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In regarding to the problem of moving target tracking and crawling, a monocular visual servo system based on ReLU network model is proposed. Firstly, the robot vision system is established for target tracking and feature extraction, and the target state is estimated from the monocular visual model; Then, the ReLU neural network is trained to construct the control strategy of the monocular visual servo system without large computational complexity and multiple solutions to the robot inverse kinematics; Finally, in order to increase the successful rate of crawling, the trajectory of the end effector is planned. The experiment is carried out on the NAO robot platform, and the results show the effectiveness of the method.