The normal based ICP (NICP) is a complete rigid registration of 3D point sets with normal information, which makes point registration accurate via imposing additional geometrical constraints. However, NICP is sensitive to inexact correspondence for its covariance is only related to reference point set. To deal with this problem, a probabilistic model is proposed to make the covariance is determined by reference and moving point set both. Moreover, a modified NICP (M-NICP) is proposed to solve the objective function, which can improves quality of point set registration. It is applied in a proposed framework of the large-scale 3D mapping which is simple and robust, as it only requires a coarse GPS prior information. Experimental results demonstrate that M-NICP outperforms common ICP variants, and the proposed 3D mapping framework can construct high quality 3D maps for navigational tasks.
['Di Wang', 'Shaoyi Du', 'Jun Zhou', 'Jianru Xue']
Accurate Modified Normal Based ICP for 3D Mapping