Robotics Group

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and non-functional properties provided by formal methods and the flexibility, low management overhead, and optimal
 
and non-functional properties provided by formal methods and the flexibility, low management overhead, and optimal
 
utilization of resources promised by autonomic, adaptive, self-aware systems.
 
utilization of resources promised by autonomic, adaptive, self-aware systems.
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[http://www.ascens-ist.eu/ Read more about ASCENS]
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Revision as of 17:37, 8 October 2012

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E-SWARM is a project funded by the European Research Council - Advanced Grants program of the European Union (Grant 246939). The main case studies have been chosen in the domains of optimization and robotics. In the robotics case study, we study the use of swarm intelligence as a tool to develop controllers for swarms of cooperating robots. The principles of swarm intelligence are employed in swarm robotics for the design of robot controllers at the individual level so as to obtain effective swarm-level behavioral strategies. We will focus on swarm behaviors characterized by the coordination and cooperation of the members of a group of robots to accomplish tasks that are beyond the capabilities of a single robot.

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The main goal of the project is the study of hierarchical communication and control strategies for swarms of heterogeneous robots, which, despite the differences among sub-groups, coherently operate in an integrated manner to achieve a common goal. This will be achieved by looking at how Nature structures and organises large groups, such as ant colonies or honeybee swarms. Natural systems are characterised by different types of hierarchical organisation (physical, spatial, functional, informational) which evolved to be tightly integrated and to ensure the survival of the system as a single unit. The H2SWARM project aims at studying the evolution of cooperative behaviours in hierarchical heterogeneous organisations, and the mechanisms that support hierarchical organisations in social insects.

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Self-aware, self-adaptive and self-expressive autonomic components, running within environments which are called “ensembles”, have been proposed to handle open-ended, highly parallel, massively distributed systems that can span millions of nodes with complex interactions and behaviours. However, these complex systems are currently difficult to develop, deploy, and manage. The goal of the ASCENS project is to build ensembles in a way that combines the maturity and wide applicability of traditional software engineering approaches with the assurance about functional and non-functional properties provided by formal methods and the flexibility, low management overhead, and optimal utilization of resources promised by autonomic, adaptive, self-aware systems.

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