Review of the Drone Applications in Urban Underground Environments

The rapid urbanization of modern cities has intensified the demand for innovative solutions to inspect, maintain, and map complex underground infrastructure, including tunnels, sewers, and utility networks. While drones have revolutionized aerial applications, their potential in GPS-denied, confined underground environments remains underexplored and warrants systematic analysis. This review paper synthesizes advancements, challenges, and opportunities in deploying drones for urban underground applications through a rigorous systematic literature review. Key findings highlight transformative use cases in infrastructure inspection, disaster response, and 3D LiDAR mapping for integration with urban digital twins. Critical technical challenges—such as sensor degradation in high-humidity environments, adaptive SLAM algorithms for GPS-denied navigation, and limited battery autonomy—are analyzed alongside emerging solutions like tethered power systems and edge-AI for real-time data processing. The study further identifies regulatory gaps in underground airspace governance and interoperability barriers between drone-collected data and urban planning tools. Future directions emphasize swarm robotics for scalable exploration, hydrogen fuel cells for extended missions, and policy frameworks to standardize safety protocols. By bridging robotics, civil engineering, and urban planning disciplines, this review provides a roadmap for researchers and practitioners to advance drone technologies while addressing societal needs for safer, cost-effective, and sustainable urban underground management.

Authors

Institutions

Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/iccea65460.2025.11103266
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Review of the Drone Applications in Urban Underground Environments

Mei Hu, Qinqi Wang, Qiyang Zhang, Fei Liu et al.
Fire Detection and Safety Systems
article

Review of the Drone Applications in Urban Underground Environments

Mei Hu, Qinqi Wang, Qiyang Zhang, Fei Liu, C. N. Tang, Hangfei Zhang
article en

Abstract

The rapid urbanization of modern cities has intensified the demand for innovative solutions to inspect, maintain, and map complex underground infrastructure, including tunnels, sewers, and utility networks. While drones have revolutionized aerial applications, their potential in GPS-denied, confined underground environments remains underexplored and warrants systematic analysis. This review paper synthesizes advancements, challenges, and opportunities in deploying drones for urban underground applications through a rigorous systematic literature review. Key findings highlight transformative use cases in infrastructure inspection, disaster response, and 3D LiDAR mapping for integration with urban digital twins. Critical technical challenges—such as sensor degradation in high-humidity environments, adaptive SLAM algorithms for GPS-denied navigation, and limited battery autonomy—are analyzed alongside emerging solutions like tethered power systems and edge-AI for real-time data processing. The study further identifies regulatory gaps in underground airspace governance and interoperability barriers between drone-collected data and urban planning tools. Future directions emphasize swarm robotics for scalable exploration, hydrogen fuel cells for extended missions, and policy frameworks to standardize safety protocols. By bridging robotics, civil engineering, and urban planning disciplines, this review provides a roadmap for researchers and practitioners to advance drone technologies while addressing societal needs for safer, cost-effective, and sustainable urban underground management.

Central South University (CN), National University of Defense Technology (CN), Hunan Cancer Hospital (CN), Xiangya Hospital Central South University (CN), PLA Army Engineering University (CN)
Sustainable cities and communities
Openalex Percentile: Top 75%
Fire Detection and Safety Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.