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Optimal position and path planning for stop-And-go laserscanning for the acquisition of 3d building models

J. Knechtel*, L. Klingbeil, J. H. Haunert, Y. Dehbi*

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Terrestrial laser scanning has become more and more popular in recent years. The according planning of the standpoint network is a crucial issue influencing the overhead and the resulting point cloud. Fully static approaches are both cost and time extensive, whereas fully kinematic approaches cannot produce the same data quality. Stop-And-go scanning, which combines the strengths of both strategies, represents a good alternative solution. In the scanning process, the standpoint planning is by now mostly a manual process based on expert knowledge and relying on the surveyor's experience. This paper provides a method based on Mixed Integer Linear Programming (MILP) ensuring an optimal placement of scanner standpoints considering all scanner-related constraints (e.g. incidence angle), a full coverage of the scenery, a sufficient overlap for the subsequent registration and an optimal route planning solving a Traveling Salesperson Problem (TSP). This enables the fully automatic application of autonomous systems for providing a complete model while performing a stop-And-go laser scanning, e.g. with the Spot robot from Boston Dynamics. Our pre-computed solution, i.e. standpoints and trajectory, has been evaluated surveying a real-world environment using a 360° panoramic laser scanner and successfully compared with a precise LoD2 building model of the underlying scene. The performed ICP-based registration issued from our fully automatic pipeline turns out to be a very good and safe alternative of the otherwise laborious target-based registration.

OriginalspracheEnglisch
TitelISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
UntertitelISPRS Congress (2022 edition), 6–11 June 2022, Nice, France
Seiten129-136
DOIs
PublikationsstatusVeröffentlicht - 17 Mai 2022
Extern publiziertJa

Publikationsreihe

NameISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
BandV-4-2022
ISSN (elektronisch)2194-9042

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