Mapping with Micro Aerial Vehicles by Registration of Sparse 3D Laser Scans

Abstract. Micro aerial vehicles (MAVs) pose specific constraints on on-board sensing, mainly limited payload and limited processing power. For accurate 3D mapping even in GPS denied environments, we have de-signed a light-weight 3D laser scanner specifically for the application on MAVs. Similar to other custom-built 3D laser scanners composed of a rotating 2D laser range finder, it exhibits different point densities within and between individual scan lines. When rotated fast, such non-uniform point densities influence neighborhood searches which in turn may neg-atively affect local feature estimation and scan registration. We present a complete pipeline for 3D mapping including pair-wise registration and global alignment of 3D scans acquired in-flight. For registration, we ex-tend a state-of-the-art registration algorithm to include topological infor-mation from approximate surface reconstructions. For global alignment, we use a graph-based approach making use of the same error metric and iteratively refine the complete vehicle trajectory. In experiments, we show that our approach can compensate for the effects caused by dif-ferent point densities up to very low angular resolutions and that we can build accurate and consistent 3D maps in-flight with a micro aerial vehicle.