摘要
The paper describes results obtained in the development of adaptive fuzzy-neural navigation subsystem for mobile legged robot. In order to keep the motion sufficiently smooth, free of sharp turnings and transversal swings when moving between closely located obstacles, fuzzy rules are updated on-line. To this end, the fuzzy rules are expressed through a layered feed-forward neural network and parameters are updated on line in two steps--the rough and fine updating. That is followed by the description of the learning fault diagnosis using binary neural network based on the Carpenter and Grossbergs＇ adaptive resonance theory.
