oru.sePublikationer
Change search
Refine search result
1 - 22 of 22
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the 'Create feeds' function.
  • 1.
    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, Aalto, 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, Vol. 22, no 1, 64-75 p.Article 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.

  • 2.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Drive the Drive: From Discrete Motion Plans to Smooth Drivable Trajectories2014In: Robotics, E-ISSN 2218-6581, Vol. 3, no 4, 400-416 p.Article in journal (Refereed)
    Abstract [en]

    Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, the discretized nature of these algorithms induces discontinuities in both state and control space of the obtained trajectories, resulting in a mismatch between the achieved and the target end pose of the vehicle. As endpose accuracy is critical for the successful loading and unloading of cargo in typical industrial applications, automatically planned paths have not been widely adopted in commercial AGV systems. The main contribution of this paper is a path smoothing approach, which builds on the output of a lattice-based motion planner to generate smooth drivable trajectories for non-holonomic industrial vehicles. The proposed approach is evaluated in several industrially relevant scenarios and found to be both fast (less than 2 s per vehicle trajectory) and accurate (end-point pose errors below 0.01 m in translation and 0.005 radians in orientation).

  • 3.
    Andreasson, Henrik
    et al.
    Örebro University, School of Science and Technology.
    Saarinen, Jari
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology. SCANIA AB, Södertälje, Sweden.
    Stoyanov, Todor
    Örebro University, School of Science and Technology.
    Lilienthal, Achim
    Örebro University, School of Science and Technology.
    Fast, continuous state path smoothing to improve navigation accuracy2015In: IEEE International Conference on Robotics and Automation (ICRA), 2015, IEEE Computer Society, 2015, 662-669 p.Conference paper (Refereed)
    Abstract [en]

    Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, the discretized nature of these algorithms induces discontinuities in both state and control space of the obtained trajectories, resulting in a mismatch between the achieved and the target end pose of the vehicle. As endpose accuracy is critical for the successful loading and unloading of cargo in typical industrial applications, automatically planned paths have not be widely adopted in commercial AGV systems. The main contribution of this paper addresses this shortcoming by introducing a path smoothing approach, which builds on the output of a lattice-based motion planner to generate smooth drivable trajectories for non-holonomic industrial vehicles. In real world tests presented in this paper we demonstrate that the proposed approach is fast enough for online use (it computes trajectories faster than they can be driven) and highly accurate. In 100 repetitions we achieve mean end-point pose errors below 0.01 meters in translation and 0.002 radians in orientation. Even the maximum errors are very small: only 0.02 meters in translation and 0.008 radians in orientation.

  • 4.
    Arain, Muhammad Asif
    et al.
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology. Scania AB, Granparksvagen 10, SE-15187 Södertälje, Sweden.
    Hernandez Bennetts, Victor
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Efficient Measurement Planning for Remote Gas Sensing with Mobile Robots2015In: 2015 IEEE International Conference on Robotics and Automation (ICRA), Washington, USA: IEEE Computer Society, 2015, 3428-3434 p.Conference paper (Refereed)
    Abstract [en]

    The problem of gas detection is relevant to manyreal-world applications, such as leak detection in industrialsettings and surveillance. In this paper we address the problemof gas detection in large areas with a mobile robotic platformequipped with a remote gas sensor. We propose a novelmethod based on convex relaxation for quickly finding anexploration plan that guarantees a complete coverage of theenvironment. Our method proves to be highly efficient in termsof computational requirements and to provide nearly-optimalsolutions. We validate our approach both in simulation andin real environments, thus demonstrating its applicability toreal-world problems.

  • 5.
    Arain, Muhammad Asif
    et al.
    Örebro University, School of Science and Technology.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Schaffernicht, Erik
    Örebro University, School of Science and Technology.
    Lilienthal, Achim J.
    Örebro University, School of Science and Technology.
    Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor2015In: Sensors, ISSN 1424-8220, Vol. 15, no 3, 6845-6871 p.Article in journal (Refereed)
    Abstract [en]

    The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

  • 6.
    Cirillo, Marcello
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Planning in inhabited environments: human-aware task planning and activity recognition2011In: Künstliche Intelligenz, ISSN 0933-1875, Vol. 25, no 4, 355-358 p.Article in journal (Refereed)
    Abstract [en]

    Our work addresses issues related to the cohabitation of service robots and people in unstructured environments. We propose new planning techniques to empower robot means-end reasoning with the capability of taking into account human intentions and preferences. We also address the problem of human activity recognition in instrumented environments. We employ a constraint-based approach to realize a continuous inference process to attach a meaning to sensor traces as detected by sensors distributed in the environment.

  • 7.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Planning in Inhabited Environments: Human-Aware Task Planning and Activity Recognition2010Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Promised some decades ago by researchers in artificial intelligence and robotics as an imminent breakthrough in our everyday lives, a robotic assistant that could work with us in our home and our workplace is a dream still far from being fulfilled. The work presented in this thesis aims at bringing this future vision a little closer to realization. Here, we start from the assumption that an efficient robotic helper should not impose constraints on users' activities, but rather perform its tasks unobtrusively to fulfill its goals and to facilitate people in achieving their objectives.  Also, the helper should be able to consider the outcome of possible future actions by the human users, to assess how those would affect the environment with respect to the agent's objectives, and to predict when its support will be needed. In this thesis we address two highly interconnected problems that are essential for the cohabitation of people and service robots: robot task planning and human activity recognition. First, we present human-aware planning, that is, our approach to robot high-level symbolic reasoning for plan generation. Human-aware planning can be applied in situations where there is a controllable agent, the robot, whose actions we can plan, and one or more uncontrollable agents, the human users, whose future actions we can only try to predict. In our approach, therefore, the knowledge of the users' current and future activities is an important prerequisite. We define human-aware as a new type of planning problem, we formalize the extensions needed by a classical planner to solve such a problem, and we present the implementation of a planner that satisfies all identified requirements. In this thesis we explore also a second issue, which is a prerequisite to the first one: human activity monitoring in intelligent environments. We adopt a knowledge driven approach to activity recognition, whereby a constraint-based domain description is used to correlate sensor readings to human activities. We validate our solutions to both human-aware planning and activity recognition both theoretically and experimentally, describing a number of explanatory examples and test runs in a real environment.

  • 8.
    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, 52-59 p.Conference 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.

  • 9.
    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, 58-65 p.Conference 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.

  • 10.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Karlsson, Lars
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Human-aware planning for robots embedded in ambient ecologies2012In: Pervasive and Mobile Computing, ISSN 1574-1192, E-ISSN 1873-1589, Vol. 8, no 4, 542-561 p.Article 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.

  • 11.
    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 intelligent systems and technology, ISSN 2157-6904, Vol. 1, no 2, Article 15- p.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.

  • 12.
    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, 172-178 p.Conference 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.

  • 13.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Lanzellotto, Federica
    Roma 3 University, Rome, Italy.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Monitoring domestic activities with temporal constraints and components2009In: Intelligent environments 2009 / [ed] V. Callaghan, A. Kameas, A. Reyes, D. Royo, M. Weber, Amsterdam: IOS Press, 2009, 117-124 p.Conference paper (Refereed)
    Abstract [en]

    Intelligent environments are increasingly rich in ubiquitous sensing capabilities that can be leveraged to know which actions a user is engaged in at any given moment in time. The ability of an intelligent environment to recognize a high-level plan of activities performed by the user in a smart home would allow to construct proactive services, such as reminding, forecasting and providing timely physical support. This article proposes an approach to human activity recognition based on temporal planning. The approach leverages on one hand the ubiquitous sensors provided by the PEIS-Home, a sensor-rich intelligent environment, and, on the other hand, the temporal representation and reasoning capabilities of OMPS, a constraint-based temporal planning and scheduling framework.

  • 14.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Pecora, Federico
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Andreasson, Henrik
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Uras, Tansel
    Department of Computer Science, University of Southern California, USA.
    Koenig, Sven
    Department of Computer Science, University of Southern California, USA.
    Integrated Motion Planning and Coordination for Industrial Vehicles2014In: Proceedings of the 24th International Conference on Automated Planning and Scheduling, 2014Conference paper (Refereed)
    Abstract [en]

    A growing interest in the industrial sector for autonomous ground vehicles has prompted significant investment in fleet management systems. Such systems need to accommodate on-line externally imposed temporal and spatial requirements, and to adhere to them even in the presence of contingencies. Moreover, a fleet management system should ensure correctness, i.e., refuse to commit to requirements that cannot be satisfied. We present an approach to obtain sets of alternative execution patterns (called trajectory envelopes) which provide these guarantees. The approach relies on a constraint-based representation shared among multiple solvers, each of which progressively refines trajectory envelopes following a least commitment principle.

  • 15.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Proactive assistance in ecologies of physically embedded intelligent systems: a constraint-based approach2011In: Handbook of research on ambient intelligence and smart environments: trends and perspectives / [ed] Nak-Young Chong, Fulvio Mastrogiovanni, IGI Global, 2011, 534-557 p.Chapter in book (Refereed)
    Abstract [en]

    The main goal of this Chapter is to introduce SAM, an integrated architecture for concurrent activity recognition, planning and execution. SAM provides a general framework to define how an intelligent environment can assess contextual information from sensory data. The architecture builds upon a temporal reasoning framework operating in closed-loop between physical sensing and actuation components in a smart environments. The capabilities of the system as well as possible examples of its use are discussed in the context of the PEIS-Home, a smart environment integrated with robotic components.

  • 16.
    Cirillo, Marcello
    et al.
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Uras, Tansel
    Department of Computer Science, University of Southern California, USA.
    Koenig, Sven
    Department of Computer Science, University of Southern California, USA.
    A lattice-based approach to multi-robot motion planning for non-holonomic vehicles2014In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014, 232-239 p.Conference paper (Refereed)
    Abstract [en]

    Coordinating fleets of autonomous, non-holonomic vehicles is paramount to many industrial applications. While there exists solutions to efficiently calculate trajectories for individual vehicles, an effective methodology to coordinate their motions and to avoid deadlocks is still missing. Decoupled approaches, where motions are calculated independently for each vehicle and then centrally coordinated for execution, have the means to identify deadlocks, but not to solve all of them. We present a novel approach that overcomes this limitation and that can be used to complement the deficiencies of decoupled solutions with centralized coordination. Here, we formally define an extension of the framework of lattice-based motion planning to multi-robot systems and we validate it experimentally. Our approach can jointly plan for multiple vehicles and it generates kinematically feasible and deadlock-free motions.

  • 17.
    Kumar, T. K. Satish
    et al.
    University of Southern California, Los Angeles, USA.
    Cirillo, Marcello
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Koenig, Sven
    University of Southern California, Los Angeles, USA.
    On the Traveling Salesman Problem with Simple Temporal Constraints2013In: Proceedings of the 10th Symposium on Abstraction, Reformulation, and Approximation (SARA), AAAI Press , 2013Conference paper (Refereed)
    Abstract [en]

    Many real-world applications require the successful combination of spatial and temporal reasoning. In this paper, we study the general framework of the Traveling Salesman Problem with Simple Temporal Constraints. Representationally, this framework subsumes the Traveling Salesman Problem, Simple Temporal Problems, as well as many of the frameworks described in the literature. We analyze the theoretical properties of the combined problem providing strong inapproximability results for the general problem, and positive results for some special cases.

  • 18.
    Kumar, T. K. Satish
    et al.
    University of Southern California, Los Angeles, USA.
    Cirillo, Marcello
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Koenig, Sven
    University of Southern California, Los Angeles, USA.
    Simple Temporal Problems with Taboo Regions2013In: Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI), AAAI Press, 2013Conference paper (Refereed)
    Abstract [en]

    In this paper, we define and study the general framework of Simple Temporal Problems with Taboo regions (STPTs) and show how these problems capture metric temporal reasoning aspects which are common to many real-world applications. STPTs encode simple temporal constraints between events and user-defined taboo regions on the timeline, during which no event is allowed to take place. We discuss two different variants of STPTs. The first one deals with (instantaneous) events, while the second one allows for (durative) processes. We also provide polynomial-time algorithms for solving them. If all events or processes cannot be scheduled outside of the taboo regions, one needs to define and reason about "soft" STPTs. We show that even "soft" STPTs can be solved in polynomial time, using reductions to max-flow problems. The resulting algorithms allow for incremental computations, which is important for the successful application of our approach in real-time domains.

  • 19.
    Pecora, Federico
    et al.
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Cirillo, Marcello
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    A constraint-based approach for multiple non-holonomic vehicle coordination in industrial scenarios2012In: ICAPS 2012 Workshop on Combining Task and Motion Planning for Real-World Applications, 2012, 45-52 p.Conference paper (Refereed)
    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.

  • 20.
    Pecora, Federico
    et al.
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    A Constraint-Based Approach for Plan Management in Intelligent Environments2009In: Proc of the Workshop on Scheduling and Planning Applications (at ICAPS-09). Thessaloniki, Greece., 2009Conference paper (Refereed)
    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.

  • 21.
    Pecora, Federico
    et al.
    Örebro University, School of Science and Technology.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Dell’Osa, Francesca
    Centre for Applied Autonomous Sensor Systems ( AASS ).
    Ullberg, Jonas
    Örebro University, School of Science and Technology.
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    A constraint-based approach for proactive, context-aware human support2012In: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, E-ISSN 1876-1372, Vol. 4, no 4, 347-367 p.Article in journal (Refereed)
    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.

  • 22.
    Pecora, Federico
    et al.
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Cirillo, Marcello
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    Dimitrov, Dimitar
    Örebro University, School of Science and Technology, Örebro University, Sweden.
    On mission-dependent coordination of multiple vehicles under spatial and temporal constraints2012In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2012, 5262-5269 p.Conference paper (Refereed)
    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.

1 - 22 of 22
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf