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CoCoRo

Financiado

Cerrado

Collective Cognitive Robots

This ambitious project aims at creating a swarm of interacting, cognitive, autonomous robots. We will develop a swarm of autonomous underwater vehicles (AUVs) that are able to interact with each other and which can balance tasks (... ver más

30/09/2014

UNI GRAZ

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

UNIVERSITAET GRAZ No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 5 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2014-09-30 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

5 Participantes

UNI GRAZ

0.00€ | Lider

SSSA

N.D. | Participante

UNIVERSITY OF YORK

N.D. | Participante

USTUTT

N.D. | Participante

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Líder del proyecto

UNIVERSITAET GRAZ No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto This ambitious project aims at creating a swarm of interacting, cognitive, autonomous robots. We will develop a swarm of autonomous underwater vehicles (AUVs) that are able to interact with each other and which can balance tasks (interactions between/within swarms). These tasks are: ecological monitoring, searching, maintaining, exploring and harvesting resources in underwater habitats. The swarm will maintain swarm integrity under conditions of dynamically changing environments and will therefore require robustness and flexibility. This will be achieved by letting the AUVs interact with each other and exchange information, resulting in a cognitive system that is aware of its environment, of local individual goals and threats and of global swarm-level goals and threats. Our consortium consists of both, biological and technical institutions and is therefore optimally qualified to achieve this goal.By a combination of locally acting and globally acting self-organizing mechanisms, information from the global level flows into the local level and influences the behaviour of individual AUVs. Such a cognitive-based scheme creates a very fast reaction of the whole collective system when optimizing the global performance. As shown by natural swimming fish swarms, such mechanisms are also flexible and scalable. The usage of cognition-generating algorithms can even allow robotic swarms to mimic each other's behaviour and to learn from each other adequate reactions to environmental changes. In addition, we plan to investigate the emergence of artificial collective pre-consciousness, which leads to self-identification and further improvement of collective performance. In this way we explore several general principles of swarm-level cognition and can assess their importance in real-world applications. This can be exploited for improving the robustness, flexibility and efficiency of other technical applications in the field of ICT.

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