论文标题
在室内建筑环境中，意识感知的标签放置计划针对无人机的稳健定位
Perception-aware Tag Placement Planning for Robust Localization of UAVs in Indoor Construction Environments
论文作者
论文摘要
基于标签的视觉惯性定位是一种轻巧的方法，用于在室内建筑环境中实现低成本无人机（UAV）的自主数据收集任务。但是，在动态施工站点上找到最佳的标签配置（即数字，大小和位置）仍然具有挑战性。本文提出了一种基于感知感知的基于遗传算法的标签位置计划者（PGA-TAPP），以确定使用4D-BIM的最佳标签配置，考虑到项目进度，安全要求和无人机的本地化性。提出的方法通过在限制安装成本的同时最大化了感兴趣的区域（ROI）中最大程度地提高了用户指定区域（ROI）的本地化，从而提供了4D计划。使用Fisher信息矩阵（FIM）量化本地化性，并封装在可通航网格中。实验结果表明，我们方法在寻找无人机在室内室内部位上的无人机定位的最佳4D标签计划计划的有效性。
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.
