Robust Real-Time Registration of RGB-D Images using Multi-Resolution Surfel Representations

Abstract

Fast and robust registration of 3D scans is required in many approaches to perception in robotics such as pose tracking or simultaneous localization and mapping. We propose a novel efficient method to register RGB-D images. We convert the image content into a multi-resolution surfel representation and exploit the dense image neighborhood to construct such views at high frame-rates on a single CPU. Our approach registers views using an efficient and robust variant of the Iterative Closest Points algorithm. We evaluate our method on a recently published benchmark dataset and achieve results beyond the state-of-the-art. We also report on the successful public demonstration of our method at RoboCup 2011. 1