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Controlling Autonomous Robots by Adaptive Chaos Control

Prof. Dr. Marc Timme:

 

Higher animals as well as bio-mechanically complex robots face the problem of how to control many sensory modalities with many different yet appropriate behaviors in an autonomous way. Here we present a new type of chaos control that we tailor-made to be both adaptive and applicable in neuron-like systems. It is capable of stabilizing a range of different periods at fixed parameters. We implement this adaptive chaos control to replace the commonly used many central pattern generators (CPGs) with intrinsically periodic dynamics by one CPG that is intrinsically chaotic but is stabilized to a variety of periodic orbits, depending on the sensory input that controls the CPG. We demonstrate by example control of a hexapod robot that this single-CPG approach makes the robot much more versatile than previously achieved and flexible in its choice of behaviors. Moreover, it can easily learn to associate appropriate behaviors to given environmental conditions. We also present the newest trends in theory on adaptive chaos control.

 

Refs.: Nature Physics 6:224 (2010); Nature Physics 6, 161 (2010); Bick, Kolodziejski and Timme (in prep.)

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