The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 729–736, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-729-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2021, 729–736, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-729-2021

  28 Jun 2021

28 Jun 2021

EFFICIENT TOUR PLANNING FOR A MEASUREMENT VEHICLE BY COMBINING NEXT BEST VIEW AND TRAVELING SALESMAN

J. Gehrung1,2, M. Hebel1, M. Arens1, and U. Stilla2 J. Gehrung et al.
  • 1Fraunhofer IOSB, Ettlingen, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, 76275 Ettlingen, Germany
  • 2Photogrammetry and Remote Sensing, Technische Universitaet Muenchen, 80333 Muenchen, Germany

Keywords: Mobile Laser Scanning, Next Best View, Traveling Salesman Problem, Evidence Grids, Change Detection

Abstract. Path planning for a measuring vehicle requires solving two popular problems from computer science, namely the search for the optimal tour and the search for the optimal viewpoint. Combining both problems results in a new variation of the Traveling Salesman Problem, which we refer to as the Explorational Traveling Salesman Problem. The solution to this problem is the optimal tour with a minimum of observations. In this paper, we formulate the basic problem, discuss it in context of the existing literature and present an iterative solution algorithm. We demonstrate how the method can be applied directly to LiDAR data using an occupancy grid. The ability of our algorithm to generate suitably efficient tours is verified based on two synthetic benchmark datasets, utilizing a ground truth determined by an exhaustive search.