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3 pages, 181 KiB

Open AccessEditorial

Special Issue on Unmanned Aerial Vehicles

by Sylvain Bertrand and Hyo-Sang Shin

Appl. Sci. 2023, 13(7), 4134; https://doi.org/10.3390/app13074134 - 24 Mar 2023

Cited by 1 | Viewed by 982

Abstract

Unmanned Aerial Vehicles (UAVs) are recognized as very useful tools to replace, help, or assist humans in various missions, such as inspection and monitoring, surveillance, search and rescue, exploration, logistics and transportation, etc [...] Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

Research

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39 pages, 1590 KiB

Open AccessArticle

Validation of a Wind Tunnel Propeller Dynamometer for Group 2 Unmanned Aircraft

by Muwanika Jdiobe, Kurt Rouser, Ryan Paul and Austin Rouser

Appl. Sci. 2022, 12(17), 8908; https://doi.org/10.3390/app12178908 - 05 Sep 2022

Cited by 1 | Viewed by 1916

Abstract

This paper presents an approach to validate a wind tunnel propeller dynamometer applicable to Group 2 unmanned aircraft. The intended use of such a dynamometer is to characterize propellers over a relevant range of sizes and operating conditions, under which such propellers are [...] Read more.

This paper presents an approach to validate a wind tunnel propeller dynamometer applicable to Group 2 unmanned aircraft. The intended use of such a dynamometer is to characterize propellers over a relevant range of sizes and operating conditions, under which such propellers are susceptible to low-Reynolds-number effects that can be challenging to experimentally detect in a wind tunnel. Even though uncertainty analysis may inspire confidence in dynamometer data, it is possible that a dynamometer design or experimental arrangement (e.g., configuration and instrumentation) is not able to detect significant propeller characteristics and may even impart artifacts in the results. The validation method proposed here compares analytical results from Blade Element Momentum Theory (BEMT) to experimental data to verify that a dynamometer captures basic propeller physics, as well as self-similar experimental results to verify that a dynamometer is able to resolve differences in propeller diameter and pitch. Two studies were conducted to verify that dynamometer experimental data match the performance predicted by BEMT. The first study considered three propellers with the same 18-inch (0.457 m) diameter and varied pitch from 10 to 14 inches (0.254 to 0.356 m). The second study held pitch constant and varied diameter from 14 to 18 inches (0.356 to 0.457 m). During testing, wind tunnel speeds ranged from 25 ft/s to 50 ft/s ( 7.62 to 15.24 m/s), and propeller rotational speeds varied from 1500 to 5500 revolutions per minute (RPM). Analytical results from a BEMT code were compared to available experimental data from previous work to show proper application of the code to predict performance. Dynamometer experimental results for thrust coefficient and propeller efficiency were then compared to BEMT results. Experimental results were consistent with the expected effect of varying pitch and diameter and were in close agreement with BEMT predictions, lending confidence that the dynamometer performed as expected and is dependable for future data collection efforts. The method used in this study is recommended for validating wind tunnel propeller dynamometers, especially for Group 2 unmanned aircraft, to ensure reliable performance data. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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24 pages, 23044 KiB

Open AccessArticle

A Small UAV Optimized for Efficient Long-Range and VTOL Missions: An Experimental Tandem-Wing Quadplane Drone

by Michał Okulski and Maciej Ławryńczuk

Appl. Sci. 2022, 12(14), 7059; https://doi.org/10.3390/app12147059 - 13 Jul 2022

Cited by 11 | Viewed by 9630

Abstract

Most types of Unmanned Aerial Vehicle (UAV, drone) missions requiring Vertical-Take-Off-and-Landing (VTOL) capability could benefit if a drone’s effective range could be extended. Example missions include Search-And-Rescue (SAR) operations, a remote inspection of distant objects, or parcel delivery. There are numerous research works [...] Read more.

Most types of Unmanned Aerial Vehicle (UAV, drone) missions requiring Vertical-Take-Off-and-Landing (VTOL) capability could benefit if a drone’s effective range could be extended. Example missions include Search-And-Rescue (SAR) operations, a remote inspection of distant objects, or parcel delivery. There are numerous research works on multi-rotor drones (e.g., quadcopters), fixed-wing drones, VTOL quadplanes, or tilt-motor/tilt-wing VTOLs. We propose a unique compact VTOL UAV optimized for long hover and long-range missions with great lifting capacity and manoeuvrability: a tandem-wing quadplane with fixed motors only. To the best of our knowledge, such a drone has not yet been researched. The drone was designed, built, and tested in flight. Construction details, its advantages, and issues are discussed in this research. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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23 pages, 9615 KiB

Open AccessArticle

Multirotor Unmanned Aerial Vehicle Configuration Optimization Approach for Development of Actuator Fault-Tolerant Structure

by Yisak Debele, Ha-Young Shi, Assefinew Wondosen, Jin-Hee Kim and Beom-Soo Kang

Appl. Sci. 2022, 12(13), 6781; https://doi.org/10.3390/app12136781 - 04 Jul 2022

Cited by 2 | Viewed by 2205

Abstract

Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing the achievable forces and moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns [...] Read more.

Presently, multirotor unmanned aerial vehicles (UAV) are utilized in numerous applications. Their design governs the system’s controllability and operation performance by influencing the achievable forces and moments produced. However, unexpected causalities, such as actuator failure, adversely affect their controllability, which raises safety concerns about their service. On the other hand, their design flexibility allows further design optimization for various performance requirements, including actuator failure tolerance. Thus, this study proposed an optimization framework that can be employed to design a novel actuator fault-tolerant multirotor UAV configuration. The approach used an attainable moment set (AMS) to evaluate the achievable moment from a multirotor configuration; similarly, standard deviation geometries (SDG) were employed to define performance requirements. Therefore, given a UAV configuration, actuator fault situation, and SDG derived from the designed mission requirement, the suggested optimization framework maximizes the scaling factor of SDG and fits it into the AMS by adjusting the design parameters up to a sufficient margin. The framework is implemented to optimize selected parameters of the Hexacopter-type of parcel delivery multirotor UAV developed by the PNU drone, and a simulation was conducted. The result showed that the optimized configuration of the UAV achieved actuator fault tolerance and operation-performing capability in the presence of a failed actuator. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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19 pages, 7506 KiB

Open AccessArticle

Swarm Intelligence with Deep Transfer Learning Driven Aerial Image Classification Model on UAV Networks

by Saud S. Alotaibi, Hanan Abdullah Mengash, Noha Negm, Radwa Marzouk, Anwer Mustafa Hilal, Mohamed A. Shamseldin, Abdelwahed Motwakel, Ishfaq Yaseen, Mohammed Rizwanullah and Abu Sarwar Zamani

Appl. Sci. 2022, 12(13), 6488; https://doi.org/10.3390/app12136488 - 26 Jun 2022

Cited by 3 | Viewed by 1539

Abstract

Nowadays, unmanned aerial vehicles (UAVs) have gradually attracted the attention of many academicians and researchers. The UAV has been found to be useful in variety of applications, such as disaster management, intelligent transportation system, wildlife monitoring, and surveillance. In UAV aerial images, learning [...] Read more.

Nowadays, unmanned aerial vehicles (UAVs) have gradually attracted the attention of many academicians and researchers. The UAV has been found to be useful in variety of applications, such as disaster management, intelligent transportation system, wildlife monitoring, and surveillance. In UAV aerial images, learning effectual image representation was central to scene classifier method. The previous approach to the scene classification method depends on feature coding models with lower-level handcrafted features or unsupervised feature learning. The emergence of convolutional neural network (CNN) is developing image classification techniques more effectively. Due to the limited resource in UAVs, it can be difficult to fine-tune the hyperparameter and the trade-offs amongst computation complexity and classifier results. This article focuses on the design of swarm intelligence with deep transfer learning driven aerial image classification (SIDTLD-AIC) model on UAV networks. The presented SIDTLD-AIC model involves the proper identification and classification of images into distinct kinds. For accomplishing this, the presented SIDTLD-AIC model follows a feature extraction module using RetinaNet model in which the hyperparameter optimization process is performed by the use of salp swarm algorithm (SSA). In addition, a cascaded long short term memory (CLSTM) model is executed for classifying the aerial images. At last, seeker optimization algorithm (SOA) is applied as a hyperparameter optimizer of the CLSTM model and thereby results in enhanced classification accuracy. To assure the better performance of the SIDTLD-AIC model, a wide range of simulations are implemented and the outcomes are investigated in many aspects. The comparative study reported the better performance of the SIDTLD-AIC model over recent approaches. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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11 pages, 460 KiB

Open AccessArticle

Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

by Laura Pierucci

Appl. Sci. 2022, 12(2), 895; https://doi.org/10.3390/app12020895 - 16 Jan 2022

Cited by 3 | Viewed by 1482

Abstract

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple [...] Read more.

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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24 pages, 9061 KiB

Open AccessArticle

Airspace Geofencing and Flight Planning for Low-Altitude, Urban, Small Unmanned Aircraft Systems

by Joseph Kim and Ella Atkins

Appl. Sci. 2022, 12(2), 576; https://doi.org/10.3390/app12020576 - 07 Jan 2022

Cited by 23 | Viewed by 4230

Abstract

Airspace geofencing is a key capability for low-altitude Unmanned Aircraft System (UAS) Traffic Management (UTM). Geofenced airspace volumes can be allocated to safely contain compatible UAS flight operations within a fly-zone (keep-in geofence) and ensure the avoidance of no-fly zones (keep-out geofences). This [...] Read more.

Airspace geofencing is a key capability for low-altitude Unmanned Aircraft System (UAS) Traffic Management (UTM). Geofenced airspace volumes can be allocated to safely contain compatible UAS flight operations within a fly-zone (keep-in geofence) and ensure the avoidance of no-fly zones (keep-out geofences). This paper presents the application of three-dimensional flight volumization algorithms to support airspace geofence management for UTM. Layered polygon geofence volumes enclose user-input waypoint-based 3-D flight trajectories, and a family of flight trajectory solutions designed to avoid keep-out geofence volumes is proposed using computational geometry. Geofencing and path planning solutions are analyzed in an accurately mapped urban environment. Urban map data processing algorithms are presented. Monte Carlo simulations statistically validate our algorithms, and runtime statistics are tabulated. Benchmark evaluation results in a Manhattan, New York City low-altitude environment compare our geofenced dynamic path planning solutions against a fixed airway corridor design. A case study with UAS route deconfliction is presented, illustrating how the proposed geofencing pipeline supports multi-vehicle deconfliction. This paper contributes to the nascent theory and the practice of dynamic airspace geofencing in support of UTM. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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19 pages, 1592 KiB

Open AccessArticle

Designing a Reliable UAV Architecture Operating in a Real Environment

by Krzysztof Andrzej Gromada and Wojciech Marcin Stecz

Appl. Sci. 2022, 12(1), 294; https://doi.org/10.3390/app12010294 - 29 Dec 2021

Cited by 7 | Viewed by 2642

Abstract

The article presents a method of designing a selected unmanned aerial platform flight scenario based on the principles of designing a reliable (Unmanned Aerial Vehicle) UAV architecture operating in an environment in which other platforms operate. The models and results presented relate to [...] Read more.

The article presents a method of designing a selected unmanned aerial platform flight scenario based on the principles of designing a reliable (Unmanned Aerial Vehicle) UAV architecture operating in an environment in which other platforms operate. The models and results presented relate to the medium-range aerial platform, subject to certification under the principles set out in aviation regulations. These platforms are subject to the certification process requirements, but their restrictions are not as restrictive as in the case of manned platforms. Issues related to modeling scenarios implemented by the platform in flight are discussed. The article describes the importance of Functional Hazard Analysis (FHA) and Fault Trees Analysis (FTA) of elements included in the hardware and software architecture of the system. The models in Unified Modeling Language (UML) used by the authors in the project are described, supporting the design of a reliable architecture of flying platforms. Examples of the transformations from user requirements modeled in the form of Use Cases to platform operation models based on State Machines and then to the final UAV operation algorithms are shown. Principles of designing system test plans and designing individual test cases to verify the system’s operation in emergencies in flight are discussed. Methods of integrating flight simulators with elements of the air platform in the form of Software-in-the-Loop (SIL) models based on selected algorithms for avoiding dangerous situations have been described. The presented results are based on a practical example of an algorithm for detecting an air collision situation of two platforms. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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23 pages, 5849 KiB

Open AccessArticle

Simulation and Analysis of Grid Formation Method for UAV Clusters Based on the 3 × 3 Magic Square and the Chain Rules of Visual Reference

by Rui Qiao, Guili Xu, Yuehua Cheng, Zhengyu Ye and Jinlong Huang

Appl. Sci. 2021, 11(23), 11560; https://doi.org/10.3390/app112311560 - 06 Dec 2021

Cited by 3 | Viewed by 1990

Abstract

Large-scale unmanned aerial vehicle (UAV) formations are vulnerable to disintegration under electromagnetic interference and fire attacks. To address this issue, this work proposed a distributed formation method of UAVs based on the 3 × 3 magic square and the chain rules of visual [...] Read more.

Large-scale unmanned aerial vehicle (UAV) formations are vulnerable to disintegration under electromagnetic interference and fire attacks. To address this issue, this work proposed a distributed formation method of UAVs based on the 3 × 3 magic square and the chain rules of visual reference. Enlightened by the biomimetic idea of the plane formation of starling flocks, this method adopts the technical means of airborne vision and a cooperative target. The topological structure of the formation’s visual reference network showed high static stability under the measurement of the network connectivity index. In addition, the dynamic self-healing ability of this network was analyzed. Finally, a simulation of a battlefield using matlab showed that, when the loss of UAVs reaches 85% for formations with different scales, the UAVs breaking formation account for 5.1–6% of the total in the corresponding scale, and those keeping formation account for 54.4–65.7% of the total undestroyed fleets. The formation method designed in this paper can maintain the maximum number of UAVs in formation on the battlefield. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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21 pages, 2825 KiB

Open AccessArticle

Terminal Distributed Cooperative Guidance Law for Multiple UAVs Based on Consistency Theory

by Zhanyuan Jiang, Jianquan Ge, Qiangqiang Xu and Tao Yang

Appl. Sci. 2021, 11(18), 8326; https://doi.org/10.3390/app11188326 - 08 Sep 2021

Cited by 3 | Viewed by 1429

Abstract

In order to realize a saturation attack of multiple unmanned aerial vehicles (UAVs) on the same target, the problem is transformed into one of multiple UAVs hitting the same target simultaneously, and a terminal distributed cooperative guidance law for multiple UAVs based on [...] Read more.

In order to realize a saturation attack of multiple unmanned aerial vehicles (UAVs) on the same target, the problem is transformed into one of multiple UAVs hitting the same target simultaneously, and a terminal distributed cooperative guidance law for multiple UAVs based on consistency theory is proposed. First, a new time-to-go estimation method is proposed, which is more accurate than the existing methods when the leading angle is large. Second, a non-singular sliding mode guidance law (NSMG) of impact time control with equivalent control term and switching control term is designed, which still appears to have excellent performance even if the initial leading angle is zero. Then, based on the predicted crack point strategy, the NSMG law is extended to attack maneuvering targets. Finally, adopting hierarchical cooperative guidance architecture, a terminal distributed cooperative guidance law based on consistency theory is designed. Numerical simulation results verify that the terminal distributed cooperative guidance law is not only applicable to different forms of communication topology, but also effective in the case of communication topology switching. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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14 pages, 615 KiB

Open AccessArticle

Evaluation of Reinforcement and Deep Learning Algorithms in Controlling Unmanned Aerial Vehicles

by Yalew Zelalem Jembre, Yuniarto Wimbo Nugroho, Muhammad Toaha Raza Khan, Muhammad Attique, Rajib Paul, Syed Hassan Ahmed Shah and Beomjoon Kim

Appl. Sci. 2021, 11(16), 7240; https://doi.org/10.3390/app11167240 - 06 Aug 2021

Cited by 9 | Viewed by 3056

Abstract

Unmanned Aerial Vehicles (UAVs) are abundantly becoming a part of society, which is a trend that is expected to grow even further. The quadrotor is one of the drone technologies that is applicable in many sectors and in both military and civilian activities, [...] Read more.

Unmanned Aerial Vehicles (UAVs) are abundantly becoming a part of society, which is a trend that is expected to grow even further. The quadrotor is one of the drone technologies that is applicable in many sectors and in both military and civilian activities, with some applications requiring autonomous flight. However, stability, path planning, and control remain significant challenges in autonomous quadrotor flights. Traditional control algorithms, such as proportional-integral-derivative (PID), have deficiencies, especially in tuning. Recently, machine learning has received great attention in flying UAVs to desired positions autonomously. In this work, we configure the quadrotor to fly autonomously by using agents (the machine learning schemes being used to fly the quadrotor autonomously) to learn about the virtual physical environment. The quadrotor will fly from an initial to a desired position. When the agent brings the quadrotor closer to the desired position, it is rewarded; otherwise, it is punished. Two reinforcement learning models, Q-learning and SARSA, and a deep learning deep Q-network network are used as agents. The simulation is conducted by integrating the robot operating system (ROS) and Gazebo, which allowed for the implementation of the learning algorithms and the physical environment, respectively. The result has shown that the Deep Q-network network with Adadelta optimizer is the best setting to fly the quadrotor from the initial to desired position. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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20 pages, 9213 KiB

Open AccessArticle

Robust Approach to Supervised Deep Neural Network Training for Real-Time Object Classification in Cluttered Indoor Environment

by Bedada Endale, Abera Tullu, Hayoung Shi and Beom-Soo Kang

Appl. Sci. 2021, 11(15), 7148; https://doi.org/10.3390/app11157148 - 02 Aug 2021

Cited by 2 | Viewed by 2282

Abstract

Unmanned aerial vehicles (UAVs) are being widely utilized for various missions: in both civilian and military sectors. Many of these missions demand UAVs to acquire artificial intelligence about the environments they are navigating in. This perception can be realized by training a computing [...] Read more.

Unmanned aerial vehicles (UAVs) are being widely utilized for various missions: in both civilian and military sectors. Many of these missions demand UAVs to acquire artificial intelligence about the environments they are navigating in. This perception can be realized by training a computing machine to classify objects in the environment. One of the well known machine training approaches is supervised deep learning, which enables a machine to classify objects. However, supervised deep learning comes with huge sacrifice in terms of time and computational resources. Collecting big input data, pre-training processes, such as labeling training data, and the need for a high performance computer for training are some of the challenges that supervised deep learning poses. To address these setbacks, this study proposes mission specific input data augmentation techniques and the design of light-weight deep neural network architecture that is capable of real-time object classification. Semi-direct visual odometry (SVO) data of augmented images are used to train the network for object classification. Ten classes of 10,000 different images in each class were used as input data where 80% were for training the network and the remaining 20% were used for network validation. For the optimization of the designed deep neural network, a sequential gradient descent algorithm was implemented. This algorithm has the advantage of handling redundancy in the data more efficiently than other algorithms. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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26 pages, 1188 KiB

Open AccessFeature PaperArticle

Path Planning Method for UAVs Based on Constrained Polygonal Space and an Extremely Sparse Waypoint Graph

by Abdul Majeed and Seong Oun Hwang

Appl. Sci. 2021, 11(12), 5340; https://doi.org/10.3390/app11125340 - 08 Jun 2021

Cited by 8 | Viewed by 3286

Abstract

Finding an optimal/quasi-optimal path for Unmanned Aerial Vehicles (UAVs) utilizing full map information yields time performance degradation in large and complex three-dimensional (3D) urban environments populated by various obstacles. A major portion of the computing time is usually wasted on modeling and exploration [...] Read more.

Finding an optimal/quasi-optimal path for Unmanned Aerial Vehicles (UAVs) utilizing full map information yields time performance degradation in large and complex three-dimensional (3D) urban environments populated by various obstacles. A major portion of the computing time is usually wasted on modeling and exploration of spaces that have a very low possibility of providing optimal/sub-optimal paths. However, computing time can be significantly reduced by searching for paths solely in the spaces that have the highest priority of providing an optimal/sub-optimal path. Many Path Planning (PP) techniques have been proposed, but a majority of the existing techniques equally evaluate many spaces of the maps, including unlikely ones, thereby creating time performance issues. Ignoring high-probability spaces and instead exploring too many spaces on maps while searching for a path yields extensive computing-time overhead. This paper presents a new PP method that finds optimal/quasi-optimal and safe (e.g., collision-free) working paths for UAVs in a 3D urban environment encompassing substantial obstacles. By using Constrained Polygonal Space (CPS) and an Extremely Sparse Waypoint Graph (ESWG) while searching for a path, the proposed PP method significantly lowers pathfinding time complexity without degrading the length of the path by much. We suggest an intelligent method exploiting obstacle geometry information to constrain the search space in a 3D polygon form from which a quasi-optimal flyable path can be found quickly. Furthermore, we perform task modeling with an ESWG using as few nodes and edges from the CPS as possible, and we find an abstract path that is subsequently improved. The results achieved from extensive experiments, and comparison with prior methods certify the efficacy of the proposed method and verify the above assertions. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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19 pages, 10943 KiB

Open AccessArticle

Machine Learning Approach to Real-Time 3D Path Planning for Autonomous Navigation of Unmanned Aerial Vehicle

by Abera Tullu, Bedada Endale, Assefinew Wondosen and Ho-Yon Hwang

Appl. Sci. 2021, 11(10), 4706; https://doi.org/10.3390/app11104706 - 20 May 2021

Cited by 21 | Viewed by 5357

Abstract

The need for civilian use of Unmanned Aerial Vehicles (UAVs) has drastically increased in recent years. Their potential applications for civilian use include door-to-door package delivery, law enforcement, first aid, and emergency services in urban areas, which put the UAVs into obstacle collision [...] Read more.

The need for civilian use of Unmanned Aerial Vehicles (UAVs) has drastically increased in recent years. Their potential applications for civilian use include door-to-door package delivery, law enforcement, first aid, and emergency services in urban areas, which put the UAVs into obstacle collision risk. Therefore, UAVs are required to be equipped with sensors so as to acquire Artificial Intelligence (AI) to avoid potential risks during mission execution. The AI comes with intensive training of an on-board machine that is responsible to autonomously navigate the UAV. The training enables the UAV to develop humanoid perception of the environment it is to be navigating in. During the mission, this perception detects and localizes objects in the environment. It is based on this AI that this work proposes a real-time three-dimensional (3D) path planner that maneuvers the UAV towards destination through obstacle-free path. The proposed path planner has a heuristic sense of

A^{⋆}

algorithm, but requires no frontier nodes to be stored in a memory unlike

A^{⋆}

. The planner relies on relative locations of detected objects (obstacles) and determines collision-free paths. This path planner is light-weight and hence a fast guidance method for real-time purposes. Its performance efficiency is proved through rigorous Software-In-The-Loop (SITL) simulations in constrained-environment and preliminary real flight tests. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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16 pages, 5566 KiB

Open AccessArticle

A Comparative Performance Evaluation of Routing Protocols for Flying Ad-Hoc Networks in Real Conditions

by Antonio Guillen-Perez, Ana-Maria Montoya, Juan-Carlos Sanchez-Aarnoutse and Maria-Dolores Cano

Appl. Sci. 2021, 11(10), 4363; https://doi.org/10.3390/app11104363 - 11 May 2021

Cited by 25 | Viewed by 3989

Abstract

Unmanned aerial vehicles (UAVs) are widely used in our modern society and their development is rapidly accelerating. Flying Ad Hoc Networks (FANETs) have opened a new window of opportunity to create new value-added services. However, the characteristics that make FANETs unique, such as [...] Read more.

Unmanned aerial vehicles (UAVs) are widely used in our modern society and their development is rapidly accelerating. Flying Ad Hoc Networks (FANETs) have opened a new window of opportunity to create new value-added services. However, the characteristics that make FANETs unique, such as node mobility, node distance, energy constraints, etc., imply that several guidelines need to be considered for their successful deployment. Although numerous routing protocols have been proposed for FANETs, due to the wide range of applications in which FANETs can be applied, not all routing protocols can be used. Due to this challenge, after breaking down and classifying the different types of existing routing protocols for FANET, this paper analyzes and compares the performance of several routing protocols (Babel, BATMAN-ADV, and OLSR) in terms of throughput and packet loss in a real deployment composed of several UAV nodes using 2.4 and 5 GHz WiFi networks. The results show that Babel achieves better performance in the studied metrics than OLSR and BATMAN-ADV, while BATMAN-ADV delivers significantly lower performance. This experimental study confirms the importance of choosing the proper routing protocol for FANETs and their performance evaluation, something that will be extremely important in a few years when this type of network will be common in our day-to-day life. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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24 pages, 9473 KiB

Open AccessFeature PaperArticle

Unmanned Aerial Traffic Management System Architecture for U-Space In-Flight Services

by Carlos Capitán, Héctor Pérez-León, Jesús Capitán, Ángel Castaño and Aníbal Ollero

Appl. Sci. 2021, 11(9), 3995; https://doi.org/10.3390/app11093995 - 28 Apr 2021

Cited by 15 | Viewed by 3424

Abstract

This paper presents a software architecture for Unmanned aerial system Traffic Management (UTM). The work is framed within the U-space ecosystem, which is the European initiative for UTM in the civil airspace. We propose a system that focuses on providing the required services [...] Read more.

This paper presents a software architecture for Unmanned aerial system Traffic Management (UTM). The work is framed within the U-space ecosystem, which is the European initiative for UTM in the civil airspace. We propose a system that focuses on providing the required services for automated decision-making during real-time threat management and conflict resolution, which is the main gap in current UTM solutions. Nonetheless, our software architecture follows an open-source design that is modular and flexible enough to accommodate additional U-space services in future developments. In its current implementation, our UTM solution is capable of tracking the aerial operations and monitoring the airspace in real time, in order to perform in-flight emergency management and tactical deconfliction. We show experimental results in order to demonstrate the UTM system working in a realistic simulation setup. For that, we performed our tests with the UTM system and the operators of the aerial aircraft located at remote locations with the consequent communication issues, and we showcased that the system was capable of managing in real time the conflicting events in two different use cases. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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14 pages, 462 KiB

Open AccessFeature PaperArticle

Drone Ground Impact Footprints with Importance Sampling: Estimation and Sensitivity Analysis

by Jérôme Morio, Baptiste Levasseur and Sylvain Bertrand

Appl. Sci. 2021, 11(9), 3871; https://doi.org/10.3390/app11093871 - 25 Apr 2021

Cited by 5 | Viewed by 1390

Abstract

This paper addresses the estimation of accurate extreme ground impact footprints and probabilistic maps due to a total loss of control of fixed-wing unmanned aerial vehicles after a main engine failure. In this paper, we focus on the ground impact footprints that contains [...] Read more.

This paper addresses the estimation of accurate extreme ground impact footprints and probabilistic maps due to a total loss of control of fixed-wing unmanned aerial vehicles after a main engine failure. In this paper, we focus on the ground impact footprints that contains 95%, 99% and 99.9% of the drone impacts. These regions are defined here with density minimum volume sets and may be estimated by Monte Carlo methods. As Monte Carlo approaches lead to an underestimation of extreme ground impact footprints, we consider in this article multiple importance sampling to evaluate them. Then, we perform a reliability oriented sensitivity analysis, to estimate the most influential uncertain parameters on the ground impact position. We show the results of these estimations on a realistic drone flight scenario. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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13 pages, 2288 KiB

Open AccessArticle

Robust Quadrotor Control through Reinforcement Learning with Disturbance Compensation

by Chen-Huan Pi, Wei-Yuan Ye and Stone Cheng

Appl. Sci. 2021, 11(7), 3257; https://doi.org/10.3390/app11073257 - 05 Apr 2021

Cited by 25 | Viewed by 4338

Abstract

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output [...] Read more.

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output is directly mapped to four actuators in an end-to-end manner. The proposed control scheme constructs a disturbance observer to estimate the external forces exerted on the three axes of the quadrotor, such as wind gusts in an outdoor environment. By introducing an interference compensator into the neural network control agent, the tracking accuracy and robustness were significantly increased in indoor and outdoor experiments. The experimental results indicate that the proposed control strategy is highly robust to external disturbances. In the experiments, compensation improved control accuracy and reduced positioning error by 75%. To the best of our knowledge, this study is the first to achieve quadrotor positioning control through low-level reinforcement learning by using a global positioning system in an outdoor environment. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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22 pages, 10857 KiB

Open AccessArticle

Bifurcation Flight Dynamic Analysis of a Strake-Wing Micro Aerial Vehicle

by Mirosław Nowakowski, Krzysztof Sibilski, Anna Sibilska-Mroziewicz and Andrzej Żyluk

Appl. Sci. 2021, 11(4), 1524; https://doi.org/10.3390/app11041524 - 08 Feb 2021

Cited by 5 | Viewed by 2371

Abstract

Non-linear phenomena are particularly important in -flight dynamics of micro-class unmanned aerial vehicles. Susceptibility to atmospheric turbulence and high manoeuvrability of such aircraft under critical flight conditions cover non-linear aerodynamics and inertia coupling. The theory of dynamical systems provides methodology for studying systems [...] Read more.

Non-linear phenomena are particularly important in -flight dynamics of micro-class unmanned aerial vehicles. Susceptibility to atmospheric turbulence and high manoeuvrability of such aircraft under critical flight conditions cover non-linear aerodynamics and inertia coupling. The theory of dynamical systems provides methodology for studying systems of non-linear ordinary differential equations. The bifurcation theory forms part of this theory and deals with stability changes leading to qualitatively different system responses. These changes are called bifurcations. There is a number of papers, the authors of which applied the bifurcation theory for analysing aircraft flight dynamics. This article analyses the dynamics of critical micro aerial vehicle flight regimes. The flight dynamics under such conditions is highly non-linear, therefore the bifurcation theory can be applied in the course of the analysis. The application of the theory of dynamical systems enabled predicting the nature of micro aerial vehicle motion instability caused by bifurcations and analysing the post-bifurcation microdrone motion. This article presents the application of bifurcation analysis, complemented with time-domain simulations, to understand the open-loop dynamics of strake-wing micro aerial vehicle model by identifying the attractors of the dynamic system that manages upset behaviour. A number of factors have been identified to cause potential critical states, including non-oscillating spirals and oscillatory spins. The analysis shows that these spirals and spins are connected in a one-parameter space and that due to improper operation of the autopilot on the spiral, it is possible to enter the oscillatory spin. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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15 pages, 4886 KiB

Open AccessArticle

Horizontal Wind Effect on the Aerodynamic Performance of Coaxial Tri-Rotor MAV

by Yao Lei, Yiqiang Ye and Zhiyong Chen

Appl. Sci. 2020, 10(23), 8612; https://doi.org/10.3390/app10238612 - 01 Dec 2020

Cited by 5 | Viewed by 1585

Abstract

The coaxial Tri-rotor micro air vehicle (MAV) is composed of three coaxial rotors where the aerodynamic characteristics of is complicated in flight especially when the wind effect is introduced. In this paper, the hovering performance of a full-scale coaxial Tri-rotor MAV is analyzed [...] Read more.

The coaxial Tri-rotor micro air vehicle (MAV) is composed of three coaxial rotors where the aerodynamic characteristics of is complicated in flight especially when the wind effect is introduced. In this paper, the hovering performance of a full-scale coaxial Tri-rotor MAV is analyzed with both the simulations and wind tunnel experiments. Firstly, the wind effect on the aerodynamic performance of coaxial Tri-rotor MAV is established with different rotor speed (1500–2300 rpm) and horizontal wind (0–4 m/s). Secondly, the thrust and power consumption of coaxial Tri-rotor (L/D = 1.6) were obtained with low-speed wind tunnel experiments. Furthermore, the streamline distribution, pressure distribution, velocity contour and vortex distribution with different horizontal wind conditions are obtained by numerical simulations. Finally, combining the experiment results and simulation results, it is noted that the horizontal wind may accelerate the aerodynamic coupling, which resulting in the greater thrust variation up to 9% of the coaxial Tri-rotor MAV at a lower rotor speed. Moreover, the aerodynamic performance is decreased with more power consumption at higher rotor speed where the wind and the downwash flow are interacted with each other. Compared with no wind flow, the shape of the downwash flow and the deformation of the vortex affect the power loading and figure of metric accordingly. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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Review

Jump to: Editorial, Research

15 pages, 2470 KiB

Open AccessReview

Development and Prospect of UAV-Based Aerial Electrostatic Spray Technology in China

by Yali Zhang, Xinrong Huang, Yubin Lan, Linlin Wang, Xiaoyang Lu, Kangting Yan, Jizhong Deng and Wen Zeng

Appl. Sci. 2021, 11(9), 4071; https://doi.org/10.3390/app11094071 - 29 Apr 2021

Cited by 15 | Viewed by 3952

Abstract

Aerial electrostatic spray technology for agriculture is the integration of precision agricultural aviation and electrostatic spray technology. It is one of the research topics that have been paid close attention to by scholars in the field of agricultural aviation. This study summarizes the [...] Read more.

Aerial electrostatic spray technology for agriculture is the integration of precision agricultural aviation and electrostatic spray technology. It is one of the research topics that have been paid close attention to by scholars in the field of agricultural aviation. This study summarizes the development of airborne electrostatic spray technology for agricultural use in China, including the early research and exploration of Chinese institutions and researchers in the aspects of nozzle structure design optimization and theoretical simulation. The research progress of UAV-based aerial electrostatic spray technology for agricultural use in China was expounded from the aspects of nozzle modification, technical feasibility study, influencing mechanism of various factors, and field efficiency tests. According to the current development of agricultural UAVs and the characteristics of the farmland environment in China, the UAV-based aerial electrostatic spray technology, which carries the airborne electrostatic spray system on the plant protection UAVs, has a wide potential in the future. At present, the application of UAV-based aerial electrostatic spray technology has yet to be further improved due to several factors, such as the optimization of the test technology for charged droplets, the impact of UAV rotor wind field, comparison study on charging modes, and the lack of technical accumulation in the research of aerial electrostatic spray technology. With the continuous improvement of the research system of agricultural aviation electrostatic spray technology, UAV-based electrostatic spray technology will give play to the advantages in increasing the droplets deposition on the target and reducing environmental pollution from the application of pesticides. This study is capable of providing a reference for the development of the UAV-based agricultural electrostatic spray technology and the spray equipment. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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