To Örebro University

oru.seÖrebro universitets publikasjoner
Endre søk
Begrens søket
123 51 - 100 of 125
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Treff pr side
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
Merk
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 51.
    Forte, Paolo
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Mannucci, Anna
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Andreasson, Henrik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Online Task Assignment and Coordination in Multi-Robot Fleets2021Inngår i: IEEE Robotics and Automation Letters, E-ISSN 2377-3766, Vol. 6, nr 3, s. 4584-4591Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We propose a loosely-coupled framework for integrated task assignment, motion planning, coordination and contro of heterogeneous fleets of robots subject to non-cooperative tasks. The approach accounts for the important real-world requiremen that tasks can be posted asynchronously. We exploit systematic search for optimal task assignment, where interference is considered as a cost and estimated with knowledge of the kinodynamic models and current state of the robots. Safety is guaranteed by an online coordination algorithm, where the absence of collisions is treated as a hard constraint. The relation between the weight of interference cost in task assignment and computational overhead is analyzed empirically, and the approach is compared against alternative realizations using local search algorithms for task assignment.

  • 52.
    Grosinger, Jasmin
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Find Out Why Reading This Paper is an Opportunity of Type Opp02014Inngår i: CogRob 2014: The 9th International Workshop on Cognitive Robotics, 2014, , s. 6Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Under what conditions should a cognitive robot act? How do we define “opportunities” for robot action? How can we characterize their properties? This paper offers an apparatus to frame thediscussion. Starting from a simple introductory example, we specifyan initial version of a formal framework of opportunity which relates current and future states and beneficial courses of action in a certain time horizon. An opportunity reasoning algorithm is presented,which opens up various new questions about the different types of opportunity and how to interleave opportunity reasoning and action execution. An implementation of this algorithm is tested in a simple experiment including a real mobile robot in a smart home environment and a user.

    Fulltekst (pdf)
    fulltext
  • 53.
    Grosinger, Jasmin
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Making Robots Proactive through Equilibrium Maintenance2016Inngår i: 25th International Joint Conference on Artificial Intelligence, 2016Konferansepaper (Fagfellevurdert)
  • 54.
    Grosinger, Jasmin
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Proactivity through equilibrium maintenance with fuzzy desirability2017Inngår i: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Institute of Electrical and Electronics Engineers (IEEE), 2017Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Proactive cognitive agents need to be capable ofboth generating their own goals and enacting them. In thispaper, we cast this problem as that ofmaintaining equilibrium,that is, seeking opportunities to act that keep the system indesirable states while avoiding undesirable ones. We characterizedesirability of states as graded preferences, using mechanismsfrom the field of fuzzy logic. As a result, opportunities for anagent to act can also be graded, and their relative preferencecan be used to infer when and how to act. This paper providesa formal description of our computational framework, andillustrates how the use of degrees of desirability leads to well-informed choices of action.

    Fulltekst (pdf)
    fulltext
  • 55.
    Grosinger, Jasmin
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Robots and Bananas: Exploring Deliberation in Cognitive Robots2014Inngår i: AI and Robotics: Papers from the AAAI-14 Workshop, 2014, , s. 2Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Under what conditions should a cognitive robot act? How do we define “opportunities” for robot action? How can we characterize their properties? In this po-sition paper, we offer an initial apparatus to formalize opportunities and to frame this discussion.

  • 56.
    Grosinger, Jasmin
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Robots that Maintain Equilibrium: Proactivity by Reasoning About User Intentions and Preferences2019Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 118, s. 85-93Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Robots need to exhibit proactive behavior if they are to be accepted in human-centered environments. A proactive robot must reason about the actions it can perform, the state of the environment, the state and the intentions of its users, and what the users deem desirable. This paper proposes a computational framework for proactive robot behavior that formalizes the above ingredients. The framework is grounded on the notion of Equilibrium Maintenance: current and future states are continuously evaluated to identify opportunities for acting that steer the system into more desirable states. We show that this process leads a robot to proactively generate its own goals and enact them, and that the obtained behavior depends on a model of user intentions, preferences, and the temporal horizon used in prediction. A number of examples show that our framework accounts for even slight variations in user preference models and perceived user intentions. We also show how the level of informedness of the system is easily customizable.

  • 57.
    Gugliermo, Simona
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik. Intelligent Transport Systems, Scania CV AB, Södertälje, Sweden.
    Schaffernicht, Erik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Koniaris, Christos
    Intelligent Transport Systems, Scania CV AB, Södertälje, Sweden.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Learning Behavior Trees From Planning Experts Using Decision Tree and Logic Factorization2023Inngår i: IEEE Robotics and Automation Letters, E-ISSN 2377-3766, Vol. 8, nr 6, s. 3534-3541Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The increased popularity of Behavior Trees (BTs) in different fields of robotics requires efficient methods for learning BTs from data instead of tediously handcrafting them. Recent research in learning from demonstration reported encouraging results that this letter extends, improves and generalizes to arbitrary planning domains. We propose BT-Factor as a new method for learning expert knowledge by representing it in a BT. Execution traces of previously manually designed plans are used to generate a BT employing a combination of decision tree learning and logic factorization techniques originating from circuit design. We test BT-Factor in an industrially-relevant simulation environment from a mining scenario and compare it against a state-of-the-art BT learning method. The results show that our method generates compact BTs easy to interpret, and capable to capture accurately the relations that are implicit in the training data.

    Fulltekst tilgjengelig fra 2025-06-01 00:00
  • 58. Günther, Martin
    et al.
    Hertzberg, Joachim
    Mansouri, Masoumeh
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Hybrid reasoning in perception: a case study2012Inngår i: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 45, nr 22, s. 90-95Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Robots operating in a complex human-inhabited environment need to represent and reason about different kinds of knowledge, including ontological, spatial, causal, temporal and resource knowledge. Often, these reasoning tasks are not mutually independent, but need to be integrated with each other. Integrated reasoning is especially important when dealing with knowledge derived from perception, which may be intrinsically incomplete or ambiguous. For instance, the non-observable property that a dish has been used and should therefore be washed can be inferred from the observable properties that it was full before and that it is empty now. In this paper, we present a hybrid reasoning framework which allows to easily integrate different kinds of reasoners. We demonstrate the suitability of our approach by integrating two kinds of reasoners, for ontological reasoning and for temporal reasoning, and using them to recognize temporally and ontologically defined object properties in point cloud data captured using an RGB-D camera.

  • 59.
    Hertzberg, Joachim
    et al.
    Osnabrück University, Osnabrück, Germany .
    Zhang, Jianwei
    Hamburg University, Hamburg, Germany .
    Zhang, Liwei
    Hamburg University, Hamburg, Germany .
    Rockel, Sebastian
    Hamburg University, Hamburg, Germany .
    Neumann, Bernd
    Hamburg University, Hamburg, Germany .
    Lehmann, Jos
    Hamburg University, Hamburg, Germany .
    Dubba, Krishna S.R.
    University of Leeds, Leeds, England .
    Cohn, Anthony G.
    University of Leeds, Leeds, England .
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Mansouri, Masoumeh
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Konečný, Štefan
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Günther, Martin
    Osnabrück University, Osnabrück, Germany .
    Stock, Sebastian
    Osnabrück University, Osnabrück, Germany .
    Seabra Lopes, Luis
    University of Aveiro, Aveiro, Portugal .
    Oliveira, Miguel
    University of Aveiro, Aveiro, Portugal .
    Lim, Gi Hyun
    University of Aveiro, Aveiro, Portugal .
    Kasaei, Hamidreza
    University of Aveiro, Aveiro, Portugal .
    Mokhtari, Vahid
    University of Aveiro, Aveiro, Portugal .
    Hotz, Lothar
    HITeC Hamburger Informatik Technologie-Center e. V., Hamburg, Germany .
    Bohlken, Wilfried
    HITeC Hamburger Informatik Technologie-Center e. V., Hamburg, Germany .
    The RACE Project: Robustness by Autonomous Competence Enhancement2014Inngår i: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 28, nr 4, s. 297-304Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.

  • 60.
    Khaliq, Ali Abdul
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Köckemann, Uwe
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Bruno, Barbara
    University of Genova, Genova, Italy.
    Recchiuto, Carmine Tommaso
    University of Genova, Genova, Italy.
    Sgorbissa, Antonio
    University of Genova, Genova, Italy.
    Bui, Ha-Duong
    Japan Advanced Institute of Science and Technology, Ishikawa, Japan.
    Chong, Nak Young
    Japan Advanced Institute of Science and Technology, Ishikawa, Japan.
    Culturally aware Planning and Execution of Robot Actions2018Inngår i: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2018, s. 326-332Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The way in which humans behave, speak andinteract is deeply influenced by their culture. For example,greeting is done differently in France, in Sweden or in Japan;and the average interpersonal distance changes from onecultural group to the other. In order to successfully coexistwith humans, robots should also adapt their behavior to theculture, customs and manners of the persons they interact with.In this paper, we deal with an important ingredient of culturaladaptation: how to generate robot plans that respect givencultural preferences, and how to execute them in a way thatis sensitive to those preferences. We present initial results inthis direction in the context of the CARESSES project, a jointEU-Japan effort to build culturally competent assistive robots.

  • 61.
    Khaliq, Ali Abdul
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Children playing with robots using stigmergy on a smart floor2016Inngår i: 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 1098-1103Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Reliable and safe interaction is essential when humans and robots move in close proximity. In this paper, we present a stigmergic approach where humans interact with robots via a smart floor. Stigmergy has been widely studied in robotic systems, however, HRI has thus far not availed itself of stigmergic solutions. We realize a stigmergic medium via RFID tags embedded in the floor, and use these to enable robot navigation, human tracking, as well as the interaction between robots and humans. The proposed method allows to employ robots with minimal sensing and computation capabilities. The approach relies only on the RFID sensors and the information stored in the tags, and no internal map is required for navigation. We design and implement a prototype game which involves a robot and a child moving together in a shared space. The prototype demonstrates that the approach is reliable and adheres to given safety constraints when human and robot are moving within close proximity of each other.

  • 62.
    Khaliq, Ali Abdul
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Inexpensive, reliable and localization-free navigation using an RFID floor2015Inngår i: 2015 European Conference on Mobile Robots (ECMR), New York: IEEE conference proceedings , 2015, artikkel-id 7324204Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Stigmergy is a principle observed in nature, in which animals store in the environment information to be used for communication or navigation. Stigmergy has recently been exploited in robotics: simple robots store a goal distance field in read-write RFID tags embedded in the floor, and later follow the gradient of this field to navigate optimally to that goal. Stigmergic navigation is localization-free, since robots only rely on the values read from the tags and do not need to know their own location. This makes navigation inexpensive (no ranging sensors) and reliable (no localization failures). To make this approach viable in practice, two issues need to be addressed: how to simplify the installation of an RFID floor; and how to follow the field gradient in a reliable way. This paper presents solutions to both problems. The solutions are validated through experiments performed on simulated and on real robots.

  • 63.
    Konečný, Štefan
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Execution Knowledge for Execution Monitoring: what, why, where and what for?2014Inngår i: IEEE/RSJ International Conference On Intelligent Robots and Systems (IROS), 2014, 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Despite the progress made in planning androbotics, autonomous plan execution on a robot remainschallenging. One of the problems is that (classical) plannersuse abstract models which are disconnected from the sensorand actuation information available during execution. Thisconnection is typically created in a non-systematic way by somesystem-specific execution software. In this paper we proposeto explicitly represent Execution Knowledge that encodes theconnection between planning models and the actual actionsand observations for a given physical system. We present anexecution monitoring framework in which Execution Knowl-edge captures the expectations about physical plan execution.A violation of these expectations indicates an execution failure.

    Fulltekst (pdf)
    Execution Knowledge
  • 64.
    Konečný, Štefan
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Stock, Sebastian
    Osnabrück University, Osnabrück, Germany.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Planning domain + execution semantics: a way towards robust execution?2014Inngår i: Qualitative Representations for Robots: Papers from the AAAI Spring Symposium, AAAI Press , 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Robots are expected to carry out complex plans in real world environments. This requires the robot to track the progress of plan execution and detect failures which may occur. Planners use very abstract world models to generate plans. Additional causal, temporal, categorical knowledge about the execution, which is not included in the planner's model, is often available. Can we use this knowledge to increase robustness of execution and provide early failure detection? We propose to use a dedicated Execution Model to monitor the executed plan based on runtime observations and rich execution knowledge. We show that the combined used of causal, temporal and categorical knowledge allows the robot to detect failures even when the effects of actions are not directly observable. A dedicated Execution model also introduces a degree of modularity, since the platform- and execution-specific knowledge does not need to be encoded into the planner.

  • 65.
    Köckemann, Uwe
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Khaliq, Ali Abdul
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Domain Reasoning for Robot Task Planning: A Position Paper2018Inngår i: PlanRob 2018: Proceedings of the 6th Workshop on Planning and Robotics / [ed] Alberto Finzi, Erez Karpas, Goldie Nejat, AndreA Orlandini, Siddharth Srivastava, ICAPS , 2018, s. 102-105Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this position paper we argue for moving towards generalpurpose domains to promote the usage of task planning forreal-world robot systems. Planning approaches should extractconcrete domains based on their current context in order tosolve problems. Towards this aim, we define the problem ofdomain reasoning, by which a planning domain is obtainedfrom a more general, multi-purpose domain definition, giventhe current deployment and context of the robot system. Weprovide examples motivating the need for domain reasoningin robot task planning, as well as a discussion of potentialsolutions to the domain reasoning problem.

  • 66.
    Köckemann, Uwe
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Karlsson, Lars
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Expressive Planning Through Constraints2013Inngår i: Twelfth Scandinavian Conference on Artificial Intelligence / [ed] Manfred Jaeger, Thomas Dyhre Nielsen, Paolo Viappiani, IOS Press, 2013, s. 155-164Konferansepaper (Fagfellevurdert)
    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.

  • 67.
    Köckemann, Uwe
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Karlsson, Lars
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Grandpa Hates Robots - Interaction Constraints for Planning in Inhabited Environments2014Inngår i: Proceedings of the 28th National Conference on Artifical Intelligence (AAAI 2014), AAAI Press, 2014, s. 2293-2299Konferansepaper (Fagfellevurdert)
    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.

  • 68.
    Köckemann, Uwe
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Karlsson, Lars
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Inferring Context and Goals for Online Human-Aware Planning2015Inngår i: International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, 2015, s. 550-557Konferansepaper (Fagfellevurdert)
    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.

  • 69.
    Köckemann, Uwe
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Karlsson, Lars
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Towards planning with very expressive languages via problem decomposition into multiple CSPs2012Inngår i: Coplas 2012: proceedings of the workshop on constraint satisfaction techniques for planning and scheduling problems / [ed] Miguel A. Salido; Roman Barták, 2012, s. 33-42Konferansepaper (Fagfellevurdert)
    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.

  • 70.
    Loutfi, Amy
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Jönsson, Arne
    SICS East.
    Karlsson, Lars
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Lind, Leili
    SICS East.
    Lindén, Maria
    Mälardalen University, Västerås, Sweden.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Voigt, Thiemo
    SICS ICT.
    Ecare@Home: A Distributed Research Environment on Semantic Interoperability2016Inngår i: Internet of Things Technologies for HealthCare. HealthyIoT 2016, Springer, 2016, s. 3-8Konferansepaper (Fagfellevurdert)
    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.

  • 71.
    Mannucci, Anna
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik. Research Center “E. Piaggio,” University of Pisa, Italy; Dipartimento di Ingegneria dell’Informazione, University of Pisa, Pisa, Italy.
    Pallottino, Lucia
    Research Center “E. Piaggio,” University of Pisa, Pisa, Italy; Dipartimento di Ingegneria dell’Informazione, University of Pisa, Pisa, Italy .
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    On Provably Safe and Live Multirobot Coordination with Online Goal Posting2021Inngår i: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 37, nr 6, s. 1973-1991Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A standing challenge in multirobot systems is to realize safe and efficient motion planning and coordination methods that are capable of accounting for uncertainties and contingencies. The challenge is rendered harder by the fact that robots may be heterogeneous and that their plans may be posted asynchronously. Most existing approaches require constraints on the infrastructureor unrealistic assumptions on robot models. In this article, we propose a centralized, loosely-coupled supervisory controller that overcomes these limitations. The approach responds to newly posed constraints and uncertainties during trajectory execution, ensuring at all times that planned robot trajectories remain kinodynamically feasible, that the fleet is in a safe state, and that there are no deadlocks or livelocks. This is achieved without the need for hand-coded rules, fixed robot priorities, or environment modification. We formally state all relevant properties of robot behavior in the most general terms possible, without assuming particular robot models or environments, and provide both formal and empirical proof that the proposed fleet control algorithms guarantee safety and liveness.

  • 72.
    Mannucci, Anna
    et al.
    Research Center E. Piaggio, University of Pisa, Pisa, Italy.
    Pallottino, Lucia
    Research Center E. Piaggio, University of Pisa, Pisa, Italy.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Provably Safe Multi-Robot Coordination With Unreliable Communication2019Inngår i: IEEE Robotics and Automation Letters, E-ISSN 2377-3766, Vol. 4, nr 4, s. 3232-3239Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Coordination is a core problem in multi-robot systems, since it is a key to ensure safety and efficiency. Both centralized and decentralized solutions have been proposed, however, most assume perfect communication. This letter proposes a centralized method that removes this assumption, and is suitable for fleets of robots driven by generic second-order dynamics. We formally prove that: first, safety is guaranteed if communication errors are limited to delays; and second, the probability of unsafety is bounded by a function of the channel model in networks with packet loss. The approach exploits knowledge of the network's non-idealities to ensure the best possible performance of the fleet. The method is validated via several experiments with simulated robots.

  • 73.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Andreasson, Henrik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Hybrid Reasoning for Multi-robot Drill Planning in Open-pit Mines2016Inngår i: Acta Polytechnica, ISSN 1210-2709, E-ISSN 1805-2363, Vol. 56, nr 1, s. 47-56Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Fleet automation often involves solving several strongly correlated sub-problems, including task allocation, motion planning, and coordination. Solutions need to account for very specific, domaindependent constraints. In addition, several aspects of the overall fleet management problem become known only online. We propose a method for solving the fleet-management problem grounded on a heuristically-guided search in the space of mutually feasible solutions to sub-problems. We focus on a mining application which requires online contingency handling and accommodating many domainspecific constraints. As contingencies occur, efficient reasoning is performed to adjust the plan online for the entire fleet.

    Fulltekst (pdf)
    fulltext
  • 74.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Andreasson, Henrik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Frederico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Towards Hybrid Reasoning for Automated Industrial Fleet Management2015Inngår i: 24th International Joint Conference on Artificial Intelligence, Workshop on Hybrid Reasoning, AAAI Press, 2015Konferansepaper (Fagfellevurdert)
    Abstract [en]

    More and more industrial applications require fleets of autonomous ground vehicles. Today's solutions to the management of these fleets still largely rely on fixed set-ups of the system, manually specified ad-hoc rules. Our aim is to replace current practice with autonomous fleets and fleet management systems that are easily adaptable to new set-ups and environments, can accommodate human-intelligible rules, and guarantee feasible and meaningful behavior of the fleet. We propose to cast the problem of autonomous fleet management to a meta-CSP that integrates task allocation, coordination and motion planning. We discuss design choices of the approach, and how it caters to the need for hybrid reasoning in terms of symbolic, metric, temporal and spatial constraints. We also comment on a preliminary realization of the system.

    Fulltekst (pdf)
    fulltext
  • 75.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Lacerda, Bruno
    Oxford Robotics Institute, University of Oxford, UK.
    Hawes, Nick
    Oxford Robotics Institute, University of Oxford, UK.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints2019Inngår i: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019, s. 478-484Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a novel modelling and planning approach for multi-robot systems under uncertain travel times. The approach uses generalised stochastic Petri nets (GSPNs) to model desired team behaviour, and allows to specify safety constraints and rewards. The GSPN is interpreted as a Markov decision process (MDP) for which we can generate policies that optimise the requirements. This representation is more compact than the equivalent multi-agent MDP, allowing us to scale better. Furthermore, it naturally allows for asynchronous execution of the generated policies across the robots, yielding smoother team behaviour. We also describe how the integration of the GSPN with a lower-level team controller allows for accurate expectations on team performance. We evaluate our approach on an industrial scenario, showing that it outperforms hand-crafted policies used in current practice.

    Fulltekst (pdf)
    Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints
  • 76.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Lagriffoul, Fabien
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Multi Vehicle Routing with Nonholonomic Constraints and Dense Dynamic Obstacles2017Inngår i: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2017, s. 3522-3529Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We introduce a variant of the multi-vehicle routing problem which accounts for nonholonomic constraints and dense, dynamic obstacles, called MVRP-DDO. The problem is strongly motivated by an industrial mining application. This paper illustrates how MVRP-DDO relates to other extensions of the vehicle routing problem. We provide an application-independent formulation of MVRP-DDO, as well as a concrete instantiation in a surface mining application. We propose a multi-abstraction search approach to compute an executable plan for the drilling operations of several machines in a very constrained environment. The approach is evaluated in terms of makespan and computation time, both of which are hard industrial requirements.

    Fulltekst (pdf)
    Multi Vehicle Routing with Nonholonomic Constraints and Dense Dynamic Obstacles
  • 77.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    A robot sets a table: a case for hybrid reasoning with different types of knowledge2016Inngår i: Journal of experimental and theoretical artificial intelligence (Print), ISSN 0952-813X, E-ISSN 1362-3079, Vol. 28, nr 5, s. 801-821Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An important contribution of AI to Robotics is the model-centred approach, whereby competent robot behaviour stems from automated reasoning in models of the world which can be changed to suit different environments, physical capabilities and tasks. However models need to capture diverse (and often application-dependent) aspects of the robot's environment and capabilities. They must also have good computational properties, as robots need to reason while they act in response to perceived context. In this article, we investigate the use of a meta-CSP-based technique to interleave reasoning in diverse knowledge types. We reify the approach through a robotic waiter case study, for which a particular selection of spatial, temporal, resource and action KR formalisms is made. Using this case study, we discuss general principles pertaining to the selection of appropriate KR formalisms and jointly reasoning about them. The resulting integration is evaluated both formally and experimentally on real and simulated robotic platforms.

  • 78.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    A representation for spatial reasoning in robotic planning2013Inngår i: IROS 2013, IEEE, 2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In order to close the sense-plan-act loop, a robotrequires several capabilities: it must match perceived contextwith general knowledge about the environment, instantiateplans into the metric space of the real world, and detectand react to contingencies. All of these capabilities includesome form of spatial reasoning — however, at different levelsof abstraction. Perception generates metric spatial knowledge,while general knowledge about the environment is often quali-tative in nature. Similarly, plans may call for the achievementof qualitative spatial relations, but actions must be preciselyinstantiated in metric space. This paper focuses on integratingqualitative and metric spatial reasoning for closing the looparound perception and actuation. We propose a knowledgerepresentation and reasoning technique, grounded on well-established spatial calculi, for combining qualitative and metricknowledge and obtaining solutions expressed in actionablemetric terms.

    Fulltekst (pdf)
    fulltext
  • 79.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Including qualitative spatial knowledge in the sense-plan-act loop2013Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper we present ongoing work on integrating qualitative andmetric spatial reasoning into planning for robots. We propose a knowledge repre-sentation and reasoning technique, grounded on well-established constraint-basedspatial calculi, for combining qualitative and metric knowledge and obtainingplans expressed in actionable metric terms.

    Fulltekst (pdf)
    fulltext
  • 80.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    More Knowledge on the Table:Planning with Space, Time and Resources for Robots2014Inngår i: 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE conference proceedings, 2014, s. 647-654Konferansepaper (Fagfellevurdert)
    Abstract [en]

    AI-based solutions for robot planning have so farfocused on very high-level abstractions of robot capabilitiesand of the environment in which they operate. However, tobe useful in a robotic context, the model provided to an AIplanner should afford both symbolic and metric constructs;its expressiveness should not hinder computational efficiency;and it should include causal, spatial, temporal and resourceaspects of the domain. We propose a planner grounded onwell-founded constraint-based calculi that adhere to theserequirements. A proof of completeness is provided, and theflexibility and portability of the approach is validated throughseveral experiments on real and simulated robot platforms.

    Fulltekst (pdf)
    fulltext
  • 81.
    Mansouri, Masoumeh
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Maintaining timelines with hybrid fuzzy context inference2012Inngår i: PSTL 2012: proceedings of the workshop on planning and scheduling with timelines / [ed] Gérard Verfaillie, Roman Barták, 2012, s. 40-47Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Timelines allow to represent temporally-rich informa-tion about plans as well as the current execution statusof plans. Recent work has addressed the related issueof inferring timelines representing contextual informa-tion — often useful for informing planning and/or planexecution monitoring processes. The present article ad-dresses the particular issue of inferring context fromgiven models of how observations relate to context,and representing this context on timelines. We strive toabandon assumptions currently made on context recog-nition, namely that hypotheses are either confirmed ordisproved. We propose a technique which allows to ac-cept the inferred context on a timeline with a degree ofpossibility. The approach is based on fuzzy constraintreasoning, and captures two sources of uncertainty: un-certainty in the model that is used to infer context, anduncertainty in the observations. We also formulate theproblem of searching for the most likely timeline as aConstraint Optimization Problem.

    Fulltekst (pdf)
    fulltext
  • 82.
    Mansouri, Masoumeh
    et al.
    Intelligent Robotics Lab, School of Computer Science, University of Birmingham, Birmingham, United Kingdom.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Schüller, Peter
    Knowledge-Based Systems Group, TU Wien, Vienna, Austria.
    Combining Task and Motion Planning: Challenges and Guidelines2021Inngår i: Frontiers in Robotics and AI, E-ISSN 2296-9144, Vol. 8, artikkel-id 637888Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can exist. Many aspects of the domain, as well as operational requirements, have an effect on how algorithms and representations are designed. Frequently, trade-offs have to be madet o build a system that is effective. We propose five research questions that we believe need to be answered to solve real-world problems that involve combined TAMP. We show which decisions and trade-offs should be made with respect to these research questions, and illustrate these on examples of existing application domains. By doing so, this article aims to provide a guideline for designing combined TAMP solutions that are adequate and effective in the target scenario.

  • 83.
    Menicatti, Roberto
    et al.
    University of Genova, Genova, Italy.
    Recchiuto, Carmine Tommaso
    University of Genova, Genova, Italy.
    Bruno, Barbara
    University of Genova, Genova, Italy.
    Zaccaria, Renato
    University of Genova, Genova, Italy.
    Khaliq, Ali Abdul
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Köckemann, Uwe
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Bui, Ha-Duong
    Japan Advanced Institute of Science and Technology, Japan .
    Chong, Nak Young
    Japan Advanced Institute of Science and Technology.
    Lim, Yuto
    Japan Advanced Institute of Science and Technology, Japan.
    Pham, Van Cu
    Japan Advanced Institute of Science and Technology, Japan.
    Tuyen, Nguyen Tan Viet
    Japan Advanced Institute of Science and Technology, Japan.
    Melo, Nicholas
    Chubu University, Japan.
    Lee, Jaeryoung
    Chubu University, Japan.
    Busy, Maxime
    Softbank Robotics Europe, Paris, France.
    Lagrue, Edouard
    Softbank Robotics Europe, Paris, France.
    Montanier, Jean–Marc
    Softbank Robotics Europe, Paris, France.
    Pandey, Amit Kumar
    Softbank Robotics Europe, Paris, France.
    Sgorbissa, Antonio
    University of Genova, Genova, Italy.
    Collaborative Development Within a Social Robotic, Multi-Disciplinary Effort: the CARESSES Case Study2018Inngår i: 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), IEEE, 2018, s. 117-124Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In many cases, complex multidisciplinary research projects may show a lack of coordinated development and integration, and a big effort is often required in the final phase of the projects in order to merge software developed by heterogeneous research groups. This is particularly true in advanced robotic projects: the objective here is to deliver a system that integrates all the hardware and software components, is capable of autonomous behaviour, and needs to be deployed in real-world scenarios toward providing an impact on future research and, ultimately, on society. On the other hand, in recent years there has been a growing interest for techniques related to software integration, but these have been mostly applied to the IT commercial domain.

    This paper presents the work performed in the context of the project CARESSES, a multidisciplinary research project focusing on socially assistive robotics that involves 9 partners from the EU and Japan. Given the complexity of the project, a huge importance has been placed on software integration, task planning and architecture definition since the first stages of the work: to this aim, some of the practices commonly used in the commercial domain for software integration, such as merging software from the early stage, have been applied. As a case study, the document describes the steps which have been followed in the first year of the project discussing strengths and weaknesses of this approach.

  • 84.
    Molina, Sergi
    et al.
    University of Lincoln, Lincoln, U.K.
    Mannucci, Anna
    Robert Bosch GmbH, Renningen, Germany.
    Magnusson, Martin
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Adolfsson, Daniel
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Andreasson, Henrik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Hamad, Mazin
    Technical University of Munich, Munich, Germany.
    Abdolshah, Saeed
    Technical University of Munich, Munich, Germany.
    Chadalavada, Ravi Teja
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Palmieri, Luigi
    Robert Bosch GmbH, Renningen, Germany.
    Linder, Timm
    Robert Bosch GmbH, Renningen, Germany.
    Swaminathan, Chittaranjan Srinivas
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Kucner, Tomasz Piotr
    Aalto University, Aalto, Finland.
    Hanheide, Marc
    University of Lincoln, Lincoln, U.K..
    Fernandez-Carmona, Manuel
    University of Lincoln, Lincoln, U.K..
    Cielniak, Grzegorz
    University of Lincoln, Lincoln, U.K..
    Duckett, Tom
    University of Lincoln, Lincoln, U.K..
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Bokesand, Simon
    Kollmorgen Automation AB, Mölndal, Sweden.
    Arras, Kai O.
    Robert Bosch GmbH, Renningen, Germany.
    Haddadin, Sami
    Technical University of Munich, Munich, Germany.
    Lilienthal, Achim J
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    The ILIAD Safety Stack: Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots2023Inngår i: IEEE robotics & automation magazine, ISSN 1070-9932, E-ISSN 1558-223XArtikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Current intralogistics services require keeping up with e-commerce demands, reducing delivery times and waste, and increasing overall flexibility. As a consequence, the use of automated guided vehicles (AGVs) and, more recently, autonomous mobile robots (AMRs) for logistics operations is steadily increasing.

  • 85.
    Palleschi, Alessandro
    et al.
    Dipartimento di Ingegneria dell’Informazione and Research Center “E.Piaggio”, University of Pisa, Pisa, Italy.
    Mannucci, Anna
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Caporale, Danilo
    Dipartimento di Ingegneria dell’Informazione and Research Center “E.Piaggio”, University of Pisa, Pisa, Italy.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Pallottino, Lucia
    Dipartimento di Ingegneria dell’Informazione and Research Center “E.Piaggio”, University of Pisa, Pisa, Italy.
    Toward distributed solutions for heterogeneous fleet coordination2020Inngår i: Proceedings of the 2nd Italian Conference on Robotics and Intelligent Machines, 2020Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Warehouse mobile robotics is nowadays entering the mass-production market. Increasing the number of mobile robots up to decades raises new challenges: current industrial practice relies on centralized fleet management, which might hinder efficacy in the case of large fleets. This paper proposes and discusses a partially and a fully distributed extension of a centralized loosely coupled algorithm for multi-robot coordination. In particular, we aim at investigating: 1) how coordination can be distributed among robots, and 2) which is the minimum amount of local information required to enforce safety. Simulation results show that a partial distribution may improve performance in terms of arrival times while preserving safety and liveness.

  • 86.
    Pecora, Federico
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Is Model-Based Robot Programming a Mirage?: A Brief Survey of AI Reasoning in Robotics2014Inngår i: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 28, nr 4, s. 255-261Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Researchers in AI and Robotics have in common the desire to “make robots intelligent”, evidence of which can be traced back to the earliest AI systems. One major contribution of AI to Robotics is the model-centered approach, whereby intelligence is the result of reasoning in models of the world which can be changed to suit different environments, physical capabilities, and tasks. Dually, robots have contributed to the formulation and resolution of challenging issues in AI, and are constantly eroding the modeling abstractions underlying AI problem solving techniques. Forty-eight years after the first AI-driven robot, this article provides an updated perspective on the successes and challenges which lie at the intersection of AI and Robotics.

  • 87.
    Pecora, Federico
    University of Rome, “La Sapienza”, Rome, Italy.
    Multi-Agent Planning and Coordination Under Resource Constraints2007Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    The research described in this thesis stems from ROBOCARE1, a three year research project aimed at developing software and robotic technology for providing intelligent support for elderly people. This thesis deals with two problems which have emerged in the course of the project’s development:

    Multi-agent coordination with scarce resources. Multi-agent planning is concerned with automatically devising plans or strategies for the coordinated enactment of concurrently executing agents. A common realistic constraint in applications which require the coordination of multiple agents is the scarcity of resources for execution. In these cases, concurrency is affected by limited capacity resources, the presence of which modifies the structure of the planning/coordination problem. Specifically, the first part of this thesis tackles this problem in two contexts, namely when planning is carried out centrally (planning from first principles), and in the context of distributed multi-agent coordination.

    Domain modeling for scheduling applications. It is often the case that the products of research in AI problem solving are employed to develop applications for supporting human decision processes. Our experience in ROBOCARE as well as other domains has often called for the customization of prototypical software for real applications. Yet the gap between what is often a research prototype and a complete decision support system is seldom easy to bridge.The second part of the thesis focuses on this issue from the point of view of scheduling software deployment.Overall, this thesis presents three contributions within the two problems mentioned above. First, we address the issue of planning in concurrent domains in which the complexity of coordination is dominated by resource constraints. To this end, an integrated planning and scheduling architecture is presented and employed to explore the structural trademarks of multi-agent coordination problems in function of their resource-related characteristics. Theoretical and experimental analyses are carried out revealing which planning strategies are most fit for achieving plans which prescribe efficient coordination subject to scarce resources.We then turn our attention to distributed multi-agent coordination techniques (specifically, a distributed constraint optimization (DCOP) reduction of the coordination problem). Again, we consider the issue of achieving coordinated action in the presence of limited resources. Specifically, resource constraints impose n-ary relations among tasks. In addition, as the number of n-ary relations due to resource contention are exponential in the size of the problem, they cannot be extensionally represented in the DCOP representation of the coordination problem. Thus, we propose an algorithm for DCOP which retains the capability to dynamically post n-ary constraints during problem resolution in order to guarantee resource-feasible solutions. Although the approach is motivated by the multi-agent coordination problem, the algorithm is employed to realize a general architecture for n-ary constraint reasoning and posting.Third, we focus on a somewhat separate issue stemming from ROBOCARE, namely a software engineering methodology for facilitating the process of customizing scheduling components in real-world applications. This work is motivated by the strong applicative requirements of ROBOCARE. We propose a software engineering methodology specific to scheduling technology development. Our experience in ROBOCARE as well as other application scenarios has fostered the development of a modeling framework which subsumes the process of component customization for scheduling applications. The framework aims to minimize the effort involved in deploying automated reasoning technology in practise, and is grounded on the use of a modeling language for defining how domain-level concepts are grounded into elements of a technology-specific scheduling ontology.

    Fulltekst (pdf)
    fulltext
  • 88.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Andreasson, Henrik
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Mansouri, Masoumeh
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Petkov, Vilian
    Technical University of Varna, Varna, Bulgaria.
    A Loosely-Coupled Approach for Multi-Robot Coordination, Motion Planning and Control, ICAPS2018Inngår i: Proceedings of the International Conference on Automated Planning and Scheduling / [ed] Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan, Delft, The Netherlands: AAAI Press, 2018, Vol. 2018-June, s. 485-493, artikkel-id 139850Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Deploying fleets of autonomous robots in real-world applications requires addressing three problems: motion planning, coordination, and control. Application-specific features of the environment and robots often narrow down the possible motion planning and control methods that can be used. This paper proposes a lightweight coordination method that implements a high-level controller for a fleet of potentially heterogeneous robots. Very few assumptions are made on robot controllers, which are required only to be able to accept set point updates and to report their current state. The approach can be used with any motion planning method for computing kinematically-feasible paths. Coordination uses heuristics to update priorities while robots are in motion, and a simple model of robot dynamics to guarantee dynamic feasibility. The approach avoids a priori discretization of the environment or of robot paths, allowing robots to “follow each other” through critical sections. We validate the method formally and experimentally with different motion planners and robot controllers, in simulation and with real robots.

  • 89.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för teknik.
    Cesta, Amedeo
    Dcop for smart homes: a case study2007Inngår i: Computational intelligence, ISSN 0824-7935, E-ISSN 1467-8640, Vol. 23, nr 4, s. 395-419Artikkel i tidsskrift (Fagfellevurdert)
  • 90.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för teknik.
    Cesta, Amedeo
    Evaluating plans through restrictiveness and resource strength2005Inngår i: Proceedings of Workshop on Integrating Planning into Scheduling (WIPIS) at ICAPS'05, 2005Konferansepaper (Fagfellevurdert)
  • 91.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för teknik.
    Cesta, Amedeo
    Planning and scheduling ingredients for a multi-agent system2002Inngår i: Proceedings of UK Planning and Scheduling SIG (PlanSig'02), 2002Konferansepaper (Fagfellevurdert)
  • 92.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Cesta, Amedeo
    The role of different solvers in planning and scheduling integration2003Inngår i: AI*IA 2003: Advances in Artificial Intelligence, Springer Berlin/Heidelberg, 2003, Vol. 2829, s. 362-374Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper attempts to analyze the issue of planning and scheduling integration from the point of view of information sharing. This concept is the basic bridging factor between the two realms of problem solving. In fact, the exchange of each solver’s point of view on the problem to be solved allows for a synergetic effort in the process of searching the space of states. In this work, we show how different solving strategies cooperate in this process by varying the degree of integration of the combined procedure. In particular, the analysis exposes the advantage of propagating sets of partial plans rather than reasoning on sequential state space representations. Also, we show how this is beneficial both to a component-based approach (in which information sharing occurs only once) and to more interleaved forms of integration.

  • 93.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Cirillo, Marcello
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    A constraint-based approach for multiple non-holonomic vehicle coordination in industrial scenarios2012Inngår i: ICAPS 2012 Workshop on Combining Task and Motion Planning for Real-World Applications, 2012, s. 45-52Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Autonomous vehicles are already widely used in industrial logisticsettings. However,  applications still lack flexibility, andmany steps of the deployment process are hand-crafted byspecialists. Here, we preset a new, modular paradigm whichcan fully solve logistic problems for AGVs, from high-leveltask planning to vehicle control. In particular, we focus ona new method for multi-robot coordination which does notrely on pre-defined traffic rules and in which feasible andcollision-free trajectories are calculated for every vehicle accordingto mission specifications. Also, our solutions canbe adapted on-line to exogenous events, control failures, orchanges in mission requirements.

    Fulltekst (pdf)
    fulltext
  • 94.
    Pecora, Federico
    et al.
    Örebro universitet, Akademin för naturvetenskap och teknik.
    Cirillo, Marcello
    Örebro universitet, Akademin för naturvetenskap och teknik.
    A Constraint-Based Approach for Plan Management in Intelligent Environments2009Inngår i: Proc of the Workshop on Scheduling and Planning Applications (at ICAPS-09). Thessaloniki, Greece., 2009Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper we address the problem of realizing a service-providing reasoning infrastructure for proactive human assistance in intelligent environments. We propose SAM, an architecture which leverages temporal knowledge represented as relations in Allen’s interval algebra and constraint-based temporal planning techniques. SAM seamlessly combines two key capabilities for contextualized service provision, namely human activity recognition and planning for controlling pervasive actuation devices.

    Fulltekst (pdf)
    FULLTEXT01
  • 95.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Cirillo, Marcello
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Dell’Osa, Francesca
    Centre for Applied Autonomous Sensor Systems ( AASS ).
    Ullberg, Jonas
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    A constraint-based approach for proactive, context-aware human support2012Inngår i: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, E-ISSN 1876-1372, Vol. 4, nr 4, s. 347-367Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this article we address the problem of realizing a service-providing reasoning infrastructure for pro-active humanassistance in intelligent environments. We propose SAM, an architecture which leverages temporal knowledge represented asrelations in Allen’s interval algebra and constraint-based temporal planning techniques. SAM provides two key capabilities forcontextualized service provision: human activity recognition and planning for controlling pervasive actuation devices. Whiledrawing inspiration from several state-of-the-art approaches, SAM provides a unique feature which has thus far not been addressedin the literature, namely the seamless integration of these two key capabilities. It does so by leveraging a constraint-basedreasoning paradigm whereby both requirements for recognition and for planning/execution are represented as constraints andreasoned upon continuously.

  • 96.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Cirillo, Marcello
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Dimitrov, Dimitar
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    On mission-dependent coordination of multiple vehicles under spatial and temporal constraints2012Inngår i: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2012, s. 5262-5269Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Coordinating multiple autonomous ground vehicles is paramount to many industrial applications. Vehicle trajectories must take into account temporal and spatial requirements, e : g :; usage of floor space and deadlines on task execution. In this paper we present an approach to obtain sets of alternative execution patterns (called trajectory envelopes) which satisfy these requirements and are conflict-free. The approach consists of multiple constraint solvers which progressively refine trajectory envelopes according to mission requirements. The approach leverages the notion of least commitment to obtain easily revisable trajectories for execution.

  • 97.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Mansouri, Masoumeh
    School of Computer Science, University of Birmingham, Birmingham, UK.
    Hawes, Nick
    Oxford Robotics Institute, Department of Engineering Science, University of Oxford, Oxford, UK.
    Kunze, Lars
    Oxford Robotics Institute, Department of Engineering Science, University of Oxford, Oxford, UK.
    Special Issue on Reintegrating Artificial Intelligence and Robotics2019Inngår i: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 33, nr 4, s. 315-317Artikkel i tidsskrift (Annet vitenskapelig)
  • 98.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för teknik.
    Modi, Jay P.
    Scerri, Paul
    Reasoning about and dynamically posting n-ary constraints in ADOPT2006Inngår i: Proceedings of Workshop on Distributed Constraint Reasoning (DCR) at AAMAS'06, 2006Konferansepaper (Annet vitenskapelig)
  • 99.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för naturvetenskap och teknik.
    Rasconi, Ricardo
    Cortellessa, Gabriella
    Cesta, Amedeo
    User-oriented problem abstractions in scheduling: customization and reuse in scheduling software architectures2006Inngår i: Innovations in Systems and Software Engineering, ISSN 1614-5046, Vol. 2, nr 1, s. 1-16Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper we describe a modeling framework aimed at facilitating the customization and deployment of artificial intelligence (AI) scheduling technology in real-world contexts. Specifically, we describe an architecture aimed at facilitating software product line development in the context of scheduling systems. The framework is based on two layers of abstraction: a first layer providing an interface with the scheduling technology, on top of which we define a formalism to abstract domain-specific concepts. We show how this two-layer modeling framework provides a versatile formalism for defining user-oriented problem abstractions, which is pivotal for facilitating interaction between domain experts and technologists. Moreover, we describe a graphical user interface (GUI)-enhanced tool which allows the domain expert to interact with the underlying core scheduling technology in domain-specific terms. This is achieved by automatically instantiating an abstract GUI template on top of the second modeling layer.

  • 100.
    Pecora, Federico
    et al.
    Örebro universitet, Institutionen för teknik.
    Rasconi, Riccardo
    Cesta, Amedeo
    Assessing the bias of classical planning strategies on makespan-optimizing scheduling2004Inngår i: Proceedings of the European Conference on Artificial Intelligence (ECAI), 2004Konferansepaper (Fagfellevurdert)
123 51 - 100 of 125
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf