Abstract
Abstract In this paper a hierarchical control architecture for a six-legged walking machine is presented. The basic components of this architecture are neural networks which are taught in using examples of the control process. It is shown how the basic components “leg control” and “leg coordination” have been implemented by recurrent and feedforward networks respectively. The teaching process and the tests of the walking behaviour have mainly been done in a simulation system. First tests of the leg control on our real walking machine LAURON are also described.
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