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An intelligent mobile robot navigation model based on dynamic approach is constructed, which is integrated both head-for-target behavior and obstacle avoidance behavior. The model is described by nonlinear differential equations. It is based on the stability theory of dynamical system. The weight coefficient of each behavior which represents superiority in competition between behaviors is optimized by genetic algorithm. Navigation of mobile robot based on this model is simulated in computer. And the feasibility of genetic algorithm application for intelligent mobile robot navigation is examined. The results indicate that genetic algorithm integrates well with the dynamic approach for intelligent mobile robot navigating.