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Terrain classification in forest environment based on combined features from laser range data

This paper conducts research on terrain classification in forest environment based on three dimensional laser ranging data. We choose height, cubic cell hit density and statistic feature of laser range data to form combined classification features. The BP artificial neural network is used as the classifier to get the traversability of forest environment based on combined features. Experiments show that combined features yield better adaptability and rightness than single feature.