3-DOF point cloud registration using congruent triangles

Abstract

In this paper, we present an efficient 3-DOF registration method to align two overlapping point clouds captured by a range sensor that experiences locally planar motion such as in many robotics applications. The algorithm follows the RANSAC framework and is based on finding a pair of congruent triangles in the source and target clouds. With the assumption of planar sensor motion, corresponding vertices of the congruent triangles must have similar elevation values, allowing our algorithm to identify them efficiently. Specifically, given a triangle in the source cloud, our algorithm first finds two vertices of a candidate congruent triangle in the target cloud and then uses the third vertex to verify, minimizing the complexity of the geometric base as well as the expected time of sampling successfully a matching congruent triangle. To improve the performance of our algorithm further, our verification of a hypothetical alignment transformation proceeds first locally by using only the points near the vertices of the congruent triangles before involving the entire cloud. Our experimental results show that the proposed algorithm outperforms state-of-the-art registration algorithms in the case of 3-DOF planar sensor motion.