In this paper, the authors present a new method for estimating normals on unorganized point clouds that preserves sharp features. It is based on a robust version of the Randomized Hough Transform (RHT). They consider the filled Hough transform accumulator as an image of the discrete probability distribution of possible normals. The normals they estimate correspond to the maximum of this distribution. They use a fixed-size accumulator for speed, statistical exploration bounds for robustness, and randomized accumulators to prevent discretization effects.