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Unmanned Aerial Vehicles (UAVs) and Their Applications
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Unmanned Aerial Vehicles (UAVs) and Their Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 18266

Special Issue Editors

Dr. Nuno Pessanha Santos

E-Mail Website
Guest Editor
Portuguese Military Academy (Academia Militar), 1163-203 Lisbon, Portugal
Interests: robotics; computer vision applications; machine learning; motion estimation; algorithm design applied to advanced robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Bruno Damas

E-Mail Website
Guest Editor
Computer and Robot Vision Lab (VisLab), Institute For Systems and Robotics, 1049-001 Lisbon, Portugal
Interests: robotics; artificial intelligence
Prof. Dr. Victor Lobo

E-Mail Website
Guest Editor
Portuguese Naval Academy (Escola Naval), 2810-001 Almada, Portugal
Interests: machine learning; self-organizing maps; robotics; algorithm design applied to advanced robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, unmanned aerial vehicles (UAVs) are becoming commonly used equipment, and their technology is evolving, from the military to the civilian domain. The precursors of this technology are based on the use of kites and balloons in the 19th century to spread information quickly.

In the UAV field, many applications have emerged in the past years, showing the advantages of civilian interest in the field. UAVs are deployed in applications such as light rail station connections, ferry station setup, tunnel traffic diversion, military applications, surveillance, and maintenance inspections, among others. It is essential to share the most current applications and algorithms with the UAV research community to be able to boost its development.

This Special Issue aims to collect original research articles and reviews on recent advances in every aspect of UAVs and their applications. If you are interested in this topic, please contact us.

Dr. Nuno Pessanha Santos
Dr. Bruno Damas
Prof. Dr. Victor Lobo
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • Unmanned aerial vehicles
  • Autonomous landing
  • Artificial intelligence
  • Computer vision
  • Control systems
  • Vehicle design
  • Military systems
  • Communication systems
  • Radar systems
  • Antenna design
 
 

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Published Papers (4 papers)

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Research

16 pages, 4649 KiB  
Article
Feasibility of Visual Question Answering (VQA) for Post-Disaster Damage Detection Using Aerial Footage
by Rafael De Sa Lowande and Hakki Erhan Sevil
Appl. Sci. 2023, 13(8), 5079; https://doi.org/10.3390/app13085079 - 19 Apr 2023
Cited by 5 | Viewed by 1729
Abstract
Natural disasters are a major source of significant damage and costly repairs around the world. After a natural disaster occurs, there is usually a significant amount of damage, and with that, there are also a lot of costs involved with repairing and aiding [...] Read more.
Natural disasters are a major source of significant damage and costly repairs around the world. After a natural disaster occurs, there is usually a significant amount of damage, and with that, there are also a lot of costs involved with repairing and aiding all the people involved. In addition, the occurrence of natural phenomena has increased significantly in the past decade. With that in mind, post-disaster damage detection is usually performed manually by human operators. Taking into consideration all the areas one has to closely look into, as well as the difficult terrain and places with hard access, it becomes easy to understand how incredibly difficult it is for a surveyor to identify and annotate every single possible damage out there. Because of that, it has become essential to find new creative solutions for damage detection and classification in the case of natural disasters, especially hurricanes. This study focuses on the feasibility of using a Visual Question Answering (VQA) method for post-disaster damage detection, using aerial footage taken from an Unmanned Aerial Vehicle (UAV). Two other approaches are also utilized to provide comparison and to evaluate the performance of VQA. Our case study on our custom dataset collected after Hurricane Sally shows successful results using VQA for post-disaster damage detection applications. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) and Their Applications)
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21 pages, 6138 KiB  
Article
ReconTraj4Drones: A Framework for the Reconstruction and Semantic Modeling of UAVs’ Trajectories on MovingPandas
by Konstantinos Kotis and Andreas Soularidis
Appl. Sci. 2023, 13(1), 670; https://doi.org/10.3390/app13010670 - 3 Jan 2023
Cited by 2 | Viewed by 2930
Abstract
Unmanned aerial vehicles (UAVs), also known as drones, are important for several application domains, such as the military, agriculture, cultural heritage documentation, surveillance, and the delivery of goods/products/services. A drone’s trajectory can be enriched with external and heterogeneous data beyond latitude, longitude, and [...] Read more.
Unmanned aerial vehicles (UAVs), also known as drones, are important for several application domains, such as the military, agriculture, cultural heritage documentation, surveillance, and the delivery of goods/products/services. A drone’s trajectory can be enriched with external and heterogeneous data beyond latitude, longitude, and timestamp to create its semantic trajectory, providing meaningful and contextual information on its movement data, enabling decision makers to acquire meaningful and enriched contextual information about the current situation in the field of its operation and eventually supporting simulations and predictions of high-level critical events. In this paper, we present an ontology-based, tool-supported framework for the reconstruction, modeling, and enrichment of drones’ semantic trajectories. This framework extends MovingPandas, a widely used and open-source trajectory analytics and visualization tool. The presented research extends our preliminary work on drones’ semantic trajectories by contributing (a) an updated methodology for the reconstruction of drones’ trajectories from geo-tagged photos taken by drones during their flights in cases in which flight plans and/or real-time movement data have been lost or corrupted; (b) an enrichment of the reconstructed trajectories with external data; (c) the semantic annotation of the enriched trajectories based on a related ontology; and (d) the use of SPARQL queries to analyze and retrieve knowledge related to the flight of a drone and the field of operations (context). An evaluation of the presented framework, namely, ReconTraj4Drones, was conducted against several criteria, using real and open datasets. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) and Their Applications)
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9 pages, 4062 KiB  
Communication
The Electronic Switch of Windings of a Standard BLDC Motor
by Vadim Carev, Jan Roháč, Sergey Tkachenko and Konstantin Alloyarov
Appl. Sci. 2022, 12(21), 11096; https://doi.org/10.3390/app122111096 - 2 Nov 2022
Cited by 5 | Viewed by 9538
Abstract
Nowadays, one of the most promising areas in the motor industry is the production of BLDC motors, which are used in a wide range of applications and products—from power tools to electrical vehicles. The windings of BLDC motors are connected according to the [...] Read more.
Nowadays, one of the most promising areas in the motor industry is the production of BLDC motors, which are used in a wide range of applications and products—from power tools to electrical vehicles. The windings of BLDC motors are connected according to the Delta or Star circuits. However, such circuits (Delta or Star) do not allow dynamically changing the parameters of the BLDC motor during operation and thus reducing the overall motor efficiency. This paper deals with and proposes an electronic switch of the BLDC motor windings, which brings an advantage in having a capability of dynamically switching the windings during operation and thus increasing the efficiency of the BLDC motor performance. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) and Their Applications)
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23 pages, 1689 KiB  
Article
A Reinforcement Learning Model of Multiple UAVs for Transporting Emergency Relief Supplies
by Daiki Hachiya, Erick Mas and Shunichi Koshimura
Appl. Sci. 2022, 12(20), 10427; https://doi.org/10.3390/app122010427 - 16 Oct 2022
Cited by 11 | Viewed by 2797
Abstract
In large-scale disasters, such as earthquakes and tsunamis, quick and sufficient transportation of emergency relief supplies is required. Logistics activities conducted to quickly provide appropriate aid supplies (relief goods) to people affected by disasters are known as humanitarian logistics (HL), and play an [...] Read more.
In large-scale disasters, such as earthquakes and tsunamis, quick and sufficient transportation of emergency relief supplies is required. Logistics activities conducted to quickly provide appropriate aid supplies (relief goods) to people affected by disasters are known as humanitarian logistics (HL), and play an important role in terms of saving the lives of those affected. In the previous last-mile distribution of HL, supplies are transported by trucks and helicopters, but these transport methods are sometimes not feasible. Therefore, the use of unmanned aerial vehicles (UAVs) to transport supplies is attracting attention due to their convenience regardless of the disaster conditions. However, existing transportation planning that utilizes UAVs may not meet some of the requirements for post-disaster transport of supplies. Equitable distribution of supplies among affected shelters is particularly important in a crisis situation, but it has not been a major consideration in the logistics of UAVs in the existing study. Therefore, this study proposes transportation planning by introducing three crucial performance metrics: (1) the rapidity of supplies, (2) the urgency of supplies, and (3) the equity of supply amounts. We formulated the routing problem of UAVs as the multi-objective, multi-trip, multi-item, and multi-UAV problem, and optimize the problem with Q-learning (QL), one of the reinforcement learning methods. We performed reinforcement learning for multiple cases with different rewards and quantitatively evaluated the transportation of each countermeasure by comparing them. The results suggest that the model improved the stability of the supply of emergency relief supplies to all evacuation centers when compared to other models. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs) and Their Applications)
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