Registration of Non-Uniform Density 3D Point Clouds using Approximate Surface Reconstruction

Abstract:
3D laser scanners composed of a rotating 2D laser range scanner exhibit different point densities within and between individual scan lines. Such non-uniform point densities influence neighbor searches which in turn may negatively affect feature estimation and scan registration. To reliably register such scans, we extend a state-of-the-art registration algorithm to include topological information from approximate surface reconstructions. We show that our approach outperforms related approaches in both refining a good initial pose estimate and registering badly aligned point clouds if no such estimate is available. In an example application, we demonstrate local 3D mapping with a micro aerial vehicle by registering sequences of non-uniform density point clouds acquired in-flight with a continuously rotating lightweight 3D scanner.