It is indispensable to obtain more information such as the 3D structure of the space target by detecting and identifying the target, when complete the on-orbit servicing and on-orbit control tasks. Both lidar and binocular stereo vision can provide three dimensional information of the environment. But it is very sensitive to the illuminance of environment and difficult to image registration at weak texture region, when we are using the binocular stereo vision in space. And lidar also has some defects such as the lidar data is sparse and the scanning frequency is low. So lidar and binocular stereo vision should be used together. The data of the lidar and binocular stereo vision are fused to make up for each others flaws.
In this paper, uniform point drift registration method is used in the fusion of point cloud which is sampled by lidar and binocular stereo vision. In this method, the two groups of point cloud are considered as one which submit to mixed probability distribution and the other one which is sampled from the points submit to mixed probability distribution. The transformation estimation between the two groups of the point cloud is maximum likelihood estimation. The transformation is required to take overall smoothness. In other words, the point clouds should be uniformed. The uniform point drift method can solve the registration problem efficiently for 3D reconstruction. Usually the time can be compressed by 10%.