It is indispensable to obtain more information such as the 3D structure of the space target by detecting and identifyingthe target, when complete the on-orbit servicing and on-orbit control tasks. Both lidar and binocular stereo vision can providethree dimensional information of the environment. But it is very sensitive to the illuminance of environment and difficult toimage registration at weak texture region, when we are using the binocular stereo vision in space. And lidar also has somedefects such as the lidar data is sparse and the scanning frequency is low. So lidar and binocular stereo vision should be usedtogether. 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 andbinocular stereo vision. In this method, the two groups of point cloud are considered as one which submit to mixed probabilitydistribution and the other one which is sampled from the points submit to mixed probability distribution. The transformationestimation between the two groups of the point cloud is maximum likelihood estimation. The transformation is required totake overall smoothness. In other words, the point clouds should be uniformed. The uniform point drift method can solve theregistration problem efficiently for 3D reconstruction. Usually the time can be compressed by 10%.
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