  Existing exploration algorithms mainly generate frontiers using random
sampling or motion primitive methods within a specific sensor range or search
space. However, frontiers generated within constrained spaces lead to
back-and-forth maneuvers in large-scale environments, thereby diminishing
exploration efficiency. To address this issue, we propose a method that
utilizes a 3D dense map to generate Segmented Exploration Regions (SERs) and
generate frontiers from a global-scale perspective. In particular, this paper
presents a novel topological map generation approach that fully utilizes
Line-of-Sight (LOS) features of LiDAR sensor points to enhance exploration
efficiency inside large-scale subterranean environments. Our topological map
contains the contributions of keyframes that generate each SER, enabling rapid
exploration through a switch between local path planning and global path
planning to each frontier. The proposed method achieved higher explored volume
generation than the state-of-the-art algorithm in a large-scale simulation
environment and demonstrated a 62% improvement in explored volume increment
performance. For validation, we conducted field tests using UAVs in real
subterranean environments, demonstrating the efficiency and speed of our
method.
