Coarse Pose Registration Using Local Geometric Features

Abstract

Coarse pose registration is a crucial step in 6DOF pose estimation. Assuming the objects to be estimated are regular and their 3D models are known, this paper presents local geometric features (LGFs) to estimate the poses of objects in point cloud. Coordinate frames describing the object's pose are defined according to geometric information. Pose estimation are performed by calculating the transformation between the frames in the scene point cloud and the reference model. Two kinds of LGFs are proposed: one is the corner edge feature (CEF) which exploits corner and radiating edges, and the other is the circle normal feature (CNF) which exploits circle center and normal vector of the plane where the circle is located. Included angle sequence of adjacent edges and circle radius, which are invariant to SE (3) transformation, are selected to identify CEF and CNF, respectively. Simulation is performed to verify the feasibility of the proposed features.