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Drones, Volume 7, Issue 3 (March 2023) – 74 articles

Cover Story (view full-size image): Visual feedback-based control for unmanned vehicles is crucial in many applications, including target tracking. However, inaccurate data and limited target information pose significant challenges. Cooperative control also presents difficulties due to communication limitations among vehicles. Our proposed solution to coordinated vision-based tracking enables a fleet of vehicles to orbit a target while coordinating phase separation. It achieves tracking using only a vehicle-target-relative line-of-sight angle and guarantees performance in the presence of communication failures, dropouts, and switching topologies, and non-ideal tracking of control commands by the vehicle autopilot. View this paper
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14 pages, 3213 KiB  
Article
A Novel Technique for Photo-Identification of the Fin Whale, Balaenoptera physalus, as Determined by Drone Aerial Images
by Eduard Degollada, Natalia Amigó, Seán A. O’Callaghan, Mila Varola, Katia Ruggero and Beatriu Tort
Drones 2023, 7(3), 220; https://doi.org/10.3390/drones7030220 - 22 Mar 2023
Cited by 4 | Viewed by 4922
Abstract
Drones have become a crucial research tool across marine environments over the past decade, being specifically useful in marine mammal research. Fin whales (Balaenoptera physalus) have been monitored feeding along the Catalan coast, Spain (NW Mediterranean), since 2014. To overcome issues [...] Read more.
Drones have become a crucial research tool across marine environments over the past decade, being specifically useful in marine mammal research. Fin whales (Balaenoptera physalus) have been monitored feeding along the Catalan coast, Spain (NW Mediterranean), since 2014. To overcome issues such as the distance between a whale and a research vessel or the lack of distinctive dorsal fin features, an aerial identification technique was developed. It uses the fin whales’ characteristic central chevron pattern (CCP) and blaze, which are clearly visible from an overhead position. A total of 237 individual whales were identified between 2015–2022 in this study area, of which there were 35 interannual recaptures. While the dorsal fin may undergo modifications over time, the CCP and blaze patterns did not naturally alter over the years, with one whale displaying the same characteristics 8 years apart between the first and the most recent sightings. As such, this coloration pattern provides a reliable identification feature to be used for the interannual identification and population monitoring of fin whales using drones. This novel technique aims to improve and unify this species cataloguing overseas by using the CCP and blaze obtained from UAV (unmanned aerial vehicle) zenithal videos as a robust identification tool. Full article
(This article belongs to the Special Issue Drone Advances in Wildlife Research)
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19 pages, 6766 KiB  
Article
Robust Planning System for Fast Autonomous Flight in Complex Unknown Environment Using Sparse Directed Frontier Points
by Yinghao Zhao, Li Yan, Jicheng Dai, Xiao Hu, Pengcheng Wei and Hong Xie
Drones 2023, 7(3), 219; https://doi.org/10.3390/drones7030219 - 21 Mar 2023
Cited by 2 | Viewed by 1713
Abstract
Path planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in cluttered environments. However, it remains a challenge to efficiently generate a high-quality trajectory for flight tasks with a high success rate. In this paper, a robust [...] Read more.
Path planning is one of the key parts of unmanned aerial vehicle (UAV) fast autonomous flight in cluttered environments. However, it remains a challenge to efficiently generate a high-quality trajectory for flight tasks with a high success rate. In this paper, a robust planning framework is proposed, which can stably support autonomous flight tasks in complex unknown environments with limited onboard computing resources. Firstly, we propose the directed frontier point information structure (DFP), which can roughly capture the frontier information of the explored environment. The planning direction of a local planner can be evaluated and rectified efficiently based on the DFP to avoid falling into traps with limited cost. Secondly, an adaptive fusion replanning method is designed to generate a high-quality trajectory efficiently by incorporating two optimization methods with different characteristics, which can both take advantage of different optimization methods while avoiding disadvantages as much as possible, but also adjust the focus of the optimization according to the actual situation to improve the success rate of the planning method. Finally, sufficient comparison and evaluation experiments in simulation environments are presented. Experimental results show the proposed method has better performance, especially in terms of adaptability and robustness, compared to typical and state-of-the-art methods in unknown complex scenarios. Moreover, the proposed system is integrated into a fully autonomous quadrotor, and the effectiveness of the proposed method is further evaluated by using the quadrotor in real-world environments. Full article
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21 pages, 1744 KiB  
Article
Drone-Based Emergent Distribution of Packages to an Island from a Land Base
by Zhi-Hua Hu, Tao Li, Xi-Dan Tian and Yue-He Wei
Drones 2023, 7(3), 218; https://doi.org/10.3390/drones7030218 - 21 Mar 2023
Cited by 2 | Viewed by 1326
Abstract
An island logistics system is vulnerable in emergency conditions and even isolated from land logistics. Drone-based distribution is an emerging solution investigated in this study to transport packages from a land base to the islands. Considering the drone costs, drone landing platforms in [...] Read more.
An island logistics system is vulnerable in emergency conditions and even isolated from land logistics. Drone-based distribution is an emerging solution investigated in this study to transport packages from a land base to the islands. Considering the drone costs, drone landing platforms in islands, and incorporation into the island ground distribution system, this study categorizes the direct, point-to-point, and cyclic bi-stage distribution modes: in the direct mode, the packages are distributed from the drone base station to the customers directly by drones; in the point-to-point mode, the packages are transported to the drone landing platform and then distributed to the customers independently; in the cyclic mode, the packages are distributed from a drone landing platform by a closed route. The modes are formulated, and evaluation metrics and solution methods are developed. In the experiments based on an island case, the models and solution methods are demonstrated, compared, and analyzed. The cyclic bi-stage distribution mode can improve drone flying distance by 50%, and an iterative heuristic algorithm can further improve drone flying distance by 27.8%, and the ground costs by 3.16%, average for the settings of twenty to sixty customers and two to four drone landing platforms. Based on the modeling and experimental studies, managerial implications and possible extensions are discussed. Full article
(This article belongs to the Special Issue The Applications of Drones in Logistics)
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25 pages, 15866 KiB  
Article
Multi-Conflict-Based Optimal Algorithm for Multi-UAV Cooperative Path Planning
by Xiaoxiong Liu, Yuzhan Su, Yan Wu and Yicong Guo
Drones 2023, 7(3), 217; https://doi.org/10.3390/drones7030217 - 21 Mar 2023
Cited by 2 | Viewed by 1547
Abstract
Multi-UAV cooperative path planning can improve the efficiency of task completion. To deal with the space and time conflicts of multi-UAVs in complex environments, a multi-collision-based multi-UAV cooperative path planning algorithm, multi-conflict-based search (MCBS), is proposed. First, the flight and cooperative constraints of [...] Read more.
Multi-UAV cooperative path planning can improve the efficiency of task completion. To deal with the space and time conflicts of multi-UAVs in complex environments, a multi-collision-based multi-UAV cooperative path planning algorithm, multi-conflict-based search (MCBS), is proposed. First, the flight and cooperative constraints of UAV are analyzed, and a three-dimensional environment model is established that incorporates geographical information. Then, hierarchical optimization is used to design collaborative algorithms. In the low-level path design, UAV flight constraints are combined with a sparse A* algorithm, and by improving the cost function, the search space is reduced, and the search time is shortened. In high-level cooperation, the priorities of different conflicts are set, heuristic information is introduced to guide the constraint tree to grow in the direction of satisfying the constraints, and the optimal path set is searched by the best priority search algorithm to reduce the convergence time. Finally, the planning results of the proposed algorithm, the traditional CBS algorithm, and the sparse A* algorithm for different UAV tasks are compared, and the influence of the optimization parameters on the calculation results is discussed. The simulation results show that the proposed algorithm can solve cooperative conflict between UAVs, improve the efficiency of path searches, and quickly find the optimal safe cooperative path that satisfies flight and cooperative constraints. Full article
(This article belongs to the Special Issue Swarm Intelligence in Multi-UAVs)
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14 pages, 1082 KiB  
Article
A Distributed Double-Loop Optimization Method with Fast Response for UAV Swarm Scheduling
by Runfeng Chen, Jie Li, Yiting Chen and Yuchong Huang
Drones 2023, 7(3), 216; https://doi.org/10.3390/drones7030216 - 21 Mar 2023
Viewed by 1154
Abstract
An unmanned aerial vehicle (UAV) swarm has broad application prospects, in which scheduling is one of the key technologies determining the completion of tasks. A market-based approach is an effective way to schedule UAVs distributively and quickly, meeting the real-time requirements of swarm [...] Read more.
An unmanned aerial vehicle (UAV) swarm has broad application prospects, in which scheduling is one of the key technologies determining the completion of tasks. A market-based approach is an effective way to schedule UAVs distributively and quickly, meeting the real-time requirements of swarm scheduling without a centre. In this paper, a double-loop framework is designed to enhance the performance of scheduling, where a new task removal method in the outer loop and a local redundant auction method in the inner loop are proposed to improve the optimization of scheduling and reduce iterations. Furthermore, a deadlock detection mechanism is introduced to avoid endless loops and the scheduling with the lowest local cost will be adopted to exit the cycle. Extensive Monte Carlo experiments show that the iterations required by the proposed method are less than the two representative algorithms consensus-based bundle algorithm (CBBA) and performance impact (PI) algorithm, and the number of allocated tasks is increased. In addition, through the deadlock avoidance mechanism, PI can completely converge as the method in this paper. Full article
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25 pages, 20160 KiB  
Article
The Development of Copper Clad Laminate Horn Antennas for Drone Interferometric Synthetic Aperture Radar
by Anthony Carpenter, James A. Lawrence, Richard Ghail and Philippa J. Mason
Drones 2023, 7(3), 215; https://doi.org/10.3390/drones7030215 - 20 Mar 2023
Cited by 3 | Viewed by 2829
Abstract
Interferometric synthetic aperture radar (InSAR) is an active remote sensing technique that typically utilises satellite data to quantify Earth surface and structural deformation. Drone InSAR should provide improved spatial-temporal data resolutions and operational flexibility. This necessitates the development of custom radar hardware for [...] Read more.
Interferometric synthetic aperture radar (InSAR) is an active remote sensing technique that typically utilises satellite data to quantify Earth surface and structural deformation. Drone InSAR should provide improved spatial-temporal data resolutions and operational flexibility. This necessitates the development of custom radar hardware for drone deployment, including antennas for the transmission and reception of microwave electromagnetic signals. We present the design, simulation, fabrication, and testing of two lightweight and inexpensive copper clad laminate (CCL)/printed circuit board (PCB) horn antennas for C-band radar deployed on the DJI Matrice 600 Pro drone. This is the first demonstration of horn antennas fabricated from CCL, and the first complete overview of antenna development for drone radar applications. The dimensions are optimised for the desired gain and centre frequency of 19 dBi and 5.4 GHz, respectively. The S11, directivity/gain, and half power beam widths (HPBW) are simulated in MATLAB, with the antennas tested in a radio frequency (RF) electromagnetic anechoic chamber using a calibrated vector network analyser (VNA) for comparison. The antennas are highly directive with gains of 15.80 and 16.25 dBi, respectively. The reduction in gain compared to the simulated value is attributed to a resonant frequency shift caused by the brass input feed increasing the electrical dimensions. The measured S11 and azimuth HPBW either meet or exceed the simulated results. A slight performance disparity between the two antennas is attributed to minor artefacts of the manufacturing and testing processes. The incorporation of the antennas into the drone payload is presented. Overall, both antennas satisfy our performance criteria and highlight the potential for CCL/PCB/FR-4 as a lightweight and inexpensive material for custom antenna production in drone radar and other antenna applications. Full article
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69 pages, 11016 KiB  
Review
A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches
by Attai Ibrahim Abubakar, Iftikhar Ahmad, Kenechi G. Omeke, Metin Ozturk, Cihat Ozturk, Ali Makine Abdel-Salam, Michael S. Mollel, Qammer H. Abbasi, Sajjad Hussain and Muhammad Ali Imran
Drones 2023, 7(3), 214; https://doi.org/10.3390/drones7030214 - 20 Mar 2023
Cited by 12 | Viewed by 4873
Abstract
Wireless communication networks have been witnessing unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Although there are many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and [...] Read more.
Wireless communication networks have been witnessing unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Although there are many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance capacity due to their easy implementation, pop-up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity where it is needed. However, UAVs mostly have limited energy storage, hence, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed—conventional and machine learning (ML). Such classification helps understand the state-of-the-art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above-mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trends in the literature. Full article
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14 pages, 2174 KiB  
Article
Deep Reinforcement Learning Based Computation Offloading in UAV-Assisted Edge Computing
by Peiying Zhang, Yu Su, Boxiao Li, Lei Liu, Cong Wang, Wei Zhang and Lizhuang Tan
Drones 2023, 7(3), 213; https://doi.org/10.3390/drones7030213 - 19 Mar 2023
Cited by 5 | Viewed by 2378
Abstract
Traditional multi-access edge computing (MEC) often has difficulty processing large amounts of data in the face of high computationally intensive tasks, so it needs to offload policies to offload computation tasks to adjacent edge servers. The computation offloading problem is a mixed integer [...] Read more.
Traditional multi-access edge computing (MEC) often has difficulty processing large amounts of data in the face of high computationally intensive tasks, so it needs to offload policies to offload computation tasks to adjacent edge servers. The computation offloading problem is a mixed integer programming non-convex problem, and it is difficult to have a good solution. Meanwihle, the cost of deploying servers is often high when providing edge computing services in remote areas or some complex terrains. In this paper, the unmanned aerial vehicle (UAV) is introduced into the multi-access edge computing network, and a computation offloading method based on deep reinforcement learning in UAV-assisted multi-access edge computing network (DRCOM) is proposed. We use the UAV as the space base station of MEC, and it transforms computation task offloading problems of MEC into two sub-problems: find the optimal solution of whether each user’s device is offloaded through deep reinforcement learning; allocate resources. We compared our algorithm with other three offloading methods, i.e., LC, CO, and LRA. The maximum computation rate of our algorithm DRCOM is 142.38% higher than LC, 50.37% higher than CO, and 12.44% higher than LRA. The experimental results demonstrate that DRCOM greatly improves the computation rate. Full article
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16 pages, 4884 KiB  
Article
Real-Time Positioning Method for UAVs in Complex Structural Health Monitoring Scenarios
by Jianguo Zhou, Linshu He and Haitao Luo
Drones 2023, 7(3), 212; https://doi.org/10.3390/drones7030212 - 19 Mar 2023
Cited by 2 | Viewed by 2115
Abstract
UAVs are becoming increasingly used in the field of structural health monitoring, and the position information of them during the tasks is crucial. However, in complex scenarios such as bridges and high-rise buildings, the GNSS positioning method cannot obtain the positions of the [...] Read more.
UAVs are becoming increasingly used in the field of structural health monitoring, and the position information of them during the tasks is crucial. However, in complex scenarios such as bridges and high-rise buildings, the GNSS positioning method cannot obtain the positions of the UAV all the time due to the blockage of satellite signals and multi-path effects. This paper proposes a real-time positioning method to address the issue combining GNSS and total station. The GNSS is first used to locate the UAV when it is not in the line of sight of the total station, and the coordinates of the UAV are transmitted to the total station for blind tracking through coordinates conversion. The total station is then used to directly track the UAV when it flies to the GNSS-denied area and appears in the field view of the total station. Experiments show that the shift from blind tracking to direct tracking can be guaranteed as the coordinates conversion error is always less than the field of view range of the total station, even if only two common points are used for coordinates conversion. In addition, high positioning accuracy can be achieved in complex structural health monitoring scenarios. Full article
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37 pages, 1522 KiB  
Review
Review of Autonomous Path Planning Algorithms for Mobile Robots
by Hongwei Qin, Shiliang Shao, Ting Wang, Xiaotian Yu, Yi Jiang and Zonghan Cao
Drones 2023, 7(3), 211; https://doi.org/10.3390/drones7030211 - 18 Mar 2023
Cited by 34 | Viewed by 8107
Abstract
Mobile robots, including ground robots, underwater robots, and unmanned aerial vehicles, play an increasingly important role in people’s work and lives. Path planning and obstacle avoidance are the core technologies for achieving autonomy in mobile robots, and they will determine the application prospects [...] Read more.
Mobile robots, including ground robots, underwater robots, and unmanned aerial vehicles, play an increasingly important role in people’s work and lives. Path planning and obstacle avoidance are the core technologies for achieving autonomy in mobile robots, and they will determine the application prospects of mobile robots. This paper introduces path planning and obstacle avoidance methods for mobile robots to provide a reference for researchers in this field. In addition, it comprehensively summarizes the recent progress and breakthroughs of mobile robots in the field of path planning and discusses future directions worthy of research in this field. We focus on the path planning algorithm of a mobile robot. We divide the path planning methods of mobile robots into the following categories: graph-based search, heuristic intelligence, local obstacle avoidance, artificial intelligence, sampling-based, planner-based, constraint problem satisfaction-based, and other algorithms. In addition, we review a path planning algorithm for multi-robot systems and different robots. We describe the basic principles of each method and highlight the most relevant studies. We also provide an in-depth discussion and comparison of path planning algorithms. Finally, we propose potential research directions in this field that are worth studying in the future. Full article
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33 pages, 2110 KiB  
Systematic Review
Systematic Review on Civilian Drones in Safety and Security Applications
by Khalifa AL-Dosari, Ziad Hunaiti and Wamadeva Balachandran
Drones 2023, 7(3), 210; https://doi.org/10.3390/drones7030210 - 18 Mar 2023
Cited by 15 | Viewed by 4764
Abstract
The employment of unmanned aerial vehicles, also known as UAVs, is expanding rapidly across various civil application areas. Some of these domains include real-time tracking, the provision of wireless coverage, sensing, searches and rescue, the delivery of goods, safety and surveillance, security, and [...] Read more.
The employment of unmanned aerial vehicles, also known as UAVs, is expanding rapidly across various civil application areas. Some of these domains include real-time tracking, the provision of wireless coverage, sensing, searches and rescue, the delivery of goods, safety and surveillance, security, and safety checks of engineering structures. Smart UAVs represent the next technology revolution in UAV technology. They promise to provide new possibilities in various applications, notably lower risk and costs for civil infrastructure. The military has traditionally used unmanned aerial vehicles (UAVs) in countries such as the United Kingdom or the United States to partake in military and dangerous operations. The application and usage of these UAVs have become more commercial. Civilians can easily buy UAVs, commonly known as drones, from online platforms or shops. The main aim of this study is to review selected publications presenting previous efforts on using Civilian Drones in Safety applications. The study was accomplished using a systematic review research approach reviewing 45 publications. Drones have become more common, and it is crucial to understand how they work, especially since they entered the civilian domain. The research shows how civilian drones have been used in numerous safety applications, such as security cameras videotaping a house to ensure its safety. Full article
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27 pages, 11254 KiB  
Article
A Robust Real-Time Ellipse Detection Method for Robot Applications
by Wenshan He, Gongping Wu, Fei Fan, Zhongyun Liu and Shujie Zhou
Drones 2023, 7(3), 209; https://doi.org/10.3390/drones7030209 - 17 Mar 2023
Viewed by 2055
Abstract
Over the years, many ellipse detection algorithms have been studied broadly, while the critical problem of accurately and effectively detecting ellipses in the real-world using robots remains a challenge. In this paper, we proposed a valuable real-time robot-oriented detector and simple tracking algorithm [...] Read more.
Over the years, many ellipse detection algorithms have been studied broadly, while the critical problem of accurately and effectively detecting ellipses in the real-world using robots remains a challenge. In this paper, we proposed a valuable real-time robot-oriented detector and simple tracking algorithm for ellipses. This method uses low-cost RGB cameras for conversion into HSV space to obtain reddish regions of interest (RROIs) contours, effective arc selection and grouping strategies, and the candidate ellipses selection procedures that eliminate invalid edges and clustering functions. Extensive experiments are conducted to adjust and verify the method’s parameters for achieving the best performance. The method combined with a simple tracking algorithm executes only approximately 30 ms on a video frame in most cases. The results show that the proposed method had high-quality performance (precision, recall, F-Measure scores) and the least execution time compared with the existing nine most advanced methods on three public actual application datasets. Our method could detect elliptical markers in real-time in practical applications, detect ellipses adaptively under natural light, well detect severely blocked and specular reflection ellipses when the elliptical object was far from or close to the robot. The average detection frequency can meet the real-time requirements (>10 Hz). Full article
(This article belongs to the Topic 3D Computer Vision and Smart Building and City)
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23 pages, 4503 KiB  
Article
Evaluation of an Innovative Rosette Flight Plan Design for Wildlife Aerial Surveys with UAS
by Julie Linchant, Philippe Lejeune, Samuel Quevauvillers, Cédric Vermeulen, Yves Brostaux, Simon Lhoest and Adrien Michez
Drones 2023, 7(3), 208; https://doi.org/10.3390/drones7030208 - 17 Mar 2023
Cited by 1 | Viewed by 1285
Abstract
(1) Regular wildlife abundance surveys are a key conservation tool. Manned aircraft flying transects often remain the best alternative for counting large ungulates. Drones have cheaper and safer logistics, however their range is generally too short for large-scale application of the traditional method. [...] Read more.
(1) Regular wildlife abundance surveys are a key conservation tool. Manned aircraft flying transects often remain the best alternative for counting large ungulates. Drones have cheaper and safer logistics, however their range is generally too short for large-scale application of the traditional method. Our paper investigates an innovative rosette flight plan for wildlife census, and evaluates relevance of this sampling protocol by comparing its statistical performance with transects, based on numerical simulations. (2) The UAS flight plan consisted in two rosettes of 6 triangular “petals” spread across the survey area, for a theoretical sampling rate of 2.95%, as opposed to a 20.04% classic sampling protocol with systematic transects. We tested the logistics of our survey design in Garamba National Park. We then modeled theoretical population distributions for both antelopes and buffaloes. We calculated animal densities in the simulated footprints of the theoretical rosette and transect flight plans. We also tested aggregating results for 2, 3 and 4 repetitions of the same rosette flight plan to increase the sampling rate. (3) Simulation results showed that the coefficient of variation associated with density estimates decreases with the number of repetitions of the rosette flight plan, and aggregating four repetitions is enough to give antelope densities with acceptable accuracy and precision while staying at a lower sampling rate. Buffalo densities displayed much higher variability and it shows the significant impact of gregariousness on density estimate accuracy and precision. (4) The method was found to be inappropriate for highly aggregative species but efficient for species that disperse widely and more randomly in their environment. Logistics required to perform a full survey in the field remain time- and resources-intensive. Therefore, we recommend it for remote parks facing difficulties to organize manned aerial counts. Lower costs and developments such as solar UASs offer interesting future perspectives. Full article
(This article belongs to the Special Issue Drones in the Wild)
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23 pages, 7549 KiB  
Article
Drone-Based Identification and Monitoring of Two Invasive Alien Plant Species in Open Sand Grasslands by Six RGB Vegetation Indices
by László Bakacsy, Zalán Tobak, Boudewijn van Leeuwen, Péter Szilassi, Csaba Biró and József Szatmári
Drones 2023, 7(3), 207; https://doi.org/10.3390/drones7030207 - 17 Mar 2023
Cited by 6 | Viewed by 2596
Abstract
Today, invasive alien species cause serious trouble for biodiversity and ecosystem services, which are essential for human survival. In order to effectively manage invasive species, it is important to know their current distribution and the dynamics of their spread. Unmanned aerial vehicle (UAV) [...] Read more.
Today, invasive alien species cause serious trouble for biodiversity and ecosystem services, which are essential for human survival. In order to effectively manage invasive species, it is important to know their current distribution and the dynamics of their spread. Unmanned aerial vehicle (UAV) monitoring is one of the best tools for gathering this information from large areas. Vegetation indices for multispectral camera images are often used for this, but RGB colour-based vegetation indices can provide a simpler and less expensive solution. The goal was to examine whether six RGB indices are suitable for identifying invasive plant species in the QGIS environment on UAV images. To examine this, we determined the shoot area and number of common milkweed (Asclepias syriaca) and the inflorescence area and number of blanket flowers (Gaillardia pulchella) as two typical invasive species in open sandy grasslands. According to the results, the cover area of common milkweed was best identified with the TGI and SSI indices. The producers’ accuracy was 76.38% (TGI) and 67.02% (SSI), while the user’s accuracy was 75.42% (TGI) and 75.12% (SSI), respectively. For the cover area of blanket flower, the IF index proved to be the most suitable index. In spite of this, it gave a low producer’s accuracy of 43.74% and user’s accuracy of 51.4%. The used methods were not suitable for the determination of milkweed shoot and the blanket flower inflorescence number, due to significant overestimation. With the methods presented here, the data of large populations of invasive species can be processed in a simple, fast, and cost-effective manner, which can ensure the precise planning of treatments for nature conservation practitioners. Full article
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19 pages, 751 KiB  
Review
A Systematic Review of UAVs for Island Coastal Environment and Risk Monitoring: Towards a Resilience Assessment
by Jérémy Jessin, Charlotte Heinzlef, Nathalie Long and Damien Serre
Drones 2023, 7(3), 206; https://doi.org/10.3390/drones7030206 - 17 Mar 2023
Cited by 5 | Viewed by 2087
Abstract
Island territories and their coastal regions are subject to a wide variety of stresses, both natural and anthropogenic. With increasing pressures on these vulnerable environments, the need to improve our knowledge of these ecosystems increases as well. Unmanned Aerial Vehicles (UAVs) have recently [...] Read more.
Island territories and their coastal regions are subject to a wide variety of stresses, both natural and anthropogenic. With increasing pressures on these vulnerable environments, the need to improve our knowledge of these ecosystems increases as well. Unmanned Aerial Vehicles (UAVs) have recently shown their worth as a tool for data acquisition in coastal zones. This literature review explores the field of UAVs in the context of coastal monitoring on island territories by highlighting the types of platforms, sensors, software, and validation methods available for this relatively new data acquisition method. Reviewing the existing literature will assist data collectors, researchers, and risk managers in more efficiently monitoring their coastal zones on vulnerable island territories. The scientific literature reviewed was strictly analyzed in peer-reviewed articles ranging from 2016 to 2022. This review then focuses on the operationalization of the concept of resilience as a risk management technique. The aim is to identify a procedure from raw data acquisition to quantifying indicators for the evaluation of the resilience of a territory and finally linking the analyzed data to a spatial decision support system. This system could aid the decision-making process and uses the islands of French Polynesia and its Resilience Observatory as a case study. Full article
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21 pages, 17339 KiB  
Article
TAN: A Transferable Adversarial Network for DNN-Based UAV SAR Automatic Target Recognition Models
by Meng Du, Yuxin Sun, Bing Sun, Zilong Wu, Lan Luo, Daping Bi and Mingyang Du
Drones 2023, 7(3), 205; https://doi.org/10.3390/drones7030205 - 16 Mar 2023
Cited by 1 | Viewed by 1343
Abstract
Recently, the unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) has become a highly sought-after topic for its wide applications in target recognition, detection, and tracking. However, SAR automatic target recognition (ATR) models based on deep neural networks (DNN) are suffering from adversarial [...] Read more.
Recently, the unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) has become a highly sought-after topic for its wide applications in target recognition, detection, and tracking. However, SAR automatic target recognition (ATR) models based on deep neural networks (DNN) are suffering from adversarial examples. Generally, non-cooperators rarely disclose any SAR-ATR model information, making adversarial attacks challenging. To tackle this issue, we propose a novel attack method called Transferable Adversarial Network (TAN). It can craft highly transferable adversarial examples in real time and attack SAR-ATR models without any prior knowledge, which is of great significance for real-world black-box attacks. The proposed method improves the transferability via a two-player game, in which we simultaneously train two encoder–decoder models: a generator that crafts malicious samples through a one-step forward mapping from original data, and an attenuator that weakens the effectiveness of malicious samples by capturing the most harmful deformations. Particularly, compared to traditional iterative methods, the encoder–decoder model can one-step map original samples to adversarial examples, thus enabling real-time attacks. Experimental results indicate that our approach achieves state-of-the-art transferability with acceptable adversarial perturbations and minimum time costs compared to existing attack methods, making real-time black-box attacks without any prior knowledge a reality. Full article
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26 pages, 742 KiB  
Article
Adjustable Fully Adaptive Cross-Entropy Algorithms for Task Assignment of Multi-UAVs
by Kehao Wang, Xun Zhang, Xuyang Qiao, Xiaobai Li, Wei Cheng, Yirui Cong and Kezhong Liu
Drones 2023, 7(3), 204; https://doi.org/10.3390/drones7030204 - 16 Mar 2023
Cited by 3 | Viewed by 1209
Abstract
This paper investigates the multiple unmanned aerial vehicle (multi-UAV) cooperative task assignment problem. Specifically, we assign different types of UAVs to accomplish the classification, attack, and verification tasks of targets under resource, precedence, and timing constraints. Due to complex coupling among these tasks, [...] Read more.
This paper investigates the multiple unmanned aerial vehicle (multi-UAV) cooperative task assignment problem. Specifically, we assign different types of UAVs to accomplish the classification, attack, and verification tasks of targets under resource, precedence, and timing constraints. Due to complex coupling among these tasks, we decompose the considered problem into two subproblems: one with continuous and independent tasks and another with continuous and correlative tasks. To solve them, we first present an adjustable, fully adaptive cross-entropy (AFACE) algorithm based on the cross-entropy (CE) method, which serves as a stepping stone for developing other algorithms. Secondly, to overcome task precedence in the first subproblem, we propose a mutually independent AFACE (MIAFACE) algorithm, which converges faster than the CE method when obtaining the optimal scheme vectors of these continuous and independent tasks. Thirdly, to deal with task coupling in the second subproblem, we present a mutually correlative AFACE (MCAFACE) algorithm to find the optimal scheme vectors of these continuous and correlative tasks, while its computational complexity is inferior to that of the MIAFACE algorithm. Finally, numerical simulations demonstrate that the proposed MIAFACE (MCAFACE, respectively) algorithm consumes less time than the existing algorithms for the continuous and independent (correlative, respectively) task assignment problem. Full article
(This article belongs to the Special Issue Multi-UAV Networks)
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19 pages, 8098 KiB  
Article
Optimal UAV Hangar Locations for Emergency Services Considering Restricted Areas
by Hannes Braßel, Thomas Zeh, Hartmut Fricke and Anette Eltner
Drones 2023, 7(3), 203; https://doi.org/10.3390/drones7030203 - 16 Mar 2023
Viewed by 1462
Abstract
With unmanned aerial vehicle(s) (UAV), swift responses to urgent needs (such as search and rescue missions or medical deliveries) can be realized. Simultaneously, legislators are establishing so-called geographical zones, which restrict UAV operations to mitigate air and ground risks to third parties. These [...] Read more.
With unmanned aerial vehicle(s) (UAV), swift responses to urgent needs (such as search and rescue missions or medical deliveries) can be realized. Simultaneously, legislators are establishing so-called geographical zones, which restrict UAV operations to mitigate air and ground risks to third parties. These geographical zones serve particular safety interests but they may also hinder the efficient usage of UAVs in time-critical missions with range-limiting battery capacities. In this study, we address a facility location problem for up to two UAV hangars and combine it with a routing problem of a standard UAV mission to consider geographical zones as restricted areas, battery constraints, and the impact of wind to increase the robustness of the solution. To this end, water rescue missions are used exemplary, for which positive and negative location factors for UAV hangars and areas of increased drowning risk as demand points are derived from open-source georeferenced data. Optimum UAV mission trajectories are computed with an A* algorithm, considering five different restriction scenarios. As this pathfinding is very time-consuming, binary occupancy grids and image-processing algorithms accelerate the computation by identifying either entirely inaccessible or restriction-free connections beforehand. For the optimum UAV hangar locations, we maximize accessibility while minimizing the service times to the hotspots, resulting in a decrease from the average service time of 570.4 s for all facility candidates to 351.1 s for one and 287.2 s for two optimum UAV hangar locations. Full article
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24 pages, 2408 KiB  
Review
Towards UAVs in Construction: Advancements, Challenges, and Future Directions for Monitoring and Inspection
by Han Liang, Seong-Cheol Lee, Woosung Bae, Jeongyun Kim and Suyoung Seo
Drones 2023, 7(3), 202; https://doi.org/10.3390/drones7030202 - 15 Mar 2023
Cited by 10 | Viewed by 7659
Abstract
The use of UAVs for monitoring and inspection in the construction industry has garnered considerable attention in recent years due to their potential to enhance safety, efficiency, and accuracy. The development and application of various types of drones and sensors in the construction [...] Read more.
The use of UAVs for monitoring and inspection in the construction industry has garnered considerable attention in recent years due to their potential to enhance safety, efficiency, and accuracy. The development and application of various types of drones and sensors in the construction industry have opened up new data collection and analysis possibilities. This paper provides a thorough examination of the latest developments in the use of UAVs for monitoring and inspection in the construction industry, including a review of the current state of UAVs and an exploration of the types of drones and sensors applied and their applications. It also highlights the technological advancements in this field. However, as with any new technology, there are challenges and limitations that need to be addressed, such as regulatory and legal concerns, technical limitations, data processing challenges, training and expertise, and safety. Finally, we offer insights into potential solutions to these challenges, such as innovative sensors and imaging technologies, integration with other construction technologies, and the use of machine learning and AI for data analysis, which are some of the potential areas for future investigation, and highlight the prospects for drone-based construction inspection. Full article
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17 pages, 3001 KiB  
Article
Control Architecture for a Quadrotor Transporting a Cable-Suspended Load of Uncertain Mass
by Pedro Outeiro, Carlos Cardeira and Paulo Oliveira
Drones 2023, 7(3), 201; https://doi.org/10.3390/drones7030201 - 15 Mar 2023
Cited by 5 | Viewed by 1627
Abstract
This paper presents an architecture for controlling a quadrotor transporting a cable-suspended load of uncertain mass. A family of trajectories is proposed that is composed by three phases—lift-off, transit, and landing—and implemented as a hybrid system. The proposed control system uses an adaptive [...] Read more.
This paper presents an architecture for controlling a quadrotor transporting a cable-suspended load of uncertain mass. A family of trajectories is proposed that is composed by three phases—lift-off, transit, and landing—and implemented as a hybrid system. The proposed control system uses an adaptive geometric controller with asymptotic tracking stability. The mass of the transported load was estimated using an adaptive mechanism, which adjusts the action resorting to a geometric control method. The resulting system was validated in simulation with a mid-flight mass reduction of the transported load, and tests were performed using a range of values of load mass and maximum forward velocity. There is work in the literature that approaches the cable-suspended component of the problem, and there are also papers focused on uncertainty in the model, mass included. This work aimed to solve these two problems simultaneously, having the uncertain component being the mass of the suspended load. Full article
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23 pages, 9855 KiB  
Article
Carrier Aircraft Flight Controller Design by Synthesizing Preview and Nonlinear Control Laws
by Baoxu Jia, Liguo Sun, Xiaoyu Liu, Shuting Xu, Wenqian Tan and Junkai Jiao
Drones 2023, 7(3), 200; https://doi.org/10.3390/drones7030200 - 15 Mar 2023
Viewed by 1350
Abstract
This paper proposes an innovative automatic carrier landing control law for carrier-based aircraft considering complex ship motion and wind environment. Specifically, a strategy is proposed to synthesize preview control with an adaptive nonlinear control scheme. Firstly, incremental nonlinear backstepping control law is adopted [...] Read more.
This paper proposes an innovative automatic carrier landing control law for carrier-based aircraft considering complex ship motion and wind environment. Specifically, a strategy is proposed to synthesize preview control with an adaptive nonlinear control scheme. Firstly, incremental nonlinear backstepping control law is adopted in the attitude control loop to enhance the anti-disturbance capability of the aircraft. Secondly, to enhance the glide slope tracking performance under severe sea conditions, the carrier motion is predicted, and the forecasted motion is adopted in an optimal preview control guidance law to compensate influences induced by carrier motion. However, synthesizing the inner-loop and outer-loop control is not that straightforward since the preview control is naturally an optimal control law which requires a state-space model. Therefore, low-order equivalent fitting of the attitude-to-altitude high-order system model needs to be performed; furthermore, a state observer needs to be designed for the low-order equivalent system to supply required states to the landing controller. Finally, to validate the proposed methodology, an unmanned tailless aircraft model is used to perform the automatic landing tasks under variant sea conditions. Results show that the automatic carrier landing system can lead to satisfactory landing precision and success rate even under severe sea conditions. Full article
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29 pages, 30616 KiB  
Article
Experimental and Numerical Considerations for the Motor-Propeller Assembly’s Air Flow Field over a Quadcopter’s Arm
by Andra Tofan-Negru, Amado Ștefan, Lucian Ștefăniță Grigore and Ionica Oncioiu
Drones 2023, 7(3), 199; https://doi.org/10.3390/drones7030199 - 15 Mar 2023
Cited by 3 | Viewed by 1596
Abstract
The aim of the paper is to validate the analytical–numerical analysis method regarding the operating regime of the propellers of a quadcopter. The research aims to mark the flow areas whose numerical results differ from the experimental ones and to investigate the possible [...] Read more.
The aim of the paper is to validate the analytical–numerical analysis method regarding the operating regime of the propellers of a quadcopter. The research aims to mark the flow areas whose numerical results differ from the experimental ones and to investigate the possible reasons for the discrepancies between the values. The paper presents the determination of the air velocity produced by the rotational movement of a quadcopter propeller for a stationary position of the drive motor. The velocities were determined both experimentally at various points located below the propeller plane using hot-wire anemometric probes and numerically using a time-lapse simulation with a rotating sliding table. The numerical simulations carried out consisted of the determination of the time variation of the velocity distribution developed by the propeller in the rotational movement for the different operating (power) cycles of the engine. In addition, a technique that utilizes reverse engineering to determine the propeller profile, the anemometric probe calibration, and the average velocity values measured at various points below the propeller plane for engine operating regimes that range from 60 to 90% are also presented. Full article
(This article belongs to the Section Drone Design and Development)
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16 pages, 9724 KiB  
Article
Application of UAV Digital Photogrammetry in Geological Investigation and Stability Evaluation of High-Steep Mine Rock Slope
by Jianning Hao, Xiuli Zhang, Chengtang Wang, Hao Wang and Haibin Wang
Drones 2023, 7(3), 198; https://doi.org/10.3390/drones7030198 - 15 Mar 2023
Cited by 3 | Viewed by 1788
Abstract
For the stability analysis of rock slope, it is very critical to obtain the spatial geometric characteristics of the structural surfaces of the rock mass accurately and effectively. As for a high-steep rock slope of an iron ore mine, in order to solve [...] Read more.
For the stability analysis of rock slope, it is very critical to obtain the spatial geometric characteristics of the structural surfaces of the rock mass accurately and effectively. As for a high-steep rock slope of an iron ore mine, in order to solve the problems of inefficiency and high risk of traditional manual geological survey, the geological survey and stability evaluation of the slope was carried out by adopting unmanned aerial vehicle digital photogrammetry (UAV-DP) technology. Firstly, a large number of high-resolution images of the slope were obtained by UAV-DP. Then, the structure from motion (SFM) method was used to construct the fine 3D point cloud model of the slope, which was subjected to coplanarity detection and K-means clustering for identifying the structural surfaces. Finally, the stability and failure model of the slope cut by the structural surfaces are analyzed by using the stereo-projection and discrete element methods. The research results show that the error between UAV-DP and manual measurement is within the acceptable range, which demonstrates the reliability of UAV-DP used in the geological investigation. Furthermore, the stability state and failure model of the slope is also consistent well with the field observation. Full article
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25 pages, 4825 KiB  
Article
Finite-Time Adaptive Consensus Tracking Control Based on Barrier Function and Cascaded High-Gain Observer
by Xinyu Zhang, Zheng H. Zhu, Fei Liao, Hui Gao, Weihao Li and Gun Li
Drones 2023, 7(3), 197; https://doi.org/10.3390/drones7030197 - 14 Mar 2023
Cited by 1 | Viewed by 1264
Abstract
This paper studies the consensus tracking control for a class of uncertain high-order nonlinear multi-agent systems under an undirected leader-following architecture. A novel distributed finite-time adaptive control framework is proposed based on the barrier function. The distributed cascaded high-gain observers are introduced to [...] Read more.
This paper studies the consensus tracking control for a class of uncertain high-order nonlinear multi-agent systems under an undirected leader-following architecture. A novel distributed finite-time adaptive control framework is proposed based on the barrier function. The distributed cascaded high-gain observers are introduced to solve the problem of robust consensus tracking with unmeasured intermediate states in multi-agent systems based on the proposed control framework. The proposed control schemes guarantee the finite-time consensus of multi-agent systems, which is proven by the finite-time Lyapunov stability and singular perturbation theory. In conclusion, numerical simulations verify the proposed control protocols’ effectiveness, and their performance advantages are shown by comparing them with another existing method. Full article
(This article belongs to the Special Issue UAV Trajectory Generation, Optimization and Cooperative Control)
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25 pages, 13596 KiB  
Article
Multi-UAV Trajectory Planning during Cooperative Tracking Based on a Fusion Algorithm Integrating MPC and Standoff
by Bo Li, Chao Song, Shuangxia Bai, Jingyi Huang, Rui Ma, Kaifang Wan and Evgeny Neretin
Drones 2023, 7(3), 196; https://doi.org/10.3390/drones7030196 - 14 Mar 2023
Cited by 8 | Viewed by 2073
Abstract
In this paper, an intelligent algorithm integrating model predictive control and Standoff algorithm is proposed to solve trajectory planning that UAVs may face while tracking a moving target cooperatively in a complex three-dimensional environment. A fusion model using model predictive control and Standoff [...] Read more.
In this paper, an intelligent algorithm integrating model predictive control and Standoff algorithm is proposed to solve trajectory planning that UAVs may face while tracking a moving target cooperatively in a complex three-dimensional environment. A fusion model using model predictive control and Standoff algorithm is thus constructed to ensure trajectory planning and formation maintenance, maximizing UAV sensors’ detection range while minimizing target loss probability. Meanwhile, with this model, a fully connected communication topology is used to complete the UAV communication, multi-UAV formation can be reconfigured and planned at the minimum cost, keeping off deficiency in avoiding real-time obstacles facing the Standoff algorithm. Simulation validation suggests that the fusion algorithm proves to be more capable of maintaining UAVs in stable formation and detecting the target, compared with the model predictive control algorithm alone, in the process of tracking the moving target in a complex 3D environment. Full article
(This article belongs to the Special Issue UAV-Assisted Intelligent Vehicular Networks)
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7 pages, 195 KiB  
Editorial
Editorial of Special Issue “Advances in UAV Detection, Classification and Tracking”
by Daobo Wang and Zain Anwar Ali
Drones 2023, 7(3), 195; https://doi.org/10.3390/drones7030195 - 14 Mar 2023
Viewed by 1342
Abstract
This is an editorial for a Special Issue of Drones titled “Advances in UAV Detection, Classification and Tracking” [...] Full article
(This article belongs to the Special Issue Advances in UAV Detection, Classification and Tracking)
19 pages, 13839 KiB  
Article
Fault-Tolerant Control for Carrier-Based UAV Based on Sliding Mode Method
by Zhuoer Yao, Zi Kan, Chong Zhen, Haoyuan Shao and Daochun Li
Drones 2023, 7(3), 194; https://doi.org/10.3390/drones7030194 - 13 Mar 2023
Cited by 5 | Viewed by 1639
Abstract
To enable a carrier-based unmanned aerial vehicle (UAV) to track the desired glide trajectory and safely land on the deck with the presence of system faults, this paper proposes a neural network-based adaptive sliding mode fault-tolerant control (NASFTC) method. Firstly, the dynamic model [...] Read more.
To enable a carrier-based unmanned aerial vehicle (UAV) to track the desired glide trajectory and safely land on the deck with the presence of system faults, this paper proposes a neural network-based adaptive sliding mode fault-tolerant control (NASFTC) method. Firstly, the dynamic model of the carrier -based UAV, the actuator fault model, the additional unknown fault model, and the control framework of the automatic carrier landing system (ACLS) were developed. Subsequently, controllers for both longitudinal and lateral channels were designed by using the NASFTC method. The controller consists of three parts: the adaptive laws for compensating the actuator faults, the RBF neural network for compensating the additional unknown faults, and the sliding mode method for ensuring overall trajectory tracking. Then, the Lyapunov function theorem was applied to carry out the stability analysis. Finally, comparative simulations under three different scenarios were conducted. The comparative results show the effectiveness of the proposed NASFTC method, which has fault-tolerant ability and can successfully control the aircraft to execute carrier landing task regardless of the actuator partial loss fault and the additional unknown fault. Full article
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19 pages, 9835 KiB  
Article
Swarm Cooperative Navigation Using Centralized Training and Decentralized Execution
by Rana Azzam, Igor Boiko and Yahya Zweiri
Drones 2023, 7(3), 193; https://doi.org/10.3390/drones7030193 - 11 Mar 2023
Cited by 3 | Viewed by 2597
Abstract
The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs in various challenging tasks. Yet conventional swarm control approaches are inadequate for coping with swarm scalability, computational requirements, and real-time performance. In this paper, we demonstrate [...] Read more.
The demand for autonomous UAV swarm operations has been on the rise following the success of UAVs in various challenging tasks. Yet conventional swarm control approaches are inadequate for coping with swarm scalability, computational requirements, and real-time performance. In this paper, we demonstrate the capability of emerging multi-agent reinforcement learning (MARL) approaches to successfully and efficiently make sequential decisions during UAV swarm collaborative tasks. We propose a scalable, real-time, MARL approach for UAV collaborative navigation where members of the swarm have to arrive at target locations at the same time. Centralized training and decentralized execution (CTDE) are used to achieve this, where a combination of negative and positive reinforcement is employed in the reward function. Curriculum learning is used to facilitate the sought performance, especially due to the high complexity of the problem which requires extensive exploration. A UAV model that highly resembles the respective physical platform is used for training the proposed framework to make training and testing realistic. The scalability of the platform to various swarm sizes, speeds, goal positions, environment dimensions, and UAV masses has been showcased in (1) a load drop-off scenario, and (2) UAV swarm formation without requiring any re-training or fine-tuning of the agents. The obtained simulation results have proven the effectiveness and generalizability of our proposed MARL framework for cooperative UAV navigation. Full article
(This article belongs to the Special Issue Intelligent Coordination of UAV Swarm Systems)
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20 pages, 10823 KiB  
Article
Speed-First: An Aggressive Gradient-Based Local Planner for Quadrotor Faster Flight
by Jiajie Yu, Jiaqi Li, Tong Zhang, Binbin Yan, Shaoyi Li and Zhongjie Meng
Drones 2023, 7(3), 192; https://doi.org/10.3390/drones7030192 - 11 Mar 2023
Viewed by 1110
Abstract
Autonomous flight for quadrotors is maturing with the development of real-time local trajectory planning. However, the current local planning method is too conservative to waste the agility of the quadrotors. So in this paper, we have focused on aggressive local trajectory planning and [...] Read more.
Autonomous flight for quadrotors is maturing with the development of real-time local trajectory planning. However, the current local planning method is too conservative to waste the agility of the quadrotors. So in this paper, we have focused on aggressive local trajectory planning and proposed a gradient-based planning method to rapidly plan faster executable trajectories while ensuring it is collision-free. A distance gradient information generation strategy is proposed, which finds a collision-free Hybrid-A* path to replace the control points in obstacles for safety and creates the distance gradient used in the back-end optimization. Besides, we present a novel and aggressive time span cost term to tackle unfeasibility and improve the overall trajectory speed. Extensive simulations and real-world experiments are tested to validate our method. The results show that our proposed method generates a more aggressive trajectory with a shorter planning time and a faster flight speed than the classical gradient-based method. Full article
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26 pages, 824 KiB  
Review
Drone-Aided Delivery Methods, Challenge, and the Future: A Methodological Review
by Xueping Li, Jose Tupayachi, Aliza Sharmin and Madelaine Martinez Ferguson
Drones 2023, 7(3), 191; https://doi.org/10.3390/drones7030191 - 10 Mar 2023
Cited by 8 | Viewed by 8294
Abstract
The use of drones for package delivery, commonly known as drone delivery or unmanned aerial vehicle (UAV) delivery, has gained significant attention from academia and industries. Compared to traditional delivery methods, it provides greater flexibility, improved accessibility, increased speed and efficiency, enhanced safety, [...] Read more.
The use of drones for package delivery, commonly known as drone delivery or unmanned aerial vehicle (UAV) delivery, has gained significant attention from academia and industries. Compared to traditional delivery methods, it provides greater flexibility, improved accessibility, increased speed and efficiency, enhanced safety, and even some environmental benefits. With the increasing interest in this technology, it is crucial for researchers and practitioners to understand the current state of the art in drone delivery. This paper aims to review the current literature on drone delivery and identify research trends, challenges, and future research directions. Specifically, the relevant literature is identified and selected using a systematic literature review approach. We then categorize the literature according to the characteristics and objectives of the problems and thoroughly analyze them based on mathematical formulations and solution techniques. We summarize key challenges and limitations associated with drone delivery from technological, safety, societal, and environmental aspects. Finally, potential research directions are identified. Full article
(This article belongs to the Special Issue The Applications of Drones in Logistics)
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