This paper presents the results of a field experiment in the Kvarntorp mine outside of Örebro in Sweden. 3D mapping of the underground mine has been used to compare two scan matching methods, namely the iterative closest point algorithm (ICP) and the normal distributions transform (NDT). The experimental results of the algorithm are compared in terms of robustness and speed. For robustness we measure how reliably 3D scans are registered with respect to different starting pose estimates. Speed is evaluated running the authors’ best implementations on the same hardware. This leads to an unbiased comparison. In these experiments, NDT was shown to converge form a larger range of initial pose estimates than ICP, and to perform faster.