In this paper, we discuss the use of adaptive filters for the control also of complex autonomous robot systems. A concept is presented to solve the resulting problem complexity by merging rule-based approaches with adaptive control, thus balancing a coarsening of the configuration/decision space by the implicit exploitation of former experience, encoded in a history array. Future work will be focussed on the detail evaluation of the approach and its implementation for a climbing robot application.
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