Perception-aware Tag Placement Planning for Robust Localization of UAVs in Indoor Construction Environments

TL;DR

This paper introduces a perception-aware genetic algorithm for optimal tag placement in indoor UAV localization, improving robustness by considering project progress, safety, and localizability in dynamic construction environments.

Contribution

It presents a novel 4D planning method using genetic algorithms and BIM data to optimize tag placement for UAV localization in indoor construction sites.

Findings

Effective 4D tag placement plans generated

Enhanced UAV localization robustness demonstrated

Cost-effective tag installation achieved

Abstract

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.