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Robotics
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UAV Systems and Swarm Robotics
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UAV Systems and Swarm Robotics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Aerospace Robotics and Autonomous Systems".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 27334

Special Issue Editors

Dr. Gerardo Flores

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Guest Editor
RAPTOR Lab (Robotics and Autonomous Platforms for Technology Operations and Research), School of Engineering, College of Arts and Sciences, Texas A&M International University, Laredo, TX 78041, USA
Interests: artificial vision; theory and applications of intelligent systems; control of nonlinear systems; design, conception and control of unmanned vehicles; terrestrial, aerial and submarine types
Special Issues, Collections and Topics in MDPI journals
Dr. Hector M. Becerra

E-Mail Website
Guest Editor
Centro de Investigación en Matemáticas (CIMAT), Jalisco S-N, Guanajuato 36240, Mexico
Interests: control of multi-agent systems and multiple robots; visual servoing and visual navigation of aerial vehicles, humanoids and wheeled robots; control of robotic systems
Special Issues, Collections and Topics in MDPI journals
Dr. Juan-Pablo Ramirez-Paredes

E-Mail Website
Guest Editor
Departamento de Ingeniería Electrónica, Universidad de Guanajuato, Guanajuato, Mexico
Interests: estimation; control; computer vision; robotics
Dr. Alexandre Brandão

E-Mail Website
Guest Editor
Núcleo de Especialização em Robótica (NERO), Department of Electrical Engineering, Graduate Program in Computer Science, Universidade Federal de Viçosa, Viçosa 36570-900, Minas Gerais, Brazil
Interests: aerial robotics; multi-robot systems; sensing for robot navigation; applied artificial intelligence; path planning; load transportation using UAS
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) and swarm robotics are two rapidly growing areas of research and development with numerous applications across various industries. UAVs are aerial vehicles that can operate autonomously or with minimal human intervention and potentially transform fields such as agriculture, environmental monitoring, and disaster response. On the other hand, swarm robotics is a branch of robotics that focuses on the coordination and collective behavior of large groups of robots. Together, UAV systems and swarm robotics have the potential to revolutionize the way we approach complex tasks, from large-scale environmental monitoring to efficient and effective disaster response. This Special Issue on "UAV Systems and Swarm Robotics" aims to bring together researchers, practitioners, and experts to showcase the latest developments, trends, and challenges in these exciting and rapidly growing fields.

We invite scientists, researchers, practitioners, and experts in the field to contribute original research articles, review articles, and case studies that advance our understanding of unmanned aerial vehicles (UAVs) and swarm robotics. This Special Issue aims to provide a platform for showcasing the latest developments, trends, and challenges in these areas and to facilitate the exchange of ideas and knowledge among researchers, practitioners, and stakeholders. The topics of interest for the Special Issue include but are not limited to UAV system design and control, swarm intelligence and coordination, UAVs in environmental monitoring and surveillance, UAVs in agriculture and forestry, swarm robotics in industrial and service applications, and UAVs in emergency response and disaster management.

Of particular interest are the following subjects:

  • Robot navigation in unknown environments;
  • Perception and mapping using UAVs or multiple robots;
  • Exploration with UAVs or with multiple robots;
  • Advanced control of UAVs;
  • UAV systems applications;
  • Distributed control;
  • Formation control;
  • Modeling and control of flying multibody robots;
  • Control of underactuated robotic systems;
  • Vision-based control of robotic systems.

Besides fundamental and practical research, papers that present an in-depth study of the state of the art in the subject of the Special Issue will be well received. Note that the submitted papers can be on research on a single UAV or a group of them.

Dr. Gerardo Flores
Dr. Hector M. Becerra
Dr. Juan-Pablo Ramirez-Paredes
Dr. Alexandre Brandão
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (11 papers)

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Research

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28 pages, 44193 KiB  
Article
Vision-Based Formation Control of Quadrotors Using a Bearing-Only Approach
by David L. Ramírez-Parada, Héctor M. Becerra, Carlos A. Toro-Arcila and Gustavo Arechavaleta
Robotics 2024, 13(8), 115; https://doi.org/10.3390/robotics13080115 - 28 Jul 2024
Viewed by 1452
Abstract
In this paper, we present a vision-based leader–follower strategy for formation control of multiple quadrotors. The leaders use a decoupled visual control scheme based on invariant features. The followers use a control scheme based only on bearing measurements, and a robust control is [...] Read more.
In this paper, we present a vision-based leader–follower strategy for formation control of multiple quadrotors. The leaders use a decoupled visual control scheme based on invariant features. The followers use a control scheme based only on bearing measurements, and a robust control is introduced to deal with perturbations generated by the unknown movement of the leaders. Using this formulation, we study a geometrical pattern formation that can use the distance between the leaders to scale the formation and cross constrained spaces, such as a window. A condition is defined for which a formation has rigidity properties considering the constrained field of view of the cameras, such that invariance to translation and scaling is achieved. This condition allows us to specify a desired formation where the followers do not need to share information between them. Results obtained in a dynamic simulator and real experiments show the effectiveness of the approach. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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26 pages, 2617 KiB  
Article
Fixed-Wing UAV Pose Estimation Using a Self-Organizing Map and Deep Learning
by Nuno Pessanha Santos
Robotics 2024, 13(8), 114; https://doi.org/10.3390/robotics13080114 - 27 Jul 2024
Cited by 1 | Viewed by 1101
Abstract
In many Unmanned Aerial Vehicle (UAV) operations, accurately estimating the UAV’s position and orientation over time is crucial for controlling its trajectory. This is especially important when considering the landing maneuver, where a ground-based camera system can estimate the UAV’s 3D position and [...] Read more.
In many Unmanned Aerial Vehicle (UAV) operations, accurately estimating the UAV’s position and orientation over time is crucial for controlling its trajectory. This is especially important when considering the landing maneuver, where a ground-based camera system can estimate the UAV’s 3D position and orientation. A Red, Green, and Blue (RGB) ground-based monocular approach can be used for this purpose, allowing for more complex algorithms and higher processing power. The proposed method uses a hybrid Artificial Neural Network (ANN) model, incorporating a Kohonen Neural Network (KNN) or Self-Organizing Map (SOM) to identify feature points representing a cluster obtained from a binary image containing the UAV. A Deep Neural Network (DNN) architecture is then used to estimate the actual UAV pose based on a single frame, including translation and orientation. Utilizing the UAV Computer-Aided Design (CAD) model, the network structure can be easily trained using a synthetic dataset, and then fine-tuning can be done to perform transfer learning to deal with real data. The experimental results demonstrate that the system achieves high accuracy, characterized by low errors in UAV pose estimation. This implementation paves the way for automating operational tasks like autonomous landing, which is especially hazardous and prone to failure. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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29 pages, 15983 KiB  
Article
Analysis of Attack Intensity on Autonomous Mobile Robots
by Elena Basan, Alexander Basan, Alexey Mushenko, Alexey Nekrasov, Colin Fidge and Alexander Lesnikov
Robotics 2024, 13(7), 101; https://doi.org/10.3390/robotics13070101 - 10 Jul 2024
Cited by 1 | Viewed by 1052
Abstract
Autonomous mobile robots (AMRs) combine a remarkable combination of mobility, adaptability, and an innate capacity for obstacle avoidance. They are exceptionally well-suited for a wide range of applications but usually operate in uncontrolled, non-deterministic environments, so the analysis and classification of security events [...] Read more.
Autonomous mobile robots (AMRs) combine a remarkable combination of mobility, adaptability, and an innate capacity for obstacle avoidance. They are exceptionally well-suited for a wide range of applications but usually operate in uncontrolled, non-deterministic environments, so the analysis and classification of security events are very important for their safe operation. In this regard, we considered the influence of different types of attacks on AMR navigation systems to subdivide them into classes and unified the effect of attacks on the system through their level of consequences and impact. Then, we built a model of an attack on a system, taking into account five methods of attack implementation and identified the unified response thresholds valid for any type of parameter, which allows for creating universal correlation rules and simplifies this process, as the trigger threshold is related to the degree of impact that the attack has on the finite subsystem. Also, we developed a methodology for classifying incidents and identifying key components of the system based on ontological models, which makes it possible to predict risks and select the optimal system configuration. The obtained results are important in the context of separating different types of destructive effects based on attack classes. Our study showed that it is sometimes difficult to divide spoofing attacks into classes by assessing only one parameter since the attacker can use a complex attack scenario, mixing the stages of the scenarios. We then showed how adding an attack intensity factor can make classification more flexible. The connections between subsystems and parameters, as well as the attack impact patterns, were determined. Finally, a set of unique rules was developed to classify destructive effects with uniform response thresholds for each parameter. In this case, we can increase the number of parameters as well as the type of parameter value. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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26 pages, 18416 KiB  
Article
An Aerial Robotic Missing-Person Search in Urban Settings—A Probabilistic Approach
by Cameron Haigh, Goldie Nejat and Beno Benhabib
Robotics 2024, 13(5), 73; https://doi.org/10.3390/robotics13050073 - 9 May 2024
Viewed by 1825
Abstract
Autonomous robotic teams have been proposed for a variety of lost-person searches in wilderness and urban settings. In the latter scenarios, for missing persons, the application of such teams, however, is more challenging than it would be in the wilderness. This paper, specifically, [...] Read more.
Autonomous robotic teams have been proposed for a variety of lost-person searches in wilderness and urban settings. In the latter scenarios, for missing persons, the application of such teams, however, is more challenging than it would be in the wilderness. This paper, specifically, examines the application of an autonomous team of unmanned aerial vehicles (UAVs) to perform a sparse, mobile-target search in an urban setting. A novel multi-UAV search-trajectory planning method, which relies on the prediction of the missing-person’s motion, given a known map of the search environment, is the primary focus. The proposed method incorporates periodic updates of the estimates of where the lost/missing person may be, allowing for intelligent re-coverage of previously searched areas. Additional significant contributions of this work include a behavior-based motion-prediction method for missing persons and a novel non-parametric estimator for iso-probability-based (missing-person-location) curves. Simulated experiments are presented to illustrate the effectiveness of the proposed search-planning method, demonstrating higher rates of missing-person detection and in shorter times compared to other methods. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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33 pages, 8086 KiB  
Article
Experimental Nonlinear and Incremental Control Stabilization of a Tail-Sitter UAV with Hardware-in-the-Loop Validation
by Alexandre Athayde, Alexandra Moutinho and José Raúl Azinheira
Robotics 2024, 13(3), 51; https://doi.org/10.3390/robotics13030051 - 16 Mar 2024
Cited by 3 | Viewed by 2131
Abstract
Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the [...] Read more.
Tail-sitters aim to combine the advantages of fixed-wing aircraft and rotorcraft but require a robust and fast stabilization strategy to perform vertical maneuvers and transitions to and from aerodynamic flight. The research conducted in this work explores different nonlinear control solutions for the problem of stabilizing a tail-sitter when hovering. For this purpose, the first controller is an existing strategy for tail-sitter control obtained from the literature, the second is an application of Nonlinear Dynamic Inversion (NDI), and the last one is its incremental version, INDI. These controllers were implemented and tuned in a simulation in order to stabilize a model of the tail-sitter, complemented by estimation methods that allow the feedback of the necessary variables. These estimators and controllers were then implemented in a microcontroller and validated in a Hardware-in-the-Loop (HITL) scenario with simple maneuvers in vertical flight. Lastly, the developed control solutions were used to stabilize the aircraft in experimental flight while being monitored by a motion capture system. The experimental results allow the validation of the model of the X-Vert and provide a comparison of the performance of the different control solutions, where the INDI presents itself as a robust control strategy with accurate tracking capabilities and less actuator demand. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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20 pages, 2092 KiB  
Article
Low-Cost Computer-Vision-Based Embedded Systems for UAVs
by Luis D. Ortega, Erick S. Loyaga, Patricio J. Cruz, Henry P. Lema, Jackeline Abad and Esteban A. Valencia
Robotics 2023, 12(6), 145; https://doi.org/10.3390/robotics12060145 - 27 Oct 2023
Cited by 8 | Viewed by 3436
Abstract
Unmanned Aerial Vehicles (UAVs) are versatile, adapting hardware and software for research. They are vital for remote monitoring, especially in challenging settings such as volcano observation with limited access. In response, economical computer vision systems provide a remedy by processing data, boosting UAV [...] Read more.
Unmanned Aerial Vehicles (UAVs) are versatile, adapting hardware and software for research. They are vital for remote monitoring, especially in challenging settings such as volcano observation with limited access. In response, economical computer vision systems provide a remedy by processing data, boosting UAV autonomy, and assisting in maneuvering. Through the application of these technologies, researchers can effectively monitor remote areas, thus improving surveillance capabilities. Moreover, flight controllers employ onboard tools to gather data, further enhancing UAV navigation during surveillance tasks. For energy efficiency and comprehensive coverage, this paper introduces a budget-friendly prototype aiding UAV navigation, minimizing effects on endurance. The prototype prioritizes improved maneuvering via the integrated landing and obstacle avoidance system (LOAS). Employing open-source software and MAVLink communication, these systems underwent testing on a Pixhawk-equipped quadcopter. Programmed on a Raspberry Pi onboard computer, the prototype includes a distance sensor and basic camera to meet low computational and weight demands.Tests occurred in controlled environments, with systems performing well in 90% of cases. The Pixhawk and Raspberry Pi documented quad actions during evasive and landing maneuvers. Results prove the prototype’s efficacy in refining UAV navigation. Integrating this cost-effective, energy-efficient model holds promise for long-term mission enhancement—cutting costs, expanding terrain coverage, and boosting surveillance capabilities. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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25 pages, 49963 KiB  
Article
Three-Dimensional Flight Corridor: An Occupancy Checking Process for Unmanned Aerial Vehicle Motion Planning inside Confined Spaces
by Sherif Mostafa and Alejandro Ramirez-Serrano
Robotics 2023, 12(5), 134; https://doi.org/10.3390/robotics12050134 - 29 Sep 2023
Cited by 3 | Viewed by 2102
Abstract
To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined (potentially unknown) spaces, such as those encountered in mining and Urban Search and Rescue (USAR), requires the enhancement of numerous technologies. Of special interest is for UAVs to identify collision-freeSafe Flight Corridors ( [...] Read more.
To deploy Unmanned Aerial Vehicles (UAVs) inside heterogeneous GPS-denied confined (potentially unknown) spaces, such as those encountered in mining and Urban Search and Rescue (USAR), requires the enhancement of numerous technologies. Of special interest is for UAVs to identify collision-freeSafe Flight Corridors (SFC+) within highly cluttered convex- and non-convex-shaped environments, which requires UAVs to perform advanced flight maneuvers while exploiting their flying capabilities. Within this paper, a novel auxiliary occupancy checking process that augments traditional 3D flight corridor generation is proposed. The 3D flight corridor is established as a topological structure based on a hand-crafted path either derived from a computer-generated environment or provided by the human operator, which captures humans’ preferences and desired flight intentions for the given space. This corridor is formulated as a series of interconnected overlapping convex polyhedra bounded by the perceived environmental geometries, which facilitates the generation of suitable 3D flight paths/trajectories that avoid local minima within the corridor boundaries. An occupancy check algorithm is employed to reduce the search space needed to identify 3D obstacle-free spaces in which their constructed polyhedron geometries are replaced with alternate convex polyhedra. To assess the feasibility and efficiency of the proposed SFC+ methodology, a comparative study is conducted against the Star-Convex Method (SCM), a prominent algorithm in the field. The results reveal the superiority of the proposed SFC+ methodology in terms of its computational efficiency and reduced search space for UAV maneuvering solutions. Various challenging confined-environment scenarios, each with different obstacle densities (confined scenarios), are utilized to verify the obtained outcomes. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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16 pages, 5369 KiB  
Article
UAS Control under GNSS Degraded and Windy Conditions
by Michail Kalaitzakis and Nikolaos Vitzilaios
Robotics 2023, 12(5), 123; https://doi.org/10.3390/robotics12050123 - 26 Aug 2023
Cited by 1 | Viewed by 1571
Abstract
Multirotor Uncrewed Aircraft Systems (UAS), widely known as aerial drones, are increasingly used in various indoor and outdoor applications. For outdoor field deployments, the plethora of UAS rely on Global Navigation Satellite Systems (GNSS) for their localization. However, dense environments and large structures [...] Read more.
Multirotor Uncrewed Aircraft Systems (UAS), widely known as aerial drones, are increasingly used in various indoor and outdoor applications. For outdoor field deployments, the plethora of UAS rely on Global Navigation Satellite Systems (GNSS) for their localization. However, dense environments and large structures can obscure the signal, resulting in a GNSS-degraded environment. Moreover, outdoor operations depend on weather conditions, and UAS flights are significantly affected by strong winds and possibly stronger wind gusts. This work presents a nonlinear model predictive position controller that uses a disturbance observer to adapt to changing weather conditions and fiducial markers to augment the system’s localization. The developed framework can be easily configured for use in multiple different rigid multirotor platforms. The effectiveness of the proposed system is shown through rigorous experimental work in both the lab and the field. The experimental results demonstrate consistent performance, regardless of the environmental conditions and platform used. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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22 pages, 2155 KiB  
Article
UAV Power Line Tracking Control Based on a Type-2 Fuzzy-PID Approach
by Guilherme A. N. Pussente, Eduardo P. de Aguiar, Andre L. M. Marcato and Milena F. Pinto
Robotics 2023, 12(2), 60; https://doi.org/10.3390/robotics12020060 - 20 Apr 2023
Cited by 8 | Viewed by 2519
Abstract
A challenge for inspecting transmission power lines with Unmanned Aerial Vehicles (UAVs) is to precisely determine their position and orientation, considering that the geo-location of these elements via GPS often needs to be more consistent. Therefore, a viable alternative is to use visual [...] Read more.
A challenge for inspecting transmission power lines with Unmanned Aerial Vehicles (UAVs) is to precisely determine their position and orientation, considering that the geo-location of these elements via GPS often needs to be more consistent. Therefore, a viable alternative is to use visual information from cameras attached to the central part of the UAV, enabling a control technique that allows the lines to be positioned at the center of the image. Therefore, this work proposes a PID (proportional–integral–derivative) controller tuned through interval type-2 fuzzy logic (IT2_PID) for the transmission line follower problem. The PID gains are selected online as the position and orientation errors and their respective derivatives change. The methodology was built in Python with the Robot Operating System (ROS) interface. The key point of the proposed methodology is its easy reproducibility, since the designed control loop does not require the mathematical model of the UAV. The tests were performed using the Gazebo simulator. The outcomes demonstrated that the proposed type-2 fuzzy variant displayed lower error values for both stabilization tests (keeping the UAV centered and oriented with the lines) and the following step in which the trajectory is time-variant, compared to the analogous T1_PID control and a classical PID controller tuned by the Zigler–Nichols method. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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Review

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45 pages, 3228 KiB  
Review
Holistic Review of UAV-Centric Situational Awareness: Applications, Limitations, and Algorithmic Challenges
by Somaiyeh MahmoudZadeh, Amirmehdi Yazdani, Yashar Kalantari, Bekir Ciftler, Fathi Aidarus and Mhd Omar Al Kadri
Robotics 2024, 13(8), 117; https://doi.org/10.3390/robotics13080117 - 29 Jul 2024
Cited by 1 | Viewed by 2201
Abstract
This paper presents a comprehensive survey of UAV-centric situational awareness (SA), delineating its applications, limitations, and underlying algorithmic challenges. It highlights the pivotal role of advanced algorithmic and strategic insights, including sensor integration, robust communication frameworks, and sophisticated data processing methodologies. The paper [...] Read more.
This paper presents a comprehensive survey of UAV-centric situational awareness (SA), delineating its applications, limitations, and underlying algorithmic challenges. It highlights the pivotal role of advanced algorithmic and strategic insights, including sensor integration, robust communication frameworks, and sophisticated data processing methodologies. The paper critically analyzes multifaceted challenges such as real-time data processing demands, adaptability in dynamic environments, and complexities introduced by advanced AI and machine learning techniques. Key contributions include a detailed exploration of UAV-centric SA’s transformative potential in industries such as precision agriculture, disaster management, and urban infrastructure monitoring, supported by case studies. In addition, the paper delves into algorithmic approaches for path planning and control, as well as strategies for multi-agent cooperative SA, addressing their respective challenges and future directions. Moreover, this paper discusses forthcoming technological advancements, such as energy-efficient AI solutions, aimed at overcoming current limitations. This holistic review provides valuable insights into the UAV-centric SA, establishing a foundation for future research and practical applications in this domain. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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28 pages, 3371 KiB  
Review
Tethered Unmanned Aerial Vehicles—A Systematic Review
by Miguel Nakajima Marques, Sandro Augusto Magalhães, Filipe Neves Dos Santos and Hélio Sousa Mendonça
Robotics 2023, 12(4), 117; https://doi.org/10.3390/robotics12040117 - 14 Aug 2023
Cited by 9 | Viewed by 6477
Abstract
In recent years, there has been a remarkable surge in the development and research of tethered aerial systems, thus reflecting a growing interest in their diverse applications. Long-term missions involving aerial vehicles present significant challenges due to the limitations of current battery solutions. [...] Read more.
In recent years, there has been a remarkable surge in the development and research of tethered aerial systems, thus reflecting a growing interest in their diverse applications. Long-term missions involving aerial vehicles present significant challenges due to the limitations of current battery solutions. Tethered vehicles can circumvent such restrictions by receiving their power from an element on the ground such as a ground station or a mobile terrestrial platform. Tethered Unmanned Aerial Vehicles (UAVs) can also be applied to load transportation achieved by a single or multiple UAVs. This paper presents a comprehensive systematic literature review, with a special focus on solutions published in the last five years (2017–2022). It emphasizes the key characteristics that are capable of grouping publications by application scope, propulsion method, energy transfer solution, perception sensors, and control techniques adopted. The search was performed in six different databases, thereby resulting in 1172 unique publications, from which 182 were considered for inclusion in the data extraction phase of this review. Among the various aircraft types, multirotors emerged as the most widely used category. We also identified significant variations in the application scope of tethered UAVs, thus leading to tailored approaches for each use case, such as the fixed-wing model being predominant in the wind generation application and the lighter-than-air aircraft in the meteorology field. Notably, the classical Proportional–Integral–Derivative (PID) control scheme emerged as the predominant control methodology across the surveyed publications. Regarding energy transfer techniques, most publications did not explicitly describe their approach. However, among those that did, high-voltage DC energy transfer emerged as the preferred solution. In summary, this systematic literature review provides valuable insights into the current state of tethered aerial systems, thereby showcasing their potential as a robust and sustainable alternative to address the challenges associated with long-duration aerial missions and load transportation. Full article
(This article belongs to the Special Issue UAV Systems and Swarm Robotics)
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