Robust iterative closest point algorithm for registration of point sets with outliers

Abstract

The problem of registering point sets with outliers including noises and missing data is discussed in this paper. To solve this problem, a novel objective function is proposed by introducing an overlapping percentage for partial registration. Moreover, a novel robust iterative closest point (ICP) algorithm is proposed which can compute rigid transformation, correspondence, and overlapping percentage automatically at each iterative step. This new algorithm uses as many point pairs as possible to yield a more reliable and accurate registration result between two m-D point sets with outliers. Experimental results demonstrate that our algorithm is more robust than the traditional ICP and the state-of-the-art algorithms.