In order to achieve accurate target tracking in global visual navigation system of automatic guided vehicle（ AGV）

a tracking method for unmarked AGV is proposed. Firstly

the moving target is detected by the frame difference method

and the moving target is tracked by particle filtering. Secondly

motion model for tracking target is established to learn the motion characteristics of target

so as to predict the travel position after the target is lost. Finally

the support vector machine（ SVM） model is used to re-identify the AGV in the prediction region and correct the prediction result of the long short time memory（ LSTM） network to achieve the target duration tracking. Experiments show that this method can better solve the problem of tracking failure due to the high similarity between target occlusion and target.