The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 521–526, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-521-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2020, 521–526, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B1-2020-521-2020

  06 Aug 2020

06 Aug 2020

UAV MISSION PLANNING FOR AUTOMATIC EXPLORATION AND SEMANTIC MAPPING

Y. Dehbi1, L. Klingbeil1, and L. Plümer2 Y. Dehbi et al.
  • 1Institute of Geodesy and Geoinformation, University of Bonn, Bonn, Germany
  • 2Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University Chengdu, China

Keywords: Mission planing, 3D Building Models, UAV, Semantics

Abstract. Unmanned Aerial Vehicles (UAVs) are used for the inspection of areas which are otherwise difficult to access. Autonomous monitoring and navigation requires a background knowledge on the surroundings of the vehicle. Most mission planing systems assume collision-free pre-defined paths and do not tolerate a GPS signal outage. Our approach makes weaker assumptions. This paper introduces a mission planing platform allowing for the integration of environmental prior knowledge such as 3D building and terrain models. This prior knowledge is integrated to pre-compute an octomap for collision detection. The semantically rich building models are used to specify semantic user queries such as roof or facade inspection. A reasoning process paves the way for semantic mission planing of hidden and a-priori unknown objects. Subsequent scene interpretation is performed by an incremental parsing process.