To address the issues of low automation in the gait training platform for bipedal robots and the difficulty in coordinating real-time observation of robot walking and status information during gait debugging by a single operator, this paper proposes a stereo vision and pose recognition-based tracking servo system for celestial orbital robots. Firstly, using a stereo camera setup, the left and right camera images are matched to obtain depth information for each pixel. Based on the depth information obtained from the images, the pose of the bipedal robot is recognized, and the depth information of each joint is extracted. The motion state of the bipedal robot is determined based on the joint depth information, and a tracking strategy is formulated for servo control. By introducing pose recognition, a higher level of automation and tracking protection can be achieved based on the changes in the bipedal robot′s pose. Experimental results demonstrate a high level of automation and dynamic tracking performance.