About this project
RUBICON will create a self-learning robotic ecology consisting of a network of sensors, effectors and mobile robot devices. This ecology will enable the participating devices to seamlessly operate in order to support applications such as ambient assisted living, security, etc.
Current approaches heavily rely on models of the environment and on human configuration and supervision and lack the ability to smoothly adapt to evolving situations. These limitations make these systems hard and costly to deploy and maintain in real world applications, as they must be tailored to the specific environment and constantly updated to suit changes in both the environments and in the applications where they are deployed. By contrast, a RUBICON ecology will be able to teach itself about its environment and learn to improve the way it carries out different tasks. The ecology will act as a persistent memory and source of intelligence for all its participants and it will exploit the mobility and the better sensing capabilities of the robots to verify and provide the feedback on its own performance.
RUBICON builds upon the existing work on PEIS Ecology performed at the AASS Cognitive Robotic Systems Lab, and goes much beyond that in adding capabilities for learning, adaptation, and goal generation.
RUBICON is a EU FP7 STREP project. The overall budget is about 3,300,000 EUR. The share of Orebro University is about 450,000 EUR.