In view of the current intelligent mobile robot in the tracking process due to the target shape on the changes in a loss of tracking target, using the Caffe deep learning framework and ROS robot operating system as a development platform, a high accuracy and high real-time target tracking system of mobile robots is designed for research. The GOTURN target tracking algorithm based on the twin convolutional neural network, which is robust to target deformation, viewing angle, slight occlusion and illumination changes is used, and the ROS system is used as a bridge to enable the offline training tracking model to be applied to the TurtleBot mobile robot in real time, also a detailed test is carried out. Experimental results show that the target tracking system is not only feasible in design, but also has the characteristics of low cost, high performance and easy expansion.