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Drones
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Advances in Quadrotor Unmanned Aerial Vehicles
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Advances in Quadrotor Unmanned Aerial Vehicles

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drone Design and Development".

Deadline for manuscript submissions: 30 December 2024 | Viewed by 8099

Special Issue Editor

Dr. Yueneng Yang

E-Mail Website
Guest Editor
Department of Aeronautics and Astronautics, College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
Interests: UAV design; flight control; sliding mode control

Special Issue Information

Dear Colleagues,

In recent times, unmanned aerial vehicles (UAVs) have played pivotal roles in many different applications. As a major member of the UAV family, quadrotor UAVs have experienced an explosive growth in number and are widely used for aerial photography, environmental monitoring, disaster relief, emergency rescue, express delivery, precision agriculture, and so on. However, due to diverse tasks, harsh environments, and complex constraints, quadrotor UAVs have suffered from various challenges in terms of reliability, robustness, and flexibility. Thus, designing quadrotor UAVs with better intelligence, exquisite functions, and advanced performances are critical.

From a methodological perspective, we are interested in studies that go beyond traditional approaches. Potential topics include, but are not limited to, the following topics:

(1) Overall design and optimization;

(2) Load design and application;

(3) Multiple drone clusters;

(4) Online mission planning;

(5) Robust and intelligent control;

(6) Sensors and actuators.

Dr. Yueneng Yang
Guest Editor

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. Drones 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 2600 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.

Published Papers (5 papers)

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Research

Jump to: Review

17 pages, 3793 KiB  
Article
Deep Deterministic Policy Gradient (DDPG) Agent-Based Sliding Mode Control for Quadrotor Attitudes
by Wenjun Hu, Yueneng Yang and Zhiyang Liu
Drones 2024, 8(3), 95; https://doi.org/10.3390/drones8030095 - 12 Mar 2024
Viewed by 838
Abstract
A novel reinforcement deep learning deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the quadrotor under study is [...] Read more.
A novel reinforcement deep learning deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the quadrotor under study is derived, and the attitude control problem is described using formulas. Second, a sliding mode controller, including its sliding mode surface and reaching law, is chosen for the nonlinear dynamic system. The stability of the designed SMC system is validated through the Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adaptively adjust the switching control gain. During the training process, the input signals for the agent are the actual and desired attitude angles, while the output action is the time-varying control gain. Finally, the trained agent mentioned above is utilized in the SMC as a parameter regulator to facilitate the adaptive adjustment of the switching control gain associated with the reaching law. The simulation results validate the robustness and effectiveness of the proposed DDPG-SMC method. Full article
(This article belongs to the Special Issue Advances in Quadrotor Unmanned Aerial Vehicles)
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21 pages, 9281 KiB  
Article
Trajectory-Tracking Control for Quadrotors Using an Adaptive Integral Terminal Sliding Mode under External Disturbances
by Shipeng Jiao, Jun Wang, Yuchen Hua, Ye Zhuang and Xuetian Yu
Drones 2024, 8(2), 67; https://doi.org/10.3390/drones8020067 - 17 Feb 2024
Cited by 1 | Viewed by 1071
Abstract
In the face of external disturbances affecting the trajectory tracking of quadrotors, a control scheme targeted at accurate position and attitude trajectory tracking was designed. Initially, a quadrotor dynamic model, essential for control design, was derived. Adaptive integral backstepping control (AIBS) was then [...] Read more.
In the face of external disturbances affecting the trajectory tracking of quadrotors, a control scheme targeted at accurate position and attitude trajectory tracking was designed. Initially, a quadrotor dynamic model, essential for control design, was derived. Adaptive integral backstepping control (AIBS) was then employed within the position loop, enabling the upper boundaries of disturbances to be estimated through adaptive estimation. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) was proposed to enable adherence to the desired Euler angles. Rapid convergence and accurate tracking were facilitated by the incorporation of the nonsingular terminal sliding mode and an integral component. The dead zone technique was deployed to curtail estimation errors, while a saturation function was used to eradicate the phenomenon of chattering. Finally, to validate the proposed control scheme, simulation experiments were conducted in the Simulink environment, and the results were contrasted with those obtained from traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS), providing evidence of the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Advances in Quadrotor Unmanned Aerial Vehicles)
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21 pages, 7284 KiB  
Article
Dynamic Scene Path Planning of UAVs Based on Deep Reinforcement Learning
by Jin Tang, Yangang Liang and Kebo Li
Drones 2024, 8(2), 60; https://doi.org/10.3390/drones8020060 - 09 Feb 2024
Viewed by 1724
Abstract
Traditional unmanned aerial vehicle path planning methods focus on addressing planning issues in static scenes, struggle to balance optimality and real-time performance, and are prone to local optima. In this paper, we propose an improved deep reinforcement learning approach for UAV path planning [...] Read more.
Traditional unmanned aerial vehicle path planning methods focus on addressing planning issues in static scenes, struggle to balance optimality and real-time performance, and are prone to local optima. In this paper, we propose an improved deep reinforcement learning approach for UAV path planning in dynamic scenarios. Firstly, we establish a task scenario including an obstacle assessment model and model the UAV’s path planning problem using the Markov Decision Process. We translate the MDP model into the framework of reinforcement learning and design the state space, action space, and reward function while incorporating heuristic rules into the action exploration policy. Secondly, we utilize the Q function approximation of an enhanced D3QN with a prioritized experience replay mechanism and design the algorithm’s network structure based on the TensorFlow framework. Through extensive training, we obtain reinforcement learning path planning policies for both static and dynamic scenes and innovatively employ a visualized action field to analyze their planning effectiveness. Simulations demonstrate that the proposed algorithm can accomplish UAV dynamic scene path planning tasks and outperforms classical methods such as A*, RRT, and DQN in terms of planning effectiveness. Full article
(This article belongs to the Special Issue Advances in Quadrotor Unmanned Aerial Vehicles)
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Review

Jump to: Research

35 pages, 4918 KiB  
Review
Historical and Current Landscapes of Autonomous Quadrotor Control: An Early-Career Researchers’ Guide
by Abner Asignacion, Jr. and Suzuki Satoshi
Drones 2024, 8(3), 72; https://doi.org/10.3390/drones8030072 - 20 Feb 2024
Viewed by 1675
Abstract
The rising demand for autonomous quadrotor flights across diverse applications has led to the introduction of novel control strategies, resulting in several comparative analyses and comprehensive reviews. However, existing reviews lack a comparative analysis of experimental results from published papers, resulting in verbosity. [...] Read more.
The rising demand for autonomous quadrotor flights across diverse applications has led to the introduction of novel control strategies, resulting in several comparative analyses and comprehensive reviews. However, existing reviews lack a comparative analysis of experimental results from published papers, resulting in verbosity. Additionally, publications featuring comparative studies often demonstrate biased comparisons by either selecting suboptimal methodologies or fine-tuning their own methods to gain an advantageous position. This review analyzes the experimental results of leading publications to identify current trends and gaps in quadrotor tracking control research. Furthermore, the analysis, accomplished through historical insights, data-driven analyses, and performance-based comparisons of published studies, distinguishes itself by objectively identifying leading controllers that have achieved outstanding performance and actual deployment across diverse applications. Crafted with the aim of assisting early-career researchers and students in gaining a comprehensive understanding, the review’s ultimate goal is to empower them to make meaningful contributions toward advancing quadrotor control technology. Lastly, this study identifies three gaps in result presentation, impeding effective comparison and decelerating progress. Currently, advanced control methodologies empower quadrotors to achieve a remarkable flight precision of 1 cm and attain flight speeds of up to 30 m/s. Full article
(This article belongs to the Special Issue Advances in Quadrotor Unmanned Aerial Vehicles)
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21 pages, 512 KiB  
Review
Review of Aerial Transportation of Suspended-Cable Payloads with Quadrotors
by Julian Estevez, Gorka Garate, Jose Manuel Lopez-Guede and Mikel Larrea
Drones 2024, 8(2), 35; https://doi.org/10.3390/drones8020035 - 25 Jan 2024
Viewed by 2103
Abstract
Payload transportation and manipulation by rotorcraft drones are receiving a lot of attention from the military, industrial and logistics research areas. The interactions between the UAV and the payload, plus the means of object attachment or manipulation (such as cables or anthropomorphic robotic [...] Read more.
Payload transportation and manipulation by rotorcraft drones are receiving a lot of attention from the military, industrial and logistics research areas. The interactions between the UAV and the payload, plus the means of object attachment or manipulation (such as cables or anthropomorphic robotic arms), may be nonlinear, introducing difficulties in the overall system performance. In this paper, we focus on the current state of the art of aerial transportation systems with suspended loads by a single UAV and a team of them and present a review of different dynamic cable models and control systems. We cover the last sixteen years of the existing literature, and we add a discussion for evaluating the main trends in the referenced research works. Full article
(This article belongs to the Special Issue Advances in Quadrotor Unmanned Aerial Vehicles)
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