A Coarse Registration Algorithm Between 3D Point Cloud and CAD Model of Non-cooperative Object for Space Manipulator

Data registration between 3D point cloud and CAD model of noncooperative object has been considered as one of key technologies for estimating spatial position and orientation of target spacecraft. The registration result will directly affect the success or failure of on-orbit capture mission for space manipulator. Usually, 3D CAD model needs to discretize into point cloud of model which can be applied to match the corresponding 3D measuring point clouds. In this article, a coarse registration algorithm of curvature features based on distance constraint consistency is proposed to solve data registration between 3D point cloud and CAD model of non-cooperative object. According to the principle of invariant curvature of rigid transformation, a set of curvature feature points which satisfies the consistency of distance constraint can be selected to calculate rotation matrix and translation vector between both sets of point clouds. Experimental results have shown that the proposed registration algorithm can achieve higher registration accuracy to provide reliable initial values of transformation parameters for subsequent fine registration work.