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Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community. In order to execute a autonomous driving on outdoors, like street and roads, it is necessary that the vehicle identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of many multi-layer perceptron neural networks(ANN) used for image-based terrain identification. The ANNs differ in image features used in input layer. Experimental tests using a car and a video camera have been conducted in real scenarios to evaluate the proposed approach.