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1.
  • Broxvall, Mathias, et al. (creator_code:aut_t)
  • Interacting with a robot ecology using task templates
  • 2007
  • record:In_t: 16th IEEE international symposium on robot and human interactive communication, RO-MAN 2007. - New York : IEEE. - 9781424416349 ; , s. 487-492
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • Robot ecologies provide a new paradigm for assistive, service, industrial, and entertainment robotics which is quickly gaining popularity. These ecologies contain a large number of robotic components pervasively embedded in the environment and interacting with each other. Human users of such systems need to be able to interface with both the system as a w hole and, if desired, which each individual component. The humans should be able to transmit, in a natural way, commands that range from basic ones, such as "turn on the lights in the bedroom", to abstract ones, such as "bring me a cup of coffee". Human users may also need to interact with task execution, especially at decision points. In this paper, we introduce an approach to interface a human user to a specific type of robot ecology, called an ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology. The ecology includes simple sensors and actuators and more complicated devices such as mobile robots. The proposed interface satisfies two requirements: 1) to easily and automatically generate component interfaces, and 2) to provide a simple mechanism by which to request and monitor the execution of tasks in the ecology.
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2.
  • Lidén, Mats, 1976-, et al. (creator_code:aut_t)
  • Two- and three-dimensional CT measurements of urinary calculi length and width : a comparative study
  • 2015
  • record:In_t: Acta Radiologica. - : Sage Publications. - 0284-1851 .- 1600-0455. ; 56:4, s. 487-492
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Background: The standard imaging procedure for a patient presenting with renal colic is unenhanced computed tomography (CT). The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on two-dimensional (2D) reformats.Purpose: To develop and validate a calculus oriented three-dimensional (3D) method for measuring the length and width of urinary calculi and to compare the calculus oriented measurements of the length and width with corresponding 2D measurements obtained in axial and coronal reformats.Material and Methods: Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3D symmetric segmentation algorithm was validated against reader size estimations. The calculus oriented size from the segmentation was then compared to the estimated size in axial and coronal 2D reformats.Results: The validation showed 0.1 +/- 0.7mm agreement against reference measure. There was a 0.4mm median bias for 3D estimated calculus length compared to 2D (P < 0.001), but no significant bias for 3D width compared to 2D.Conclusion: The length of a calculus in axial and coronal reformats becomes underestimated compared to 3D if its orientation is not aligned to the image planes. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.
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3.
  • Saffiotti, Alessandro, et al. (creator_code:aut_t)
  • Affordances in an ecology of physically embedded intelligent systems
  • 2008
  • record:In_t: Towards affordance-based robot control. - Berlin : Springer. - 9783540779148 - 9783540779155 ; , s. 106-121
  • swepub:Mat_chapter_t (swepub:level_scientificother_t)abstract
    • The concept of Ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology, combines insights fromthe fields of autonomous robotics and ambient intelligence to provide a new solution to building intelligent robotic systems in the service of people. The concept of PEIS- Ecology also offers an interesting setting to study the applicability of Gibson's notion of affordances to an ecology of robots. In this paper we introduce this concept, and discuss its potential and implications both from an application point of view and from an ecological (Gibsonian) point of view. We also discuss some new scientific challenges introduced by a Peis- Ecology, present our current steps toward its realization, and point at a few experimental results that show the viability of this concept.
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4.
  • Saffiotti, Alessandro, et al. (creator_code:aut_t)
  • The PEIS-ecology project : a progress report
  • 2007
  • record:In_t: Proceedings of the ICRA-07 Workshop on Network Robot Systems. Roma, Italy, 2007. ; , s. 16-22
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • The concept of Ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology, combines insights from the fields of ubiquitous robotics and ambient intelligence to provide a new solution to building intelligent robots in the service of people. While this concept provides great potential, it also presents a number of new scientific challenges. The PEIS-Ecology project is an ongoing collaborative project between Swedish and Korean researchers which addresses these challenges. In this paper we introduce the concept of PEIS-Ecology, discuss its potential and its challenges, and present our current steps toward its realization. We also point to experimental results that show the viability of this concept.
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5.
  • Amato, G., et al. (creator_code:aut_t)
  • Robotic Ubiquitous Cognitive Ecology for Smart Homes
  • 2015
  • record:In_t: Journal of Intelligent and Robotic Systems. - : Springer. - 0921-0296 .- 1573-0409. ; 80, s. S57-S81
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent-based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a proof of concept smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feedback received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work.
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6.
  • Amato, Giuseppe, et al. (creator_code:aut_t)
  • Robotic UBIquitous COgnitive Network
  • 2012
  • record:In_t: Ambient Intelligence. - Berlin, Heidelberg : Springer-Verlag New York. - 9783642287824 - 9783642287831 ; , s. 191-195
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them self-adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The EU FP7 project RUBICON develops self-sustaining learning solutions yielding cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, agent control systems, wireless sensor networks and machine learning. This paper briefly illustrates how these techniques are being extended, integrated, and applied to AAL applications.
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7.
  • Bacciu, D., et al. (creator_code:aut_t)
  • Self-sustaining learning for robotic ecologies
  • 2012
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specificarea, and to channel it to a central processing node for on-line or off-line analysis. The WSN technology,however, can be used for much more ambitious goals. We claim that merging the concepts and technology ofWSN with the concepts and technology of distributed robotics and multi-agent systems can open new waysto design systems able to provide intelligent services in our homes and working places. We also claim thatendowing these systems with learning capabilities can greatly increase their viability and acceptability, bysimplifying design, customization and adaptation to changing user needs. To support these claims, we illus-trate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors,effectors and mobile robots.
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8.
  • Bordignon, Mirko, et al. (creator_code:aut_t)
  • Seamless integration of robots and tiny embedded devices in a PEIS-ecology
  • 2007
  • record:In_t: IEEE/RSJ international  conference on intelligent robots and systems, IROS 2007. - New York : IEEE. - 9781424409129 ; , s. 3101-3106
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • The fields of autonomous robotics and ambient intelligence are converging toward the vision of smart robotic environments, in which tasks are performed via the cooperation of many networked robotic devices. To enable this vision, we need a common communication and cooperation model that can be shared between robotic devices at different scales, ranging from standard mobile robots to tiny embedded devices. Unfortunately, today's robot middlewares are too heavy to run on tiny devices, and middlewares for embedded devices are too simple to support the cooperation models needed by an autonomous smart environment. In this paper, we propose a middleware model which allows the seamless integration of standard robots and simple off-the-shelf embedded devices. Our middleware is suitable for building truly ubiquitous robotics applications, in which devices of very different scales and capabilities can cooperate in a uniform way. We discuss the principles and implementation of our middleware, and show an experiment in which a mobile robot, a commercial mote, and a custom-built mote cooperate in a home service scenario.
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9.
  • Broxvall, Mathias (creator_code:aut_t)
  • A middleware for ecologies of robotic devices
  • 2007
  • record:In_t: Proceedings of the 1st international conference on Robot communication and coordination, RoboComm '07. - Piscataway : IEEE press. - 9789639799080 ; , s. Art no 30-
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • The fields of autonomous robotics and ambient intelligence are converging toward the vision of smart robotic environments, or ubiquitous robotics, in which tasks are performed via the cooperation of many simple networked robotic devices. The concept of Ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology, combines insights from these fields to provide a new solution to building intelligent robots in the service of people. To enable this vision, we need a common communication and cooperation model that allows dynamically assembled ad-hoc networks of robotic devices, a flexible introspection and configuration model allowing automatic (re)configuration and that can be shared between robotic devices at different scales, ranging from standard mobile robots to tiny networked embedded devices. In this paper we discuss the development of a middleware suitable for ubiquitous robotics in general and PEIS-Ecologies in specific. Our middleware is suitable for building truly ubiquitous robotics applications, in which devices of very different scales and capabilities can cooperate in a uniform way. We discuss the principles and implementation of our middleware, and also point to experimental results that show the viability of this concept.
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10.
  • Broxvall, Mathias, et al. (creator_code:aut_t)
  • An ecological approach to odour recognition in intelligent environments
  • 2006
  • record:In_t: 2006 IEEE International Conference on Robotics and automation, ICRA 2006. - 0780395050 ; , s. 2066-2071
  • swepub:Mat_conferencepaper_t (swepub:level_refereed_t)abstract
    • We present a new approach for odour detection and recognition based on a so-called PEIS-Ecology: a network of gas sensors and a mobile robot are integrated in an intelligent environment. The environment can provide information regarding the location of potential odour sources, which is then relayed to a mobile robot equipped with an electronic nose. The robot can then perform a more thorough analysis of the odour character. This is a novel approach which alleviates some the challenges in mobile olfaction techniques by single and embedded mobile robots. The environment also provides contextual information which can be used to constrain the learning of odours, which is shown to improve classification performance.
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