Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs)

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 13711

Special Issue Editors


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Guest Editor
Faculty of Smart Vehicle System Engineering, Chosun University, Gwangju 61452, Korea
Interests: energy-efficient path planning; battery state estimation; unmanned system algorithm; SW development
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Guest Editor
Department of Mechanical Engineering; New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA
Interests: robotics and control; multi-agent systems; uncertainty quantification; optimization; asynchronous algorithm
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907, USA
Interests: predictive maintenance; heath monitoring for ground and aerial vehicles; data analytics; AI; innovation; nonlinear systems analysis and synthesis; adaptation; estimation; filtering; control; general artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicle (UAV) services such as sensing, mapping, goods and equipment delivery, inspection, and monitoring have started to grow rapidly with the rapidly falling prices of both drones and the sensors mounted on them. Many of these services involve the gathering of data and their processing with complex algorithms, either in real time or on the cloud, and the precise navigation and path planning of the drones. We invite articles on all aspects of these problems involving UAV services including, but not limited to, the topics below:

  • Data processing and sensor fusion;
  • Obstacle and collision avoidance;
  • Trajectory generation of a single UAV or a group of UAVs;
  • Formation/collaborative control of multiple UAVs;
  • Communications and networks among UAVs;
  • Mission planning for various purposes.

Articles may be submitted on all the areas that currently abound in the news: the inspection of farms, vineyards, ranch animals, petrochemical refineries, oil pipelines and battlefields; the delivery of pesticides and herbicides, food in restaurants, and packages to remote areas and residences; the cutting edge of photography, filming and journalism; search and rescue after catastrophic natural/man-made disasters such as earthquakes, floods, tsunamis, wildfires and explosions; the mapping of various fields—optical, magnetic, acoustic and chemical; and reconnaissance and tactical bombing on the battlefield. Most of these applications have been performed using single UAVs to date, though the use of a multiplicity of UAVs can significantly improve performance.

Prof. Dr. Sunghun Jung
Prof. Dr. Kooktae Lee
Prof. Dr. Kartik B. Ariyur
Guest Editors

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Keywords

  • unmanned aerial vehicle (UAV)
  • data processing and sensor fusion
  • obstacle and collision avoidance
  • trajectory generation
  • formation and collaborative control
  • communications and networks
  • mission planning

Published Papers (5 papers)

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Research

14 pages, 2216 KiB  
Article
Hybrid Power System for the Range Extension of Security Robots: Prototyping Phase
by Woosuk Sung and Yong-Gu Park
Appl. Sci. 2021, 11(24), 12095; https://0-doi-org.brum.beds.ac.uk/10.3390/app112412095 - 19 Dec 2021
Viewed by 1586
Abstract
This paper describes our best practices related to hybrid power system (HPS) development with a focus on the prototyping phase. Based on the main development goals of our security robot, 24 h continuous operation on a single charge as a top priority, the [...] Read more.
This paper describes our best practices related to hybrid power system (HPS) development with a focus on the prototyping phase. Based on the main development goals of our security robot, 24 h continuous operation on a single charge as a top priority, the HPS specifications were developed in the previous phase. For long-duration missions, batteries are hybridized with hydrogen fuel cells. By hybridization, the practical issues of fuel cells can be addressed such as lack of durability and low power density. With the developed specifications of the HPS, its components were acquired and installed to build a prototype. Using an electronic load coupled with a charge-discharge system controller, the constructed prototype was tested, discovering the maximum output power (850 W) that the fuel cell can sustain for 24 h. To further increase the energy density of the HPS, its structure was converted to a plug-in hybrid. With the developed HPS simulator, the converted HPS was simulated, predicting an extended hours of operation (2.07 h) based on the larger battery (7S12P) over the widest SOC window (90%). The plug-in HPS prototype was integrated into the security robot. On a dedicated chassis dynamometer, the integrated prototype was tested, demonstrating its capability to continuously operate the security robot for 24 h. Full article
(This article belongs to the Special Issue Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs))
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19 pages, 4804 KiB  
Article
Hybrid Power System for the Range Extension of Security Robots: Specification Development Phase
by Woosuk Sung
Appl. Sci. 2021, 11(23), 11577; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311577 - 06 Dec 2021
Cited by 1 | Viewed by 1646
Abstract
This paper describes our best practices related to hybrid power system (HPS) development, with a focus on the specification development phase. The HPS specifications are based on the main development goals of our security robot, which place top priority on 24 h continuous [...] Read more.
This paper describes our best practices related to hybrid power system (HPS) development, with a focus on the specification development phase. The HPS specifications are based on the main development goals of our security robot, which place top priority on 24 h continuous operation on a single charge. Similar to human guards, security robots are expected to operate 24 h per day, seven days per week, but existing battery-powered robots cannot meet these goals. For long-duration missions, their operating times are too short, and their charging times are too long. As an effective alternative, hydrogen fuel cells are combined with batteries to hybridize the power systems of security robots. In this study, several HPS structures were comprehensively compared by selecting a one-stage series structure. Component specifications were determined based on the selected structure to achieve the main development goals of our security robot. To verify whether the determined specifications are valid, a HPS simulator was developed. The key operating conditions for the HPS were simulated, including overloading, terminal short-circuiting, and drive cycling. Under critical conditions, the behavior of the entire system and its components was confirmed. The developed specifications will eventually be carried over to the prototyping phase. Full article
(This article belongs to the Special Issue Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs))
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21 pages, 96285 KiB  
Article
End-to-End Deep Reinforcement Learning for Image-Based UAV Autonomous Control
by Jiang Zhao, Jiaming Sun, Zhihao Cai, Longhong Wang and Yingxun Wang
Appl. Sci. 2021, 11(18), 8419; https://0-doi-org.brum.beds.ac.uk/10.3390/app11188419 - 10 Sep 2021
Cited by 6 | Viewed by 2163
Abstract
To achieve the perception-based autonomous control of UAVs, schemes with onboard sensing and computing are popular in state-of-the-art work, which often consist of several separated modules with respective complicated algorithms. Most methods depend on handcrafted designs and prior models with little capacity for [...] Read more.
To achieve the perception-based autonomous control of UAVs, schemes with onboard sensing and computing are popular in state-of-the-art work, which often consist of several separated modules with respective complicated algorithms. Most methods depend on handcrafted designs and prior models with little capacity for adaptation and generalization. Inspired by the research on deep reinforcement learning, this paper proposes a new end-to-end autonomous control method to simplify the separate modules in the traditional control pipeline into a single neural network. An image-based reinforcement learning framework is established, depending on the design of the network architecture and the reward function. Training is performed with model-free algorithms developed according to the specific mission, and the control policy network can map the input image directly to the continuous actuator control command. A simulation environment for the scenario of UAV landing was built. In addition, the results under different typical cases, including both the small and large initial lateral or heading angle offsets, show that the proposed end-to-end method is feasible for perception-based autonomous control. Full article
(This article belongs to the Special Issue Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs))
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33 pages, 12917 KiB  
Article
Conceptual Design and Multi-Disciplinary Computational Investigations of Multirotor Unmanned Aerial Vehicle for Environmental Applications
by Vijayanandh Raja, Senthil Kumar Solaiappan, Parvathy Rajendran, Senthil Kumar Madasamy and Sunghun Jung
Appl. Sci. 2021, 11(18), 8364; https://0-doi-org.brum.beds.ac.uk/10.3390/app11188364 - 09 Sep 2021
Cited by 14 | Viewed by 2933
Abstract
This study focuses on establishing a conceptual design for a multirotor unmanned aerial vehicle (UAV). The objectives of this octocopter are to reduce the number of flight cancelations and car accidents owing to low-visibility issues and to improve abnormal environmental conditions due to [...] Read more.
This study focuses on establishing a conceptual design for a multirotor unmanned aerial vehicle (UAV). The objectives of this octocopter are to reduce the number of flight cancelations and car accidents owing to low-visibility issues and to improve abnormal environmental conditions due to the presence of smoke. The proposed octocopter contains a convergent–divergent [CD] duct-based storage tank, which provides a platform to store saltwater and allows it to fly in foggy zones. Fine saltwater is sprayed from the octocopter and dispersed into the low clouds, thereby altering the vapor’s microphysical processes to break it up and improve visibility. The nature of the seawater and its enhanced fluid properties, due to the involvement of octocopter, creates the fluid flow mixing between atmospheric fluids and spraying particles, which increases the settling of foggy and smokey content groundward. For deployment, the conceptual design of the octocopter was initially constructed through analytical approaches. Additionally, three unique historical relationships were created. The standard engineering approaches involved in this work were stability analysis through MATLAB and fluid-property analysis through computational fluid dynamics (CFD) cum multiple reference frame (MRF) tools. The systematic model of this octocopter was developed by CATIA, and thereafter CFD and fluid–structure-interaction (FSI) analyses were computed, in ANSYS Workbench, on the octocopter for various environmental conditions. The aerodynamic forces on the drone, the enhancement of dynamic pressure by the presence of high amounts of rotors and nozzle sprayer, suitable material to resist aerodynamic loadings, and tests on the efficiency of the controller and its electronic components were investigated in detail. Finally, the proposed octocopter-based dynamic system was conceptually constructed. Full article
(This article belongs to the Special Issue Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs))
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22 pages, 3983 KiB  
Article
Wildlife Monitoring Using a Multi-UAV System with Optimal Transport Theory
by Rabiul Hasan Kabir and Kooktae Lee
Appl. Sci. 2021, 11(9), 4070; https://0-doi-org.brum.beds.ac.uk/10.3390/app11094070 - 29 Apr 2021
Cited by 14 | Viewed by 3834
Abstract
This paper addresses a wildlife monitoring problem using a team of unmanned aerial vehicles (UAVs) with the optimal transport theory. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based [...] Read more.
This paper addresses a wildlife monitoring problem using a team of unmanned aerial vehicles (UAVs) with the optimal transport theory. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based sensing or GPS trackers. However, there still exist unsolved problems as to how the UAVs need to cover a spacious domain to detect animals as many as possible. In this paper, we propose the optimal transport-based wildlife monitoring strategy for a multi-UAV system, to prioritize monitoring areas while incorporating complementary information such as GPS trackers and satellite-based sensing. Through the proposed scheme, the UAVs can explore the large-size domain effectively and collaboratively with a given priority. The time-varying nature of wildlife due to their movements is modeled as a stochastic process, which is included in the proposed work to reflect the spatio-temporal evolution of their position estimation. In this way, the proposed monitoring plan can lead to wildlife monitoring with a high detection rate. Various simulation results including statistical data are provided to validate the proposed work. In all different simulations, it is shown that the proposed scheme significantly outperforms other UAV-based wildlife monitoring strategies in terms of the target detection rate up to 3.6 times. Full article
(This article belongs to the Special Issue Cutting-Edge Technologies of the Unmanned Aerial Vehicles (UAVs))
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