Simultaneous planning of standpoints and routing for laser scanning of buildings with network redundancy

Stop-and-go laser scanning is becoming increasingly prevalent in a variety of applications, e.g., the survey of the built environment. For this, a surveyor needs to select a set of standpoints as well as the route between them. This choice, however, has a high impact on both the economic efficiency of the respective survey as well as the completeness, accuracy, and subsequent registrability of the resulting point cloud. Assuming a set of building footprints as input, this article proposes a one-step optimization method to find the minimal number of selected standpoints based on scanner-related constraints. At the same time, we incorporate the length of the shortest route connecting the standpoints in the objective function. A local search method to speed up the time for solving the corresponding Mixed-Integer Linear Program (MILP) is additionally presented. The results for different scenarios show constantly shorter routes in comparison to existing approaches while still maintaining the minimal number of standpoints. Moreover, in our formulation we aim to minimize the effects of inaccuracies in the software-based registration. Inspired by the ideas of network survivability, we to this end propose a novel definition of connectivity tailored for laser scanning networks. On this basis, we enforce redundancy for the registration network of the survey. To prove the applicability of our formulation, we applied it to a large real-world scenario. This paves the way for the future use of fully automatic autonomous systems to provide a complete and high-quality model of the underlying building scenery. • Simultaneous optimization of the number of standpoints and length of the route between them for stop-and-go laser scanning. • Enforcing network redundancy inspired by the concepts of network survivability to minimize the effect of measurement inaccuracies. • Beyond the optimal solution presenting a heuristic based on local search. • Testing of the approach on a large real-world scenario.