Abstract: A moving object tracking approach for a quadrupedal robot based on a Siamese network comprises an RNN-based object detector for locating moving objects. The position information of moving objects is sent into a ResNet-based feature extractor. For regressing bounding boxes of a target object, a Siamese adaptive network is employed. Experimental results on several public benchmarks show that this approach achieves excellent VOT performances, e.g., it obtains EAO score by 0.452 points, Accuracy score by 0.592 points, and Robustness score by 0.155 points on public benchmark VOT2018. it is successfully used on a quadrupedal robot, which can accurately track a specific moving object in real-world complicated scenes.