Enhancing Underground Drone Endurance by Optimizing Battery Efficiency, Communication Robustness, And Navigation Autonomy

Underground mining, tunneling, and subsurface inspection environments present uniquely demanding conditions for autonomous drone operations, where endurance, stability, and communication reliability are consistently challenged by confined geometries, GPS-denied spaces, dust-laden air, and electromagnetic interference.Enhancing drone performance in these environments requires a holistic optimization framework that addresses the three core constraints limiting operational duration: battery efficiency, communication robustness, and navigation autonomy.From a broad perspective, endurance is influenced by power consumption patterns shaped by propulsion load, sensor suite demands, and continuous obstacle-avoidance processing.Improved battery chemistry, intelligent power-distribution algorithms, and adaptive thrust management significantly extend mission duration while reducing thermal stress on onboard components.Communication robustness becomes increasingly critical as drones operate deeper into underground networks where signal attenuation is severe.Employing hybrid communication architectures such as relay drones, tethered links, mesh networks, and low-frequency radio systems ensures consistent data transmission and real-time command exchange.These systems prevent mission dropouts and support continuous monitoring in complex layouts where line-of-sight is frequently obstructed.Navigation autonomy provides the third pillar of endurance improvement.Advanced SLAM frameworks, visual-inertial odometry, LiDAR-based mapping, and onboard decision-making reduce the need for high-bandwidth external control.Autonomous path optimization minimizes unnecessary maneuvering, conserves battery life, and enhances safety by predicting hazardous voids or unstable surfaces before entry.By integrating these technological advancements, underground drones can achieve significantly longer flight durations, improved operational reliability, and superior mapping performance in some of the world's most challenging environments.This multi-dimensional enhancement framework supports safer inspections, faster geotechnical assessments, and more efficient underground operations across mining, civil engineering, and emergency-response domains.

Publication Details

Journal
International Journal of Computer Applications Technology and Research
Published
2025-11-25
DOI
https://doi.org/10.7753/ijcatr0512.1012
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Underground Drone Endurance by Optimizing Battery Efficiency, Communication Robustness, And Navigation Autonomy

International Journal of Computer Applications Technology and Research
UAV Applications and Optimization
article

Enhancing Underground Drone Endurance by Optimizing Battery Efficiency, Communication Robustness, And Navigation Autonomy

article en

Abstract

Underground mining, tunneling, and subsurface inspection environments present uniquely demanding conditions for autonomous drone operations, where endurance, stability, and communication reliability are consistently challenged by confined geometries, GPS-denied spaces, dust-laden air, and electromagnetic interference.Enhancing drone performance in these environments requires a holistic optimization framework that addresses the three core constraints limiting operational duration: battery efficiency, communication robustness, and navigation autonomy.From a broad perspective, endurance is influenced by power consumption patterns shaped by propulsion load, sensor suite demands, and continuous obstacle-avoidance processing.Improved battery chemistry, intelligent power-distribution algorithms, and adaptive thrust management significantly extend mission duration while reducing thermal stress on onboard components.Communication robustness becomes increasingly critical as drones operate deeper into underground networks where signal attenuation is severe.Employing hybrid communication architectures such as relay drones, tethered links, mesh networks, and low-frequency radio systems ensures consistent data transmission and real-time command exchange.These systems prevent mission dropouts and support continuous monitoring in complex layouts where line-of-sight is frequently obstructed.Navigation autonomy provides the third pillar of endurance improvement.Advanced SLAM frameworks, visual-inertial odometry, LiDAR-based mapping, and onboard decision-making reduce the need for high-bandwidth external control.Autonomous path optimization minimizes unnecessary maneuvering, conserves battery life, and enhances safety by predicting hazardous voids or unstable surfaces before entry.By integrating these technological advancements, underground drones can achieve significantly longer flight durations, improved operational reliability, and superior mapping performance in some of the world's most challenging environments.This multi-dimensional enhancement framework supports safer inspections, faster geotechnical assessments, and more efficient underground operations across mining, civil engineering, and emergency-response domains.

International Journal of Computer Applications Technology and Research
Openalex Percentile: Top 53%
UAV Applications and Optimization
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.

Enhancing Underground Drone Endurance by Optimizing Battery Efficiency, Communication Robustness, And Navigation Autonomy · International Journal of Computer Applications Technology and Research (2025) | TGRS Research Map | TGRS