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Collective Cognitive Robots

Description du projet


Cognitive Systems and Robotics

The CoCoRo project aims at developing a swarm of autonomous underwater vehicles (AUVs) that are able to interact with each other and which can balance tasks such as ecological monitoring, searching, maintaining, exploring and harvesting resources in underwater habitats. The swarm will maintain swarm integrity under conditions of dynamically changing environments. 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. This can be exploited for improving the robustness, flexibility and efficiency of other technical applications in the field of ICT.

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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FP7-ICT-2009-6
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Coordinateur

UNIVERSITAET GRAZ
Contribution de l’UE
€ 810 420,00
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