Terrain drivability analysis in 3D laser range data for autonomous robot navigation in unstructured environments

Authors:
Frank Neuhaus;Denis Dillenberger;Johannes Pellenz;Dietrich Paulus
Affiliations:
Active Vision Group, University of Koblenz-Landau, Koblenz, Germany;Active Vision Group, University of Koblenz-Landau, Koblenz, Germany;Active Vision Group, University of Koblenz-Landau, Koblenz, Germany;Active Vision Group, University of Koblenz-Landau, Koblenz, Germany
Venue:
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Year:
2009

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Abstract

Three-dimensional laser range finders provide autonomous systems with vast amounts of information. However, autonomous robots navigating in unstructured environments are usually not interested in every geometric detail of their surroundings. Instead, they require real-time information about the location of obstacles and the condition of drivable areas. In this paper, we first present grid-based algorithms for classifying regions as either drivable or not. In a subsequent step, drivable regions are further examined using a novel algorithm which determines the local terrain roughness. This information can be used by a path planning algorithm to decide whether to prefer a rough, muddy area, or a plain street, which would not be possible using binary drivability information only.