Volume XLII-4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 143–148, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-143-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 143–148, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-143-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Sep 2018

19 Sep 2018

SCAN PLANNING AND ROUTE OPTIMIZATION FOR CONTROL OF EXECUTION OF AS-DESIGNED BIM

L. Díaz-Vilariño1,2, E. Frías1, J. Balado1, and H. González-Jorge1 L. Díaz-Vilariño et al.
  • 1Applied Geotechnologies Group, Dept. Natural Resources and Environmental Engineering, University of Vigo, Campus Lagoas-Marcosende, CP 36310 Vigo, Spain
  • 2Dept. Civil Engineering, University of Porto, s/n, R. Dr. Roberto Frias, 4200-465 Porto, Portugal

Keywords: BIM, control of execution, scan-to-BIM, path planning, visibility, spatial analysis, computational geometry

Abstract. Scan-to-BIM systems have been recently proposed for the dimensional and quality assessment of as-built construction components with planned works. The procedure is generally based on the geometric alignment and comparison of as-built laser scans with as-designed BIM models. A major concern in Scan-to-BIM procedures is point cloud quality in terms of data completeness and consequently, the scanning process should be designed in order to obtain a full coverage of the scene while avoiding major occlusions. This work proposes a method to optimize the number and scan positions for Scan-to-BIM procedures following stop & go scanning. The method is based on a visibility analysis using a ray-tracing algorithm. In addition, the optimal route between scan positions is formulated as a travelling salesman problem and solved using a suboptimal ant colony optimization algorithm. The distribution of candidate positions follows a grid-based structure, although other distributions based on triangulation or tessellation can be implemented to reduce the number of candidate positions and processing time.