Volume IV-2/W7
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W7, 39–46, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W7-39-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W7, 39–46, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W7-39-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  16 Sep 2019

16 Sep 2019

A REPRESENTATION OF MLS DATA AS A BASIS FOR TERRAIN NAVIGABILITY ANALYSIS AND SENSOR DEPLOYMENT PLANNING

J. Gehrung1,2, M. Hebel1, M. Arens1, and U. Stilla2 J. Gehrung et al.
  • 1Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275 Ettlingen, Germany
  • 2Photogrammetry and Remote Sensing, Technical University of Munich (TUM), Germany

Keywords: Mobile Laser Scanning, Spatial Analysis, Occupancy Grid, Density Function, Heatmap

Abstract. Recording an ever-changing urban environment in a structured manner requires sensor deployment planning. In case of mobile sensor platforms, this also includes verifying the terrain navigability. Solving both tasks would usually require different application-specific data structures and tools. In this work, we propose a theoretical framework that provides a uniform representation for spatial information as well as the tools required to combine, manipulate and visualize it. We provide an efficient implementation of the framework utilizing octree-based evidence grids. Our approach can be used to solve complex tasks by combining simple spatial information sources, which we demonstrate by providing simple solutions to the aforementioned applications. Despite the use of a volumetric approach, our runtimes are within the range of minutes.