Host: Japan SOciety for Fuzzy Theory and intelligent informatics
Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"
Object identification, classification and modelling in unknown or known environments have become an interesting research topic. In this paper, a fusion algorithm combining fuzzy reasoning and neural network is presented for object classification in mobile robot navigation. The imprecise information generated by sonar range finders are filtered and normalized by using Tsukamoto type fuzzy inference system. Then the filtered range information and the pre-processed image data are fused through a back propagation type feedforward neural network to classify the objects in the world environment. Some experimental results show the effectiveness of the proposed methodology.