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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 22583

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Special Issue Editors

Dr. Andrzej Łukaszewicz

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Guest Editor

Institute of Mechanical Engineering, Faculty of Mechanical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland
Interests: UAV design; CAD; CAx; lattice structures; topology optimization; fibre composites; UGV and UAV collaboration; new applications for UAVs; AM techniques; 3D printing drones parts
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Carlos Tavares Calafate

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Guest Editor

Computer Engineering Department (DISCA), Universitat Politècnica de València (UPV), 46022 Valencia, Spain
Interests: ad hoc and vehicular networks; unmanned aerial vehicles; smart cities and Internet of Things; QoS; network protocols; video streaming; network security
Special Issues, Collections and Topics in MDPI journals

Dr. Wojciech Giernacki

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Guest Editor

Institute of Robotics and Machine Intelligence, Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland
Interests: UAV control and simulation; machine learning for UAV autonomous control; motion and mission planning; autonomy reliability and safety of UAVs; multi-robot systems; swarm robotics; relative UAV localization; object tracking; perception and multi-sensor fusion; optimization techniques for UAVs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned aerial vehicles (UAVs) represent a hot topic today as they have shown their suitability for handling the different challenges related to various areas, including search and rescue missions, monitoring of disaster areas, aiding in emergency situations, improvements to precision agriculture, environmental monitoring, delivery of goods, etc.

Despite their success, there are still many challenges to face in order to achieve efficient solutions in areas such as sensing, flight control, swarm coordination, collision avoidance, environmental awareness, robotic manipulation, etc.

This Special Issue addresses novel contributions to the state of the art in the UAV area by focusing on contributions that address the aforementioned challenges. In particular, topics of interest include but are not limited to the following ones:

- Novel applications for UAVs;

- UAV/UGV/UMV collaboration;

- Unconventional UAVs’ solutions, prototypes, etc.;

- Unconventional UAV propulsion;

- New UAVs’ airframe design;

- Advanced sensing solutions for UAVs;

- UAV networking and communications solutions;

- Machine learning approaches for autonomous drones and drone swarms;

- UAS traffic management (UTM) in the context of U-Space;

- Experimental results (prototypes, field tests, etc.);

- UAV/UGV/UMV collaboration;

- CAx systems in UAV design;

- Efficiency of UAV platforms;

- FEA in UAV design;

- CFD analysis of UAV;

- New materials in UAV;

- Advanced fiber composites in UAV;

- Aerial swarm robotics.

Dr. Andrzej Łukaszewicz
Prof. Dr. Carlos Tavares Calafate
Prof. Dr. Wojciech Giernacki
Guest Editors

Manuscript Submission Information

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Published Papers (9 papers)

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Research

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26 pages, 2058 KiB

Open AccessArticle

Web Real-Time Communications-Based Unmanned-Aerial-Vehicle-Borne Internet of Things and Stringent Time Sensitivity: A Case Study

by Agnieszka Chodorek and Robert Ryszard Chodorek

Sensors 2025, 25(2), 524; https://doi.org/10.3390/s25020524 - 17 Jan 2025

Cited by 1 | Viewed by 1077

Abstract

The currently observed development of time-sensitive applications also affects wireless communication with the IoT carried by UAVs. Although research on wireless low-latency networks has matured, there are still issues to solve at the transport layer. Since there is a general agreement that classical transport solutions are not able to achieve end-to-end delays in the single-digit millisecond range, in this paper, the use of WebRTC is proposed as a potential solution to this problem. This article examines UAV-borne WebRTC-based IoT in an outdoor environment. The results of field experiments conducted under various network conditions show that, in highly reliable networks, UAV and WebRTC-based IoT achieved stable end-to-end delays well below 10 ms during error-free air-to-ground transmissions, and below 10 ms in the immediate vicinity of the retransmitted packet. The significant advantage of the WebRTC data channel over the classic WebSocket is also demonstrated. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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13 pages, 13020 KiB

Open AccessArticle

Classification of Unmanned Aerial Vehicles Based on Acoustic Signals Obtained in External Environmental Conditions

by Marzena Mięsikowska

Sensors 2024, 24(17), 5663; https://doi.org/10.3390/s24175663 - 30 Aug 2024

Viewed by 1225

Abstract

Detection of unmanned aerial vehicles (UAVs) and their classification on the basis of acoustic signals recorded in the presence of UAVs is a very important source of information. Such information can be the basis of certain decisions. It can support the autonomy of drones and their decision-making system, enabling them to cooperate in a swarm. The aim of this study was to classify acoustic signals recorded in the presence of 17 drones while they hovered individually at a height of 8 m above the recording equipment. The signals were obtained for the drones one at a time in external environmental conditions. Mel-frequency cepstral coefficients (MFCCs) were evaluated from the recorded signals. A discriminant analysis was performed based on 12 MFCCs. The grouping factor was the drone model. The result of the classification is a score of 98.8%. This means that on the basis of acoustic signals recorded in the presence of a drone, it is possible not only to detect the object but also to classify its model. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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29 pages, 7388 KiB

Open AccessArticle

UAV-UGV Collaborative Localisation with Minimum Sensing

by A. H. T. Eranga De Silva and Jayantha Katupitiya

Sensors 2024, 24(14), 4629; https://doi.org/10.3390/s24144629 - 17 Jul 2024

Viewed by 1486

Abstract

This paper presents a novel methodology to localise Unmanned Ground Vehicles (UGVs) using Unmanned Aerial Vehicles (UAVs). The UGVs are assumed to be operating in a Global Navigation Satellite System (GNSS)-denied environment. The localisation of the ground vehicles is achieved using UAVs that have full access to the GNSS. The UAVs use range sensors to localise the UGV. One of the major requirements is to use the minimum number of UAVs, which is two UAVs in this paper. Using only two UAVs leads to a significant complication that results an estimation unobservability under certain circumstances. As a solution to the unobservability problem, the main contribution of this paper is to present a methodology to treat the unobservability problem. A Constrained Extended Kalman Filter (CEKF)-based solution, which uses novel kinematics and heuristics-based constraints, is presented. The proposed methodology has been assessed based on the stochastic observability using the Posterior Cramér–Rao Bound (PCRB), and the results demonstrate the successful operation of the proposed localisation method. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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21 pages, 14918 KiB

Open AccessArticle

Real-Time Object Detection from UAV Inspection Videos by Combining YOLOv5s and DeepStream

by Shidun Xie, Guanghong Deng, Baihao Lin, Wenlong Jing, Yong Li and Xiaodan Zhao

Sensors 2024, 24(12), 3862; https://doi.org/10.3390/s24123862 - 14 Jun 2024

Viewed by 1604

Abstract

The high-altitude real-time inspection of unmanned aerial vehicles (UAVs) has always been a very challenging task. Because high-altitude inspections are susceptible to interference from different weather conditions, interference from communication signals and a larger field of view result in a smaller object area to be identified. We adopted a method that combines a UAV system scheduling platform with artificial intelligence object detection to implement the UAV automatic inspection technology. We trained the YOLOv5s model on five different categories of vehicle data sets, in which mAP50 and mAP50-95 reached 93.2% and 71.7%, respectively. The YOLOv5s model size is only 13.76 MB, and the detection speed of a single inspection photo reaches 11.26 ms. It is a relatively lightweight model and is suitable for deployment on edge devices for real-time detection. In the original DeepStream framework, we set up the http communication protocol to start quickly to enable different users to call and use it at the same time. In addition, asynchronous sending of alarm frame interception function was added and the auxiliary services were set up to quickly resume video streaming after interruption. We deployed the trained YOLOv5s model on the improved DeepStream framework to implement automatic UAV inspection. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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23 pages, 8365 KiB

Open AccessArticle

Resilient Multi-Sensor UAV Navigation with a Hybrid Federated Fusion Architecture

by Sorin Andrei Negru, Patrick Geragersian, Ivan Petrunin and Weisi Guo

Sensors 2024, 24(3), 981; https://doi.org/10.3390/s24030981 - 2 Feb 2024

Cited by 9 | Viewed by 3134

Abstract

Future UAV (unmanned aerial vehicle) operations in urban environments demand a PNT (position, navigation, and timing) solution that is both robust and resilient. While a GNSS (global navigation satellite system) can provide an accurate position under open-sky assumptions, the complexity of urban operations leads to NLOS (non-line-of-sight) and multipath effects, which in turn impact the accuracy of the PNT data. A key research question within the research community pertains to determining the appropriate hybrid fusion architecture that can ensure the resilience and continuity of UAV operations in urban environments, minimizing significant degradations of PNT data. In this context, we present a novel federated fusion architecture that integrates data from the GNSS, the IMU (inertial measurement unit), a monocular camera, and a barometer to cope with the GNSS multipath and positioning performance degradation. Within the federated fusion architecture, local filters are implemented using EKFs (extended Kalman filters), while a master filter is used in the form of a GRU (gated recurrent unit) block. Data collection is performed by setting up a virtual environment in AirSim for the visual odometry aid and barometer data, while Spirent GSS7000 hardware is used to collect the GNSS and IMU data. The hybrid fusion architecture is compared to a classic federated architecture (formed only by EKFs) and tested under different light and weather conditions to assess its resilience, including multipath and GNSS outages. The proposed solution demonstrates improved resilience and robustness in a range of degraded conditions while maintaining a good level of positioning performance with a 95th percentile error of 0.54 m for the square scenario and 1.72 m for the survey scenario. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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14 pages, 5878 KiB

Open AccessArticle

Computational Study of a Motion Sensor to Simultaneously Measure Two Physical Quantities in All Three Directions for a UAV

by Kamran Siddique and Yoshifumi Ogami

Sensors 2023, 23(11), 5265; https://doi.org/10.3390/s23115265 - 1 Jun 2023

Cited by 1 | Viewed by 1382

Abstract

Cross-axis sensitivity is generally undesirable, and lower values are required for the accurate performance of a thermal accelerometer. In this study, errors in devices are utilized to simultaneously measure two physical quantities of an unmanned aerial vehicle (UAV) in the X-, Y-, and Z-directions, i.e., where three accelerations and three rotations can also be simultaneously measured using a single motion sensor. The 3D structures of thermal accelerometers were designed and simulated in a FEM simulator using commercially available FLUENT 18.2 software Obtained temperature responses were correlated with input physical quantities, and a graphical relationship was created between peak temperature values and input accelerations and rotations. Using this graphical representation, any values of acceleration from 1g to 4g and rotational speed from 200 to 1000°/s can be simultaneously measured in all three directions. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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19 pages, 758 KiB

Open AccessArticle

UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits

by Amr Amrallah, Ehab Mahmoud Mohamed, Gia Khanh Tran and Kei Sakaguchi

Sensors 2023, 23(3), 1402; https://doi.org/10.3390/s23031402 - 26 Jan 2023

Cited by 19 | Viewed by 2900

Abstract

Over the past few years, with the rapid increase in the number of natural disasters, the need to provide smart emergency wireless communication services has become crucial. Unmanned aerial Vehicles (UAVs) have gained much attention as promising candidates due to their unprecedented capabilities and broad flexibility. In this paper, we investigate a UAV-based emergency wireless communication network for a post-disaster area. Our optimization problem aims to optimize the UAV’s flight trajectory to maximize the number of visited ground users during the flight period. Then, a dual cost-aware multi-armed bandit algorithm is adopted to tackle this problem under the limited available energy for both the UAV and ground users. Simulation results show that the proposed algorithm could solve the optimization problem and maximize the achievable throughput under these energy constraints. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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Review

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27 pages, 6231 KiB

Open AccessReview

A Review of Unmanned Aerial Vehicle Based Antenna and Propagation Measurements

by Venkat R. Kandregula, Zaharias D. Zaharis, Qasim Z. Ahmed, Faheem A. Khan, Tian Hong Loh, Jason Schreiber, Alexandre Jean René Serres and Pavlos I. Lazaridis

Sensors 2024, 24(22), 7395; https://doi.org/10.3390/s24227395 - 20 Nov 2024

Cited by 3 | Viewed by 2261

Abstract

This paper presents a comprehensive survey of state-of-the-art UAV–based antennas and propagation measurements. Unmanned aerial vehicles (UAVs) have emerged as powerful tools for in situ electromagnetic field assessments due to their flexibility, cost-effectiveness, and ability to operate in challenging environments. This paper highlights various UAV applications, from testing large–scale antenna arrays, such as those used in the square kilometer array (SKA), to evaluating channel models for 5G/6G networks. Additionally, the review discusses technical challenges, such as positioning accuracy and antenna alignment, and it provides insights into the latest advancements in portable measurement systems and antenna designs tailored for UAV use. During the UAV–based antenna measurements, key contributors to the relatively small inaccuracies of around 0.5 to 1 dB are identified. In addition to factors such as GPS positioning errors and UAV vibrations, ground reflections can significantly contribute to inaccuracies, leading to variations in the measured radiation patterns of the antenna. By minimizing ground reflections during UAV–based antenna measurements, errors in key measured antenna parameters, such as HPBW, realized gain, and the front-to-back ratio, can be effectively mitigated. To understand the source of propagation losses in a UAV to ground link, simulations were conducted in CST. These simulations identified scattering effects caused by surrounding buildings. Additionally, by simulating a UAV with a horn antenna, potential sources of electromagnetic coupling between the antenna and the UAV body were detected. The survey concludes by identifying key areas for future research and emphasizing the potential of UAVs to revolutionize antenna and propagation measurement practices to avoid the inaccuracies of the antenna parameters measured by the UAV. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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13 pages, 1096 KiB

Open AccessReview

Review on Type of Sensors and Detection Method of Anti-Collision System of Unmanned Aerial Vehicle

by Navaneetha Krishna Chandran, Mohammed Thariq Hameed Sultan, Andrzej Łukaszewicz, Farah Syazwani Shahar, Andriy Holovatyy and Wojciech Giernacki

Sensors 2023, 23(15), 6810; https://doi.org/10.3390/s23156810 - 30 Jul 2023

Cited by 15 | Viewed by 5358

Abstract

Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used in various industries for many applications, such as inspection, logistics, agriculture, and many more. This is because performing a task using UAV makes the job more efficient and reduces the workload needed. However, for a UAV to be operated manually or autonomously, the UAV must be equipped with proper safety features. An anti-collision system is one of the most crucial and fundamental safety features that UAVs must be equipped with. The anti-collision system allows the UAV to maintain a safe distance from any obstacles. The anti-collision technologies are of crucial relevance to assure the survival and safety of UAVs. Anti-collision of UAVs can be varied in the aspect of sensor usage and the system’s working principle. This article provides a comprehensive overview of anti-collision technologies for UAVs. It also presents drone safety laws and regulations that prevent a collision at the policy level. The process of anti-collision technologies is studied from three aspects: Obstacle detection, collision prediction, and collision avoidance. A detailed overview and comparison of the methods of each element and an analysis of their advantages and disadvantages have been provided. In addition, the future trends of UAV anti-collision technologies from the viewpoint of fast obstacle detection and wireless networking are presented. Full article

(This article belongs to the Special Issue New Methods and Applications for UAVs)

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