information. We show how verifying execution expectations can be formulated and solved as a planning problem involving sensing actions. Our approach is illustrated by showing test scenarios run in an indoor environment using a mobile robot.

  • 10.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Handling uncertainty in semantic-knowledge based execution monitoring2007In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on Oct. 29 2007-Nov. 2 2007, NEW YORK: IEEE , 2007, p. 443-449Chapter in book (Other academic)
    Abstract [en]

    Executing plans by mobile robots, in real world environments, faces the challenging issues of uncertainty and environment dynamics. Thus, execution monitoring is needed to verify that plan actions are executed as expected. Semantic domain-knowledge has lately been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when a robot moves into a room asserted to be an office, it would expect to see a desk and a chair. We propose to extend the semantic knowledge-based execution monitoring to take uncertainty in actions and sensing into account when verifying the expectations derived from semantic knowledge. We consider symbolic probabilistic action models, and show how semantic knowledge is used together with a probabilistic sensing model in the monitoring process of such actions. Our approach is illustrated by showing test scenarios ran in an indoor environment using a mobile robot

  • 11.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Handling uncertainty in semantic-knowledge based execution monitoring2007In: IEEE/RSJ international conference on intelligent robots and systems, IROS 2007 San Diego, CA, 2007, New York: IEEE , 2007, p. 437-443Conference paper (Refereed)
    Abstract [en]

    Executing plans by mobile robots, in real world environments, faces the challenging issues of uncertainty and environment dynamics. Thus, execution monitoring is needed to verify that plan actions are executed as expected. Semantic domain-knowledge has lately been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when a robot moves into a room asserted to be an office, it would expect to see a desk and a chair. We propose to extend the semantic knowledge-based execution monitoring to take uncertainty in actions and sensing into account when verifying the expectations derived from semantic knowledge. We consider symbolic probabilistic action models, and show how semantic knowledge is used together with a probabilistic sensing model in the monitoring process of such actions. Our approach is illustrated by showing test scenarios run in an indoor environment using a mobile robot.

  • 12.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Monitoring the execution of robot plans using semantic knowledge2008In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 56, no 11, p. 942-954Article in journal (Refereed)
    Abstract [en]

    Even the best laid plans can fail, and robot plans executed in real world domains tend to do so often. The ability of a robot to reliably monitor the execution of plans and detect failures is essential to its performance and its autonomy. In this paper, we propose a technique to increase the reliability of monitoring symbolic robot plans. We use semantic domain knowledge to derive implicit expectations of the execution of actions in the plan, and then match these expectations against observations. We present two realizations of this approach: a crisp one, which assumes deterministic actions and reliable sensing, and uses a standard knowledge representation system (LOOM); and a probabilistic one, which takes into account uncertainty in action effects, in sensing, and in world states. We perform an extensive validation of these realizations through experiments performed both in simulation and on real robots.

  • 13.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Semantic knowledge-based execution monitoring for mobile robots2007In: 2007 IEEE international conference on robotics and automation (ICRA), 2007, p. 3693-3698Conference paper (Refereed)
    Abstract [en]

    We describe a novel intelligent execution monitoring approach for mobile robots acting in indoor environments such as offices and houses. Traditionally, monitoring execution in mobile robotics amounted to looking for discrepancies between the model-based predicted state of executing an action and the real world state as computed from sensing data. We propose to employ semantic knowledge as a source of information to monitor execution. The key idea is to compute implicit expectations, from semantic domain information, that can be observed at run time by the robot to make sure actions are executed correctly. We present the semantic knowledge representation formalism, and how semantic knowledge is used in monitoring. We also describe experiments run in an indoor environment using a real mobile robot

  • 14.
    Bouguerra, Abdelbaki
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Situation assessment for sensor-based recovery planning2006In: 17th European Conference on Artificial Intelligence (ECAI) / [ed] Gerhard Brewka, Silvia Coradeschi, Anna Perini, Paolo Traverso, IOS Press, 2006, p. 673-677Conference paper (Refereed)
    Abstract [en]

    We present an approach for recovery from perceptual failures, or more precisely anchoring failures. Anchoring is the problem of connecting symbols representing objects to sensor data corresponding to the same objects. The approach is based on using planning, but our focus is not on the plan generation per se. We focus on the very important aspect of situation assessment and how it is carried out for recovering from anchoring failures. The proposed approach uses background knowledge to create hypotheses about world states and handles uncertainty in terms of probabilistic belief states. This work is relevant both from the perspective of developing the anchoring framework, and as a study in plan-based recovery from epistemic failures in mobile robots. Experiments on a mobile robot are shown to validate the applicability of the proposed approach.

  • 15.
    Broxvall, Mathias
    et al.
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Have another look on failures and recovery planning in perceptual anchoring2004Conference paper (Refereed)
    Abstract [en]

    An important requirement for autonomous systems is the ability to detect and recover from exceptional situations such as failures in observations. In this paper we demonstrate how techniques for planning with sensing under uncertainty can play a major role in solving the problem of recovering from such situations. In this first step we concentrate on failures in perceptual anchoring, that is how to connect a symbol representing an object to the percepts of that object. We provide a classification of failures and present planning-based methods for recovering from them. We illustrate our approach by showing tests run on a mobile robot equipped with a color camera.

  • 16.
    Broxvall, Mathias
    et al.
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Recovery planning for ambiguous cases in perceptual anchoring2005In: Proceedings of the 20th national conference on Artificial intelligence, AAAI-05: volume 3, 2005, p. 1254-1260Conference paper (Refereed)
    Abstract [en]

    An autonomous robot using symbolic reasoning, sensing and acting in a real environment needs the ability to create and maintain the connection between symbols representing objects in the world and the corresponding perceptual representations given by its sensors. This connection has been named perceptual anchoring. In complex environments, anchoring is not always easy to establish: the situation may often be ambiguous as to which percept actually corresponds to a given symbol. In this paper, we extend perceptual anchoring to deal robustly with ambiguous situations by providing general methods for detecting them and recovering from them. We consider different kinds of ambiguous situations and present planning-based methods to recover from them. We illustrate our approach by showing experiments involving a mobile robot equipped with a color camera and an electronic nose.

  • 17.
    Broxvall, Mathias
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Steps toward detecting and recovering from perceptual failures2004In: Proceedings of the 8th international conference on intelligent autonomous systems, 2004, p. 793-800Conference paper (Refereed)
    Abstract [en]

    An important requirement for autonomous systems is the ability to detect and recover from exceptional situations such as failures in observations. In this paper we investigate how traditional AI planning techniques can be used to reason about observations and to recover from these situations. In this first step we concentrate on failures in perceptual anchoring. We illustrate our approach by showing experiments run on a mobile robot equipped with a color camera.

  • 18.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    A framework for human-aware robot planning2008In: Tenth Scandinavian conference on artificial intelligence / [ed] A. Holst, P. Kreuger, P. Funk, Amsterdam: IOS press , 2008, p. 52-59Conference paper (Refereed)
    Abstract [en]

    Robots that share their workspace with humans, like household or service robots, need to take into account the presence of humans when planning their actions. In this paper, we present a framework for human-aware planning in which we consider three kinds of human-robot interaction. We focus in particular on the core module of the framework, a human-aware planner that generates a sequence of actions for a robot, taking into account the status of the environment, the goals of the robot and the forecasted plan of the human. We present a first realization of this planner, together with two simple experiments that demonstrate the feasibility of our approach.

  • 19.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    A human-aware robot task planner2009In: Proceedings of the 19th international conference on automated planning and scheduling, ICAPS 2009 / [ed] Alfonso Gerevini, Adele Howe, Amedeo Cesta, Ioannis Refanidis, Menlo Park: AAAI press , 2009, p. 58-65Conference paper (Refereed)
    Abstract [en]

    The growing presence of household robots in inhabited environments arises the need for new robot task planning techniques. These techniques should take into consideration not only the actions that the robot can perform or unexpected external events, but also the actions performed by a human sharing the same environment, in order to improve the cohabitation of the two agents, e.g., by avoiding undesired situations for the human. In this paper, we present a human-aware planner able to address this problem. This planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. The planner has been tested as a standalone component and in conjunction with our framework for human-robot interaction in a real environment.

  • 20.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Human-aware planning for robots embedded in ambient ecologies2012In: Pervasive and Mobile Computing, ISSN 1574-1192, E-ISSN 1873-1589, Vol. 8, no 4, p. 542-561Article in journal (Refereed)
    Abstract [en]

    We address the issue of human-robot cohabitation in smart environments. In particular, the presence of humans in a robot's work space has a profound influence on how the latter should plan its actions. We propose the use of Human-Aware Planning, an approach in which the robot exploits the capabilities of a sensor-rich environment to obtain information about the (current and future) activities of the people in the environment, and plans its tasks accordingly.

    Here, we formally describe the planning problem behind our approach, we analyze its complexity and we detail the algorithm of our planner. We then show two application scenarios that could benefit from the techniques described. The first scenario illustrates the applicability of human-aware planning in a domestic setting, while the second one illustrates its use for a robotic helper in a hospital. Finally, we present a five hour-long test run in a smart home equipped with real sensors, where a cleaning robot has been deployed and where a human subject is acting. This test run in a real setting is meant to demonstrate the feasibility of our approach to human-robot interaction.

  • 21.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Human-aware task planning: an application to mobile robots2010In: ACM transactions on interactive intelligent systems, ISSN 2157-6904, Vol. 1, no 2, p. Article 15-Article in journal (Refereed)
    Abstract [en]

    Consider a house cleaning robot planning its activities for the day. Assume that the robot expects the human inhabitant to first dress, then have breakfast, and finally go out. Then, it should plan not to clean the bedroom while the human is dressing, and to clean the kitchen after the human has had breakfast. In general, robots operating in inhabited environments, like households and future factory floors, should plan their behavior taking into account the actions that will be performed by the humans sharing the same environment. This would improve human-robot cohabitation, for example, by avoiding undesired situations for the human. Unfortunately, current task planners only consider the robot's actions and unexpected external events in the planning process, and cannot accommodate expectations about the actions of the humans.

    In this article, we present a human-aware planner able to address this problem. Our planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. Our planner has been tested both as a stand-alone component and within a full framework for human-robot interaction in a real environment.

  • 22.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Human-aware task planning for mobile robots2009In: Proceedings of the 5th international conference on advanced robotics, ICAR 2009, New York: IEEE conference proceedings, 2009, p. 172-178Conference paper (Refereed)
    Abstract [en]

    Robots that share their workspace with people, like household or service robots, need to take into account the presence of humans when planning their actions. In this paper, we present a framework for human-aware planning that would make the robots capable of performing their tasks without interfering with the user in his every day life. We focus in particular on the core module of the framework, a humanaware planner that generates a sequence of actions for a robot, taking into account the state of the environment and the goals of the robot, together with a set of forecasted possible plans of the human. We describe the planner and its relations to other system components like a plan recognizer, and present a series of experiments performed with a household robot in a small apartment.

  • 23.
    Coradeschi, Silvia
    et al.
    Örebro University, School of Science and Technology.
    Cesta, Amadeo
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Cortellessa, Gabriella
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Coraci, Luca
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Gonzalez, Javier
    Málaga University, Málaga, Spain.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Furfari, Francesco
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Orlandini, Andrea
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Palumbo, Filippo
    Consiglio Nazionale Delle Ricerche, Bari, Italy.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    von Rump, Stephan
    Giraff AB, Stockholm, Sweden.
    Ullberg, Jonas
    Örebro University, School of Science and Technology.
    Östlund, Britt
    Lund University, Lund, Sweden.
    GiraffPlus: combining social interaction and long term monitoring for promoting independent living2013In: 2013 6TH INTERNATIONAL CONFERENCE ON HUMAN SYSTEM INTERACTIONS (HSI), New York, 2013, p. 578-585Conference paper (Refereed)
    Abstract [en]

    Early detection and adaptive support to changing individual needs related to ageing is an important challenge in today’s society. In this paper we present a system called GiraffPlus that aims at addressing such a challenge and is developed in an on-going European project. The system consists of a network of home sensors that can be automatically configured to collect data for a range of monitoring services; a semi-autonomous telepresence robot; a sophisticated context recognition system that can give high-level and long term interpretations of the collected data and respond to certain events; and personalized services delivered through adaptive user interfaces for primary users. The system performs a range of services including data collection and analysis of long term trends in behaviors and physiological parameters (e.g. relating to sleep or daily activity); warnings, alarms and reminders; and social interaction through the telepresence robot. The latter is based on the Giraff telepresence robot, which is already in place in a number of homes. Particular emphasis is put on user evaluation outside the laboratories. A distinctive aspect of the project is that the GiraffPlus system will be installed and evaluated in at least 15 homes of elderly people. The concept of “useworthiness” is central in order to assure that the GiraffPlus system provides services that are easy to use and worth using. In addition, by using existing and affordable components we strive to achieve a system that is affordable and close to commercialization.

  • 24.
    Coradeschi, Silvia
    et al.
    Örebro University, Department of Technology.
    Driankov, Dimiter
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    Fuzzy anchoring2001In: The 10th IEEE international conference on fuzzy systems, 2001, p. 111-114Conference paper (Refereed)
    Abstract [en]

    An intelligent physical agent must incorporate motor and perceptual processes to interface with the physical world, and abstract cognitive processes to reason about the world and the options available. One crucial aspect of incorporating cognitive processes into a physically embedded reasoning system is the integration between the symbols used by the reasoning processes to denote physical objects, and the perceptual data corresponding to these objects. We treat this integration aspect by proposing a fuzzy computational theory of anchoring. Anchoring is the process of creating and maintaining the correspondence between symbols and percepts that refer to the same physical objects. Modeling this process using fuzzy set-theoretic notions enables dealing with perceptual data that can be affected by uncertainty/imprecision and imprecise/vague linguistic descriptions of objects

  • 25.
    d. C. Silva-Lopez, Lia Susana
    et al.
    Örebro University, School of Science and Technology.
    Broxvall, Mathias
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Towards configuration planning with partially ordered preferences: representation and results2015In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 9, no 2, p. 173-183Article in journal (Refereed)
    Abstract [en]

    Configuration planning for a distributed robotic system is the problem of how to configure the system over time in order to achieve some causal and/or information goals. A configuration plan specifies what components (sensor, actuator and computational devices), should be active at different times and how they should exchange information. However, not all plans that solve a given problem need to be equally good, and for that purpose it may be important to take preferences into account. In this paper we present an algorithm for configuration planning that incorporates general partially ordered preferences. The planner supports multiple preference categories, and hence it solves a multiple-objective optimization problem: for a given problem, it finds all possible valid, non-dominated configuration plans. The planner has been able to successfully cope with partial ordering relations between quantitative preferences in practically acceptable times, as shown in the empirical results. Preferences here are represented as c-semirings, and are used for establishing dominance of a solution over another in order to obtain a set of configuration plans that will constitute the solution of a configuration planning problem with partially ordered preferences. The dominance operators tested in this paper are Pareto and Lorenz dominance. Our solver considers one guiding heuristic for obtaining the first solution, and then switches to a dominance based monotonically decreasing heuristic used for pruning dominated partial configuration plans. In our empirical results, we perform a statistical study in the space of problem instances and establish families of problems for which our approach is computationally feasible.

  • 26.
    Eriksen, Niklas
    et al.
    Örebro University, School of Science and Technology.
    Hilmerby, Sören
    Örebro University, School of Science and Technology.
    Johansson, Madelaine
    Örebro University.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Starting from Scratch: Implementing CDIO in a new Master of Science in Engineering2016Conference paper (Other academic)
    Abstract [en]

    In 2015, Örebro University was granted the rights to provide a Master of Science in Engineering (5 year engineering programme). This fall we launch two programmes, in Computer Science and Industrial Economics. The basis of these programmes rests on a pedagogical approach of increasing interest, namely CDIO (Conceive-Design-Implement-Operate), which aims to provide a framework particularly suited for technical and engineering programmes.

    A number of non-trivial challenges were addressed when crafting a programme that conforms to the CDIO standards and guidelines. In particular, one of the more difficult tasks is to ensure that a programme in its entirety satisfies both the CDIO goals and the learning outcomes in the Swedish Higher Education Ordinance in a coherent and meaningful way. A further challenge is to educate the entire teaching core to help them adopt the model, and to guide the staff in finding proper use of CDIO within each different subject.

    This talk presents how these challenges were addressed in adopting CDIO during the application process and the initial implementation stages. It describes how a department in rapid development was able to anchor the concepts of the pedagogical model with its teachers and programme directors. In particular, we outline the tools and processes which were used in order to create familiarity and consensus with the teaching core responsible for the new education. The talk also describes the difficulties encountered in applying a single pedagogical model to an education, and outlines the iterative process taken in order to integrate CDIO in a new programme and within its various courses.

  • 27.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Conditional progressive planning under uncertainty2001Conference paper (Refereed)
    Abstract [en]

    In this article, we describe a possibilis - tic/probabilistic conditional planner called PTLplan Being inspired by Bacchus and Ka - banza's TLplan, PTLplan is a progressive planner that uses strategic knowledge encoded in a tem - poral logic to reduce its search space Actions effects and sensing can be context dependent and uncertain, and the information the planning agent has at each point in time is represented as a set of situations with associated possibilities or probabilities Besides presenting the planner itself - its representation of actions and plans, and its algorithm - we also provide some promising data from performance tests

  • 28.
    Karlsson, Lars
    et al.
    Örebro University, School of Science and Technology.
    Bidot, Julien
    Örebro University, School of Science and Technology.
    Lagriffoul, Fabien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Hillenbrand, Ulrich
    Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen, Germany.
    Schmidt, Florian
    Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Oberpfaffenhofen, Germany.
    Combining task and path planning for a humanoid two-arm robotic system2012In: Combining Task and Motion Planning for Real-World Applications (ICAPS workshop), 2012, p. 13-20Conference paper (Refereed)
  • 29.
    Karlsson, Lars
    et al.
    Örebro University, School of Science and Technology.
    Bidot, Julien
    Örebro University, School of Science and Technology.
    Lagriffoul, Fabien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Hillenbrand, Ulrich
    Deutschen Zentrums für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, Germany.
    Schmidt, Florian
    Deutschen Zentrums für Luft- und Raumfahrt (DLR), Oberpfaffenhofen, Germany.
    Progress and challenges in planning for a two-arm robot2012Conference paper (Refereed)
  • 30.
    Karlsson, Lars
    et al.
    Örebro University, Department of Technology.
    Bouguerra, Abdelbaki
    Örebro University, Department of Technology.
    Broxvall, Mathias
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    To secure an anchor: a recovery planning approach to ambiguity in perceptual anchoring2008In: AI Communications, ISSN 0921-7126, E-ISSN 1875-8452, Vol. 21, no 1, p. 1-14Article in journal (Refereed)
    Abstract [en]

    An autonomous robot using symbolic reasoning, sensing and acting in a real environment needs the ability to create and maintain the connection between symbols representing objects in the world and the corresponding perceptual representations given by its sensors. This connection has been named perceptual anchoring. In complex environments, anchoring is not always easy to establish: the situation may often be ambiguous as to which percept actually corresponds to a given symbol.

    In this paper, we extend perceptual anchoring to deal robustly with ambiguous situations by providing general methods for detecting them and recovering from them. We consider different kinds of ambiguous situations. We also present methods to recover from these situations based onautomatically formulating them as conditional planning problems that then are solved by a planner.

    We illustrate our approach by showing experiments involving a mobile robot equipped with a color camera and an electronic nose.

  • 31.
    Karlsson, Lars
    et al.
    Örebro University, Department of Technology.
    Schiavinotto, Tommaso
    Technische Universität Darmstadt.
    Progressive planning for mobile robots: a progress report2002In: Advances in Plan-Based Control of Robotic Agents / [ed] Michael Beetz, Joachim Hertzberg, Malik Ghallab, Martha E. Pollack, 2002, Vol. 2466, p. 273-297Conference paper (Refereed)
    Abstract [en]

    In this article, we describe a possibilistic/probabilistic conditional planner called PTLplan, and how this planner can be integrated with a behavior-based fuzzy control system called the Thinking Cap in order to execute the generated plans. Being inspired by Bacchus and Kabanza's TLplan, PTLplan is a progressive planner that uses strategic knowledge encoded in a temporal logic to reduce its search space. Actions' effects and sensing can be context dependent and uncertain, and the resulting plans may contain conditional branches. When these plans are executed by the control system, they are transformed into B-plans which essentially are combinations of fuzzy behaviors to be executed in different contexts

  • 32.
    Klügl, Franziska
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Towards Pattern-Oriented Design of Agent-Based Simulation Models2009In: MULTI-AGENT SYSTEM TECHNOLOGIES, PROCEEDINGS / [ed] Braubach, L; VanderHoek, W; Petta, P; Pokahr, A, Berlin, Germany: Springer, 2009, p. 41-53Conference paper (Refereed)
    Abstract [en]

    The formalization and use of experiences in good model design would make an important contribution to increasing the efficiency of modeling as well as to supporting the knowledge transfer from experienced modelers to modeling novices. We propose to address this problem by providing a set of model design patterns inspired by patterns in Software Engineering for capturing the reusable essence of a solution to specific partial modeling problem. This contribution provides a First step formulating the vision and indicating how patterns and which types of patterns can play a role in agent-based model design.

  • 33.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Alirezaie, Marjan
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Integrating Ontologies for Context-based Constraint-based Planning2018In: MRC 2018: Modelling and Reasoning in Context, 2018, p. 22-29Conference paper (Refereed)
    Abstract [en]

    We describe an approach for integrating ontologies with a constraint-based planner to compile configuration planning domains based on the current context. We consider two alternative approaches: The first one integrates SPARQL queries directly with the planner while the second one generates SPARQL queries dynamically from provided triples. The first approach offers the full freedom of the SPARQL query language, while the second offers a more dynamic way for the planner to influence queries based on what is currently relevant for the planner. We evaluate the approach based on how much redundancy is removed by “outsourcing” knowledge into the ontology compared to modeling it directly into the domain of the planner.

  • 34.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Configuration Planning with Temporal Constraints2017In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), AAAI Press, 2017Conference paper (Refereed)
    Abstract [en]

    Configuration planning is a branch of task planning that takes into consideration both causal and information dependencies and goals.This type of planning is interesting, for instance, in smart home environmentswhich contain various sensors and robots to provide services to the inhabitants.Requests for information, for instance from an activity recognition system, should cause the smart home to configure itselfin such a way that all requested information will be providedwhen it is needed.This paper addresses temporal configuration planning in which information availability and goals are linked to temporalintervals which are subject to constrains.We propose and compare two approaches based on constraint-based planning. The first approach models information via conditions andeffects of planning operators and essentially reduces configuration planningto constraint-based temporal planning. The second approach solves information dependencies separatelyfrom task planning and optimizes the cost of reaching individual information goals.We compare these approaches in terms of thetime it takes to solve problems and the quality of the solutions they provide.

  • 35.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Expressive Planning Through Constraints2013In: Twelfth Scandinavian Conference on Artificial Intelligence / [ed] Manfred Jaeger, Thomas Dyhre Nielsen, Paolo Viappiani, IOS Press, 2013, p. 155-164Conference paper (Refereed)
    Abstract [en]

    The real-world applicability of automated planners depends on the  expressiveness of the problem modeling language.  Contemporary  planners can deal with causal features of the problem, but only  limited forms of temporal, resource and relational constraints.  These constraints should be fully supported for dealing with  real-world applications.  We propose a highly-expressive, action-based planning language which  includes causal, relational, temporal and resource constraints.  This paper also contributes an approach for solving such rich  planning problems by decomposition and constraint reasoning.  The approach is general with respect to the types of constraints  used in the problem definition language, in that additional solvers  need only satisfy certain formal properties. The approach is  evaluated on a domain which utilizes many features offered by the  introduced language.

  • 36.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Grandpa Hates Robots - Interaction Constraints for Planning in Inhabited Environments2014In: Proceedings of the 28th National Conference on Artifical Intelligence (AAAI 2014), AAAI Press, 2014, p. 2293-2299Conference paper (Refereed)
    Abstract [en]

    Consider a family whose home is equipped with several service robots. The actions planned for the robots must adhere to {\em Interaction Constraints (ICs)} relating them to human activities and preferences. These constraints must be sufficiently expressive to model both temporal and logical dependencies among robot actions and human behavior, and must accommodate incomplete information regarding human activities. In this paper we introduce an approach for automatically generating plans that are conformant wrt.~given ICs and partially specified human activities. The approach allows to separate causal reasoning about actions from reasoning about \ICs, and we illustrate the computational advantage this brings with experiments on a large-scale (semi-)realistic household domain with hundreds of human activities and several robots.

  • 37.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Inferring Context and Goals for Online Human-Aware Planning2015In: International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, 2015, p. 550-557Conference paper (Refereed)
    Abstract [en]

    Planning for robots in environments co-inhabited by humans entails handling exogenous events during plan execution. Such events require plans to be continuously adapted to ensure that they remain "human-aware", i.e., adherent to human preferences and needs. We use an approach whereby human-awareness is enforced through so-called interaction constraints. Interaction constraints are used to infer context and appropriate goals online. The current plan is modified at run time so as to achieve courses of action that are continuously human-aware. The approach is evaluated in a research facility environment in which we simulate multiple days of planning and execution.

  • 38.
    Köckemann, Uwe
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Towards planning with very expressive languages via problem decomposition into multiple CSPs2012In: Coplas 2012: proceedings of the workshop on constraint satisfaction techniques for planning and scheduling problems / [ed] Miguel A. Salido, Roman Barták, 2012, p. 33-42Conference paper (Refereed)
    Abstract [en]

    The main contribution of this paper is a planning language that can handle temporal constraints, resources and background knowledge. We provide a solver for this language based on problem decomposition that uses constraint satisfaction problems (CSPs) as a common ground. We argue that the usage of more expressive languages not only allows a more direct modeling of planning domains, but can speed up the planning process as well. We also present an experiment in support of that argument.

  • 39.
    Lagriffoul, Fabien
    et al.
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar
    Örebro University, School of Science and Technology.
    Bidot, Julien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Efficiently combining task and motion planning using geometric constraints2014In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 33, no 14, p. 1726-1747Article in journal (Refereed)
    Abstract [en]

    We propose a constraint-based approach to address a class of problems encountered in combined task and motion planning (CTAMP), which we call kinematically constrained problems. CTAMP is a hybrid planning process in which task planning and geometric reasoning are interleaved. During this process, symbolic action sequences generated by a task planner are geometrically evaluated. This geometric evaluation is a search problem per se, which we refer to as geometric backtrack search. In kinematically constrained problems, a significant computational effort is spent on geometric backtrack search, which impairs search at the task level. At the basis of our approach to address this problem, is the introduction of an intermediate layer between task planning and geometric reasoning. A set of constraints is automatically generated from the symbolic action sequences to evaluate, and combined with a set of constraints derived from the kinematic model of the robot. The resulting constraint network is then used to prune the search space during geometric backtrack search. We present experimental evidence that our approach significantly reduces the complexity of geometric backtrack search on various types of problem.

  • 40.
    Lagriffoul, Fabien
    et al.
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar
    Örebro University, School of Science and Technology. INRIA Rhône-Alpes, France.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Bidot, Julien
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Using Geometric Constraints for Efficiently Combining Task and Motion PlanningIn: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176Article in journal (Refereed)
    Abstract [en]

    We propose a constraint-based approach to address a class of problems encountered in Combined Task and Motion Planning (CTAMP), which we call geometrically constrained problems. CTAMP is a hybrid planning process in which task planning and geometric reasoning are interleaved. During this process, symbolic action sequences generated by a task planner are geometrically evaluated. This geometric evaluation is a search problem per se, which we refer to asgeometric backtrack search. In geometrically constrained problems, a significant computational effort is spent on geometric backtrack search, which impairs search at the task-level. At the basis of our approach to address this problem, is the introduction of an intermediate layer between task planning and geometric reasoning. A set of constraints is automatically generated from the symbolic action sequences to evaluate, and combined with a set of constraints derived from the kinematic model of the robot. The resulting constraint network is then used to prune the search space during geometric backtrack search. We present experimental evidence that our approach significantly reduces the complexity of geometric backtrack search on various types of problem.

  • 41.
    Lagriffoul, Fabien
    et al.
    Örebro University, School of Science and Technology.
    Dimitrov, Dimitar
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Constraint propagation on interval bounds for dealing with geometric backtracking2012In: Proceedings of  the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), Institute of Electrical and Electronics Engineers (IEEE), 2012, p. 957-964Conference paper (Refereed)
    Abstract [en]

    The combination of task and motion planning presents us with a new problem that we call geometric backtracking. This problem arises from the fact that a single symbolic state or action can be geometrically instantiated in infinitely many ways. When a symbolic action cannot begeometrically validated, we may need to backtrack in thespace of geometric configurations, which greatly increases thecomplexity of the whole planning process. In this paper, weaddress this problem using intervals to represent geometricconfigurations, and constraint propagation techniques to shrinkthese intervals according to the geometric constraints of the problem. After propagation, either (i) the intervals are shrunk, thus reducing the search space in which geometric backtracking may occur, or (ii) the constraints are inconsistent, indicating then infeasibility of the sequence of actions without further effort. We illustrate our approach on scenarios in which a two-arm robot manipulates a set of objects, and report experiments that show how the search space is reduced.

  • 42.
    Lagriffoul, Fabien
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Bidot, Julien
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Combining Task and Motion Planning is Not Always a Good Idea2013Conference paper (Refereed)
    Abstract [en]

    Combining task and motion planning requires tointerleave causal and geometric reasoning, in order to guaranteethe plan to be executable in the real world. The resulting searchspace, which is the cross product of the symbolic search spaceand the geometric search space, is huge. Systematically calling ageometric reasoner while evaluating symbolic actions is costly. Onthe other hand, geometric reasoning can prune out large parts ofthis search space if geometrically infeasible actions are detectedearly. Hence, we hypothesized the existence of a search depthlevel, until which geometric reasoning can be interleaved withsymbolic reasoning with tractable combinatorial explosion, whilekeeping the benefits of this pruning. In this paper, we propose asimple model that proves the existence of such search depth level,and validate it empirically through experiments in simulation

  • 43.
    Lagriffoul, Fabien
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Constraints on intervals for reducing the search space of geometric configurations2012In: Combining Task and Motion Planning for Real-World Applications (ICAPS workshop) / [ed] Marcello Cirillo, Brian Gerkey, Federico Pecora, Mike Stilman, 2012, p. 5-12Conference paper (Refereed)
  • 44.
    Loutfi, Amy
    et al.
    Örebro University, Department of Technology.
    Broxvall, Mathias
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Object recognition: a new application for smelling robots2005In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 52, no 4, p. 272-289Article in journal (Refereed)
    Abstract [en]

    Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses, it is now possible to detect and recognize a range of different odours for a variety of applications. In this work, we introduce a new application where electronic olfaction is used in cooperation with other types of sensors on a mobile robot in order to acquire the odour property of objects.We examine the problem of deciding when, how and where the electronic nose (e-nose) should be activated by planning for active perception and we consider the problem of integrating the information provided by the e-nose with both prior information and information from other sensors (e.g., vision). Experiments performed on a mobile robot equipped with an e-nose are presented.

  • 45.
    Loutfi, Amy
    et al.
    Örebro University, School of Science and Technology.
    Jönsson, Arne
    SICS East.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Lind, Leili
    SICS East.
    Lindén, Maria
    Mälardalen University, Västerås, Sweden.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Voigt, Thiemo
    SICS ICT.
    Ecare@Home: A Distributed Research Environment on Semantic Interoperability2016Conference paper (Refereed)
    Abstract [en]

    This paper presents the motivation and challenges to developingsemantic interoperability for an internet of things network that isused in the context of home based care. The paper describes a researchenvironment which examines these challenges and illustrates the motivationthrough a scenario whereby a network of devices in the home isused to provide high-level information about elderly patients by leveragingfrom techniques in context awareness, automated reasoning, andconguration planning.

  • 46.
    Loutfi, Amy
    et al.
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Broxvall, Mathias
    Örebro University, Department of Technology.
    Putting olfaction into action: anchoring symbols to sensor data using olfaction and planning2005In: Workshop on planning and learning in a priori unknown or dynamic domains: Proceedings of the 19th IJCAI conference Edinburgh, UK, August 2005, 2005, p. 35-40Conference paper (Refereed)
    Abstract [en]

    Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses (e-noses) it is now possible to train a system to detect and recognise a range of different odours. In this work, we integrate the electronic nose on a multi-sensing mobile robotic platform. We plan for perceptual actions and examine when, how and where the e-nose should be activated.

    Finally, experiments are performed on a mobile robot equipped with an e-nose together with a variety of sensors and used for object detection.

  • 47.
    Loutfi, Amy
    et al.
    Örebro University, Department of Technology.
    Coradeschi, Silvia
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Broxvall, Mathias
    Örebro University, Department of Technology.
    Putting olfaction into action: using an electronic nose on an multi-sensing mobile robot2004In: Proceedings of the 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS 2004), 2004, p. 337-342Conference paper (Refereed)
    Abstract [en]

    Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses it is now possible to detect and recognise a range of different odours for a variety of applications. An existing application is to use electronic olfaction on mobile robots for the purpose of odour based navigation. In this work, we introduce a new application where electronic olfaction is used in cooperation with other types of sensors on a mobile robot in order to acquire the odour

  • 48.
    Lundh, Robert
    et al.
    Örebro University, Department of Technology.
    Karlsson, Lars
    Örebro University, Department of Technology.
    Saffiotti, Alessandro
    Örebro University, Department of Technology.
    An algorithm for generating configurations of groups of robots2007Report (Other academic)
    Abstract [en]

    This work is about the use of artificial intelligence (AI) planning techniques to automatically configure cooperation among robots. We consider groups of autonomous robots in which robots can help each other by offering information producing resources and functionalities. A configuration in this context, is a way to allocate and connect functionalities among robots. In general, different configurations can be used to solve the same task, depending on the current situation. Configuration generation is the problem of automatically generating a configuration for some specific purpose given a set of robotic devices possessing dfferent functionalities. In this paper, we consider an existing configuration planner both from a theoretical point of view (soundness, completeness, and optimality), and an empirical point of view (scalability). We also present a technique to improve the scalability of the configuration planner.

  • 49.
    Lundh, Robert
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Automatic configuration of multi-robot systems: planning for multiple steps2008In: Proceeding of the 2008 conference on ECAI 2008: 18th European conference on artificial intelligence / [ed] Malik Ghallab, Constantine D. Spyropoulos, Nikos Fakotakis, Nikos Avouris, Amsterdam: IOS Press , 2008, p. 616-620Conference paper (Refereed)
    Abstract [en]

    We consider multi-robot systems where robots need to cooperate tightly by sharing functionalities with each other. There are methods for automatically configuring a multi-robot system for tight cooperation, but they only produce a single configuration. In this paper, we show how methods for automatic configuration can be integrated with methods for task planning in order to produce a complete plan were each step is a configuration. We also consider the issues of monitoring and replanning in this context, and we demonstrate our approach on a real multi-robot system, the PEIS-Ecology

  • 50.
    Lundh, Robert
    et al.
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Automatic configuration of multi-robot systems: planning for multiple steps2008In: ECAI 2008, PROCEEDINGS, 2008, p. 616-620Conference paper (Refereed)
    Abstract [en]

    We consider multi-robot systems where robots need to cooperate tightly by sharing functionalities with each other. There are methods for automatically configuring a multi-robot system for tight cooperation, but they only produce a single configuration. In this paper, we show how methods for automatic configuration can be integrated with methods for task planning in order to produce a complete plan were each step is a configuration. We also consider the issues of monitoring and replanning in this context, and we demonstrate our approach on a real multi-robot system, the PEIS-Ecology.

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