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Drones
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Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors
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Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (26 March 2026) | Viewed by 8509

Special Issue Editors

Dr. Dayi Zhang

E-Mail Website
Guest Editor
Electronic and Electrical Engineering Department, University of Strathclyde, Glasgow, UK
Interests: automated inspection; industrial drones; ultrasound; photogrammetry
Prof. Dr. Gordon Dobie

E-Mail Website
Guest Editor
Electronic and Electrical Engineering Department, University of Strathclyde, Glasgow, UK
Interests: UAV; robotics; automated inspection; automated analysis; photogrammetry
Special Issues, Collections and Topics in MDPI journals
Dr. Jesus Enrique Sierra-Garcia

E-Mail Website
Guest Editor
Digitalization, Systems Engineering and Automation, University of Burgos, Burgos, Spain
Interests: industrial robotics; automatic regulation; process control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The use of unmanned aerial vehicles (UAVs) has seen exponential growth across various domains due to their versatility and ability to perform tasks that are either too dangerous or impractical for human workers. In recent years, UAV technology has evolved considerably, offering advanced solutions for monitoring, inspection, and data collection. These developments are particularly beneficial in critical industrial sectors where safety and precision are paramount. For instance, in environments like nuclear power plants, oil refineries, and gas processing facilities, UAVs can access areas that are hazardous or challenging for humans, thereby minimizing risks and enhancing operational effectiveness. However, UAVs currently employed in industrial sectors encounter significant challenges, such as difficulties with indoor navigation and localization, as well as problematic interactions with surfaces when flying close to objects. These issues limit the practical application of UAVs in complex industrial environments. These challenges underscore the need for advancements in UAV technology to enhance their safety, reliability, and operational efficiency before they can be widely adopted in many industrial sectors. Moreover, the integration of UAVs into industrial workflows demands robust solutions to address issues such as real-time data processing and obstacle avoidance. Addressing these technical difficulties is crucial for leveraging the full potential of UAVs in tasks such as inspection, maintenance, and monitoring in industries like manufacturing, construction, and energy.

This Special Issue will focus on the pivotal role of UAVs in enhancing operations within critical industrial sectors. UAV technology is rapidly advancing, providing significant improvements in safety, efficiency, and data accuracy in industries such as nuclear power, oil and gas, and other hazardous environments. We invite original research articles and insightful case studies that demonstrate innovative UAV applications in these high-stakes fields. Key areas of interest include, but are not limited to, infrastructure inspection and maintenance, safety monitoring, environmental impact assessments, and operational efficiency in nuclear stations, and the oil and gas processing sectors.

This Special Issue will showcase the latest advancements, best practices, and forward-looking trends in UAV technology, offering essential knowledge for researchers, industry professionals, and regulatory bodies.

This Special Issue will welcome manuscripts that discuss the following themes:

  • Novel UAV designs that improve indoor flyability, especially in complex industrial environments;
  • Innovative UAV designs that enhance and optimize interactions when operating near surfaces;
  • Novel sensors that are well suited to UAV applications in industrial sectors including those for ecological assessments and pollution tracking inside facilities;
  • Advanced UAV designs for hazardous environments, such as nuclear power stations, energy facilities, etc.;
  • Advanced systems for precise UAV localization in industrial sectors;
  • The use of UAVs for non-destructive testing, especially those that can perform quantitative inspections.

We look forward to receiving your original research articles and reviews.

Dr. Dayi Zhang
Prof. Dr. Gordon Dobie
Dr. Jesus Enrique Sierra-Garcia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced unmanned aerial vehicles
  • unmanned aerial vehicles in industrial sectors
  • autonomous UAV systems
  • UAV-based critical infrastructure monitoring
  • hazardous environment inspection using UAVs
  • UAV technology advancements
  • infrastructure maintenance using UAVs
  • UAV environmental impact assessment

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

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24 pages, 9489 KB  
Article
Detection of Missing Insulators in High-Voltage Transmission Lines Using UAV Images
by Yulong Zhang, Xianghong Xue, Lingxia Mu, Jing Xin, Yichi Yang and Youmin Zhang
Drones 2026, 10(3), 213; https://doi.org/10.3390/drones10030213 - 18 Mar 2026
Viewed by 382
Abstract
Insulators are essential components in high-voltage transmission lines and require regular inspection to ensure reliable power delivery. Traditional manual inspection methods are inefficient and labor intensive, highlighting the need for intelligent and automated solutions. In this study, we propose a missing insulator detection [...] Read more.
Insulators are essential components in high-voltage transmission lines and require regular inspection to ensure reliable power delivery. Traditional manual inspection methods are inefficient and labor intensive, highlighting the need for intelligent and automated solutions. In this study, we propose a missing insulator detection method that integrates Unmanned Aerial Vehicle (UAV) imaging with deep learning techniques. Firstly, an improved Faster Region-based Convolutional Neural Network (Faster R-CNN) is employed to detect and localize insulators in aerial images. Secondly, the localized insulators are segmented using an improved U-Net to reduce background interference. A bounding box regression approach is adopted to obtain the minimum enclosing rectangles, and the insulators are aligned vertically. Adaptive thresholding is then applied to extract binary images of the insulators. These binary images are further transformed into defect curves, from which missing insulators are identified based on curve distribution. To address the limited availability of labeled samples, a transfer learning-based strategy is adopted to improve model generalization. A dataset of glass insulators was collected using a DJI M300 UAV equipped with an H20T camera along a 330 kV overhead transmission line. On the collected UAV insulator dataset, the proposed method achieved an AP@0.5 of 99.85% and an average IoU of 88.56% for insulator string detection, while the improved U-Net achieved an mIoU of 89.73% for insulator string segmentation. Outdoor flight experiments further verified performance under varying backgrounds and illumination conditions in our UAV inspection scenarios. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors)
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22 pages, 38941 KB  
Article
Fusion Framework of Remote Sensing and Electromagnetic Scattering Features of Drones for Monitoring Freighters
by Zeyang Zhou and Jun Huang
Drones 2026, 10(1), 74; https://doi.org/10.3390/drones10010074 - 22 Jan 2026
Viewed by 591
Abstract
Certain types of unmanned aerial vehicles (UAVs) represent convenient platforms for remote sensing observation as well as low-altitude targets that are themselves monitored by other devices. In order to study remote sensing grayscale and radar cross-section (RCS) in an example drone, we present [...] Read more.
Certain types of unmanned aerial vehicles (UAVs) represent convenient platforms for remote sensing observation as well as low-altitude targets that are themselves monitored by other devices. In order to study remote sensing grayscale and radar cross-section (RCS) in an example drone, we present a fusion framework based on remote sensing imaging and electromagnetic scattering calculations. The results indicate that the quadcopter drone shows weak visual effects in remote sensing grayscale images while exhibiting strong dynamic electromagnetic scattering features that can exceed 29.6815 dBm2 fluctuations. The average and peak RCS of the example UAV are higher than those of the quadcopter in the given cases. The example freighter exhibits the most intuitive grayscale features and the largest RCS mean under the given observation conditions, with a peak of 51.6186 dBm2. Compared to the UAV, the small boat with a sharp bow design has similar dimensions while exhibiting lower RCS features and intuitive remote sensing grayscale. Under cross-scale conditions, grayscale imaging is beneficial for monitoring UAVs, freighters, and other nearby boats. Dynamic RCS features and grayscale local magnification are suitable for locating and recognizing drones. The established approach is effective in learning remote sensing grayscale and electromagnetic scattering features of drones used for observing freighters. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors)
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26 pages, 6312 KB  
Article
A Novel Telescopic Aerial Manipulator for Installing and Grasping the Insulator Inspection Robot on Power Lines: Design, Control, and Experiment
by Peng Yang, Hao Wang, Xiuwei Huang, Jiawei Gu, Tao Deng and Zonghui Yuan
Drones 2025, 9(11), 741; https://doi.org/10.3390/drones9110741 - 24 Oct 2025
Cited by 1 | Viewed by 1453
Abstract
Insulators on power lines require regular maintenance by operators in high-altitude hazardous environments, and the emergence of aerial manipulators provides an efficient and safe support for this scenario. In this study, a lightweight telescopic aerial manipulator system is developed, which can realize the [...] Read more.
Insulators on power lines require regular maintenance by operators in high-altitude hazardous environments, and the emergence of aerial manipulators provides an efficient and safe support for this scenario. In this study, a lightweight telescopic aerial manipulator system is developed, which can realize the installation and retrieval of insulator inspection robots on power lines. The aerial manipulator has three degrees of freedom, including two telescopic scissor mechanisms and one pitch rotation mechanism. Multiple types of cameras and sensors are specifically configured in the structure, and the total mass of the structure is 2.2 kg. Next, the kinematic model, dynamic model, and instantaneous contact force model of the designed aerial manipulator are derived. Then, the hybrid position/force control strategy of the aerial manipulator and the visual detection and estimation algorithm are designed to complete the operation or complete the task. Finally, the lifting external load test, grasp and installation operation test, as well as outdoor flight operation test are carried out. The test results not only quantitatively evaluate the effectiveness of the structural design and control design of the system but also verify that the aerial manipulator can complete the accurate automatic grasp and installation operation of the 3.6 kg target device in outdoor flight. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors)
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20 pages, 18992 KB  
Article
Application of LMM-Derived Prompt-Based AIGC in Low-Altitude Drone-Based Concrete Crack Monitoring
by Shijun Pan, Zhun Fan, Keisuke Yoshida, Shujia Qin, Takashi Kojima and Satoshi Nishiyama
Drones 2025, 9(9), 660; https://doi.org/10.3390/drones9090660 - 21 Sep 2025
Viewed by 1048
Abstract
In recent years, large multimodal models (LMMs), such as ChatGPT 4o and DeepSeek R1—artificial intelligence systems capable of multimodal (e.g., image and text) human–computer interaction—have gained traction in industrial and civil engineering applications. Concurrently, insufficient real-world drone-view data (specifically close-distance, high-resolution imagery) for [...] Read more.
In recent years, large multimodal models (LMMs), such as ChatGPT 4o and DeepSeek R1—artificial intelligence systems capable of multimodal (e.g., image and text) human–computer interaction—have gained traction in industrial and civil engineering applications. Concurrently, insufficient real-world drone-view data (specifically close-distance, high-resolution imagery) for civil engineering scenarios has heightened the importance of artificially generated content (AIGC) or synthetic data as supplementary inputs. AIGC is typically produced via text-to-image generative models (e.g., Stable Diffusion, DALL-E) guided by user-defined prompts. This study leverages LMMs to interpret key parameters for drone-based image generation (e.g., color, texture, scene composition, photographic style) and applies prompt engineering to systematize these parameters. The resulting LMM-generated prompts were used to synthesize training data for a You Only Look Once version 8 segmentation model (YOLOv8-seg). To address the need for detailed crack-distribution mapping in low-altitude drone-based monitoring, the trained YOLOv8-seg model was evaluated on close-distance crack benchmark datasets. The experimental results confirm that LMM-prompted AIGC is a viable supplement for low-altitude drone crack monitoring, achieving >80% classification accuracy (images with/without cracks) at a confidence threshold of 0.5. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors)
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Review

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34 pages, 11872 KB  
Review
Are Modern Market-Available Multi-Rotor Drones Ready to Automatically Inspect Industrial Facilities?
by Ntmitrii Gyrichidi, Alexandra Khalyasmaa, Stanislav Eroshenko and Alexey Romanov
Drones 2024, 8(10), 549; https://doi.org/10.3390/drones8100549 - 3 Oct 2024
Cited by 1 | Viewed by 3509
Abstract
Industrial inspection is a well-known application area for unmanned aerial vehicles (UAVs), but are modern market-available drones fully suitable for inspections of larger-scale industrial facilities? This review summarizes the pros and cons of aerial large-scale facility inspection, distinguishing it from other inspection scenarios [...] Read more.
Industrial inspection is a well-known application area for unmanned aerial vehicles (UAVs), but are modern market-available drones fully suitable for inspections of larger-scale industrial facilities? This review summarizes the pros and cons of aerial large-scale facility inspection, distinguishing it from other inspection scenarios implemented with drones. Moreover, based on paper analysis and additionally performed experimental studies, it reveals specific issues related to modern commercial drone software and demonstrates that market-available UAVs (including DJI and Autel Robotics) more or less suffer from the same problems. The discovered issues include a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) shift, an identification of multiple images captured from the same point, limitations of custom mission generation with external tools and mission length, an incorrect flight time prediction, an unpredictable time of reaching a waypoint with a small radius, deviation from the pre-planned route line between two waypoints, a high pitch angle during acceleration/deceleration, an automatic landing cancellation in a strong wind, and flight monitoring issues related to ground station software. Finally, on the basis of the paper review, we propose solutions to these issues, which helped us overcome them during the first autonomous inspection of a 2400 megawatts thermal power plant. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) Applications in Critical Industrial Sectors)
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