  Tag-based visual-inertial localization is a lightweight method for enabling
autonomous data collection missions of low-cost unmanned aerial vehicles (UAVs)
in indoor construction environments. However, finding the optimal tag
configuration (i.e., number, size, and location) on dynamic construction sites
remains challenging. This paper proposes a perception-aware genetic
algorithm-based tag placement planner (PGA-TaPP) to determine the optimal tag
configuration using 4D-BIM, considering the project progress, safety
requirements, and UAV's localizability. The proposed method provides a 4D plan
for tag placement by maximizing the localizability in user-specified regions of
interest (ROIs) while limiting the installation costs. Localizability is
quantified using the Fisher information matrix (FIM) and encapsulated in
navigable grids. The experimental results show the effectiveness of our method
in finding an optimal 4D tag placement plan for the robust localization of UAVs
on under-construction indoor sites.

Robotics