PUB - Publikationen an der Universität Bielefeld

Self-optimization is a concept for mechatronic systems to leave open the choice among system objectives as a degree of freedom until runtime to allow better adaptation to changing system and environment conditions. Demonstration and knowledge transfer of the concept is not easy as the effects of it in mechatronic systems are hard to see in a complex system. To further spread the idea of self-optimization, an intuitive anchor is needed to make it easier to talk about the concept. Also the abstraction from technical details facilitates focusing on the concept. We have developed a multi-agent heterogeneous robotic demonstrator that allows showing the process of self-optimization on a timescale of minutes. The demonstrator decomposes the roles in a mechatronic system to robotic agents. An association between a function and the behavior of the robot is achieved. After having demonstrated the setup for expert and non-expert audiences we have seen the encouraging effect that discussions spin off easily and allow to spread the idea effectively. We present the concept of self-optimization, the behavior-based demonstrator scenario implemented using BeBot miniature and Paderkicker robots in an office environment.