A generic approach to realtime robot control and parallel processing for industrial scenarios

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.