Special Issue "Unmanned Aerial Vehicles (UAVs)"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (31 December 2019).

Special Issue Editors

Dr. Sunghun Jung
Website
Guest Editor
Determent of Smart Mobile Convergence System, Chosun University, Gwangju, 61452, Korea
Interests: energy-efficient path planning, battery-state estimation, unmanned-system algorithm and SW development
Special Issues and Collections in MDPI journals
Dr. Donghoon Shin
Website
Co-Guest Editor
Department of Mechanical Engineering, Republic of Korea Naval Academy, Jinhae, South Korea
Interests: vehicle dynamics and control; environment perception; V2X communiation; Risk assessment; sensor fusion

Special Issue Information

Dear Colleagues,

Unmanned Aerial Vehicle (UAV) services such as sensing, mapping, goods and equipment delivery, inspection, and monitoring have started to grow rapidly with the rapidly falling prices of both drones and the sensors mounted on them. Many of these services involve the gathering of data and its processing with complex algorithms either in real time or on the cloud, and precise navigation and path-planning of the drones. We invite articles on all aspects of these problems involving UAV services including data processing and sensor fusion, obstacle and collision avoidance, trajectory generation single UAVs or groups of UAVs, communications and networks among UAVs, mission planning for various purposes, and so on.

Articles may be submitted in all the areas that currently abound in the news: inspection of farms, vineyards, ranch animals, petrochemical refineries, oil pipelines, and battlefields; delivery of pesticides and herbicides, food in restaurants, and packages to remote areas and residences; the cutting edge of photography, filming, and journalism; the mapping of various fields—optical, magnetic, acoustic, and chemical; and reconnaissance and tactical bombing in battlefield. Most of these applications are performed by single UAVs till now, though use of a multiplicity of UAVs can significantly improve performance.

Prof. Dr. Sunghun Jung
Dr. Donghoon Shin
Guest Editor

Manuscript Submission Information

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Keywords

  • unmanned aerial vehicle (UAV)
  • data processing and sensor fusion
  • obstacle and collision avoidance
  • trajectory generation
  • communications and networks
  • mission planning

Published Papers (26 papers)

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Research

Open AccessArticle
Flight Strategy Optimization for High-Altitude Solar-Powered Aircraft Based on Gravity Energy Reserving and Mission Altitude
Appl. Sci. 2020, 10(7), 2243; https://doi.org/10.3390/app10072243 - 26 Mar 2020
Abstract
High-altitude long-duration (HALE) flight capability is one of the ultimate goals pursued by human aviation technology, and the high-altitude solar-powered aircraft (SPA) is the most promising technical approach to achieve this target as well as wide application prospects. Due to the particularity of [...] Read more.
High-altitude long-duration (HALE) flight capability is one of the ultimate goals pursued by human aviation technology, and the high-altitude solar-powered aircraft (SPA) is the most promising technical approach to achieve this target as well as wide application prospects. Due to the particularity of the energy system, the flight strategy optimization through the storage of gravity potential energy and other methods is a significant way to enhance the flight and application abilities for the SPA. In this study, a flight strategy optimization model has been proposed for the aim of HALE flight capability, which is based on the gravity energy reserving and mission altitude in practical engineering applications. This integrated model contains the five flight path phase model, the three-dimensional kinematic model, aerodynamic model, solar irradiation model and energy store and loss model. To solve the optimization problem of three-dimensional flight strategy, the Gauss pseudo-spectral Method (GPM) was employed to establish and calculate the optimal target as its advantages in treating process constraints and terminal constraints for the multiphase optimization problem. At last, the flight trajectory optimization with minimal battery mass for Zephyr 7 was studied by the GPOPS with some function files in MATLAB. The results indicate that the Zephyr 7 can reduce the battery mass from 16 kg to 12.61 kg for the day and night cycle flight and missions, which equals to increasing the battery specific energy by 23.1%. Meanwhile, the optimization results also show that the attitude angel may contribute to increasing the energy gained by photovoltaic cells. In addition, this optimized flight strategy brings the possibility of monthly or annual continuous flight for SPA as the simulation date is set to the autumnal day. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Converting a Fixed-Wing Internal Combustion Engine RPAS into an Electric Lithium-Ion Battery-Driven RPAS
Appl. Sci. 2020, 10(5), 1573; https://doi.org/10.3390/app10051573 - 25 Feb 2020
Abstract
It is well proved that remotely piloted aircraft systems (RPASs) are very useful systems for remote sensing in precision agricultural labors. INTA (National Institute for Aerospace Applications) and the University of Huelva are involved in Tecnolivo Project that proposes the development of a [...] Read more.
It is well proved that remotely piloted aircraft systems (RPASs) are very useful systems for remote sensing in precision agricultural labors. INTA (National Institute for Aerospace Applications) and the University of Huelva are involved in Tecnolivo Project that proposes the development of a marketable and easy-to-use technological solution that allows integrated, ecological, and optimized management of the olive grove through non-invasive monitoring of key agronomic parameters using RPASs. The information collected by the RPAS in regards to the state of the vegetation, such as hydric stress levels, plague detection, or maturation of the fruit, are very interesting for farmers when it comes to make decisions about their crops. Current RPAS applications for precision agriculture are mainly developed for small- to medium-sized crops using rotary-wing RPASs with small range and endurance operation, leaving aside large-sized crops. This work shows the conversion of a fully declassified and obsolete fixed-wing internal combustion engine (ICE) remotely piloted aircraft (RPA), used as aerial target for military applications and in reconnaissance and surveillance missions at low cost, into an electric lithium polymer (LiPo) battery-driven RPA that will be used for precision agriculture in large-sized crop applications, as well as other applications for tracking and monitoring of endangered animal species in national parks. This RPA, being over twenty years old, has undergone a deep change. The applied methodology consisted of the design of a new propulsion system, based on an electric motor and batteries, maintaining the main airworthiness characteristics of the aircraft. Some other novelties achieved in this study were: (1) Change to a more efficient engine, less heavy and bulky, with a greater ratio of torque vs. size. Modernization of the fly control system and geolocation system. (2) Modification of the type and material of the propeller, reaching a higher performance. (3) Replacement of a polluting fuel, such as gasoline, with electricity from renewable sources. (4) Development of a new control software, etc. Preliminary results indicate that the endurance achieved with the new energy and propulsion systems and the payload weight available in the RPA meet the expectations of the use of this type of RPAS in the study of large areas of crops and surveillance. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Adaptive Neural Fault-Tolerant Control for the Yaw Control of UAV Helicopters with Input Saturation and Full-State Constraints
Appl. Sci. 2020, 10(4), 1404; https://doi.org/10.3390/app10041404 - 19 Feb 2020
Abstract
In this paper, an adaptive neural fault-tolerant tracking control scheme is presented for the yaw control of an unmanned-aerial-vehicle helicopter. The scheme incorporates a non-affine nonlinear system that manages actuator faults, input saturation, full-state constraints, and external disturbances. Firstly, by using a Taylor [...] Read more.
In this paper, an adaptive neural fault-tolerant tracking control scheme is presented for the yaw control of an unmanned-aerial-vehicle helicopter. The scheme incorporates a non-affine nonlinear system that manages actuator faults, input saturation, full-state constraints, and external disturbances. Firstly, by using a Taylor series expansion technique, the non-affine nonlinear system is transformed into an affine-form expression to facilitate the desired control design. In comparison with previous techniques, the actuator efficiency is explicit. Then, a neural network is considered to approximate unknown nonlinear functions, and a time-varying barrier Lyapunov function is employed to prevent transgression of the full-state variables using a backstepping technique. Robust adaptive control laws are designed to handle parameter uncertainties and unknown bounded disturbances to cut down the number of learning parameters and simplify the computational burden. Moreover, an auxiliary system is constructed to guarantee the pitch angle of the UAV helicopter yaw control system to satisfy the input constraint. Uniform boundedness of all signals in a closed-loop system is ensured via Lyapunov theory; the tracking error converges to a small neighborhood near zero. Finally, when the numerical simulations are applied to a yaw control of helicopter, the adaptive neural controller demonstrates the effectiveness of the proposed technique. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Optimization Dubins Path of Multiple UAVs for Post-Earthquake Rapid-Assessment
Appl. Sci. 2020, 10(4), 1388; https://doi.org/10.3390/app10041388 - 19 Feb 2020
Cited by 1
Abstract
In the last decade, with the wide application of UAVs in post-earthquake relief operations, the images and videos of affected areas obtained by UAVs immediately after a seismic event have become an important source of information for post-earthquake rapid assessment, which is crucial [...] Read more.
In the last decade, with the wide application of UAVs in post-earthquake relief operations, the images and videos of affected areas obtained by UAVs immediately after a seismic event have become an important source of information for post-earthquake rapid assessment, which is crucial for initiating effective emergency response operations. In this study, we first consider the kinematic constraints of UAV and the Dubins curve is introduced to fit the shortest flyable path for each UAV that meets the maximum curvature constraint. Second, based on the actual requirements of post-earthquake rapid assessment, heterogeneous UAVs, multi-depot launching, and targets allowed access to multiple times, the paper proposes a multi-UAV rapid-assessment routing problem (MURARP). The MURARP is modeled as the multi-depot revisit-allowed Dubins TOP with variable profit (MD-RDTOP-VP) which is a variant of the team orienteering problem (TOP). Third, a hybrid genetic simulated annealing (HGSA) algorithm is developed to solve the problem. The result of numerical experiments shows that the HGSA algorithm can quickly plan flyable paths for heterogeneous UAVs to maximize the expected profit. Finally, a case study based on real data of the 2017 Jiuzhaigou earthquake in China shows how the method can be applied in a post-earthquake scenario. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Adaptive TCP Transmission Adjustment for UAV Network Infrastructure
Appl. Sci. 2020, 10(3), 1161; https://doi.org/10.3390/app10031161 - 09 Feb 2020
Abstract
A UAV network composed of multiple UAVs allows a wide operating radius and various tasks to be performed. However, a UAV network mostly suffers from high probability of transmission failure due to interference or mobility. Also, nodes connected to the network often experience [...] Read more.
A UAV network composed of multiple UAVs allows a wide operating radius and various tasks to be performed. However, a UAV network mostly suffers from high probability of transmission failure due to interference or mobility. Also, nodes connected to the network often experience connection loss and segment loss caused by frequent node mobility and routing update. Since congestion is not the only cause of data loss in UAV networks, the TCP congestion control should not be run if there is a possibility of transient link instability unless a reduction in transmission speed is required. For this reason, we propose an algorithm to improve the transmission performance of UAV network through TCP with Slow-Start threshold (Ssthresh) value adjusted. The adjustment algorithm is called Adaptive Ssthresh Reviser for flying Ad hoc Network (ASRAN) that quickly restores unnecessary decrease of transmission speed in UAV network. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Learning-Based Anomaly Detection and Monitoring for Swarm Drone Flights
Appl. Sci. 2019, 9(24), 5477; https://doi.org/10.3390/app9245477 - 13 Dec 2019
Cited by 1
Abstract
This paper addresses anomaly detection and monitoring for swarm drone flights. While the current practice of swarm flight typically relies on the operator’s naked eyes to monitor health of the multiple vehicles, this work proposes a machine learning-based framework to enable detection of [...] Read more.
This paper addresses anomaly detection and monitoring for swarm drone flights. While the current practice of swarm flight typically relies on the operator’s naked eyes to monitor health of the multiple vehicles, this work proposes a machine learning-based framework to enable detection of abnormal behavior of a large number of flying drones on the fly. The method works in two steps: a sequence of two unsupervised learning procedures reduces the dimensionality of the real flight test data and labels them as normal and abnormal cases; then, a deep neural network classifier with one-dimensional convolution layers followed by fully connected multi-layer perceptron extracts the associated features and distinguishes the anomaly from normal conditions. The proposed anomaly detection scheme is validated on the real flight test data, highlighting its capability of online implementation. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Robust Backstepping Trajectory Tracking Control of a Quadrotor with Input Saturation via Extended State Observer
Appl. Sci. 2019, 9(23), 5184; https://doi.org/10.3390/app9235184 - 29 Nov 2019
Cited by 1
Abstract
Quadrotor unmanned aerial vehicles have become increasingly popular in several applications, and the improvement of their control performance has been documented in several studies. Nevertheless, the design of a high-performance tracking controller for aerial vehicles that reliably functions in the simultaneous presence of [...] Read more.
Quadrotor unmanned aerial vehicles have become increasingly popular in several applications, and the improvement of their control performance has been documented in several studies. Nevertheless, the design of a high-performance tracking controller for aerial vehicles that reliably functions in the simultaneous presence of model uncertainties, external disturbances, and control input saturation still remains a challenge. In this paper, we present a robust backstepping trajectory tracking control of a quadrotor with input saturation. The controller design accounts for both parameterized uncertainties and external disturbances, whereas a new auxiliary system is proposed to cope with control input saturation. Taking into account that only the position and attitude of the quadrotor are measurable, we devise an extended state observer to supply the estimations of unmeasured states, model uncertainties, and external disturbances. We strictly prove the stability of the closed-loop system by using the Lyapunov theory and demonstrate the effectiveness of the proposed algorithm through numerical simulations. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
A Novel Searching Method Using Reinforcement Learning Scheme for Multi-UAVs in Unknown Environments
Appl. Sci. 2019, 9(22), 4964; https://doi.org/10.3390/app9224964 - 18 Nov 2019
Abstract
In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established, in which models of [...] Read more.
In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established, in which models of the environment, UAV dynamics, target dynamics, and sensor detection are involved. Then, the search map is updated and extended using the concept of the territory awareness information map. Finally, according to the search efficiency function, a reward and punishment function is designed, and an RL method is used to generate a multi-UAV cooperative search path online. The simulation results show that the proposed algorithm could effectively perform the search task in the sea area with no prior information. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Autonomous Target Tracking of UAV Using High-Speed Visual Feedback
Appl. Sci. 2019, 9(21), 4552; https://doi.org/10.3390/app9214552 - 26 Oct 2019
Cited by 2
Abstract
Most current unmanned aerial vehicles (UAVs) primarily use a global positioning system (GPS) and an inertial measurement unit (IMU) for position estimation. However, compared to birds and insects, the abilities of current UAVs to recognize the environment are not sufficient. To achieve autonomous [...] Read more.
Most current unmanned aerial vehicles (UAVs) primarily use a global positioning system (GPS) and an inertial measurement unit (IMU) for position estimation. However, compared to birds and insects, the abilities of current UAVs to recognize the environment are not sufficient. To achieve autonomous flight of UAVs, like birds, the UAVs should be able to process and respond to information from their surrounding environment immediately. Therefore, in this paper, we propose a direct visual servoing system for UAVs, using an onboard high-speed monocular camera. There are two advantages of this system. First, the high image sampling rates help to improve the ability to recognize the environment. Second, the issue of control latency can be effectively solved because the position control signals are transmitted to the flight controller directly. In the experiment, the UAV could recognize a target at update rates of about 350 Hz, and a target tracking task was successfully realized. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
A Lateral-Directional Control Method for High Aspect Ratio Full-Wing UAV and Flight Tests
Appl. Sci. 2019, 9(20), 4236; https://doi.org/10.3390/app9204236 - 10 Oct 2019
Abstract
To solve the lateral-directional control problem of the high aspect ratio full-wing unmanned aerial vehicle (UAV) without an aileron and rudder, a control method is proposed that uses the differential thrust of propellers as the control output and the yaw angle as the [...] Read more.
To solve the lateral-directional control problem of the high aspect ratio full-wing unmanned aerial vehicle (UAV) without an aileron and rudder, a control method is proposed that uses the differential thrust of propellers as the control output and the yaw angle as the controlled attitude angle. Meanwhile, simulation analysis and experimental verification are carried out. First, a lateral-direction mathematical model and a differential thrust of propeller model of the full-wing drone are established. The influence of the aerodynamic derivative C Y β on the lateral-direction mode is analyzed. Second, based on nonlinear dynamic inversion (NDI) and active disturbance rejection control (ADRC) theories, a yaw angle controller that uses the differential thrust of propellers as the control output is designed. Finally, the vector field (VF) method is improved to obtain the straight-line trajectory tracking method satisfying different speeds, and the logic of waypoint switching is given. The research shows that C Y β has a great influence on the dutch roll damping of the drone. For the full-wing configuration, it is feasible to use the yaw angle as the controlled attitude angle without considering the roll angle. The simulation and experimental results show that the designed lateral-directional control method for the high aspect ratio full-wing UAV has a good control effect and disturbance rejection ability. Meanwhile, the control method has less parameters to adjust and less calculation, which is very suitable for engineering applications. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Quadcopter Adaptive Trajectory Tracking Control: A New Approach via Backstepping Technique
Appl. Sci. 2019, 9(18), 3873; https://doi.org/10.3390/app9183873 - 15 Sep 2019
Cited by 3
Abstract
Nowadays, quadcopter unmanned aerial vehicles play important roles in several real-world applications and the improvement of their control performance has become an increasingly attractive topic of a great number of studies. In this paper, we present a new approach for the design and [...] Read more.
Nowadays, quadcopter unmanned aerial vehicles play important roles in several real-world applications and the improvement of their control performance has become an increasingly attractive topic of a great number of studies. In this paper, we present a new approach for the design and stability analysis of a quadcopter adaptive trajectory tracking control. Based on the quadcopter nonlinear dynamics model which is obtained by using the Euler–Lagrange approach, the tracking controller is devised via the backstepping control technique. Besides, an adaptive law is proposed to deal with the system parameterized uncertainties and to guarantee that the control input is finite. In addition, the vehicle’s vertical descending acceleration is ensured to not exceed the gravitational acceleration by making use of a barrier Lyapunov function. It is shown that the suitable parameter estimator is stable and the tracking errors are guaranteed to be asymptotically stable simultaneously. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our method to that of existing approaches. The simulation results demonstrate the effectiveness of the proposed algorithm. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
PDDL Planning with Natural Language-Based Scene Understanding for UAV-UGV Cooperation
Appl. Sci. 2019, 9(18), 3789; https://doi.org/10.3390/app9183789 - 10 Sep 2019
Abstract
Natural-language-based scene understanding can enable heterogeneous robots to cooperate efficiently in large and unconstructed environments. However, studies on symbolic planning rarely consider the semantic knowledge acquisition problem associated with the surrounding environments. Further, recent developments in deep learning methods show outstanding performance for [...] Read more.
Natural-language-based scene understanding can enable heterogeneous robots to cooperate efficiently in large and unconstructed environments. However, studies on symbolic planning rarely consider the semantic knowledge acquisition problem associated with the surrounding environments. Further, recent developments in deep learning methods show outstanding performance for semantic scene understanding using natural language. In this paper, a cooperation framework that connects deep learning techniques and a symbolic planner for heterogeneous robots is proposed. The framework is largely composed of the scene understanding engine, planning agent, and knowledge engine. We employ neural networks for natural-language-based scene understanding to share environmental information among robots. We then generate a sequence of actions for each robot using a planning domain definition language planner. JENA-TDB is used for knowledge acquisition storage. The proposed method is validated using simulation results obtained from one unmanned aerial and three ground vehicles. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Testing Procedure of Unmanned Aerial Vehicles (UAVs) Trajectory in Automatic Missions
Appl. Sci. 2019, 9(17), 3488; https://doi.org/10.3390/app9173488 - 23 Aug 2019
Cited by 1
Abstract
This paper describes an experimental test campaign while using an Unmanned Aerial Vehicle (UAV) and measuring the obtained UAV positions during different flight tasks and in different operative conditions. A new test procedure has been presented and tested for different devices in various [...] Read more.
This paper describes an experimental test campaign while using an Unmanned Aerial Vehicle (UAV) and measuring the obtained UAV positions during different flight tasks and in different operative conditions. A new test procedure has been presented and tested for different devices in various weather conditions. This paper describes and analyses the measurements of the flight trajectory of the UAV that was performed with the use of a robotic total station (RTS), as compared to the design data and the data recorded in the internal memory of the UAV. Five different test tasks have been conducted. The obtained results have allowed for the assessment of the correctness of task performance as compared to the design and to determine the flying accuracy of the entire UAV set. The proposed set of tasks can be successfully utilised to control the correctness of operation of various types of UAVs and it may be implemented as a universal test to verify the algorithms optimising take-offs and landings, test flights of the objects, as well as flight planning in various terrain and weather conditions, which will increase the safety of the flights while using UAVs. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Detection and Tracking of Moving Pedestrians with a Small Unmanned Aerial Vehicle
Appl. Sci. 2019, 9(16), 3359; https://doi.org/10.3390/app9163359 - 15 Aug 2019
Cited by 1
Abstract
Small unmanned aircraft vehicles (SUAVs) or drones are very useful for visual detection and tracking due to their efficiency in capturing scenes. This paper addresses the detection and tracking of moving pedestrians with an SUAV. The detection step consists of frame subtraction, followed [...] Read more.
Small unmanned aircraft vehicles (SUAVs) or drones are very useful for visual detection and tracking due to their efficiency in capturing scenes. This paper addresses the detection and tracking of moving pedestrians with an SUAV. The detection step consists of frame subtraction, followed by thresholding, morphological filter, and false alarm reduction, taking into consideration the true size of targets. The center of the detected area is input to the next tracking stage. Interacting multiple model (IMM) filtering estimates the state of vectors and covariance matrices, using multiple modes of Kalman filtering. In the experiments, a dozen people and one car are captured by a stationary drone above the road. The Kalman filter and the IMM filter with two or three modes are compared in the accuracy of the state estimation. The root-mean squared errors (RMSE) of position and velocity are obtained for each target and show the good accuracy in detecting and tracking the target position—the average detection rate is 96.5%. When the two-mode IMM filter is used, the minimum average position and velocity RMSE obtained are around 0.8 m and 0.59 m/s, respectively. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Development of Path Planning Tool for Unmanned System Considering Energy Consumption
Appl. Sci. 2019, 9(16), 3341; https://doi.org/10.3390/app9163341 - 14 Aug 2019
Cited by 1
Abstract
Increasing the flight endurance of unmanned aerial vehicles (UAVs) has received attention recently. To solve this problem, two research topics have generally appeared: Shortest-path planning (SPP) and remaining-flying-range estimation. In this work, energy-efficient path planning by considering the distance between waypoint nodes, the [...] Read more.
Increasing the flight endurance of unmanned aerial vehicles (UAVs) has received attention recently. To solve this problem, two research topics have generally appeared: Shortest-path planning (SPP) and remaining-flying-range estimation. In this work, energy-efficient path planning by considering the distance between waypoint nodes, the minimum and maximum speed of the UAV, the weight of the UAV, and the angle between two intersecting edges is proposed. The performances of energy-efficient path planning (EEPP) and generic shortest-path planning are compared using extended-Kalman-filter-based state-of-charge and state-of-power estimation. Using this path-planning tool and considering energy consumption during flight operation, two different path plans can be obtained and compared in advance so that the operator can decide which path to choose by consulting a comparison chart. According to the experimental results, the EEPP algorithm results in 0.96% of improved SOC leftover and 11.03 ( W ) of lowered SOP compared to the SPP algorithm. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Intelligent Human–UAV Interaction System with Joint Cross-Validation over Action–Gesture Recognition and Scene Understanding
Appl. Sci. 2019, 9(16), 3277; https://doi.org/10.3390/app9163277 - 09 Aug 2019
Abstract
We propose an intelligent human–unmanned aerial vehicle (UAV) interaction system, in which, instead of using the conventional remote controller, the UAV flight actions are controlled by a deep learning-based action–gesture joint detection system. The Resnet-based scene-understanding algorithm is introduced into the proposed system [...] Read more.
We propose an intelligent human–unmanned aerial vehicle (UAV) interaction system, in which, instead of using the conventional remote controller, the UAV flight actions are controlled by a deep learning-based action–gesture joint detection system. The Resnet-based scene-understanding algorithm is introduced into the proposed system to enable the UAV to adjust its flight strategy automatically, according to the flying conditions. Meanwhile, both the deep learning-based action detection and multi-feature cascade gesture recognition methods are employed by a cross-validation process to create the corresponding flight action. The effectiveness and efficiency of the proposed system are confirmed by its application to controlling the flight action of a real flying UAV for more than 3 h. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
A Neural Network Based Landing Method for an Unmanned Aerial Vehicle with Soft Landing Gears
Appl. Sci. 2019, 9(15), 2976; https://doi.org/10.3390/app9152976 - 25 Jul 2019
Abstract
This paper presents the design, implementation, and testing of a soft landing gear together with a neural network-based control method for replicating avian landing behavior on non-flat surfaces. With full consideration of unmanned aerial vehicles and landing gear requirements, a quadrotor helicopter, comprised [...] Read more.
This paper presents the design, implementation, and testing of a soft landing gear together with a neural network-based control method for replicating avian landing behavior on non-flat surfaces. With full consideration of unmanned aerial vehicles and landing gear requirements, a quadrotor helicopter, comprised of one flying unit and one landing assistance unit, is employed. Considering the touchdown speed and posture, a novel design of a soft mechanism for non-flat surfaces is proposed, in order to absorb the remaining landing impact. The framework of the control strategy is designed based on a derived dynamic model. A neural network-based backstepping controller is applied to achieve the desired trajectory. The simulation and outdoor testing results attest to the effectiveness and reliability of the proposed control method. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Path Planning for Multi-UAV Formation Rendezvous Based on Distributed Cooperative Particle Swarm Optimization
Appl. Sci. 2019, 9(13), 2621; https://doi.org/10.3390/app9132621 - 28 Jun 2019
Cited by 3
Abstract
This paper studies the problem of generating cooperative feasible paths for formation rendezvous of unmanned aerial vehicles (UAVs). Cooperative path-planning for multi-UAV formation rendezvous is mostly a complicated multi-objective optimization problem with many coupled constraints. In order to satisfy the kinematic constraints, i.e., [...] Read more.
This paper studies the problem of generating cooperative feasible paths for formation rendezvous of unmanned aerial vehicles (UAVs). Cooperative path-planning for multi-UAV formation rendezvous is mostly a complicated multi-objective optimization problem with many coupled constraints. In order to satisfy the kinematic constraints, i.e., the maximum curvature constraint and the requirement of continuous curvature of the UAV path, the Pythagorean hodograph (PH) curve is adopted as the parameterized path because of its curvature continuity and rational intrinsic properties. Inspired by the co-evolutionary theory, a distributed cooperative particle swarm optimization (DCPSO) algorithm with an elite keeping strategy is proposed to generate a flyable and safe path for each UAV. This proposed algorithm can meet the kinematic constraints of UAVs and the cooperation requirements among UAVs. Meanwhile, the optimal or sub-optimal paths can be obtained. Finally, numerical simulations in 2-D and 3-D environments are conducted to demonstrate the feasibility and stability of the proposed algorithm. Simulation results show that the paths generated by the proposed DCPSO can not only meet the kinematic constraints of UAVs and safety requirements, but also achieve the simultaneous arrival and collision avoidance between UAVs for formation rendezvous. Compared with the cooperative co-evolutionary genetic algorithm (CCGA), the proposed DCPSO has better stability and a higher searching success rate. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Multi-UAV Mission Allocation under Constraint
Appl. Sci. 2019, 9(11), 2184; https://doi.org/10.3390/app9112184 - 28 May 2019
Cited by 4
Abstract
This paper is devoted to the unmanned aerial vehicle (UAV) mission allocation problem. To solve this problem in a more realistic battlefield environment, an improved mathematical model for UAV mission allocation is proposed. Being different from previous formulations, this model not only considers [...] Read more.
This paper is devoted to the unmanned aerial vehicle (UAV) mission allocation problem. To solve this problem in a more realistic battlefield environment, an improved mathematical model for UAV mission allocation is proposed. Being different from previous formulations, this model not only considers the difference in the importance of the target but also the constraints of the time window. In addition, an indicator of reconnaissance reward is added to this model. Each target area has a different importance, just as the strategic value of each region is different in combat. In this paper, we randomly generate the value factor for each reconnaissance area. To solve the mathematical model with different operational intentions, a dimensionality reduction process for which the reconnaissance reward is the optimization objective is presented. Finally, based on the improved model, the simulation result with Lingo is compared with that of non-dominated sorting genetic algorithm with elite strategy (NSGA-II) and genetic algorithm (GA) to verify the reliability and the effectiveness of the improved method. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
A Hierarchical Mission Planning Method for Simultaneous Arrival of Multi-UAV Coalition
Appl. Sci. 2019, 9(10), 1986; https://doi.org/10.3390/app9101986 - 15 May 2019
Cited by 1
Abstract
A hierarchical mission planning method was proposed to solve a simultaneous attack mission planning problem for multi-unmanned aerial vehicles (UAVs). The method consisted of three phases aiming to decouple and solve the mission planning problem. In the first phase, the Pythagorean hodograph (PH) [...] Read more.
A hierarchical mission planning method was proposed to solve a simultaneous attack mission planning problem for multi-unmanned aerial vehicles (UAVs). The method consisted of three phases aiming to decouple and solve the mission planning problem. In the first phase, the Pythagorean hodograph (PH) curve was used in the path estimation process for each UAV, which also served as the input for the task allocation process. In the second phase, a task allocation algorithm based on a negotiation mechanism was proposed to assign the targets. Considering the resource requirement, time-dependent value of targets and resource consumption of UAVs, the proposed task allocation algorithm can generate a feasible allocation strategy and get the maximum system utility. In the last phase, a path planning method was proposed to generate a simultaneous arrival PH path for each UAV considering UAV’s kinematic constraint and collision avoidance with obstacles. The comparison simulations showed that the path estimation process using the PH curve and the proposed task allocation algorithm improved the system utility, and the hierarchical mission planning method has potential in a real mission. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
An Integrated Adaptive Kalman Filter for High-Speed UAVs
Appl. Sci. 2019, 9(9), 1916; https://doi.org/10.3390/app9091916 - 09 May 2019
Cited by 1
Abstract
In order to solve the problems of filtering divergence and low accuracy in Kalman filter (KF) applications in a high-speed unmanned aerial vehicle (UAV), this paper proposed a new method of integrated robust adaptive Kalman filter: strong adaptive Kalman filter (SAKF). The simulation [...] Read more.
In order to solve the problems of filtering divergence and low accuracy in Kalman filter (KF) applications in a high-speed unmanned aerial vehicle (UAV), this paper proposed a new method of integrated robust adaptive Kalman filter: strong adaptive Kalman filter (SAKF). The simulation of two high-dynamic conditions and a practical experiment were designed to verify the new multi-sensor data fusion algorithm. Then the performance of the Sage–Husa adaptive Kalman filter (SHAKF), strong tracking filter (STF), H filter and SAKF were compared. The results of the simulation and practical experiments show that the SAKF can automatically select its filtering process under different conditions, according to an anomaly criterion. SAKF combines the advantages of SHAKF, H filter and STF, and has the characteristics of high accuracy, robustness and good tracking skill. The research has proved that SAKF is more appropriate in high-speed UAV navigation than single filter algorithms. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Launch Performance Degradation of the Rupture-Type Missile Canister
Appl. Sci. 2019, 9(7), 1290; https://doi.org/10.3390/app9071290 - 27 Mar 2019
Abstract
This paper describes the degradation of launch performance caused by the remnants of a missile canister cover with a sabot interface, on interference with adjacent structures. First, by including the material plastic behavior and element deletion, we predict interference between the structures and [...] Read more.
This paper describes the degradation of launch performance caused by the remnants of a missile canister cover with a sabot interface, on interference with adjacent structures. First, by including the material plastic behavior and element deletion, we predict interference between the structures and the detached part, followed by excessive deformation. Second, we verify that the support ring deformation, which is induced by an interaction with the cover remains, increases for fastener separations with abnormal fastener installations. This increase further triggers interference with the boosters on the bottom of a missile. Lastly, we analyze the variation of material property in a high-speed environment. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Nonlinear Modeling and Flight Validation of a Small-Scale Compound Helicopter
Appl. Sci. 2019, 9(6), 1087; https://doi.org/10.3390/app9061087 - 14 Mar 2019
Abstract
The compound configuration is a good option for helicopters to break through speed limitation and improve maneuverability. However, the compound configuration applied on the small-scale helicopter has not been investigated in detail. In this study, an 11-state nonlinear dynamics model of a small-scale [...] Read more.
The compound configuration is a good option for helicopters to break through speed limitation and improve maneuverability. However, the compound configuration applied on the small-scale helicopter has not been investigated in detail. In this study, an 11-state nonlinear dynamics model of a small-scale compound helicopter was established with the help of first physical principles and linear modification method. The ducted fan, free-rotate wing and horizontal stabilizer were considered in the compound configurations. To validate the accuracy of the model, high-quality flight data were obtained in hover and forward flights from 15 m/s to 32 m/s. Results show that the overall responses of the developed nonlinear model matched the hover data. In forward flight, it was proved that the nonlinear model has high accuracy in agreement with trim results and time-domain simulations. The wing model works well below 27 m/s. Furthermore, the effectiveness of the elevator and aileron in high speed was also verified in the simulation of a coordinated turn. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Research on the Collision Avoidance Algorithm for Fixed-Wing UAVs Based on Maneuver Coordination and Planned Trajectories Prediction
Appl. Sci. 2019, 9(4), 798; https://doi.org/10.3390/app9040798 - 25 Feb 2019
Cited by 3
Abstract
This paper presents a novel collision avoidance (CA) algorithm for a cooperative fixed-wing unmanned aerial vehicle (UAV). The method is based on maneuver coordination and planned trajectory prediction. Each aircraft in a conflict generates three available maneuvers and predicts the corresponding planned trajectories. [...] Read more.
This paper presents a novel collision avoidance (CA) algorithm for a cooperative fixed-wing unmanned aerial vehicle (UAV). The method is based on maneuver coordination and planned trajectory prediction. Each aircraft in a conflict generates three available maneuvers and predicts the corresponding planned trajectories. The algorithm coordinates planned trajectories between participants in a conflict, determines which combination of planned trajectories provides the best separation, eventually makes an agreement on the maneuver for collision avoidance and activates the preferred maneuvers when a collision is imminent. The emphasis is placed on providing protection for UAVs, while activating maneuvers late enough to reduce interference, which is necessary for collision avoidance in the formation and clustering of UAVs. The CA has been validated with various simulations to show the advantage of collision avoidance for continuous conflicts in multiple, high-dynamic, high-density and three-dimensional (3D) environments. It eliminates the disadvantage of traditional CA, which has high uncertainty, and takes the performance parameters of different aircraft into consideration and makes full use of the maneuverability of fixed-wing aircraft. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Control of Flow around an Oscillating Plate for Lift Enhancement by Plasma Actuators
Appl. Sci. 2019, 9(4), 776; https://doi.org/10.3390/app9040776 - 22 Feb 2019
Cited by 2
Abstract
During insect flight, a feathering motion of the wing’s controls vortex shedding for lift enhancement. In this study, in order to control the flow around a wing flapping with simplified sinusoidal motion, plasma actuators were introduced to simplify the complex feathering motion. In [...] Read more.
During insect flight, a feathering motion of the wing’s controls vortex shedding for lift enhancement. In this study, in order to control the flow around a wing flapping with simplified sinusoidal motion, plasma actuators were introduced to simplify the complex feathering motion. In a wind tunnel, a smoke-wire method was enacted to visualize the flow fields around an oscillating plate with an attack angle of 4° in a uniform flow for the baseline and controlled cases. The actuator placed around the leading edge was found to suppress the flow separation on the top surface. Numerical simulations were performed to investigate the control effects on the fluctuating lift, where the control effects by the intermittently driven actuator were also predicted. The actuator installed on the top surface throughout the up-stroke motion was found to suppress vortex shedding from the trailing edge, which resulted in an 11% lift enhancement compared to the baseline case. In regard to the effects of the installation position, it was found that the actuator placed on the top surface was effective, compared to the cases for installation on the bottom surface or both surfaces. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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Open AccessArticle
Effects of Vehicular Communication on Risk Assessment in Automated Driving Vehicles
Appl. Sci. 2018, 8(12), 2632; https://doi.org/10.3390/app8122632 - 15 Dec 2018
Cited by 3
Abstract
This paper proposes a human-centered risk assessment algorithm designed to find the intervention moment of drive mode and active safety mode while monitoring threat vehicles ahead to overcome effects of vehicular communication on risk assessment in automated driving vehicle. Although a conventional radar [...] Read more.
This paper proposes a human-centered risk assessment algorithm designed to find the intervention moment of drive mode and active safety mode while monitoring threat vehicles ahead to overcome effects of vehicular communication on risk assessment in automated driving vehicle. Although a conventional radar system is known to be best fitted on-board ranging sensor in terms of longitudinal safety, it is generally not enough for a reliable automated driving because of sensing uncertainty of the traffic environments and incomplete perception results due to sensor limitations. This can be overcome by implementing vehicle-to-vehicle (V2V) communication which provides complementary source of target vehicle’s dynamic behavior. Using V2V communication with vehicle internal and surround information obtained from the on-board sensor system, future vehicle motion has been predicted. With accurately predicted motion of a remote vehicle, a collision risk and the automated drive mode are determined by incorporating human factor. Effects of the V2V communication on a human-centered risk assessment algorithm have been investigated through a safe triangle analysis. The computer simulation studies have been conducted in order to validate the performance of the proposed algorithm. It has been shown that the V2V communication with the proposed risk assessment algorithm allows a faster drive mode decision and active safety intervention moment. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles (UAVs))
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