Cognitive Systems and Robotics Self-learning robotic ecology RUBICON will create a self-learning robotic ecology, consisting of a network of sensors, effectors and mobile robot devices. Enabling robots to seamlessly operate as part of these ecologies is an important challenge for robotics R&D, in order to support applications such as ambient assisted living, security and so on. Current approaches heavily rely on models of the environment and on human configuration/supervision and lack the ability to smoothly adapt to evolving situations. RUBICON ecology will be able to teach itself about its environment and learn to improve the way it carries out different tasks. The project will reduce the amount of preparation and pre-programming that robotic and/or wireless sensor network solutions require when they are deployed. In addition, RUBICON ecologies will reduce the need to maintain and re-configure already-deployed systems.
Field of science
- /natural sciences/biological sciences/neurobiology/neuroscience/computational neuroscience
- /natural sciences/biological sciences/ecology
- /engineering and technology/electrical engineering, electronic engineering, information engineering/information engineering/telecommunications/wireless
- /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/robotics
Call for proposal
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