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Unmanned Aircraft Systems with Autonomous Navigation

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 26973

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Special Issue Editors

Dr. Umberto Papa

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Guest Editor

Department of Science and Technology, University of Naples “Parthenope”, 80143 Naples, Italy
Interests: unmanned aircraft systems; flight mechanics and dynamics; sensor fusion; structural loads; structure analysis; air navigation
Special Issues, Collections and Topics in MDPI journals

Prof. Marcello Rosario Napolitano

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Guest Editor

Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV 26506-6106, USA
Interests: flight testing; flight controls; flight mechanics; application of neural networks to flight controls

Dr. Giuseppe Del Core

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Guest Editor

Department of Science and Technology, University of Naples “Parthenope”, 80143 Naples, Italy
Interests: flight mechanics and dynamics of manned and unmanned aircraft
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Dr. Salvatore Ponte

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Guest Editor

Department of Engineering, University of Campania “L. Vanvitelli”, 81031 Aversa, Italy
Interests: UAV/UAS; avionics and navigation systems; flight control; remote sensing; data analysis and processing; control systems; sensors and sensor fusion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial systems play an increasingly remarkable role in widely diffused application fields, from military defense programs and strategies to civil and commercial utilization. UAS are usually involved in dull, dirty and dangerous (DDD) scenarios, which require reliable, extended-capability, easy-to-use and cost-effective fixed-wing or rotary-wing platforms. Therefore, it is important to provide onboard systems capable of recognizing the environment around the aerial vehicle, detecting and avoiding obstacles, implementing path planning and management strategies, defining safe landing areas, and achieving full autonomy, especially for BVLOS (beyond visual line-of-sight) missions. The technical and economic challenges implied by the issues related to autonomous navigation range from hardware (sensors, platforms, controllers, etc.) to software (data processing and filtering techniques, optimal control, state estimation, innovative algorithms, etc.), and from modeling to practical realizations.

The aim of this Special Issue is to seek high-quality contributions that highlight novel research results and emerging applications, addressing recent breakthroughs in UAS autonomous navigation and related fields, such as flight mechanics and control, structural design, sensor design, etc.

The topics of interest include the following:

2D and 3D mapping, target detection and obstacle avoidance;
The active perception of targets in cluttered environments (foliage, forests, etc.);
Vision-based and optical flow techniques;
Sensors and sensor fusion techniques;
Design models for guidance and controlled flight;
State estimation, data analysis and filtering techniques (KF, EKF, particle filtering, fuzzy logic, etc.);
Path planning and path management;
Optimal control and strategies (neural networks, fuzzy logic, reinforcement learning, evolutionary and genetic algorithms, AI, etc.);
Navigation in GPS-denied environments;
Autolanding and safe landing area definition (SLAD);
Environmental effects on UAVs (wind, etc.);
Autonomous UAV or MAV swarms, and distributed architectures;
BVLOS autonomous navigation.

Technical Program Committee Members:
MSc Gennaro Ariante, Department of Science and Technology, University of Naples Parthenope Naples, Italy.
Mr. Alberto Greco, Department of Science and Technology, University of Naples Parthenope Naples, Italy.

Dr. Umberto Papa
Prof. Marcello Rosario Napolitano
Prof. Giuseppe Del Core
Prof. Salvatore Ponte
Guest Editors

Manuscript Submission Information

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

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

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Unmanned aircraft systems
Autonomous navigation
Flight mechanics and dynamics
Sensor fusion
Filtering techniques
Optimization algorithms
State estimation

Published Papers (11 papers)

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Editorial

Jump to: Research

4 pages, 173 KiB

Open AccessEditorial

Unmanned Aircraft Systems with Autonomous Navigation

by Umberto Papa

Electronics 2023, 12(7), 1591; https://doi.org/10.3390/electronics12071591 - 28 Mar 2023

Cited by 1 | Viewed by 980

Abstract

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

Research

Jump to: Editorial

12 pages, 1499 KiB

Open AccessArticle

UAV Sensors Autonomous Integrity Monitoring—SAIM

by Georgia Koukiou and Vassilis Anastassopoulos

Electronics 2023, 12(3), 746; https://doi.org/10.3390/electronics12030746 - 02 Feb 2023

Cited by 3 | Viewed by 1294

Abstract

For Unmanned Aerial Vehicles (UAVs), it is of crucial importance to develop a technically advanced Collision Avoidance System (CAS). Such a system must necessarily consist of many sensors of various types, each one having special characteristics and performance. The poor performance of one of the sensors can lead to a total failure in collision avoidance if there is no provision for the performance of each separate sensor to be continuously monitored. In this work, a Sensor Autonomous Integrity Monitoring (SAIM) methodology is proposed. The configuration of the sensors and their interaction is based on a fusion procedure that involves a total of five sensors. Accordingly, the performance of each one of the sensors is continuously checked against the combined (fused) operation of the other four. A complementary experiment with a total of four sensors, one of which had low performance, was also conducted. Experimental results reveal a reliable approach for Sensor Autonomous Integrity Monitoring (SAIM). The method can be easily extended to a larger number of sensors. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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14 pages, 9112 KiB

Open AccessArticle

Indoor Localization Using Positional Tracking Feature of Stereo Camera on Quadcopter

by Ahmad Riyad Firdaus, Andreas Hutagalung, Agus Syahputra and Riska Analia

Electronics 2023, 12(2), 406; https://doi.org/10.3390/electronics12020406 - 13 Jan 2023

Cited by 4 | Viewed by 1808

Abstract

During the maneuvering of most unmanned aerial vehicles (UAVs), the GPS is one of the sensors used for navigation. However, this kind of sensor cannot handle indoor navigation applications well. Using a camera might be the answer to performing indoor navigation using its coordinate system. In this study, we considered indoor navigation applications using the ZED2 stereo camera for the quadcopter. To use the ZED 2 camera as a navigation sensor, we first transformed its coordinates into the North, East, down (NED) system to enable the drone to understand its position and maintain stability in a particular position. The experiment was performed using a real-time application to confirm the feasibility of this approach for indoor localization. In the real-time application, we commanded the quadcopter to follow triangular and rectangular paths. The results indicated that the quadcopter was able to follow the paths and maintain its stability in specific coordinate positions. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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17 pages, 4882 KiB

Open AccessArticle

Use of UAVs and Deep Learning for Beach Litter Monitoring

by Roland Pfeiffer, Gianluca Valentino, Sebastiano D’Amico, Luca Piroddi, Luciano Galone, Stefano Calleja, Reuben A. Farrugia and Emanuele Colica

Electronics 2023, 12(1), 198; https://doi.org/10.3390/electronics12010198 - 31 Dec 2022

Cited by 4 | Viewed by 1866

Abstract

Stranded beach litter is a ubiquitous issue. Manual monitoring and retrieval can be cost and labour intensive. Therefore, automatic litter monitoring and retrieval is an essential mitigation strategy. In this paper, we present important foundational blocks that can be expanded into an autonomous monitoring-and-retrieval pipeline based on drone surveys and object detection using deep learning. Drone footage collected on the islands of Malta and Gozo in Sicily (Italy) and the Red Sea coast was combined with publicly available litter datasets and used to train an object detection algorithm (YOLOv5) to detect litter objects in footage recorded during drone surveys. Across all classes of litter objects, the 50%–95% mean average precision (mAP50-95) was 0.252, with the performance on single well-represented classes reaching up to 0.674. We also present an approach to geolocate objects detected by the algorithm, assigning latitude and longitude coordinates to each detection. In combination with beach morphology information derived from digital elevation models (DEMs) for path finding and identifying inaccessible areas for an autonomous litter retrieval robot, this research provides important building blocks for an automated monitoring-and-retrieval pipeline. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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19 pages, 4511 KiB

Open AccessArticle

Post-Flood UAV-Based Free Space Optics Recovery Communications with Spatial Mode Diversity

by Angela Amphawan, Norhana Arsad, Tse-Kian Neo, Muhammed Basheer Jasser and Athirah Mohd Ramly

Electronics 2022, 11(14), 2257; https://doi.org/10.3390/electronics11142257 - 19 Jul 2022

Cited by 5 | Viewed by 2046

Abstract

The deployment of unmanned aerial vehicles (UAVs) for free space optical communications is an attractive solution for forwarding the vital health information of victims from a flood-stricken area to neighboring ground base stations during rescue operations. A critical challenge to this is maintaining an acceptable signal quality between the ground base station and UAV-based free space optics relay. This is largely unattainable due to rapid UAV propeller and body movements, which result in fluctuations in the beam alignment and frequent link failures. To address this issue, linearly polarized Laguerre–Gaussian modes were leveraged for spatial mode diversity to prevent link failures over a 400 m link. Spatial mode diversity successfully improved the bit error rate by 38% to 55%. This was due to a 10% to 19% increase in the predominant mode power from spatial mode diversity. The time-varying channel matrix indicated the presence of nonlinear deterministic chaos. This opens up new possibilities for research on state-space reconstruction of the channel matrix. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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20 pages, 1582 KiB

Open AccessArticle

Cross-Layer Optimization Spatial Multi-Channel Directional Neighbor Discovery with Random Reply in mmWave FANET

by Yifei Song, Liang Zeng, Zeyu Liu, Zhe Song, Jie Zeng and Jianping An

Electronics 2022, 11(10), 1566; https://doi.org/10.3390/electronics11101566 - 13 May 2022

Cited by 4 | Viewed by 1523

Abstract

MmWave FANETs play an increasingly important role in the development of UAVs technology. Fast neighbor discovery is a key bottleneck in mmWave FANETs. In this paper, we propose a two-way neighbor discovery algorithm based on a spatial multi-channel through cross-layer optimization. Firstly, we give two boundary conditions of the physical (PHY) layer and media access control (MAC) layer for successful link establishment of mmWave neighbor discovery and give the optimal pairing of antenna beamwidth in different stages and scenarios using cross-layer optimization. Then, a mmWave neighbor discovery algorithm based on a spatial multi-channel is proposed, which greatly reduces the convergence time by increasing the discovery probability of nodes in the network. Finally, a random reply algorithm is proposed based on dynamic reserved time slots. By adjusting the probability of reply and the number of reserved time slots, the neighbor discovery time can be further reduced when the number of nodes is larger. Simulations show that as the network scale is 100 to 500 nodes, the convergence time is 10 times higher than that of the single channel algorithm. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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22 pages, 14549 KiB

Open AccessArticle

Verification in Relevant Environment of a Physics-Based Synthetic Sensor for Flow Angle Estimation

by Angelo Lerro, Piero Gili and Marco Pisani

Electronics 2022, 11(1), 165; https://doi.org/10.3390/electronics11010165 - 05 Jan 2022

Cited by 3 | Viewed by 1485

Abstract

In the area of synthetic sensors for flow angle estimation, the present work aims to describe the verification in a relevant environment of a physics-based approach using a dedicated technological demonstrator. The flow angle synthetic solution is based on a model-free, or physics-based, scheme and, therefore, it is applicable to any flying body. The demonstrator also encompasses physical sensors that provide all the necessary inputs to the synthetic sensors to estimate the angle-of-attack and the angle-of-sideslip. The uncertainty budgets of the physical sensors are evaluated to corrupt the flight simulator data with the aim of reproducing a realistic scenario to verify the synthetic sensors. The proposed approach for the flow angle estimation is suitable for modern and future aircraft, such as drones and urban mobility air vehicles. The results presented in this work show that the proposed approach can be effective in relevant scenarios even though some limitations can arise. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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22 pages, 2668 KiB

Open AccessArticle

Iterative Learning Sliding Mode Control for UAV Trajectory Tracking

by Lanh Van Nguyen, Manh Duong Phung and Quang Phuc Ha

Electronics 2021, 10(20), 2474; https://doi.org/10.3390/electronics10202474 - 12 Oct 2021

Cited by 16 | Viewed by 3096

Abstract

This paper presents a novel iterative learning sliding mode controller (ILSMC) that can be applied to the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs) subject to model uncertainties and external disturbances. Here, the proposed ILSMC is integrated in the outer loop of a controlled system. The control development, conducted in the discrete-time domain, does not require a priori information of the disturbance bound as with conventional SMC techniques. It only involves an equivalent control term for the desired dynamics in the closed loop and an iterative learning term to drive the system state toward the sliding surface to maintain robust performance. By learning from previous iterations, the ILSMC can yield very accurate tracking performance when a sliding mode is induced without control chattering. The design is then applied to the attitude control of a 3DR Solo UAV with a built-in PID controller. The simulation results and experimental validation with real-time data demonstrate the advantages of the proposed control scheme over existing techniques. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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25 pages, 6335 KiB

Open AccessArticle

A Hybrid-Driven Optimization Framework for Fixed-Wing UAV Maneuvering Flight Planning

by Renshan Zhang, Su Cao, Kuang Zhao, Huangchao Yu and Yongyang Hu

Electronics 2021, 10(19), 2330; https://doi.org/10.3390/electronics10192330 - 23 Sep 2021

Cited by 6 | Viewed by 2421

Abstract

Performing autonomous maneuvering flight planning and optimization remains a challenge for unmanned aerial vehicles (UAVs), especially for fixed-wing UAVs due to its high maneuverability and model complexity. A novel hybrid-driven fixed-wing UAV maneuver optimization framework, inspired by apprenticeship learning and nonlinear programing approaches, is proposed in this paper. The work consists of two main aspects: (1) Identifying the model parameters for a certain fixed-wing UAV based on the demonstrated flight data performed by human pilot. Then, the features of the maneuvers can be described by the positional/attitude/compound key-frames. Eventually, each of the maneuvers can be decomposed into several motion primitives. (2) Formulating the maneuver planning issue into a minimum-time optimization problem, a novel nonlinear programming algorithm was developed, which was unnecessary to determine the exact time for the UAV to pass by the key-frames. The simulation results illustrate the effectiveness of the proposed framework in several scenarios, as both the preservation of geometric features and the minimization of maneuver times were ensured. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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20 pages, 8280 KiB

Open AccessArticle

Estimation of Airspeed, Angle of Attack, and Sideslip for Small Unmanned Aerial Vehicles (UAVs) Using a Micro-Pitot Tube

by Gennaro Ariante, Salvatore Ponte, Umberto Papa and Giuseppe Del Core

Electronics 2021, 10(19), 2325; https://doi.org/10.3390/electronics10192325 - 22 Sep 2021

Cited by 4 | Viewed by 3520

Abstract

Fixed and rotary-wing unmanned aircraft systems (UASs), originally developed for military purposes, have widely spread in scientific, civilian, commercial, and recreational applications. Among the most interesting and challenging aspects of small UAS technology are endurance enhancement and autonomous flight; i.e., mission management and control. This paper proposes a practical method for estimation of true and calibrated airspeed, Angle of Attack (AOA), and Angle of Sideslip (AOS) for small unmanned aerial vehicles (UAVs, up to 20 kg mass, 1200 ft altitude above ground level, and airspeed of up to 100 knots) or light aircraft, for which weight, size, cost, and power-consumption requirements do not allow solutions used in large airplanes (typically, arrays of multi-hole Pitot probes). The sensors used in this research were a static and dynamic pressure sensor (“micro-Pitot tube” MPX2010DP differential pressure sensor) and a 10 degrees of freedom (DoF) inertial measurement unit (IMU) for attitude determination. Kalman and complementary filtering were applied for measurement noise removal and data fusion, respectively, achieving global exponential stability of the estimation error. The methodology was tested using experimental data from a prototype of the devised sensor suite, in various indoor-acquisition campaigns and laboratory tests under controlled conditions. AOA and AOS estimates were validated via correlation between the AOA measured by the micro-Pitot and vertical accelerometer measurements, since lift force can be modeled as a linear function of AOA in normal flight. The results confirmed the validity of the proposed approach, which could have interesting applications in energy-harvesting techniques. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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33 pages, 4525 KiB

Open AccessArticle

Design, Simulation, Analysis and Optimization of PID and Fuzzy Based Control Systems for a Quadcopter

by Isaac S. Leal, Chamil Abeykoon and Yasith S. Perera

Electronics 2021, 10(18), 2218; https://doi.org/10.3390/electronics10182218 - 10 Sep 2021

Cited by 17 | Viewed by 4930

Abstract

Unmanned aerial vehicles or drones are becoming one of the key machines/tools of the modern world, particularly in military applications. Numerous research works are underway to explore the possibility of using these machines in other applications such as parcel delivery, construction work, hurricane hunting, 3D mapping, protecting wildlife, agricultural activities, search and rescue, etc. Since these machines are unmanned vehicles, their functionality is completely dependent upon the performance of their control system. This paper presents a comprehensive approach for dynamic modeling, control system design, simulation and optimization of a quadcopter. The main objective is to study the behavior of different controllers when the model is working under linear and/or non-linear conditions, and therefore, to define the possible limitations of the controllers. Five different control systems are proposed to improve the control performance, mainly the stability of the system. Additionally, a path simulator was also developed with the intention of describing the vehicle’s movements and hence to detect faults intuitively. The proposed PID and Fuzzy-PD control systems showed promising responses to the tests carried out. The results indicated the limits of the PID controller over non-linear conditions and the effectiveness of the controllers was enhanced by the implementation of a genetic algorithm to autotune the controllers in order to adapt to changing conditions. Full article

(This article belongs to the Special Issue Unmanned Aircraft Systems with Autonomous Navigation)

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