Rotation and translation invariant 3D descriptor for surfaces

We present a descriptor estimator for surface-based 3D input data for coarse localization of mobile robots. From the input pointclouds surfaces are reconstructed and simplified to detect stable keypoints which are used to evaluate rotation and translation invariant features. The invariance is achieved by transforming the triangulated input data into the frequency domain by Fourier transformation and spherical harmonics. The pipeline was evaluated against state of the art algorithms and tested to localize a mobile robot. The source code is publicly available.