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Advances in Unmanned Aerial Vehicle (UAV) System

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 June 2024 | Viewed by 20788

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Special Issue Editors

Dr. Shanling Dong

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Guest Editor

College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Interests: networked control systems; intelligent control; information fusion

Prof. Dr. Meiqin Liu

E-Mail Website
Guest Editor

College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Interests: theory and applications of artificial intelligence; perception and processing of underwater information; multi-sensor information fusion

Special Issue Information

Dear Colleagues,

With the increasing development of communication technology, sensor technology, and artificial intelligence, unmanned aerial vehicles (UAVs) have been widely used in both military and civil applications. They have received great attention from researchers and much effort has been put in as well. Accordingly, the objective of this special issue is to present the new advances in UAV systems.

The topics of this special issue include, but are not limited to, modeling, path planning, localization, formation control, coordination control, fault diagnosis, security control, performance optimization, hardware design, tracking control, obstacle avoidance, vision-based navigation, reinforcement learning, dynamic simulation, experiments, and applications.

Best regards

Dr. Shanling Dong
Prof. Dr. Meiqin Liu
Guest Editors

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Keywords

path planning
localization
fault diagnosis
optimization
hardware design
navigation
security
control
intelligent learning
analysis and applications

Published Papers (14 papers)

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Research

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23 pages, 4357 KiB

Open AccessArticle

Affine Formation Maneuver Control for Multi-Agent Based on Optimal Flight System

by Chao Kang, Jihui Xu and Yuan Bian

Appl. Sci. 2024, 14(6), 2292; https://doi.org/10.3390/app14062292 - 8 Mar 2024

Viewed by 397

Abstract

The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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18 pages, 6859 KiB

Open AccessArticle

Multi-View Jujube Tree Trunks Stereo Reconstruction Based on UAV Remote Sensing Imaging Acquisition System

by Shunkang Ling, Jingbin Li, Longpeng Ding and Nianyi Wang

Appl. Sci. 2024, 14(4), 1364; https://doi.org/10.3390/app14041364 - 7 Feb 2024

Cited by 2 | Viewed by 607

Abstract

High-quality agricultural multi-view stereo reconstruction technology is the key to precision and informatization in agriculture. Multi-view stereo reconstruction methods are an important part of 3D vision technology. In the multi-view stereo 3D reconstruction method based on deep learning, the effect of feature extraction directly affects the accuracy of reconstruction. Aiming at the actual problems in orchard fruit tree reconstruction, this paper designs an improved multi-view stereo structure based on the combination of remote sensing and artificial intelligence to realize the accurate reconstruction of jujube tree trunks. Firstly, an automatic key frame extraction method is proposed for the DSST target tracking algorithm to quickly recognize and extract high-quality data. Secondly, a composite U-Net feature extraction network is designed to enhance the reconstruction accuracy, while the DRE-Net feature extraction enhancement network improved by the parallel self-attention mechanism enhances the reconstruction completeness. Comparison tests show different levels of improvement on the Technical University of Denmark (DTU) dataset compared to other deep learning-based methods. Ablation test on the self-constructed dataset, the MVSNet + Co U-Net + DRE-Net_SA method proposed in this paper improves 20.4% in Accuracy, 12.8% in Completion, and 16.8% in Overall compared to the base model, which verifies the real effectiveness of the scheme. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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21 pages, 11256 KiB

Open AccessArticle

Vision-Guided Hierarchical Control and Autonomous Positioning for Aerial Manipulator

by Xia Ye, Haohao Cui, Lidong Wang, Shangjun Xie and Hong Ni

Appl. Sci. 2023, 13(22), 12172; https://doi.org/10.3390/app132212172 - 9 Nov 2023

Viewed by 742

Abstract

Aerial manipulator systems possess active operational capability, and by incorporating various sensors, the systems’ autonomy is further enhanced. In this paper, we address the challenge of accurate positioning between an aerial manipulator and the operational targets during tasks such as grasping and delivery in the absence of motion capture systems indoors. We propose a vision-guided aerial manipulator system comprising a quad-rotor UAV and a single-degree-of-freedom manipulator. First, the overall structure of the aerial manipulator is designed, and a hierarchical control system is established. We employ the fusion of LiDAR-based SLAM (simultaneous localization and mapping) and IMU (inertial measurement unit) to enhance the positioning accuracy of the aerial manipulator. Real-time target detection and recognition are achieved by combining a depth camera and laser sensor for distance measurements, enabling adjustment of the grasping pose of the aerial manipulator. Finally, we employ a segmented grasping strategy to position and grasp the target object precisely. Experimental results demonstrate that the designed aerial manipulator system maintains a stable orientation within a certain range of ±5° during operation; its position movement is independent of orientation changes. The successful autonomous grasping of lightweight cylindrical objects in real-world scenarios verifies the effectiveness and rationality of the proposed system, ensuring high operational efficiency and robust disturbance resistance. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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20 pages, 1330 KiB

Open AccessArticle

Multi-UAV Cooperative Searching and Tracking for Moving Targets Based on Multi-Agent Reinforcement Learning

by Kai Su and Feng Qian

Appl. Sci. 2023, 13(21), 11905; https://doi.org/10.3390/app132111905 - 31 Oct 2023

Viewed by 1182

Abstract

In this paper, we propose a distributed multi-agent reinforcement learning (MARL) method to learn cooperative searching and tracking policies for multiple unmanned aerial vehicles (UAVs) with limited sensing range and communication ability. Firstly, we describe the system model for multi-UAV cooperative searching and tracking for moving targets and consider average observation rate and average exploration rate as the metrics. Moreover, we propose the information update and fusion mechanisms to enhance environment perception ability of the multi-UAV system. Then, the details of our method are demonstrated, including observation and action space representation, reward function design and training framework based on multi-agent proximal policy optimization (MAPPO). The simulation results have shown that our method has well convergence performance and outperforms other baseline algorithms in terms of average observation rate and average exploration rate. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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17 pages, 2552 KiB

Open AccessArticle

Adaptive Backstepping Control of Quadrotor UAVs with Output Constraints and Input Saturation

by Jianming Li, Lili Wan, Jing Li and Kai Hou

Appl. Sci. 2023, 13(15), 8710; https://doi.org/10.3390/app13158710 - 28 Jul 2023

Viewed by 1027

Abstract

The control performance of quadrotor unmanned aerial vehicles (UAVs) in complex environments can be affected by external disturbances and other factors. In this paper, an adaptive neural network backstepping controller based on the barrier Lyapunov function (BLF) is designed for a quadrotor UAV with internal uncertainties, input–output constraints and external disturbances. Radial basis function neural networks are used to approximate the uncertainties in the dynamic model of the UAV, while the minimum parameter learning method is combined to accelerate the adjustment speed of neural network weights. A robust term is designed to balance the total system disturbance and improve the anti-interference performance. The BLF is used to handle the output constraint so that the constrained parameters cannot break the predefined constraints. An auxiliary system is introduced to solve input saturation and avoid the dependence of tracking error on the input amplitude in the method of approximating input saturation using the smoothing function. The stability of the control system is demonstrated by the Lyapunov method. The simulation results show that the proposed method has high tracking accuracy compared with the backstepping dynamic surface control method, and the input and output are in the predefined range. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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17 pages, 5264 KiB

Open AccessArticle

Research on Demand-Based Scheduling Scheme of Urban Low-Altitude Logistics UAVs

by Honghai Zhang, Shixin Wu, Ouge Feng, Tian Tian, Yuting Huang and Gang Zhong

Appl. Sci. 2023, 13(9), 5370; https://doi.org/10.3390/app13095370 - 25 Apr 2023

Cited by 5 | Viewed by 1356

Abstract

Aiming at the problem of the scheduling scheme of urban low-altitude logistics unmanned aerial vehicles (UAVs), this paper establishes a demand-based UAV scheduling scheme model using an improved simulated annealing algorithm, taking minimizing the cost of distribution as the objective function and considering restrictions such as UAV performance constraints, airspace constraints, and distribution constraints, among others. For verification, actual express data and airspace constraints in Shanghai are taken as examples. Two urban air traffic networks are constructed using road and building data. The analysis results show that the planning scheme of this model is superior to other forecasting models in terms of delivery cost and delivery time. In addition, this model can flexibly calculate the optimal scheduling scheme under the constraints of multiple parameters, according to the requirements of delivery volume, delivery distance, UAV performance, etc. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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14 pages, 633 KiB

Open AccessArticle

Redundancy-Reduction-Based Hierarchical Design in Synchronization of Multi-Agent Systems

by Haoyi Que, Zhaowen Xu and Hongye Su

Appl. Sci. 2023, 13(4), 2486; https://doi.org/10.3390/app13042486 - 15 Feb 2023

Viewed by 975

Abstract

In this paper, a layered, undirected-network-structure, optimization approach is proposed to reduce the redundancy in multi-agent information synchronization and improve the computing rate. Based on the traversing binary tree and aperiodic sampling of the complex delayed networks theory, we proposed a network-partitioning method for pinning dynamic networks, with a more simplified, analyzable structure, and all of the traversed nodes are mathematically asymptotically synchronized at the same time. Moreover, a systematic implementable approach is proposed for application. The approach could be separated into two main steps: the first is a method of network partition that reduces the trivial interaction, which does not affect the information traversal, and the second involves applying the time-dependent functional approach of Lyapunov to give global exponential conditions, under the criteria for the synchronization of multiple agents, with a lower conservatism of the decision variables compared to some other results, so that the information available could fully benefit from the actual discrete-time communication pattern. Both mathematical proofs and numerical example evidence are presented to demonstrate the effectiveness of the implemented approach. This class contains a number of practically interesting systems, for instance, unmanned aerial vehicle (UAV) formation systems or the ground-air coordinated unmanned aerial system. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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25 pages, 12615 KiB

Open AccessArticle

A Logistics UAV Parcel-Receiving Station and Public Air-Route Planning Method Based on Bi-Layer Optimization

by Honghai Zhang, Fei Wang, Dikun Feng, Sen Du, Gang Zhong, Cheng Deng and Ji Zhou

Appl. Sci. 2023, 13(3), 1842; https://doi.org/10.3390/app13031842 - 31 Jan 2023

Cited by 3 | Viewed by 1347

Abstract

The popularity of unmanned aerial vehicle (UAV) technology has made UAV logistics transportation possible. However, based on the current development status of logistics UAVs, there are difficulties in using UAVs directly for door-to-door logistics transportation. Therefore, it is necessary to establish UAV parcel-receiving stations that can gather logistics needs in a small area. The construction of stations allows the UAVs to transport back and forth between the distribution warehouse and the established stations, enabling customers to send and receive packages at the more convenient stations. Based on the current situation, it is a more appropriate air–ground cooperative transport mode to solve the “last-mile” cargo transportation problem. In this paper, a bi-layer UAV parcel-receiving station and public air-route planning method is proposed to explore the interaction between station location and public route planning, and is solved with a genetic algorithm and max–min ant system (GA-MMAS). The model proposed in this paper can determine the location of the stations and plan the public air routes between the warehouse and stations simultaneously. Simulation results show that the planning results of the bi-layer optimization model proposed in this paper meet the requirements of station location and public air-route planning. Compared with the layered planning results, the cost of the upper-layer model is reduced by 5.12% on average, and the cost of the lower-layer model is reduced by 4.48%. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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18 pages, 1543 KiB

Open AccessArticle

Artificial Intelligence-Enabled Exploratory Cyber-Physical Safety Analyzer Framework for Civilian Urban Air Mobility

by Md. Shirajum Munir, Sumit Howlader Dipro, Kamrul Hasan, Tariqul Islam and Sachin Shetty

Appl. Sci. 2023, 13(2), 755; https://doi.org/10.3390/app13020755 - 5 Jan 2023

Cited by 2 | Viewed by 1663

Abstract

Urban air mobility (UAM) has become a potential candidate for civilization for serving smart citizens, such as through delivery, surveillance, and air taxis. However, safety concerns have grown since commercial UAM uses a publicly available communication infrastructure that enhances the risk of jamming and spoofing attacks to steal or crash crafts in UAM. To protect commercial UAM from cyberattacks and theft, this work proposes an artificial intelligence (AI)-enabled exploratory cyber-physical safety analyzer framework. The proposed framework devises supervised learning-based AI schemes such as decision tree, random forests, logistic regression, K-nearest neighbors (KNN), and long short-term memory (LSTM) for predicting and detecting cyber jamming and spoofing attacks. Then, the developed framework analyzes the conditional dependencies based on the Pearson’s correlation coefficient among the control messages for finding the cause of potential attacks based on the outcome of the AI algorithm. This work considers the UAM attitude control scenario for determining jam and spoofing attacks as a use case to validate the proposed framework with a state-of-the-art UAV attack dataset. The experiment results show the efficacy of the proposed framework in terms of around

99.9 %

accuracy for jamming and spoofing detection with a decision tree, random forests, and KNN while efficiently finding the root cause of the attack. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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17 pages, 1049 KiB

Open AccessArticle

An Adaptive Launch Control for Balloon-Borne UAVs with Large Wingspans

by Yanpeng Hu, Yanfei Hu, Xiaomiao Ding, Guannan Zeng and Jin Guo

Appl. Sci. 2022, 12(21), 10992; https://doi.org/10.3390/app122110992 - 30 Oct 2022

Cited by 1 | Viewed by 1530

Abstract

Near space has attracted major countries’ attention due to the fact that it is a new cognitive space of Earth and acts as an important national security space. Near-space solar-powered unmanned aerial vehicles (UAVs) are becoming a focus of research in the aviation field. However, it is difficult for solar-powered UAVs to climb such high heights and achieving optimal cruising levels is challenging. A balloon-borne-based aircraft that rises with the help of a balloon avoids difficult climbing processes and initiates a new research direction in the near-space aviation domain. Simultaneously, the special mode of taking off poses a great challenge for the pull-up control of balloon-borne aircraft, especially for large wingspan aircraft. In this paper, we propose an adaptive launch control for the pull-up process of large-scale balloon-borne-based aircraft. First, the flight control of the pull-up process for a large-scale balloon-borne-based aircraft is analyzed. Then, a flight dynamic model considering elastic deformation is established. Finally, an adaptive aircraft pull-up control algorithm is proposed. We evaluate it by performing simulation experiments and comparing it with the latest control algorithm utilized in physical experiments. The experiment’s results demonstrate the effectiveness of the proposed algorithm with respect to overcoming challenges in controlling pull-up processes and its superiority compared to the latest control algorithm. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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21 pages, 4906 KiB

Open AccessArticle

Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops

by Liliam Rodríguez-Guerrero, Alejandro Benítez-Morales, Omar-Jacobo Santos-Sánchez, Orlando García-Pérez, Hugo Romero-Trejo, Mario-Oscar Ordaz-Oliver and Jesús-Patricio Ordaz-Oliver

Appl. Sci. 2022, 12(18), 9075; https://doi.org/10.3390/app12189075 - 9 Sep 2022

Cited by 2 | Viewed by 1206

Abstract

In this paper, a robust control technique is developed to achieve the quadrotor stabilization against unmodeled matching vanishing dynamics. The synthesis of the proposed robust control is based on the Lyapunov approach and the backstepping method allowing to construct an iterative control algorithm. To compare the performance of the proposed controller, a Proportional Derivative (PD) controller is used to obtain experimental results in an outdoor environment. To compare the closed-loop system responses with both controllers, the Integral Absolute Error is computed and several tests are conducted to calculate the error standard deviation. Ultimately, employing the robust backstepping control approach in pest recognition in maize crops, which is a specific task of precision agriculture, demonstrates its effectiveness in improving the trajectory tracking of the vehicle while it captures images of the crops. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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27 pages, 8560 KiB

Open AccessArticle

Modeling and Optimal Control for Rotary Unmanned Aerial Vehicles in Northern Ireland Climate

by Jack Gibson and Muhammad Usman Hadi

Appl. Sci. 2022, 12(15), 7677; https://doi.org/10.3390/app12157677 - 30 Jul 2022

Cited by 2 | Viewed by 1913

Abstract

Rotary Unmanned Aerial Vehicles (RUAVs) suffer in average Northern Irish winters due to heavy wind preventing vital tasks from being performed in the economy, such as search and rescue or civil engineering observations. This work provides enhanced stability of RUAVs under wind disturbances by using metaheuristic algorithms to select optimal controller gains. Previous work demonstrated how Particle Swarm Optimization can be used to tune optimal controllers; this work uses a machine learning algorithm (Genetic Algorithm) to tune the controller. Simulations carried out on Full State Feedback, Full State Compensator and Linear Quadratic Gaussian controllers tuned by a variety of techniques revealed that the Genetic Algorithm outperformed conventional manual tuning by 20% and Particle Swarm Optimization by 17% in performance measured in settling time. The proposed method tunes the feedback gains and Kalman filter by Genetic Algorithm, which outperforms the manually tuned conventional schemes and “GA-Hybrid” approach. The conditions required to employ Reinforcement Learning as an alternative method for RUAV stabilization in future scope is also explored. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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15 pages, 7430 KiB

Open AccessArticle

RCC Structural Deformation and Damage Quantification Using Unmanned Aerial Vehicle Image Correlation Technique

by Kumar Kumarapu, Shashi Mesapam, Venkat Reddy Keesara, Anoop Kumar Shukla, Naga Venkata Sai Kumar Manapragada and Babar Javed

Appl. Sci. 2022, 12(13), 6574; https://doi.org/10.3390/app12136574 - 29 Jun 2022

Cited by 9 | Viewed by 2006

Abstract

Reinforced cement concrete (RCC) is universally acknowledged as a low-cost, rigid, and high-strength construction material. Major structures like buildings, bridges, dams, etc., are made of RCC and subjected to repetitive loading during their service life for which structural performance deteriorates with time. Bridges and high-rise structures, being above ground level, are hard to equip with the contact mechanical methods to inspect strains and displacements for structural health monitoring (SHM). A non-contact, optical and computer vision based full field measuring technique called digital image correlation (DIC) technique was developed in the recent past to specifically evaluate bridge decks. Generally, optical images of structure in field conditions are not acquired precisely perpendicular to the object, which instinctively affects the deformation results obtained during loading conditions. An unmanned aerial vehicle (UAV) equipped with DIC vision-based technique acts as a rapid and cost-effective tool to quantify the serviceability of bridges by measuring strains and displacements at inaccessible locations. In this study, a non-contact unmanned aerial vehicle image correlation (UAVIC) technique is used on a scaled bridge girder and a contact method of measuring deformations with a dial gauge. Both investigations are correlated for accuracy assessment, and it is understood that results in laboratory conditions are 90% accurate. Similarly, the UAVIC technique is also performed on a rail over the bridge in the field conditions to understand the feasibility of the proposed method and evaluate damage quantification of it. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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Review

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16 pages, 299 KiB

Open AccessReview

Unmanned Aircraft Systems: A Latin American Review and Analysis from the Colombian Context

by Gabriel J. Sánchez-Zuluaga, Luisa Isaza-Giraldo, Germán Darío Zapata-Madrigal, Rodolfo García-Sierra and John E. Candelo-Becerra

Appl. Sci. 2023, 13(3), 1801; https://doi.org/10.3390/app13031801 - 31 Jan 2023

Viewed by 3481

Abstract

The usage of unmanned aircraft systems to complete routine, commercial, and industrial tasks has increased throughout the world, evidencing better profitability and reducing risks for operators. However, in some countries, there is a low implementation of unmanned aircraft systems, particularly in the electrical sector, due to a lack of appropriation or adaptation of technology to the local environment. Therefore, this paper presents an analysis of the uses of unmanned aircraft systems in the electrical industry worldwide and its possible application to a local context to identify how the expansion of unmanned aerial vehicles is helping various industries. The contribution of this paper is to show how the employment of unmanned aerial vehicles can help in any particular task in the electrical sector and the appropriation of these technologies in a country, showing a possible categorization of unmanned aerial vehicles based on future applications and current regulations. The analysis was carried out in the Colombian context, considering the current regulation and the impact of its use. This research considers safety, security, and privacy implications, including the reduction of personal harm with low operation costs. In addition, the importance of future implementations in Colombia is discussed as a topic of interest for any electrical company, researchers, and government entities. Full article

(This article belongs to the Special Issue Advances in Unmanned Aerial Vehicle (UAV) System)

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