Fast 3D mapping by matching planes extracted from range sensor point-clouds

Authors:
Kaustubh Pathak;Narunas Vaskevicius;Jann Poppinga;Max Pfingsthorn;Sören Schwertfeger;Andreas Birk
Affiliations:
Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany;Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany;Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany;Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany;Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany;Dept. of Computer Science, Jacobs University Bremen, Bremen, Germany
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

This article addresses fast 3D mapping by a mobile robot in a predominantly planar environment. It is based on a novel pose registration algorithm based entirely on matching features composed of plane-segments extracted from point-clouds sampled from a 3D sensor. The approach has advantages in terms of robustness, speed and storage as compared to the voxel based approaches. Unlike previous approaches, the uncertainty in plane parameters is utilized to compute the uncertainty in the pose computed by scan-registration. The algorithm is illustrated by creating a full 3D model of a multi-level robot testing arena.