Aiming at the 3D measurement and 3D reconstruction of underground pipeline network, a scheme for camera motion estimation and 3D reconstruction of pipeline network based on active stereo omnidirection vision sensor (ASODVS) is presented in this work. A pipe robot equipped with ASODVS travels along the pipeline, obtaining the inpipe panoramic texture images and laser scanning images in real time. The central point of the lasers projected on the inner wall is analyzed and the point cloud data of the pipe crosssection are calculated. Then the panoramic texture images are processed in the following steps. First, the feature points are extracted and matched adopting the SURF algorithm; Second, the wrong matched points are removed using RANSAC method; Third, the motion poses are estimated utilizing the polar geometry principle and optimized with the BA approach; Finally, the point cloud data are converted from the camera coordinate system to the world coordinate system with the motion poses of the camera, completing the 3D reconstruction of the underground pipe network. Experimental results show that the proposed system is capable to estimate the motion poses of the panoramic camera precisely and achieve a realtime 3D reconstruction of the inner pipeline, realizing the synchronization of walking, data acquisition, processing and analysis, 3D modeling for the pipeline inspection robot.