Civil and Public Domain Applications of Unmanned Aviation

Topic Information

Dear Colleagues,

Unmanned systems have witnessed unprecedented levels of growth during the past decade. Although military applications have dominated the field for years, there is a major shift to civil and public domain applications in which aerial platforms are used across a wide spectrum of diverse applications in urban and rural areas. This Topic focuses on civil and public domain applications and on the societal impact of unmanned aviation and its effect on everyday quality of life. Although the technical challenges cover a wide spectrum of topics, of particular importance are the following topics:

• bioinspired aerial platforms;
• hybrid platforms;
• design resiliency;
• human factors;
• the framework and regulations for integration into the national air-space.

Submitted papers will include, but are not be limited to, extended versions of accepted conference papers in ICUAS 2024, which will be held on 4–7th June, Chania, Crete, Greece. The maximum percentage of overlap will be 30%. Authors must reference the corresponding conference papers. The extended version of the accepted conference papers in ICUAS 2024 will enjoy a 20% discount on the Article Processing Charge.

Prof. Dr. Hyoun Jin Kim
Dr. Giuseppe Loianno
Prof. Dr. Didier Theilliol
Prof. Dr. Nikolaos Tsourveloudis
Prof. Dr. Kimon P. Valavanis
Dr. Nikolaos Vitzilaios
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Aerospace aerospace	2.1	3.4	2014	21.3 Days	CHF 2400
Automation automation	-	2.9	2020	24.1 Days	CHF 1000
Drones drones	4.4	5.6	2017	19.2 Days	CHF 2600
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400
Remote Sensing remotesensing	4.2	8.3	2009	23.9 Days	CHF 2700

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Published Papers (6 papers)

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All Aerospace Automation Drones Electronics Remote Sensing

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27 pages, 10812 KiB  

Open AccessArticle

Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments

by Yuanjun Zhu, Xuejun Zhang, Yan Li, Yang Liu and Jianxiang Ma

Drones 2024, 8(11), 678; https://doi.org/10.3390/drones8110678 - 17 Nov 2024

Viewed by 715

Abstract

As a novel mode of urban air mobility (UAM), unmanned aerial vehicles (UAVs) pose a great amount of risk to ground people. Assessing ground risk and mitigation effects correctly is a focused issue. This paper proposes a grid-based risk matrix framework for assessing [...] Read more.

As a novel mode of urban air mobility (UAM), unmanned aerial vehicles (UAVs) pose a great amount of risk to ground people. Assessing ground risk and mitigation effects correctly is a focused issue. This paper proposes a grid-based risk matrix framework for assessing the ground risk associated with two types of UAVs, namely fixed-wing and quadrotor. The framework has a three-stage structure of “intrinsic risk assessment—mitigation effect—final map generation”. First, the intrinsic risk to ground populations caused by potential UAV crashes is quantified. Second, the mitigation effects are measured by establishing a mathematical model with a focus on the ground sheltering and parachute systems. Finally, a modular approach is presented for generating a ground risk map of UAVs, aiming to effectively characterize the effects of each influencing factor on the failure process of UAVs. The framework facilitates the modular analysis and quantification of the impact of diverse risk factors on UAV ground risk. It also provides a new perspective for analyzing ground risk mitigation measures, such as ground sheltering and UAV parachute systems. A case study experiment on a realistic urban environment in Shenzhen shows that the risk map generated by the presented framework can accurately characterize the distribution of ground risk posed by various UAVs. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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24 pages, 5194 KiB  

Open AccessArticle

Decentralized Multi-Agent Search for Moving Targets Using Road Network Gaussian Process Regressions

by Brady Moon, Christine Akagi and Cameron K. Peterson

Drones 2024, 8(11), 606; https://doi.org/10.3390/drones8110606 - 23 Oct 2024

Viewed by 3309

Abstract

Unmanned aerial vehicles (UAVs) can collaborate as teams to accomplish diverse mission objectives, such as target search and tracking. This paper introduces a method that leverages accumulated target-density information over the course of a UAV mission to adapt path-planning rewards, guiding UAVs toward [...] Read more.

Unmanned aerial vehicles (UAVs) can collaborate as teams to accomplish diverse mission objectives, such as target search and tracking. This paper introduces a method that leverages accumulated target-density information over the course of a UAV mission to adapt path-planning rewards, guiding UAVs toward areas with a higher likelihood of target presence. The target density is modeled using a Gaussian process, which is iteratively updated as the UAVs search the environment. Unlike conventional search algorithms that prioritize unexplored regions, this approach incentivizes revisiting target-rich areas. The target-density information is shared across UAVs using decentralized consensus filters, enabling cooperative path selection that balances the exploration of uncertain regions with the exploitation of known high-density areas. The framework presented in this paper provides an adaptive cooperative search method that can quickly develop an understanding of the region’s target-dense areas, helping UAVs refine their search. Through Monte Carlo simulations, we demonstrate this method in both a 2D grid region and road networks, showing up to a 26% improvement in target density estimates. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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20 pages, 7568 KiB  

Open AccessArticle

Application of End-to-End Perception Framework Based on Boosted DETR in UAV Inspection of Overhead Transmission Lines

by Jinyu Wang, Lijun Jin, Yingna Li and Pei Cao

Drones 2024, 8(10), 545; https://doi.org/10.3390/drones8100545 - 1 Oct 2024

Cited by 1 | Viewed by 1469

Abstract

As crucial predecessor tasks for fault detection and transmission line inspection, insulators, anti-vibration hammers, and arc sag detection are critical jobs. Due to the complexity of the high-voltage transmission line environment and other factors, target detection work on transmission lines remains challenging. A [...] Read more.

As crucial predecessor tasks for fault detection and transmission line inspection, insulators, anti-vibration hammers, and arc sag detection are critical jobs. Due to the complexity of the high-voltage transmission line environment and other factors, target detection work on transmission lines remains challenging. A method for high-voltage transmission line inspection based on DETR (TLI-DETR) is proposed to detect insulators, anti-vibration hammers, and arc sag. This model achieves a better balance in terms of speed and accuracy than previous methods. Due to environmental interference such as mountainous forests, rivers, and lakes, this paper uses the Improved Multi-Scale Retinex with Color Restoration (IMSRCR) algorithm to make edge extraction more robust with less noise interference. Based on the TLI-DETR’s feature extraction network, we introduce the edge and semantic information by Momentum Comparison (MoCo) to boost the model’s feature extraction ability for small targets. The different shooting angles and distances of drones result in the target images taking up small proportions and impeding each other. Consequently, the statistical profiling of the area and aspect ratio of transmission line targets captured by UAV generate target query vectors with prior information to enable the model to adapt to the detection needs of transmission line targets more accurately and effectively improve the detection accuracy of small targets. The experimental results show that this method has excellent performance in high-voltage transmission line detection, achieving up to 91.65% accuracy and a 55FPS detection speed, which provides a technical basis for the online detection of transmission line targets. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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19 pages, 3020 KiB  

Open AccessArticle

Cooperative Drone Transportation of a Cable-Suspended Load: Dynamics and Control

by Elia Costantini, Emanuele Luigi de Angelis and Fabrizio Giulietti

Drones 2024, 8(9), 434; https://doi.org/10.3390/drones8090434 - 26 Aug 2024

Viewed by 1572

Abstract

The cooperative transportation of a cable-suspended load by two unmanned rotorcraft is analyzed. Initially, the equations describing a system composed of three point masses and two rigid cables are derived. The model is then linearized about the hovering condition, and analytical expressions are [...] Read more.

The cooperative transportation of a cable-suspended load by two unmanned rotorcraft is analyzed. Initially, the equations describing a system composed of three point masses and two rigid cables are derived. The model is then linearized about the hovering condition, and analytical expressions are derived to describe the eigenstructure of the open-loop system. Thanks to the specific parameterization of the problem, the different dynamic modes are outlined and discussed within an analytical framework. A novel controller is designed to enable the UAVs in the formation to perform trajectory tracking, maintain formation geometry, and stabilize payload swing simultaneously. A preliminary investigation of closed-loop stability is conducted using a linear approach. Validation is performed in a realistic simulation scenario where two drones are modeled as rigid bodies under the effect of external disturbances and rotor-generated forces and moments, as obtained by Blade Element Theory. The proposed method demonstrates relative simplicity and significantly improves the flying qualities of delivery operations while minimizing hazardous payload oscillations and reducing energy demand. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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20 pages, 5258 KiB  

Open AccessArticle

YOMO-Runwaynet: A Lightweight Fixed-Wing Aircraft Runway Detection Algorithm Combining YOLO and MobileRunwaynet

by Wei Dai, Zhengjun Zhai, Dezhong Wang, Zhaozi Zu, Siyuan Shen, Xinlei Lv, Sheng Lu and Lei Wang

Drones 2024, 8(7), 330; https://doi.org/10.3390/drones8070330 - 18 Jul 2024

Cited by 1 | Viewed by 1617

Abstract

The runway detection algorithm for fixed-wing aircraft is a hot topic in the field of aircraft visual navigation. High accuracy, high fault tolerance, and lightweight design are the core requirements in the domain of runway feature detection. This paper aims to address these [...] Read more.

The runway detection algorithm for fixed-wing aircraft is a hot topic in the field of aircraft visual navigation. High accuracy, high fault tolerance, and lightweight design are the core requirements in the domain of runway feature detection. This paper aims to address these needs by proposing a lightweight runway feature detection algorithm named YOMO-Runwaynet, designed for edge devices. The algorithm features a lightweight network architecture that follows the YOMO inference framework, combining the advantages of YOLO and MobileNetV3 in feature extraction and operational speed. Firstly, a lightweight attention module is introduced into MnasNet, and the improved MobileNetV3 is employed as the backbone network to enhance the feature extraction efficiency. Then, PANet and SPPnet are incorporated to aggregate the features from multiple effective feature layers. Subsequently, to reduce latency and improve efficiency, YOMO-Runwaynet generates a single optimal prediction for each object, eliminating the need for non-maximum suppression (NMS). Finally, experimental results on embedded devices demonstrate that YOMO-Runwaynet achieves a detection accuracy of over 89.5% on the ATD (Aerovista Runway Dataset), with a pixel error rate of less than 0.003 for runway keypoint detection, and an inference speed exceeding 90.9 FPS. These results indicate that the YOMO-Runwaynet algorithm offers high accuracy and real-time performance, providing effective support for the visual navigation of fixed-wing aircraft. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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27 pages, 849 KiB  

Open AccessReview

A Critical Review of Information Provision for U-Space Traffic Autonomous Guidance

by Ivan Panov and Asim Ul Haq

Aerospace 2024, 11(6), 471; https://doi.org/10.3390/aerospace11060471 - 12 Jun 2024

Cited by 2 | Viewed by 1858

Abstract

This paper identifies and classifies the essential constraints that must be addressed to allow U-space traffic autonomous guidance. Based on an extensive analysis of the state of the art in robotic guidance, physics of flight, flight safety, communication and navigation, uncrewed aircraft missions, [...] Read more.

This paper identifies and classifies the essential constraints that must be addressed to allow U-space traffic autonomous guidance. Based on an extensive analysis of the state of the art in robotic guidance, physics of flight, flight safety, communication and navigation, uncrewed aircraft missions, artificial intelligence (AI), social expectations in Europe on drones, etc., we analyzed the existing constraints and the information needs that are of essential importance to address the identified constraints. We compared the identified information needs with the last edition of the U-space Concept of Operations and identified critical gaps between the needs and proposed services. A high-level methodology to identify, measure, and close the gaps is proposed. Full article

(This article belongs to the Topic Civil and Public Domain Applications of Unmanned Aviation)

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