[01] Demin Alexander, Institute of Informatics Systems, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.

This paper proposes a learning control system for modular robots with many degrees of freedom. The system is based on cooperative module training, from discovering common monitor rules for all the modules to their subsequent specification in accordance with semantic probabilistic inference approach. Using an interactive 3D-simulator, a series of successful experiments was conducted in teaching the models of snake-like and multiped robots. The results of experiments have shown that the proposed control system model is quite effective and can be used to control complex modular systems with many degrees of freedom.

Control System, Pattern Recognition, Knowledge Discovery, Data Mining

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