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Visual guided AGV realizes position conversion based on identifiers recognition. The Hu moment algorithm is able to extract the feature parameters of characters and, combined with the machine learning classification algorithms, to classify them. The operation speed of Hu moment algorithm is fast, but its recognition accuracy is low. By analyzing its principle formulas, it was found that the large numerical range is due to the high order in formulas, which lead to a poor data closeness. Based on this, the Hu moment formulas were improved and new algorithm was constructed. Through detecting the UCI character database and taking an online testing on AGV, it is proved that the improved Hu moment algorithm can extract the feature faster and improve the accuracy of character classification of machine learning algorithm, indicating that the improved Hu moment algorithm has good practicability in character recognition of visual AGV.