Abstract
This chapter contains many applications of homeokinetic learning to high-dimensional robotic systems. The examples chosen for investigation and proposed as experiments to the reader comprise various robots ranging from dog-like, to snake-like up to humanoid robots in different environmental situations. The aim of the experiments is to understand how the controller can learn to “feel” the specific physical properties of the body in its environment and manages to get in a kind of functional resonance with the physical system. In order to better bring out the characteristics of homeokinetic learning in these systems, we use a kind of physical scaffolding, for instance suspending the Humanoid like a bungee jumper, putting it in the Rhoenrad, or hanging it at the high bar. Interestingly, in all situations the robots develop whole-body motion patterns that seemingly are related to the specific environmental situation: the Dog starts playing with a barrier eventually jumping or climbing over it; the Snake develops coiling and jumping modes; we observe emerging climbing behaviors of a Humanoid like trying to get out of a pit; and wrestling like scenarios if a Humanoid is encountering a companion. Eventually, in our robotic zoo all kinds of robots are brought together so that homeokinesis can prove its robustness against heavy interactions with other robots or dynamical objects. Essentially this chapter provides a phenomenological overview and invites to play around with numerous simulations to see the “playful machine” in action.
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© 2011 Springer-Verlag Berlin Heidelberg
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Der, R., Martius, G. (2011). High-Dimensional Robotic Systems. In: The Playful Machine. Cognitive Systems Monographs, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20253-7_10
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DOI: https://doi.org/10.1007/978-3-642-20253-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20252-0
Online ISBN: 978-3-642-20253-7
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