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22 pages, 38189 KiB

Open AccessArticle

Visual Odometry in GPS-Denied Zones for Fixed-Wing Unmanned Aerial Vehicle with Reduced Accumulative Error Based on Satellite Imagery

by Pablo Mateos-Ramirez, Javier Gomez-Avila, Carlos Villaseñor and Nancy Arana-Daniel

Appl. Sci. 2024, 14(16), 7420; https://doi.org/10.3390/app14167420 - 22 Aug 2024

Viewed by 621

Abstract

In this paper, we present a method for estimating GPS coordinates from visual information captured by a monocular camera mounted on a fixed-wing tactical Unmanned Aerial Vehicle at high altitudes (up to 3000 m) in GPS-denied zones. The main challenge in visual odometry [...] Read more.

In this paper, we present a method for estimating GPS coordinates from visual information captured by a monocular camera mounted on a fixed-wing tactical Unmanned Aerial Vehicle at high altitudes (up to 3000 m) in GPS-denied zones. The main challenge in visual odometry using aerial images is the computation of the scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is a reduction in the accumulated error by comparing the images from the camera with satellite images without requiring the dynamic model of the vehicle. The algorithm has been tested in real-world flight experiments at altitudes above 1000 m and in missions over 17 km. It has been proven that the algorithm prevents an increase in the accumulated error. Full article

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

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16 pages, 12036 KiB

Open AccessArticle

Tilt-X: Development of a Pitch-Axis Tiltrotor Quadcopter for Maximizing Horizontal Pulling Force and Yaw Moment

by Xiaodi Tao and Seong Young Ko

Appl. Sci. 2024, 14(14), 6181; https://doi.org/10.3390/app14146181 - 16 Jul 2024

Viewed by 1107

Abstract

In recent years, there has been a significant amount of research on tiltrotor multicopter unmanned aerial vehicles (TM-UAVs) in aerial robotics. Despite the varying frame types of TM-UAVs, they all still aim to decouple the propeller from the body, which means that the [...] Read more.

In recent years, there has been a significant amount of research on tiltrotor multicopter unmanned aerial vehicles (TM-UAVs) in aerial robotics. Despite the varying frame types of TM-UAVs, they all still aim to decouple the propeller from the body, which means that the propeller’s attitude control is independent of the body’s attitude control. On the one hand, this solves the issue of multicopter unmanned aerial vehicles (M-UAVs) being limited by small roll and pitch angles, thereby improving flight performance. On the other hand, it addresses the drawbacks of M-UAVs as typical underactuated systems. However, the fact still remains that it cannot significantly change thrust direction, thus providing the necessary wrench direction for aerial manipulation. This paper presents a pitch-axis tiltrotor quadcopter unmanned aerial vehicle (UAV) design named Tilt-X, which can maximize horizontal pulling force and yaw moment when used as an aerial manipulator. This design contributes to tasks such as pushing, pulling, and twisting. The reliability of the design has been demonstrated through dynamic modeling and experimental validation. Full article

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

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15 pages, 518 KiB

Open AccessArticle

On the Analysis of Coverage Feedback in a Fuzzing Proprietary System

by Daehee Jang, Jaemin Kim, Jiho Kim, Woohyeop Im, Minwoo Jeong, Byeongcheol Choi and Chongkyung Kil

Appl. Sci. 2024, 14(13), 5939; https://doi.org/10.3390/app14135939 - 8 Jul 2024

Viewed by 927

Abstract

Coverage feedback is one of the key mechanisms for improving the effectiveness of fuzzers by measuring and comparing the executed code regions while processing input data. In general, such guidance should always improve the performance of fuzzers to better find unexplored code regions. [...] Read more.

Coverage feedback is one of the key mechanisms for improving the effectiveness of fuzzers by measuring and comparing the executed code regions while processing input data. In general, such guidance should always improve the performance of fuzzers to better find unexplored code regions. However, proprietary systems with uncommon I/O interfaces (e.g., UAV system, IoT devices, satellite firmware) require extensive engineering/porting efforts to apply coverage feedback support in developing their fuzzing platform. In this paper, we evaluate the detailed efficacy of coverage feedback in fuzzing based on 44 real-world bugs we found using OSS-Fuzz. Our analysis uncovered when and how code coverage information can be helpful, and our experiment demonstrates that although coverage guidance is always helpful to some extent, its effectiveness depends on various external factors. Therefore, such factors should be carefully considered for optimizing the cost and efficiency in designing the fuzzing architecture of proprietary systems. Full article

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

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25 pages, 5745 KiB

Open AccessArticle

Research on Kalman Filter Fusion Navigation Algorithm Assisted by CNN-LSTM Neural Network

by Kai Chen, Pengtao Zhang, Liang You and Jian Sun

Appl. Sci. 2024, 14(13), 5493; https://doi.org/10.3390/app14135493 - 25 Jun 2024

Viewed by 645

Abstract

In response to the challenge of single navigation methods failing to meet the high precision requirements for unmanned aerial vehicle (UAV) navigation in complex environments, a novel algorithm that integrates Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) navigation information is proposed to enhance [...] Read more.

In response to the challenge of single navigation methods failing to meet the high precision requirements for unmanned aerial vehicle (UAV) navigation in complex environments, a novel algorithm that integrates Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) navigation information is proposed to enhance the positioning accuracy and robustness of UAV navigation systems. First, the fundamental principles of Kalman filtering and its application in navigation are introduced. Second, the basic principles of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks and their applications in the navigation domain are elaborated. Subsequently, an algorithm based on a CNN and LSTM-assisted Kalman filtering fusion navigation is proposed. Finally, the feasibility and effectiveness of the proposed algorithm are validated through experiments. Experimental results demonstrate that the Kalman filtering fusion navigation algorithm assisted by a CNN and LSTM significantly improves the positioning accuracy and robustness of UAV navigation systems in highly interfered complex environments. Full article

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

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25 pages, 4698 KiB

Open AccessArticle

Three-Dimensional Path Planning for Post-Disaster Rescue UAV by Integrating Improved Grey Wolf Optimizer and Artificial Potential Field Method

by Dan Han, Qizhou Yu, Hao Jiang, Yaqing Chen, Xinyu Zhu and Lifang Wang

Appl. Sci. 2024, 14(11), 4461; https://doi.org/10.3390/app14114461 - 23 May 2024

Cited by 1 | Viewed by 846

Abstract

The path planning of unmanned aerial vehicles (UAVs) is crucial in UAV search and rescue operations to ensure efficient and safe search activities. However, most existing path planning algorithms are not suitable for post-disaster mountain rescue mission scenarios. Therefore, this paper proposes the [...] Read more.

The path planning of unmanned aerial vehicles (UAVs) is crucial in UAV search and rescue operations to ensure efficient and safe search activities. However, most existing path planning algorithms are not suitable for post-disaster mountain rescue mission scenarios. Therefore, this paper proposes the IGWO-IAPF algorithm based on the fusion of the improved grey wolf optimizer (GWO) and the improved artificial potential field (APF) algorithm. This algorithm builds upon the grey wolf optimizer and introduces several improvements. Firstly, a nonlinear adjustment strategy for control parameters is proposed to balance the global and local search capabilities of the algorithm. Secondly, an optimized individual position update strategy is employed to coordinate the algorithm’s search ability and reduce the probability of falling into local optima. Additionally, a waypoint attraction force is incorporated into the traditional artificial potential field algorithm based on the force field to fulfill the requirements of three-dimensional path planning and further reduce the probability of falling into local optima. The IGWO is used to generate an initial path, where each point is assigned an attraction force, and then the IAPF is utilized for subsequent path planning. The simulation results demonstrate that the improved IGWO exhibits approximately a 60% improvement in convergence compared to the conventional GWO. Furthermore, the integrated IGWO-IAPF algorithm shows an approximately 10% improvement in path planning effectiveness compared to other traditional algorithms. It possesses characteristics such as shorter flight distance and higher safety, making it suitable for meeting the requirements of post-disaster rescue missions. Full article

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

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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

Cited by 1 | Viewed by 789

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 [...] Read more.

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 3 | Viewed by 977

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 [...] Read more.

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 1079

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 [...] Read more.

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

Cited by 3 | Viewed by 2136

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 [...] Read more.

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

Cited by 4 | Viewed by 1624

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 [...] Read more.

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 6 | Viewed by 2048

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 [...] Read more.

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 1172

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 [...] Read more.

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 1671

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 [...] Read more.

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 4 | Viewed by 2092

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 [...] Read more.

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 1860

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 [...] Read more.

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 1467

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. [...] Read more.

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 5 | Viewed by 2228

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 [...] Read more.

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 2440

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 [...] Read more.

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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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

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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 [...] Read more.

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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