Authors:
Marco Langerwisch
and
Bernardo Wagner
Affiliation:
Leibniz Universität Hannover, Germany
Keyword(s):
3D laser range finders, Scan matching, Point cloud registration, Iterative closest point algorithm, Virtual 2D scans, Real time, Mobile robots.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
For mapping purposes, autonomous robots have to be capable to register 3D range images taken by 3D laser sensors into a common coordinate system. One approach is the Iterative Closest Point (ICP) algorithm. Due to its high computational costs, the ICP algorithm is not suitable for registering 3D range images online. This paper presents a novel approach for registering indoor 3D range images using orthogonal virtual 2D scans, utilizing the typical structure of indoor environments. The 3D registration process is split into three 2D registration steps, and hence the computational effort is reduced. First experiments show that the approach is capable of registering 3D range images much more efficient than ICP algorithm and in real time.