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Artykuły w czasopismach na temat „Fleet of UAVs”

Autor: Grafiati
Data publikacji: 14 grudnia 2024
Data aktualizacji: 31 lipca 2025

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1

Фесенко, Герман Вікторович, та Вячеслав Сергійович Харченко. "МОДЕЛІ НАДІЙНОСТІ УГРУПОВАНЬ ФЛОТІВ БПЛА З КОВЗНИМ РЕЗЕРВУВАННЯМ ДЛЯ МОНІТОРИНГУ ПОТЕНЦІЙНО НЕБЕЗПЕЧНИХ ОБ’ЄКТІВ". RADIOELECTRONIC AND COMPUTER SYSTEMS, № 2 (21 червня 2019): 147–56. http://dx.doi.org/10.32620/reks.2019.2.14.

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Over the past years, unmanned aerial vehicles have been used to solve the problems of pre-and post-accident monitoring of nuclear power plants and other potentially dangerous objects. The use of a fleet (fleet grouping) of the unmanned aerial vehicle (UAV) for monitoring missions is due to the special conditions of the aggressive environment, which causes the failures of certain UAVs, and therefore needs to ensure a high level of reliability of such a fleet (the group of fleets). The most effective way to solve this problem is to use k-out-of-n redundancy. The subject of the study is a UAV fle
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Thibbotuwawa, Bocewicz, Zbigniew, and Nielsen. "A Solution Approach for UAV Fleet Mission Planning in Changing Weather Conditions." Applied Sciences 9, no. 19 (2019): 3972. http://dx.doi.org/10.3390/app9193972.

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With a rising demand for utilizing unmanned aerial vehicles (UAVs) to deliver materials in outdoor environments, particular attention must be given to all the different aspects influencing the deployment of UAVs for such purposes. These aspects include the characteristics of the UAV fleet (e.g. size of fleet, UAV specifications and capabilities), the energy consumption (highly affected by weather conditions and payload) and the characteristics of the network and customer locations. All these aspects must be taken into account when aiming to achieve deliveries to customers in a safe and timely
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Godio, Simone, Stefano Primatesta, Giorgio Guglieri, and Fabio Dovis. "A Bioinspired Neural Network-Based Approach for Cooperative Coverage Planning of UAVs." Information 12, no. 2 (2021): 51. http://dx.doi.org/10.3390/info12020051.

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This paper describes a bioinspired neural-network-based approach to solve a coverage planning problem for a fleet of unmanned aerial vehicles exploring critical areas. The main goal is to fully cover the map, maintaining a uniform distribution of the fleet on the map, and avoiding collisions between vehicles and other obstacles. This specific task is suitable for surveillance applications, where the uniform distribution of the fleet in the map permits them to reach any position on the map as fast as possible in emergency scenarios. To solve this problem, a bioinspired neural network structure
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Larson, Jonathan, Paul Isihara, Gabriel Flores, et al. "A priori assessment of a smart-navigated unmanned aerial vehicle disaster cargo fleet." SIMULATION 96, no. 8 (2020): 641–53. http://dx.doi.org/10.1177/0037549720921447.

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The United Nations Office for the Coordination of Humanitarian Affairs has asserted that risks in deployment of unmanned aerial vehicles (UAVs) within disaster response must be reduced by careful development of best-practice standards before implementing such systems. With recent humanitarian field tests of cargo UAVs as indication that implementation may soon become reality, a priori assessment of a smart-navigated (autonomous) UAV disaster cargo fleet via simulation modeling and analysis is vital to the best-practice development process. Logistical problems with ground transport of relief su
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Thibbotuwawa, Amila, Grzegorz Bocewicz, Grzegorz Radzki, Peter Nielsen, and Zbigniew Banaszak. "UAV Mission Planning Resistant to Weather Uncertainty." Sensors 20, no. 2 (2020): 515. http://dx.doi.org/10.3390/s20020515.

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Fleet mission planning for Unmanned Aerial Vehicles (UAVs) is the process of creating flight plans for a specific set of objectives and typically over a time period. Due to the increasing focus on the usage of large UAVs, a key challenge is to conduct mission planning addressing changing weather conditions, collision avoidance, and energy constraints specific to these types of UAVs. This paper presents a declarative approach for solving the complex mission planning resistant to weather uncertainty. The approach has been tested on several examples, analyzing how customer satisfaction is influen
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Gadiraju, Divija Swetha, Prasenjit Karmakar, Vijay K. Shah, and Vaneet Aggarwal. "GLIDE: Multi-Agent Deep Reinforcement Learning for Coordinated UAV Control in Dynamic Military Environments." Information 15, no. 8 (2024): 477. http://dx.doi.org/10.3390/info15080477.

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Unmanned aerial vehicles (UAVs) are widely used for missions in dynamic environments. Deep Reinforcement Learning (DRL) can find effective strategies for multiple agents that need to cooperate to complete the task. In this article, the challenge of controlling the movement of a fleet of UAVs is addressed by Multi-Agent Deep Reinforcement Learning (MARL). The collaborative movement of the UAV fleet can be controlled centrally and also in a decentralized fashion, which is studied in this work. We consider a dynamic military environment with a fleet of UAVs, whose task is to destroy enemy targets
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Kats, Vladimir, and Eugene Levner. "Maximizing the Average Environmental Benefit of a Fleet of Drones under a Periodic Schedule of Tasks." Algorithms 17, no. 7 (2024): 283. http://dx.doi.org/10.3390/a17070283.

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Unmanned aerial vehicles (UAVs, drones) are not just a technological achievement based on modern ideas of artificial intelligence; they also provide a sustainable solution for green technologies in logistics, transport, and material handling. In particular, using battery-powered UAVs to transport products can significantly decrease energy and fuel expenses, reduce environmental pollution, and improve the efficiency of clean technologies through improved energy-saving efficiency. We consider the problem of maximizing the average environmental benefit of a fleet of drones given a periodic schedu
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Bit-Monnot, Arthur, Rafael Bailon-Ruiz, and Simon Lacroix. "A Local Search Approach to Observation Planning with Multiple UAVs." Proceedings of the International Conference on Automated Planning and Scheduling 28 (June 15, 2018): 437–45. http://dx.doi.org/10.1609/icaps.v28i1.13924.

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Observation planning for Unmanned Aerial Vehicles (UAVs) is a challenging task as it requires planning trajectories over a large continuous space and with motion models that can not be directly encoded into current planners. Furthermore, realistic problems often require complex objective functions that complicate problem decomposition. In this paper, we propose a local search approach to plan the trajectories of a fleet of UAVs on an observation mission. The strength of the approach lies in its loose coupling with domain specific requirements such as the UAV model or the objective function tha
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José-Torra, Ferran, Antonio Pascual-Iserte, and Josep Vidal. "A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations." Sensors 18, no. 10 (2018): 3411. http://dx.doi.org/10.3390/s18103411.

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This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous positioning strategy is developed, based on a fair distribution of the radio resources among all the users of all the cells in a given scenario, in such a way that the user bitrate is the same regardless the users’ distribution and spatial density. Moreover, two realistic constraints are added related to
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He, Ping Chuan, and Shu Ling Dai. "Parallel Niche Genetic Algorithm for UAV Fleet Stealth Coverage 3D Corridors Real-Time Planning." Advanced Materials Research 846-847 (November 2013): 1189–96. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1189.

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This paper presents a parallel improved niche genetic algorithm (PINGA) for 3D stealth coverage corridors real-time planning of unmanned aerial vehicles (UAVs) operating in a threat rich environment. 3D corridor was suggested to meet the diversity kinematics constraints of UAVs. Niche genetic algorithm (NGA) was improved by merging neighborhood mutation operator and hill climbing algorithm, and performed in parallel. Additionally, the crowding strategy based on high value targets was used to generate coverage trajectories in the area of interest (AOI). Preliminary results in virtual environmen
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Zhang, Yongchao, Wei Xu, Helin Ye, and Zhuoyong Shi. "A Two-Stage Optimization Framework for UAV Fleet Sizing and Task Allocation in Emergency Logistics Using the GWO and CBBA." Drones 9, no. 7 (2025): 501. https://doi.org/10.3390/drones9070501.

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The joint optimization of fleet size and task allocation presents a critical challenge in deploying Unmanned Aerial Vehicles (UAVs) for time-sensitive missions such as emergency logistics. Conventional approaches often rely on pre-determined fleet sizes or computationally intensive centralized optimizers, which can lead to suboptimal performance. To address this gap, this paper proposes a novel two-stage hierarchical framework that integrates the Grey Wolf Optimizer (GWO) with the Consensus-Based Bundle Algorithm (CBBA). At the strategic level, the GWO determines the optimal number of UAVs by
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Slim, M., M. Saied, H. Mazeh, H. Shraim, and C. Francis. "Fault-Tolerant Control Design for Multirotor UAVs Formation Flight." Giroskopiya i Navigatsiya 29, no. 2 (2021): 78–96. http://dx.doi.org/10.17285/0869-7035.0064.

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This paper proposes the use of the Gbest-Guided Artificial Bee Colony (GABC) algorithm to solve an online optimization problem for the leaderless distributed formation control of hexarotor Unmanned Aerial Vehicles (UAVs). The GABC is employed to optimize a cost function for each agent while ensuring the convergence of the fleet to the target position and averting both obstacles and collisions with other UAVs. The GABC algorithm has been shown to be competitive with some other conventional biological-inspired algorithms such as the Particle Swarm Optimization (PSO). Fault-Tolerant Control (FTC)
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13

Grasso, Christian, and Giovanni Schembra. "A Fleet of MEC UAVs to Extend a 5G Network Slice for Video Monitoring with Low-Latency Constraints." Journal of Sensor and Actuator Networks 8, no. 1 (2019): 3. http://dx.doi.org/10.3390/jsan8010003.

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In the last decade, video surveillance systems have become more and more popular. Thanks to a decrease in price of video camera devices and the diffusion of cheap small unmanned aerial vehicles (UAVs), video monitoring is today adopted in a wide range of application cases, from road traffic control to precision agriculture. This leads to capture a great amount of visual material to be monitored and screened for event detection. However, information that is gathered from a platform of video monitoring UAVs may produce high-volume data, whose processing is unfeasible to be done locally by the sa
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14

Zaitseva, Elena, Vitaly Levashenko, Ravil Mukhamediev, Nicolae Brinzei, Andriy Kovalenko, and Adilkhan Symagulov. "Review of Reliability Assessment Methods of Drone Swarm (Fleet) and a New Importance Evaluation Based Method of Drone Swarm Structure Analysis." Mathematics 11, no. 11 (2023): 2551. http://dx.doi.org/10.3390/math11112551.

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Drones, or UAVs, are developed very intensively. There are many effective applications of drones for problems of monitoring, searching, detection, communication, delivery, and transportation of cargo in various sectors of the economy. The reliability of drones in the resolution of these problems should play a principal role. Therefore, studies encompassing reliability analysis of drones and swarms (fleets) of drones are important. As shown in this paper, the analysis of drone reliability and its components is considered in studies often. Reliability analysis of drone swarms is investigated les
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Rinaldi, Marco, and Stefano Primatesta. "Comprehensive Task Optimization Architecture for Urban UAV-Based Intelligent Transportation System." Drones 8, no. 9 (2024): 473. http://dx.doi.org/10.3390/drones8090473.

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This paper tackles the problem of resource sharing and dynamic task assignment in a task scheduling architecture designed to enable a persistent, safe, and energy-efficient Intelligent Transportation System (ITS) based on multi-rotor Unmanned Aerial Vehicles (UAVs). The addressed task allocation problem consists of heterogenous pick-up and delivery tasks with time deadline constraints to be allocated to a heterogenous fleet of UAVs in an urban operational area. The proposed architecture is distributed among the UAVs and inspired by market-based allocation algorithms. By exploiting a multi-auct
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Bassolillo, Salvatore Rosario, Egidio D’Amato, and Immacolata Notaro. "A Consensus-Driven Distributed Moving Horizon Estimation Approach for Target Detection Within Unmanned Aerial Vehicle Formations in Rescue Operations." Drones 9, no. 2 (2025): 127. https://doi.org/10.3390/drones9020127.

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In the last decades, the increasing employment of unmanned aerial vehicles (UAVs) in civil applications has highlighted the potential of coordinated multi-aircraft missions. Such an approach offers advantages in terms of cost-effectiveness, operational flexibility, and mission success rates, particularly in complex scenarios such as search and rescue operations, environmental monitoring, and surveillance. However, achieving global situational awareness, although essential, represents a significant challenge, due to computational and communication constraints. This paper proposes a Distributed
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Ekechi, Chijioke C., Tarek Elfouly, Ali Alouani, and Tamer Khattab. "A Survey on UAV Control with Multi-Agent Reinforcement Learning." Drones 9, no. 7 (2025): 484. https://doi.org/10.3390/drones9070484.

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Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in both governmental and civilian applications, offering significant reductions in operational costs by minimizing human involvement. There is a growing demand for autonomous, scalable, and intelligent coordination strategies in complex aerial missions involving multiple Unmanned Aerial Vehicles (UAVs). Traditional control techniques often fall short in dynamic, uncertain, or large-scale environments where decentralized decision-making and inter-agent cooperation are crucial. A potentially effective technique used for UAV fleet
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Reineman, Benjamin D., Luc Lenain, and W. Kendall Melville. "The Use of Ship-Launched Fixed-Wing UAVs for Measuring the Marine Atmospheric Boundary Layer and Ocean Surface Processes." Journal of Atmospheric and Oceanic Technology 33, no. 9 (2016): 2029–52. http://dx.doi.org/10.1175/jtech-d-15-0019.1.

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AbstractThe deployment and recovery of autonomous or remotely piloted platforms from research vessels have become a way of significantly extending the capabilities and reach of the research fleet. This paper describes the use of ship-launched and ship-recovered Boeing–Insitu ScanEagle unmanned aerial vehicles (UAVs). The UAVs were instrumented to characterize the marine atmospheric boundary layer (MABL) structure and dynamics, and to measure ocean surface processes during the October 2012 Equatorial Mixing (EquatorMix) experiment in the central Pacific and during the July 2013 Trident Warrior
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Lagkas, Thomas, Vasileios Argyriou, Stamatia Bibi, and Panagiotis Sarigiannidis. "UAV IoT Framework Views and Challenges: Towards Protecting Drones as “Things”." Sensors 18, no. 11 (2018): 4015. http://dx.doi.org/10.3390/s18114015.

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Unmanned aerial vehicles (UAVs) have enormous potential in enabling new applications in various areas, ranging from military, security, medicine, and surveillance to traffic-monitoring applications. Lately, there has been heavy investment in the development of UAVs and multi-UAVs systems that can collaborate and complete missions more efficiently and economically. Emerging technologies such as 4G/5G networks have significant potential on UAVs equipped with cameras, sensors, and GPS receivers in delivering Internet of Things (IoT) services from great heights, creating an airborne domain of the
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Bocewicz, Grzegorz, Grzegorz Radzki, Izabela Nielsen, Marcin Witczak, and Banaszak Zbigniew. "UAVs fleet mission planning robust to changing weather conditions." IFAC-PapersOnLine 53, no. 2 (2020): 10518–24. http://dx.doi.org/10.1016/j.ifacol.2020.12.2798.

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Bailon-Ruiz, Rafael, Arthur Bit-Monnot, and Simon Lacroix. "Real-time wildfire monitoring with a fleet of UAVs." Robotics and Autonomous Systems 152 (June 2022): 104071. http://dx.doi.org/10.1016/j.robot.2022.104071.

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Tipantuña, Christian, Xavier Hesselbach, Victor Sánchez-Aguero, Francisco Valera, Ivan Vidal, and Borja Nogales. "An NFV-Based Energy Scheduling Algorithm for a 5G Enabled Fleet of Programmable Unmanned Aerial Vehicles." Wireless Communications and Mobile Computing 2019 (February 20, 2019): 1–20. http://dx.doi.org/10.1155/2019/4734821.

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The fifth generation of mobile networks (5G) is expected to provide diverse and stringent improvements such as greater connectivity, bandwidth, throughput, availability, improved coverage, and lower latency. Considering this, drones or Unmanned Aerial Vehicles (UAVs) and Internet of Things (IoT) devices are perfect examples of existing technology that can take advantage of the capabilities provided by 5G technology. In particular, UAVs are expected to be an important component of 5G networks implementations and support different communication requirements and applications. UAVs working togethe
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Su, Wenjia, Min Gao, Xinbao Gao, and Zhaolong Xuan. "Enhanced Multi-UAV Path Planning in Complex Environments With Voronoi-Based Obstacle Modelling and Q-Learning." International Journal of Aerospace Engineering 2024 (May 27, 2024): 1–14. http://dx.doi.org/10.1155/2024/5114696.

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To tackle the challenge of obstacle avoidance path planning for multiple unmanned aerial vehicles (UAVs) in intricate environments, this study introduces a Voronoi graph–based model to represent the obstacle-laden environment and employs a Markov decision process (MDP) for single UAV path planning. The traditional Q-learning algorithm is enhanced by adjusting the initial state of the Q-table and fine-tuning the reward and penalty values, enabling the acquisition of efficient obstacle avoidance paths for individual UAVs in complex settings. Leveraging the improved Q-learning algorithm for singl
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Felli, Lorenzo, Romeo Giuliano, Andrea De Negri, Francesco Terlizzi, Franco Mazzenga, and Alessandro Vizzarri. "Maximal LoRa Range for Unmanned Aerial Vehicle Fleet Service in Different Environmental Conditions." IoT 5, no. 3 (2024): 509–23. http://dx.doi.org/10.3390/iot5030023.

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This study investigates communication between UAVs using long range (LoRa) devices, focusing on the interaction between a LoRa gateway UAV and other UAVs equipped with LoRa transmitters. By conducting experiments across various geographical regions, this study aims to delineate the fundamental boundary conditions for the efficient control of a UAV fleet. The parameters under analysis encompass inter-device spacing, radio interference effects, and terrain topography. This research yields pivotal insights into communication network design and optimization, thereby enhancing operational efficienc
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Lissandrini, Nicola, Giulia Michieletto, Riccardo Antonello, Marta Galvan, Alberto Franco, and Angelo Cenedese. "Cooperative Optimization of UAVs Formation Visual Tracking." Robotics 8, no. 3 (2019): 52. http://dx.doi.org/10.3390/robotics8030052.

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The use of unmanned vehicles to perform tiring, hazardous, repetitive tasks, is becoming a reality out of the academy laboratories, getting more and more interest for several application fields from the industrial, to the civil, to the military contexts. In particular, these technologies appear quite promising when they employ several low-cost resource-constrained vehicles leveraging their coordination to perform complex tasks with efficiency, flexibility, and adaptation that are superior to those of a single agent (even if more instrumented). In this work, we study one of said applications, n
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Almeida, M., H. Hildmann, and G. Solmaz. "DISTRIBUTED UAV-SWARM-BASED REAL-TIME GEOMATIC DATA COLLECTION UNDER DYNAMICALLY CHANGING RESOLUTION REQUIREMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 5–12. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-5-2017.

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Unmanned Aerial Vehicles (UAVs) have been used for reconnaissance and surveillance missions as far back as the Vietnam War, but with the recent rapid increase in autonomy, precision and performance capabilities – and due to the massive reduction in cost and size – UAVs have become pervasive products, available and affordable for the general public. The use cases for UAVs are in the areas of disaster recovery, environmental mapping & protection and increasingly also as extended eyes and ears of civil security forces such as fire-fighters and emergency respons
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Zemlianko, H., and V. Kharchenko. "Cyber Security Systems of Highly Functional Uav Fleets for Monitoring Critical Infrastructure: Analysis of Disruptions, Attacks and Counterapproaches." Èlektronnoe modelirovanie 46, no. 1 (2024): 41–54. http://dx.doi.org/10.15407/emodel.46.01.041.

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The modern world is becoming increasingly dependent on the security of critical infrastructure facilities (CIF), which is monitored by UAVs, their fleets and multifunctional fleet systems (MFS UAVs). The UAV MFS have a complex digital infrastructure (DIS). The DIS is based on new information technologies that have certain security deficiencies and create new cyber threats, in particular, due to specific vulnerabilities that can be exploited externally. The provi-sion of cyber security of the CIS of the MBF of UAVs has been studied thanks to the develop-ment of a sequence of analysis of cyber t
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Kabashkin, Igor. "Availability of Services in Wireless Sensor Network with Aerial Base Station Placement." Journal of Sensor and Actuator Networks 12, no. 3 (2023): 39. http://dx.doi.org/10.3390/jsan12030039.

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Internet of Things technologies use many sensors combined with wireless networks for cyber-physical systems in various applications. Mobility is an essential characteristic for many objects that use sensors. In mobile sensor networks, the availability of communication channels is crucial, especially for mission-critical applications. This article presents models for analyzing the availability of sensor services in a wireless network with aerial base station placement (ABSP), considering the real conditions for using unmanned aerial vehicles (UAVs). The studied system uses a UAV-assisted mobile
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Bousbaa, Fatima Zohra, Chaker Abdelaziz Kerrache, Zohra Mahi, Abdou El Karim Tahari, Nasreddine Lagraa, and Mohamed Bachir Yagoubi. "GeoUAVs: A new geocast routing protocol for fleet of UAVs." Computer Communications 149 (January 2020): 259–69. http://dx.doi.org/10.1016/j.comcom.2019.10.026.

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Calamoneri, Tiziana, Federico Corò, and Simona Mancini. "Autonomous data detection and inspection with a fleet of UAVs." Computers & Operations Research 168 (August 2024): 106678. http://dx.doi.org/10.1016/j.cor.2024.106678.

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Bemposta Rosende, Sergio, Javier Sánchez-Soriano, Carlos Quiterio Gómez Muñoz, and Javier Fernández Andrés. "Remote Management Architecture of UAV Fleets for Maintenance, Surveillance, and Security Tasks in Solar Power Plants." Energies 13, no. 21 (2020): 5712. http://dx.doi.org/10.3390/en13215712.

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This article presents a remote management architecture of an unmanned aerial vehicles (UAVs) fleet to aid in the management of solar power plants and object tracking. The proposed system is a competitive advantage for sola r energy production plants, due to the reduction in costs for maintenance, surveillance, and security tasks, especially in large solar farms. This new approach consists of creating a hardware and software architecture that allows for performing different tasks automatically, as well as remotely using fleets of UAVs. The entire system, composed of the aircraft, the servers, c
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Han, Peng, Xinyue Yang, Kin Huat Low, and Yifei Zhao. "Parametric Analysis of Landing Capacity for UAV Fleet Operations with Specific Airspace Structures and Rule-Based Constraints." Drones 8, no. 12 (2024): 770. https://doi.org/10.3390/drones8120770.

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As Urban Air Mobility (UAM) moves toward implementation, managing high-density, high-volume flights in urban airspaces becomes increasingly critical. In such environments, the design of vertiport airspace structures plays a key role in determining how many UAVs can operate safely and efficiently within a specific airspace. Existing studies have not fully explored the complex interdependencies between airspace structure parameters and fleet operation capacity, particularly regarding how various structural components and their configurations affect UAV fleet performance. This paper addresses the
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DEWMINI, Janani, W. Madushan FERNANDO, Izabela Iwa NIELSEN, Grzegorz BOCEWICZ, Amila THIBBOTUWAWA, and Zbigniew BANASZAK. "IDENTIFYING THE POTENTIAL OF UNMANNED AERIAL VEHICLE ROUTING FOR BLOOD DISTRIBUTION IN EMERGENCY REQUESTS." Applied Computer Science 19, no. 4 (2023): 68–87. http://dx.doi.org/10.35784/acs-2023-36.

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This study is focusing on identifying the potential of Unmanned Aerial Vehicle (UAV) routing for blood distribution in emergency requests in Sri Lanka compared to existing transportation modes. Capacitated Unmanned Aerial Vehicle Routing Problem was used as the methodology to find the optimal distribution plan between blood banks directing emergency requests. The developed UAV routing model was tested for different instances to compare the results. Finally, the proposed distribution process via UAVs was compared with the current distribution process for the objective function set up in the mod
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Alhaqbani, Amjaad, Heba Kurdi, and Kamal Youcef-Toumi. "Fish-Inspired Task Allocation Algorithm for Multiple Unmanned Aerial Vehicles in Search and Rescue Missions." Remote Sensing 13, no. 1 (2020): 27. http://dx.doi.org/10.3390/rs13010027.

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The challenge concerning the optimal allocation of tasks across multiple unmanned aerial vehicles (multi-UAVs) has significantly spurred research interest due to its contribution to the success of various fleet missions. This challenge becomes more complex in time-constrained missions, particularly if they are conducted in hostile environments, such as search and rescue (SAR) missions. In this study, a novel fish-inspired algorithm for multi-UAV missions (FIAM) for task allocation is proposed, which was inspired by the adaptive schooling and foraging behaviors of fish. FIAM shows that UAVs in
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Bono, Antonio, Luigi D’Alfonso, Giuseppe Fedele, Anselmo Filice, and Enrico Natalizio. "Path Planning and Control of a UAV Fleet in Bridge Management Systems." Remote Sensing 14, no. 8 (2022): 1858. http://dx.doi.org/10.3390/rs14081858.

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Traditional methodologies for precise inspection of bridges (pavement, beams, column cap, column, joints and inside box girder, etc.) with By-bridge equipment, Aerial Work Platform (AWP) or via ropes have several limits that can be overcome by using Unmanned Aerial Vehicles (UAVs). The constant development in this field allows us to go beyond the manual control and the use of a single UAV. In the context of inspection rules, this research provides new inputs to the multilevel approach used today and to the methods of structural inspection with drones. Today, UAV-based inspections are limited b
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Ibenthal, Julius, Michel Kieffer, Luc Meyer, Hélène Piet-Lahanier, and Sébastien Reynaud. "Bounded-error target localization and tracking using a fleet of UAVs." Automatica 132 (October 2021): 109809. http://dx.doi.org/10.1016/j.automatica.2021.109809.

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Feng, Yi, Cong Zhang, Stanley Baek, Samir Rawashdeh, and Alireza Mohammadi. "Autonomous Landing of a UAV on a Moving Platform Using Model Predictive Control." Drones 2, no. 4 (2018): 34. http://dx.doi.org/10.3390/drones2040034.

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Developing methods for autonomous landing of an unmanned aerial vehicle (UAV) on a mobile platform has been an active area of research over the past decade, as it offers an attractive solution for cases where rapid deployment and recovery of a fleet of UAVs, continuous flight tasks, extended operational ranges, and mobile recharging stations are desired. In this work, we present a new autonomous landing method that can be implemented on micro UAVs that require high-bandwidth feedback control loops for safe landing under various uncertainties and wind disturbances. We present our system archite
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Pham, Thiem V., and Thanh Dong Nguyen. "Path-Following Formation of Fixed-Wing UAVs under Communication Delay: A Vector Field Approach." Drones 8, no. 6 (2024): 237. http://dx.doi.org/10.3390/drones8060237.

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In many applications, such as atmospheric observation or disaster monitoring, cooperative control of a fleet of UAVs is crucial because it is effective in repeated tasks. In this work, we provide a workable and useful cooperative guiding algorithm for several fixed-wing UAVs to construct a path-following formation with communication delays. The two primary components of our concept are path-following (lateral guidance) and path formation (longitudinal guidance). The former is in charge of ensuring that, in the presence of wind disturbance, the lateral distance between the UAV and its targeted
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Alvear, Oscar, Nicola Roberto Zema, Enrico Natalizio, and Carlos T. Calafate. "Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility." Journal of Advanced Transportation 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/8204353.

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Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local pa
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Sun, Xiaolei, Naiming Qi, and Weiran Yao. "Boolean Networks-Based Auction Algorithm for Task Assignment of Multiple UAVs." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/425356.

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This paper presents an application of Boolean networks-based auction algorithm (BNAA) for task assignment in unmanned aerial vehicles (UAVs) systems. Under reasonable assumptions, the assignment framework consists of mission control system, communication network, and ground control station. As the improved algorithm of consensus-based bundle algorithm (CBBA), the BNAA utilizes a cluster-based combinatorial auction policy to handle multiple tasks. Instead of empirical method based on look-up table about conditional variables, Boolean network is introduced into consensus routine of BNAA for solv
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Radzki, Grzegorz, Izabela Nielsen, Paulina Golińska-Dawson, Grzegorz Bocewicz, and Zbigniew Banaszak. "Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments." Sustainability 13, no. 9 (2021): 5228. http://dx.doi.org/10.3390/su13095228.

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Unmanned aerial vehicles (UAVs) create an interesting alternative for establishing more sustainable urban freight deliveries. The substitution of traditional trucks in the last-mile distribution by a UAV fleet can contribute to urban sustainability by reducing air pollution and increasing urban freight efficiency. This paper presents a novel approach to the joint proactive and reactive planning of deliveries by a UAV fleet. We develop a receding horizon-based approach to reactive, online planning for the UAV fleet’s mission. We considered the delivery of goods to spatially dispersed customers
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Hassan, Zohaib, Syed Irtiza Ali Shah, and Ahsan Sarwar Rana. "Charging Station Distribution Optimization Using Drone Fleet in a Disaster." Journal of Robotics 2022 (July 31, 2022): 1–13. http://dx.doi.org/10.1155/2022/7329346.

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A disaster is an unforeseen calamity that can cause damage to properties and can bring about a loss of human lives. Usually, many relief supplies, such as clean water, food, and medical supplies, are required by disaster victims. Quick response and rapid distribution of essential relief items into the affected region can save countless lives and prevent or slow down the effects of disasters. In this regard, disaster management comes into play, which is highly dependent on the topography and access of the disaster-hit area. If the disaster-hit site has little or no road connectivity, the use of
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Loroch, Leszek, and Andrzej Żyluk. "New Technologies for Air Traffic Security." Journal of Konbin 7, no. 4 (2008): 95–112. http://dx.doi.org/10.2478/v10040-008-0081-z.

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New Technologies for Air Traffic Security Security of increasing intensity of air traffic requires significant technological support. In Europe, the dynamics of this phenomenon will be additionally stimulated by implementation of unmanned aerial vehicles (UAVs) into the air traffic. For effective operation of aircraft fleet it is necessary to employ new on-board diagnostic devices and flight recorders in order to evaluate technical condition of aircraft's instrumentation. Reducing the pilots' workload requires the development of new integrated digital avionics. On the other hand, in order to m
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Perez-Montenegro, Carlos, Matteo Scanavino, Nicoletta Bloise, Elisa Capello, Giorgio Guglieri, and Alessandro Rizzo. "A Mission Coordinator Approach for a Fleet of UAVs in Urban Scenarios." Transportation Research Procedia 35 (2018): 110–19. http://dx.doi.org/10.1016/j.trpro.2018.12.018.

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El Ferik, Sami, and Olapido Raphael Thompson. "Biologically Inspired Control Of A Fleet Of Uavs With Threat Evasion Strategy." Asian Journal of Control 18, no. 6 (2016): 2283–300. http://dx.doi.org/10.1002/asjc.1324.

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Zhou, Jinlun, Honghai Zhang, Mingzhuang Hua, Fei Wang, and Jia Yi. "P-DRL: A Framework for Multi-UAVs Dynamic Formation Control under Operational Uncertainty and Unknown Environment." Drones 8, no. 9 (2024): 475. http://dx.doi.org/10.3390/drones8090475.

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Unmanned aerial vehicle (UAV) formation flying is an efficient and economical operation mode for air transportation systems. To improve the effectiveness of synergetic formation control for UAVs, this paper proposes a pairwise conflict resolution approach for UAV formation through mathematical analysis and designs a dynamic pairing and deep reinforcement learning framework (P-DRL formation control framework). Firstly, a new pairwise UAV formation control theorem is proposed, which breaks down the multi-UAVs formation control problem into multiple sequential control problems involving UAV pairs
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Grzegorz, Radzki, Bocewicz Grzegorz, Dybala Bogdan, and Banaszak Zbigniew. "Reactive Planning-Driven Approach to Online UAVs Mission Rerouting and Rescheduling." Applied Sciences 11, no. 19 (2021): 8898. http://dx.doi.org/10.3390/app11198898.

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The presented problem concerns the route planning of a UAV fleet carrying out deliveries to spatially dispersed customers in a highly dynamic and unpredictable environment within a specified timeframe. The developed model allows for predictive (i.e., taking into account forecasted changing weather conditions) and reactive (i.e., enabling contingency UAVs rerouting) delivery mission planning (i.e., NP-hard problem) in terms of the constraint satisfaction problem. Due to the need to implement an emergency return of the UAV to the base or handling ad hoc ordered deliveries, sufficient conditions
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Cordeiro, Thiago F. K., João Y. Ishihara, and Henrique C. Ferreira. "A Decentralized Low-Chattering Sliding Mode Formation Flight Controller for a Swarm of UAVs." Sensors 20, no. 11 (2020): 3094. http://dx.doi.org/10.3390/s20113094.

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In this paper, a nonlinear robust formation flight controller for a swarm of unmanned aerial vehicles (UAVs) is presented. It is based on the virtual leader approach and is capable of achieving and maintaining a formation with time-varying shape. By using a decentralized architecture, the local controller in each UAV uses information only from the UAV itself, its neighbors, and from the virtual leader. Also, a synchronization control objective provides a mechanism to weight between the fleet achieving the desired formation shape, that is, achieving the desired relative position between the UAV
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Shuaibu, Abdullahi Sani, Ashraf Sharif Mahmoud, and Tarek Rahil Sheltami. "A Review of Last-Mile Delivery Optimization: Strategies, Technologies, Drone Integration, and Future Trends." Drones 9, no. 3 (2025): 158. https://doi.org/10.3390/drones9030158.

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Last-mile delivery (LMD) is an important aspect of contemporary logistics that directly affects operational cost, efficiency, and customer satisfaction. In this paper, we provide a review of the optimization techniques of LMD, focusing on Artificial Intelligence (AI) driven decision-making, IoT-supported real-time monitoring, and hybrid delivery networks. The combination of AI and IoT improves predictive analytics, dynamic routing, and fleet management, but scalability and regulatory issues are still major concerns. Hybrid frameworks that integrate drones or Unmanned Aerial Vehicles (UAVs), gr
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Htiouech, Skander, Khalil Chebil, Mahdi Khemakhem, Fidaa Abed, and Monaji H. Alkiani. "An Extended Model for the UAVs-Assisted Multiperiodic Crowd Tracking Problem." Complexity 2023 (February 1, 2023): 1–14. http://dx.doi.org/10.1155/2023/3001812.

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The multiperiodic crowd tracking (MPCT) problem is an extension of the periodic crowd tracking (PCT) problem, recently addressed in the literature and solved using an iterative solver called PCTs solver. For a given crowded event, the MPCT consists of follow-up crowds, using unmanned aerial vehicles (UAVs) during different periods in a life-cycle of an open crowded area (OCA). Our main motivation is to remedy an important limitation of the PCTs solver called “PCTs solver myopia” which is, in certain cases, unable to manage the fleet of UAVs to cover all the periods of a given OCA life-cycle du
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