3,100 research outputs found

    Intensity-based image registration using multiple distributed agents

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    Image registration is the process of geometrically aligning images taken from different sensors, viewpoints or instances in time. It plays a key role in the detection of defects or anomalies for automated visual inspection. A multiagent distributed blackboard system has been developed for intensity-based image registration. The images are divided into segments and allocated to agents on separate processors, allowing parallel computation of a similarity metric that measures the degree of likeness between reference and sensed images after the application of a transform. The need for a dedicated control module is removed by coordination of agents via the blackboard. Tests show that additional agents increase speed, provided the communication capacity of the blackboard is not saturated. The success of the approach in achieving registration, despite significant misalignment of the original images, is demonstrated in the detection of manufacturing defects on screen-printed plastic bottles and printed circuit boards

    Engineering environment-mediated coordination via nature-inspired laws

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    SAPERE is a general multiagent framework to support the development of self-organizing pervasive computing services. One of the key aspects of the SAPERE approach is to have all interactions between agents take place in an indirect way, via a shared spatial environment. In such environment, a set of nature-inspired coordination laws have been defined to rule the coordination activities of the application agents and promote the provisioning of adaptive and self-organizing services

    Location-dependent services for mobile users

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    Abstract—One of the main issues in mobile services ’ research (M-service) is supporting M-service availability, regardless of the user’s context (physical location, device employed, etc.). However, most scenarios also require the enforcement of context-awareness, to dynamically adapt M-services depending on the context in which they are requested. In this paper, we focus on the problem of adapting M-services depending on the users ’ location, whether physical (in space) or logical (within a specific distributed group/application). To this end, we propose a framework to model users ’ location via a multiplicity of local and active service contexts. First, service contexts represent the mean to access to M-services available within a physical locality. This leads to an intrinsic dependency of M-service on the users’ physical location. Second, the execution of service contexts can be tuned depending on who is requesting what M-service. This enables adapting M-services to the logical location of users (e.g., a request can lead to different executions for users belonging to different groups/applications). The paper firstly describes the framework in general terms, showing how it can facilitate the design of distributed applications involving mobile users as well as mobile agents. Then, it shows how the MARS coordination middleware, implementing service contexts in terms of programmable tuple spaces, can be used to develop and deploy applications and M-services coherently with the above framework. A case study is introduced and discussed through the paper to clarify our approach and to show its effectiveness. Index Terms—Context-awareness, coordination infrastructures, M-services, mobility, multiagent systems. I

    Engineering Agent Systems for Decision Support

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    This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain

    Management and Control of Domestic Smart Grid Technology

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    Emerging new technologies like distributed generation, distributed storage, and demand-side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption, and storage techniques, a more energy-efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a virtual power plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved.\ud \u

    Towards adaptive multi-robot systems: self-organization and self-adaptation

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    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
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