Reflexes from self-organizing control in autonomous robots

Frank Hesse, Ralf Der, J. Michael Herrmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Homeokinetic learning provides a route to the self-organization of elementary behaviors in autonomous robots by establishing low-level sensomotoric loops. Strength and duration of the internal parameter changes which are caused by the homeokinetic adaptation provide a natural evaluation of external states, which can be used to incorporate information from additional sensory inputs and to extend the function of the low-level behavior to more general situations. We illustrate the approach by two examples, a mobile robot and a human-like hand which are driven by the same low-level scheme, but use the second-order information in different ways to achieve either risk avoidance and unconstrained movement or constrained movement. While the low-level adaptation follows a set of rigid learning rules, the second-order learning exerts a modulatory effect to the elementary behaviors and to the distribution of their inputs.
Original languageEnglish
Title of host publicationProceedings of the Seventh International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems.
EditorsLuc Berthouze, Christopher G. Prince , Michael Littman, Hideki Kozima, Christian Balkenius
PublisherLund University
Number of pages8
Publication statusPublished - 2007


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