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In this paper, we introduce an intrinsically parallel framework striving for increased flexibility in development of robotic, computer vision, and machine intelligence applications. The primary goal is to provide a sound and easy-to-use, but yet efficient base architecture for complex sensor-based robotic systems with focus on industrial scenarios. The framework combines promising ideas of recent neuroscientific research with a blackboard information storage mechanism and an implementation of the multi-agent paradigm. Additionally, a generic set of tools for realtime data acquisition and robot control, integration of external software components, and user interaction is provided. The paper is completed with a tutorial section showing how the building blocks afore described can be composed to applications of increasing complexity.
Date of Conference: 14-17 March 2010