Configuration information acquisition and matching are two important steps in the self-reconfiguring process of self-reconfigurable robots. The process of configuration information acquisition was introduced, and a self-reconfiguring configuration matching strategy based on graded optimization mechanism was proposed. The first-grade optimization was to search common connection between matching scheme and goal configuration. The second-grade optimization, whose object function was constructed in terms of configuration connectivity, was to search common topology according to the results of the first-grade optimization. The entire process of configuration information acquisition and matching was verified by an experiment and genetic algorithm (GA). The result shows the accuracy of the configuration information acquisition and the effectiveness of the configuration matching method.