sensors-logo

Journal Browser

Journal Browser

Special Issue "Unmanned Aerial Vehicle Networks, Systems and Applications"

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

Deadline for manuscript submissions: closed (15 October 2018).

Special Issue Editors

Prof. Dr. Carlos Tavares Calafate
Website
Guest Editor
Department of Computer Engineering, Technical University of Valencia, Valencia, Spain
Interests: ad-hoc and vehicular networks; UAVs, smart cities and IoT; QoS; network protocols; video streaming; network security
Special Issues and Collections in MDPI journals
Prof. Dr. Claudio Palazzi
Website
Guest Editor
Department of Mathematics, University of Padua, Via Trieste, 35131 Padova, Italy
Interests: Wireless Networks; Web Squared; Online Entertainment; Mobile applications
Special Issues and Collections in MDPI journals
Prof. Dr. Armir Bujari
Website
Guest Editor
Università degli Studi di Padova, Via Trieste 63 - 35121, Padova, Italy
Interests: design, analysis and performance evaluation of protocols for wired/wireless networks with an emphasis on mobility, distributed sensing, mobile applications and multimedia entertainment

Special Issue Information

Dear Colleagues,

Unmanned Aerial Vehicles (UAVs), often called “drones”, have recently received much attention from academia and industry due to a plethora of exciting applications including 3D-mapping, search and rescue, surveillance, farmland and construction monitoring, delivery of light-weight objects and products, and video production.

While traditional mobile systems respond to device mobility (such as smartphones), drones allow computer systems to actively control device location, allowing them to interact with the physical world in new ways and with new-found scale, efficiency, or precision. The startup cost to experiment with and build real drone applications has dropped dramatically in recent years, also thanks to technological developments driven by the smartphone industry and the rise of the “makers” and DIY movements.

This Special Issue welcomes contributions dealing with all facets of drones as mobile computing platforms, including system aspects, theoretical studies, algorithms, networks protocols and communication systems to support air-to-ground and UAV-to-UAV coordination, as well as requirements, constraints, dependability, and regulations. We are particularly looking for papers reporting on experimental results of deployed systems, summaries of challenges or advancements, measurements, and innovative applications.

Prof. Dr. Carlos Tavares Calafate
Prof. Dr. Claudio E. Palazzi
Prof. Dr. Armir Bujari
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 papers will be 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. Sensors 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 2000 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

  • UAV applications and UAV-based systems
  • Network protocols and communication systems for UAV-based solutions
  • Algorithms and intelligent solutions for UAV-based deployments
  • Sensing solutions based on UAVs
  • UAV swarms and interaction between UAVs and IoT solutions
  • Integration of UAVs in Smart City solutions

Published Papers (37 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Fusion of Enhanced and Synthetic Vision System Images for Runway and Horizon Detection
Sensors 2019, 19(17), 3802; https://doi.org/10.3390/s19173802 - 03 Sep 2019
Cited by 2
Abstract
Networked operation of unmanned air vehicles (UAVs) demands fusion of information from disparate sources for accurate flight control. In this investigation, a novel sensor fusion architecture for detecting aircraft runway and horizons as well as enhancing the awareness of surrounding terrain is introduced [...] Read more.
Networked operation of unmanned air vehicles (UAVs) demands fusion of information from disparate sources for accurate flight control. In this investigation, a novel sensor fusion architecture for detecting aircraft runway and horizons as well as enhancing the awareness of surrounding terrain is introduced based on fusion of enhanced vision system (EVS) and synthetic vision system (SVS) images. EVS and SVS image fusion has yet to be implemented in real-world situations due to signal misalignment. We address this through a registration step to align EVS and SVS images. Four fusion rules combining discrete wavelet transform (DWT) sub-bands are formulated, implemented, and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and pairs containing simulated turbulence. Evaluations reveal that runways and horizons can be detected accurately even in poor visibility. Furthermore, it is demonstrated that different aspects of EVS and SVS images can be emphasized by using different DWT fusion rules. The procedure is autonomous throughout landing, irrespective of weather. The fusion architecture developed in this study holds promise for incorporation into manned heads-up displays (HUDs) and UAV remote displays to assist pilots landing aircraft in poor lighting and varying weather. The algorithm also provides a basis for rule selection in other signal fusion applications. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessFeature PaperArticle
A Distributed Architecture for Human-Drone Teaming: Timing Challenges and Interaction Opportunities
Sensors 2019, 19(6), 1379; https://doi.org/10.3390/s19061379 - 20 Mar 2019
Cited by 4
Abstract
Drones are expected to operate autonomously, yet they will also interact with humans to solve tasks together. To support civilian human-drone teams, we propose a distributed architecture where sophisticated operations such as image recognition, coordination with humans, and flight-control decisions are made, not [...] Read more.
Drones are expected to operate autonomously, yet they will also interact with humans to solve tasks together. To support civilian human-drone teams, we propose a distributed architecture where sophisticated operations such as image recognition, coordination with humans, and flight-control decisions are made, not on-board the drone, but remotely. The benefits of such an architecture are the increased computational power available for image recognition and the possibility to integrate interfaces for humans. On the downside, communication is necessary, resulting in the delayed reception of commands. In this article, we discuss the design considerations of the distributed approach, a sample implementation on a smartphone, and an application to the concrete use case of bookshelf inventory. Further, we report experimentally-derived first insights into messaging and command response delays with a custom drone connected through Wi-Fi. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
EffFeu Project: Towards Mission-Guided Application of Drones in Safety and Security Environments
Sensors 2019, 19(4), 973; https://doi.org/10.3390/s19040973 - 25 Feb 2019
Cited by 3
Abstract
The number of unmanned aerial system (UAS) applications for supporting rescue forces is growing in recent years. Nevertheless, the analysis of sensed information and control of unmanned aerial vehicle (UAV) creates an enormous psychological and emotional load for the involved humans especially in [...] Read more.
The number of unmanned aerial system (UAS) applications for supporting rescue forces is growing in recent years. Nevertheless, the analysis of sensed information and control of unmanned aerial vehicle (UAV) creates an enormous psychological and emotional load for the involved humans especially in critical and hectic situations. The introduced research project EffFeu (Efficient Operation of Unmanned Aerial Vehicle for Industrial Firefighters) especially focuses on a holistic integration of UAS in the daily work of industrial firefighters. This is done by enabling autonomous mission-guided control on top of the presented overall system architecture, goal-oriented high-level task control, comprehensive localisation process combining several approaches to enable the transition from and to GNSS-supported and GNSS-denied environments, as well as a deep-learning based object recognition of relevant entities. This work describes the concepts, current stage, and first evaluation results of the research project. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Development of a Recognition System for Spraying Areas from Unmanned Aerial Vehicles Using a Machine Learning Approach
Sensors 2019, 19(2), 313; https://doi.org/10.3390/s19020313 - 14 Jan 2019
Cited by 2
Abstract
Unmanned aerial vehicle (UAV)-based spraying systems have recently become important for the precision application of pesticides, using machine learning approaches. Therefore, the objective of this research was to develop a machine learning system that has the advantages of high computational speed and good [...] Read more.
Unmanned aerial vehicle (UAV)-based spraying systems have recently become important for the precision application of pesticides, using machine learning approaches. Therefore, the objective of this research was to develop a machine learning system that has the advantages of high computational speed and good accuracy for recognizing spray and non-spray areas for UAV-based sprayers. A machine learning system was developed by using the mutual subspace method (MSM) for images collected from a UAV. Two target lands: agricultural croplands and orchard areas, were considered in building two classifiers for distinguishing spray and non-spray areas. The field experiments were conducted in target areas to train and test the system by using a commercial UAV (DJI Phantom 3 Pro) with an onboard 4K camera. The images were collected from low (5 m) and high (15 m) altitudes for croplands and orchards, respectively. The recognition system was divided into offline and online systems. In the offline recognition system, 74.4% accuracy was obtained for the classifiers in recognizing spray and non-spray areas for croplands. In the case of orchards, the average classifier recognition accuracy of spray and non-spray areas was 77%. On the other hand, the online recognition system performance had an average accuracy of 65.1% for croplands, and 75.1% for orchards. The computational time for the online recognition system was minimal, with an average of 0.0031 s for classifier recognition. The developed machine learning system had an average recognition accuracy of 70%, which can be implemented in an autonomous UAV spray system for recognizing spray and non-spray areas for real-time applications. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Centralized Unmanned Aerial Vehicle Mesh Network Placement Scheme: A Multi-Objective Evolutionary Algorithm Approach
Sensors 2018, 18(12), 4387; https://doi.org/10.3390/s18124387 - 11 Dec 2018
Cited by 6
Abstract
In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in military operations to prevent pilot losses. Nowadays, the fast technological evolution has enabled the production of a class of cost-effective UAVs that can service a plethora of public and civilian applications, especially [...] Read more.
In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in military operations to prevent pilot losses. Nowadays, the fast technological evolution has enabled the production of a class of cost-effective UAVs that can service a plethora of public and civilian applications, especially when configured to work cooperatively to accomplish a task. However, designing a communication network among the UAVs is a challenging task. In this article, we propose a centralized UAV placement strategy, where UAVs are used as flying access points forming a mesh network, providing connectivity to ground nodes deployed in a target area. The geographical placement of UAVs is optimized based on a Multi-Objective Evolutionary Algorithm (MOEA). The goal of the proposed scheme is to cover all ground nodes using a minimum number of UAVs, while maximizing the fulfillment of their data rate requirements. The UAVs can employ different data rates depending on the channel conditions, which are expressed by the Signal-to-Noise-Ratio (SNR). In this work, the elitist Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to find a set of optimal positions to place UAVs, given the positions of the ground nodes. We evaluate the trade-off between the number of UAVs used to cover the target area and the data rate requirement of the ground nodes. Simulation results show that the proposed algorithm can optimize the UAV placement given the requirement and the positions of the ground nodes in the geographical area. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Aerial Coverage Analysis of Cellular Systems at LTE and mmWave Frequencies Using 3D City Models
Sensors 2018, 18(12), 4311; https://doi.org/10.3390/s18124311 - 06 Dec 2018
Cited by 6
Abstract
Cellular connectivity for UAV systems is interesting because it promises coverage in beyond visual line of sight scenarios. Inter-cell interference has been shown to be the main limiting factor at high altitudes. Using a realistic 3D simulator model, with real base station locations, [...] Read more.
Cellular connectivity for UAV systems is interesting because it promises coverage in beyond visual line of sight scenarios. Inter-cell interference has been shown to be the main limiting factor at high altitudes. Using a realistic 3D simulator model, with real base station locations, this study confirms that UAVs at high altitudes suffer from significant interference, resulting in a worse coverage compared to ground users. When replacing the existing base stations by mmWave cells, our results indicate that ground coverage is decreased to only 90%, while UAVs just above rooftop level have a coverage probability of 100%. However, UAVs at higher altitude still suffer from excessive interference. Beamforming has the potential to improve mmWave link budget and to decrease interference and is for this reason a promising technology for ensuring connectivity to aerial users. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Visual-Inertial Odometry with Robust Initialization and Online Scale Estimation
Sensors 2018, 18(12), 4287; https://doi.org/10.3390/s18124287 - 05 Dec 2018
Cited by 3
Abstract
Visual-inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when [...] Read more.
Visual-inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework and the stable initialization of scale and gravity using relative pose constraints. To account for the ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the European Robotics Challenge (EuRoC) dataset verify the efficacy and accuracy of the proposed method. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Visual-Based SLAM Configurations for Cooperative Multi-UAV Systems with a Lead Agent: An Observability-Based Approach
Sensors 2018, 18(12), 4243; https://doi.org/10.3390/s18124243 - 03 Dec 2018
Cited by 3
Abstract
In this work, the problem of the cooperative visual-based SLAM for the class of multi-UA systems that integrates a lead agent has been addressed. In these kinds of systems, a team of aerial robots flying in formation must follow a dynamic lead agent, [...] Read more.
In this work, the problem of the cooperative visual-based SLAM for the class of multi-UA systems that integrates a lead agent has been addressed. In these kinds of systems, a team of aerial robots flying in formation must follow a dynamic lead agent, which can be another aerial robot, vehicle or even a human. A fundamental problem that must be addressed for these kinds of systems has to do with the estimation of the states of the aerial robots as well as the state of the lead agent. In this work, the use of a cooperative visual-based SLAM approach is studied in order to solve the above problem. In this case, three different system configurations are proposed and investigated by means of an intensive nonlinear observability analysis. In addition, a high-level control scheme is proposed that allows to control the formation of the UAVs with respect to the lead agent. In this work, several theoretical results are obtained, together with an extensive set of computer simulations which are presented in order to numerically validate the proposal and to show that it can perform well under different circumstances (e.g., GPS-challenging environments). That is, the proposed method is able to operate robustly under many conditions providing a good position estimation of the aerial vehicles and the lead agent as well. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Collaborative UAV-WSN Network for Monitoring Large Areas
Sensors 2018, 18(12), 4202; https://doi.org/10.3390/s18124202 - 30 Nov 2018
Cited by 24
Abstract
Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better [...] Read more.
Large-scale monitoring systems have seen rapid development in recent years. Wireless sensor networks (WSN), composed of thousands of sensing, computing and communication nodes, form the backbone of such systems. Integration with unmanned aerial vehicles (UAVs) leads to increased monitoring area and to better overall performance. This paper presents a hybrid UAV-WSN network which is self-configured to improve the acquisition of environmental data across large areas. A prime objective and novelty of the heterogeneous multi-agent scheme proposed here is the optimal generation of reference trajectories, parameterized after inter- and intra-line distances. The main contribution is the trajectory design, optimized to avoid interdicted regions, to pass near predefined way-points, with guaranteed communication time, and to minimize total path length. Mixed-integer description is employed into the associated constrained optimization problem. The second novelty is the sensor localization and clustering method for optimal ground coverage taking into account the communication information between UAV and a subset of ground sensors (i.e., the cluster heads). Results show improvements in both network and data collection efficiency metrics by implementing the proposed algorithms. These are initially evaluated by means of simulation and then validated on a realistic WSN-UAV test-bed, thus bringing significant practical value. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Cooperative UAV Scheme for Enhancing Video Transmission and Global Network Energy Efficiency
Sensors 2018, 18(12), 4155; https://doi.org/10.3390/s18124155 - 27 Nov 2018
Cited by 8
Abstract
Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be [...] Read more.
Collaboration between multiple Unmanned Aerial Vehicles (UAVs) to set up a Flying Ad Hoc Network (FANET) is a growing trend since future applications claim for more autonomous and rapid deployable systems. The user experience on watching videos transmitted over FANETs should always be satisfactory even under influence of topology changes caused by the energy consumption of UAVs. In addition, the FANET must keep the UAVs cooperating as much as possible during a mission. However, one of the main challenges in FANET is how to mitigate the impact of limited energy resources of UAVs on the FANET operation in order to monitor the environment for a long period of time. In this sense, UAV replacement is required in order to avoid the premature death of nodes, network disconnections, route failures, void areas, and low-quality video transmissions. In addition, decision-making must take into account energy consumption associated with UAV movements, since they are generally quite energy-intensive. This article proposes a cooperative UAV scheme for enhancing video transmission and global energy efficiency called VOEI. The main goal of VOEI is to maintain the video with QoE support while supporting the nodes with a good connectivity quality level and flying for a long period of time. Based on an Software Defined Network (SDN) paradigm, the VOEI assumes the existence of a centrailized controller node to compute reliable and energy-efficiency routes, as well as detects the appropriate moment for UAV replacement by considering global FANET context information to provide energy-efficiency operations. Based on simulation results, we conclude that VOEI can effectively mitigate the energy challenges of FANET, since it provides energy-efficiency operations, avoiding network death, route failure, and void area, as well as network partitioning compared to state-of-the-art algorithm. In addition, VOEI delivers videos with suitable Quality of Experience (QoE) to end-users at any time, which is not achieved by the state-of-the-art algorithm. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Adaptable and Automated Small UAV Deployments via Virtualization
Sensors 2018, 18(12), 4116; https://doi.org/10.3390/s18124116 - 23 Nov 2018
Cited by 11
Abstract
In this paper, we present a practical solution to support the adaptable and automated deployment of applications of Small Unmanned Aerial Vehicles (SUAVs). Our solution is based on virtualization technologies, and considers SUAVs as programmable network platforms capable of executing virtual functions and [...] Read more.
In this paper, we present a practical solution to support the adaptable and automated deployment of applications of Small Unmanned Aerial Vehicles (SUAVs). Our solution is based on virtualization technologies, and considers SUAVs as programmable network platforms capable of executing virtual functions and services, which may be dynamically selected according to the requirements specified by the operator of the aerial vehicles. This way, SUAVs can be flexibly and rapidly adapted to different missions with heterogeneous objectives. The design of our solution is based on Network Function Virtualization (NFV) technologies, developed under the umbrella of the fifth generation of mobile networks (5G), as well as on existing Internet protocol standards, including flying ad hoc network routing protocols. We implemented a functional prototype of our solution using well-known open source technologies, and we demonstrated its practical feasibility with the execution of an IP telephony service. This service was implemented as a set of virtualized network functions, which were automatically deployed and interconnected over an infrastructure of SUAVs, being the telephony service tested with real voice-over-IP terminals. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Decentralized 3D Collision Avoidance for Multiple UAVs in Outdoor Environments
Sensors 2018, 18(12), 4101; https://doi.org/10.3390/s18124101 - 23 Nov 2018
Cited by 5
Abstract
The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional [...] Read more.
The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional challenges: (i) accurate positioning systems are costly; (ii) communication can be unreliable or delayed; and (iii) external conditions like wind gusts affect UAVs’ maneuverability. In this paper, we present 3D-SWAP, a decentralized algorithm for 3D collision avoidance with multiple UAVs. 3D-SWAP operates reactively without high computational requirements and allows UAVs to integrate measurements from their local sensors with positions of other teammates within communication range. We tested 3D-SWAP with our team of custom-designed UAVs. First, we used a Software-In-The-Loop simulator for system integration and evaluation. Second, we run field experiments with up to three UAVs in an outdoor scenario with uncontrolled conditions (i.e., noisy positioning systems, wind gusts, etc). We report our results and our procedures for this field experimentation. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Proactive Coverage Area Decisions Based on Data Field for Drone Base Station Deployment
Sensors 2018, 18(11), 3917; https://doi.org/10.3390/s18113917 - 13 Nov 2018
Cited by 2
Abstract
Using the drone base station (DBS) to alleviate the network coverage supply-demand mismatch is an attractive issue. Found in DBS-assisted cellular mobile networks, the deployment of DBSs to cope with the dynamic load requirements is an important problem. The authors propose a proactive [...] Read more.
Using the drone base station (DBS) to alleviate the network coverage supply-demand mismatch is an attractive issue. Found in DBS-assisted cellular mobile networks, the deployment of DBSs to cope with the dynamic load requirements is an important problem. The authors propose a proactive DBS deployment method to enhance the DBS deployment flexibility based on network traffic. The proposed scheme uses potential value and minimum distance to decide the areas that most need to be covered, which are named as proactive coverage areas (PCAs), whereby the DBSs are assigned to cover those PCAs. Meanwhile, when the number of required DBSs is determined, the energy consumption is related to the coverage radius and the altitude of DBSs. Therefore, the proposed method further investigates the on-demand coverage radius and then obtains the altitude of DBSs. Simulations show that the proposed proactive DBS deployment method provides better coverage performance with a significant complexity reduction. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network
Sensors 2018, 18(11), 3916; https://doi.org/10.3390/s18113916 - 13 Nov 2018
Cited by 1
Abstract
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations. The performance of a [...] Read more.
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations. The performance of a UAV data-link system is affected by the health status of both the hardware and UAV data-links. This paper proposes a method for predicting the health state of a UAV data-link system based on a Bayesian network fusion of information about potential hardware device failures and link failures. Our model employs the Bayesian network to describe the information and uncertainty associated with a complex multi-level system. To predict the health status of the UAV data-link, we use the health status information about the root node equipment with various life characteristics along with the health status of the links as affected by the bit error rate. In order to test the validity of the model, we tested its prediction of the health of a multi-level solar-powered unmanned aerial vehicle data-link system and the result shows that the method can quantitatively predict the health status of the solar-powered UAV data-link system. The results can provide guidance for improving the reliability of UAV data-link system and lay a foundation for predicting the health status of a UAV data-link system accurately. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs
Sensors 2018, 18(11), 3814; https://doi.org/10.3390/s18113814 - 07 Nov 2018
Cited by 6
Abstract
The development of Unmanned Aerial Vehicles (UAV) along with the ubiquity of Internet of Things (IoT) enables the creation of systems that, leveraging 5G enhancements, can provide real-time multimedia communications and data streaming. However, the usage of the UAVs introduces new constraints, such [...] Read more.
The development of Unmanned Aerial Vehicles (UAV) along with the ubiquity of Internet of Things (IoT) enables the creation of systems that, leveraging 5G enhancements, can provide real-time multimedia communications and data streaming. However, the usage of the UAVs introduces new constraints, such as unstable network communications and security pitfalls. In this work, the experience of implementing a system architecture for data and multimedia transmission using a multi-UAV system is presented. The system aims at creating an IoT ecosystem to bridge UAVs and other types of devices, such as smartphones and sensors, while coping with the fallback in an unstable communication environment. Furthermore, this work proposes a detailed description of a system architecture designed for remote drone fleet control. The proposed system provides an efficient, reliable and secure system for multi-UAV remote control that will offer the on-demand usage of available sensors, smartphones and unmanned vehicle infrastructure. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Location-Aware Waypoint-Based Routing Protocol for Airborne DTNs in Search and Rescue Scenarios
Sensors 2018, 18(11), 3758; https://doi.org/10.3390/s18113758 - 03 Nov 2018
Cited by 6
Abstract
In this paper, we propose GeoSaW, a delay-tolerant routing protocol for Airborne Networks in Search and Rescue scenarios. The protocol exploits the geographical information of UAVs to make appropriate message forwarding decisions. More precisely, the information about the future UAV’s motion path is [...] Read more.
In this paper, we propose GeoSaW, a delay-tolerant routing protocol for Airborne Networks in Search and Rescue scenarios. The protocol exploits the geographical information of UAVs to make appropriate message forwarding decisions. More precisely, the information about the future UAV’s motion path is exploited to select the best UAV carrying the message towards the destination. Simulation results show that the proposed solution outperforms the classic DTN routing protocols in terms of several performance metrics. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption
Sensors 2018, 18(11), 3756; https://doi.org/10.3390/s18113756 - 03 Nov 2018
Cited by 4
Abstract
The past decade has seen a substantial increase in the use of small unmanned aerial vehicles (UAVs) in both civil and military applications. This article addresses an important aspect of refueling in the context of routing multiple small UAVs to complete a surveillance [...] Read more.
The past decade has seen a substantial increase in the use of small unmanned aerial vehicles (UAVs) in both civil and military applications. This article addresses an important aspect of refueling in the context of routing multiple small UAVs to complete a surveillance or data collection mission. Specifically, this article formulates a multiple-UAV routing problem with the refueling constraint of minimizing the overall fuel consumption for all the vehicles as a two-stage stochastic optimization problem with uncertainty associated with the fuel consumption of each vehicle. The two-stage model allows for the application of sample average approximation (SAA). Although the SAA solution asymptotically converges to the optimal solution for the two-stage model, the SAA run time can be prohibitive for medium- and large-scale test instances. Hence, we develop a tabu search-based heuristic that exploits the model structure while considering the uncertainty in fuel consumption. Extensive computational experiments corroborate the benefits of the two-stage model compared to a deterministic model and the effectiveness of the heuristic for obtaining high-quality solutions. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Design and Simulation of the Opportunistic Computation Offloading with Learning-Based Prediction for Unmanned Aerial Vehicle (UAV) Clustering Networks
Sensors 2018, 18(11), 3751; https://doi.org/10.3390/s18113751 - 02 Nov 2018
Cited by 9
Abstract
Drones have recently become extremely popular, especially in military and civilian applications. Examples of drone utilization include reconnaissance, surveillance, and packet delivery. As time has passed, drones’ tasks have become larger and more complex. As a result, swarms or clusters of drones are [...] Read more.
Drones have recently become extremely popular, especially in military and civilian applications. Examples of drone utilization include reconnaissance, surveillance, and packet delivery. As time has passed, drones’ tasks have become larger and more complex. As a result, swarms or clusters of drones are preferred, because they offer more coverage, flexibility, and reliability. However, drone systems have limited computing power and energy resources, which means that sometimes it is difficult for drones to finish their tasks on schedule. A solution to this is required so that drone clusters can complete their work faster. One possible solution is an offloading scheme between drone clusters. In this study, we propose an opportunistic computational offloading system, which allows for a drone cluster with a high intensity task to borrow computing resources opportunistically from other nearby drone clusters. We design an artificial neural network-based response time prediction module for deciding whether it is faster to finish tasks by offloading them to other drone clusters. The offloading scheme is conducted only if the predicted offloading response time is smaller than the local computing time. Through simulation results, we show that our proposed scheme can decrease the response time of drone clusters through an opportunistic offloading process. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
An Augmented Reality Geo-Registration Method for Ground Target Localization from a Low-Cost UAV Platform
Sensors 2018, 18(11), 3739; https://doi.org/10.3390/s18113739 - 02 Nov 2018
Abstract
This paper presents an augmented reality-based method for geo-registering videos from low-cost multi-rotor Unmanned Aerial Vehicles (UAVs). The goal of the proposed method is to conduct an accurate geo-registration and target localization on a UAV video stream. The geo-registration of video stream requires [...] Read more.
This paper presents an augmented reality-based method for geo-registering videos from low-cost multi-rotor Unmanned Aerial Vehicles (UAVs). The goal of the proposed method is to conduct an accurate geo-registration and target localization on a UAV video stream. The geo-registration of video stream requires accurate attitude data. However, the Inertial Measurement Unit (IMU) sensors on most low-cost UAVs are not capable of being directly used for geo-registering the video. The magnetic compasses on UAVs are more vulnerable to the interferences in the working environment than the accelerometers. Thus the camera yaw error is the main sources of the registration error. In this research, to enhance the low accuracy attitude data from the onboard IMU, an extended Kalman Filter (EKF) model is used to merge Real Time Kinematic Global Positioning System (RTK GPS) data with the IMU data. In the merge process, the high accuracy RTK GPS data can be used to promote the accuracy and stability of the 3-axis body attitude data. A method of target localization based on the geo-registration model is proposed to determine the coordinates of the ground targets in the video. The proposed method uses a modified extended Kalman Filter to combine the data from RTK GPS and the IMU to improve the accuracy of the geo-registration and the localization result of the ground targets. The localization results are compared to the reference point coordinates from satellite image. The comparison indicates that the proposed method can provide practical geo-registration and target localization results. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Efficient Deployment of Multi-UAVs in Massively Crowded Events
Sensors 2018, 18(11), 3640; https://doi.org/10.3390/s18113640 - 26 Oct 2018
Cited by 2
Abstract
In this paper, the efficient 3D placement of UAV as an aerial base station in providing wireless coverage for users in a small and large coverage area is investigated. In the case of providing wireless coverage for outdoor and indoor users in a [...] Read more.
In this paper, the efficient 3D placement of UAV as an aerial base station in providing wireless coverage for users in a small and large coverage area is investigated. In the case of providing wireless coverage for outdoor and indoor users in a small area, the Particle Swarm Optimization (PSO) and K-means with Ternary Search (KTS) algorithms are invoked to find an efficient 3D location of a single UAV with the objective of minimizing its required transmit power. It was observed that a single UAV at the 3D location found using the PSO algorithm requires less transmit power, by a factor of 1/5 compared to that when using the KTS algorithm. In the case of providing wireless coverage for users in three different shapes of a large coverage area, namely square, rectangle and circular regions, the problems of finding an efficient placement of multiple UAVs equipped with a directional antenna are formulated with the objective to maximize the coverage area and coverage density using the Circle Packing Theory (CPT). Then, the UAV efficient altitude placement is formulated with the objective of minimizing its required transmit power. It is observed that the large number of UAVs does not necessarily result in the maximum coverage density. Based on the simulation results, the deployment of 16, 19 and 26 UAVs is capable of providing the maximum coverage density of 78.5%, 82.5% and 80.3% for the case of a square region with the dimensions of 2 km × 2 km, a rectangle region with the dimensions of 6 km × 1.8 km and a circular region with the radius of 1.125 km, respectively. These observations are obtained when the UAVs are located at the optimum altitude, where the required transmit power for each UAV is reasonably small. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Flying Ad Hoc Networks: A New Domain for Network Communications
Sensors 2018, 18(10), 3571; https://doi.org/10.3390/s18103571 - 21 Oct 2018
Cited by 25
Abstract
The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, [...] Read more.
The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Development of a Multispectral Albedometer and Deployment on an Unmanned Aircraft for Evaluating Satellite Retrieved Surface Reflectance over Nevada’s Black Rock Desert
Sensors 2018, 18(10), 3504; https://doi.org/10.3390/s18103504 - 17 Oct 2018
Cited by 2
Abstract
Bright surfaces across the western U.S. lead to uncertainties in satellite derived aerosol optical depth (AOD) where AOD is typically overestimated. With this in mind, a compact and portable instrument was developed to measure surface albedo on an unmanned aircraft system [...] Read more.
Bright surfaces across the western U.S. lead to uncertainties in satellite derived aerosol optical depth (AOD) where AOD is typically overestimated. With this in mind, a compact and portable instrument was developed to measure surface albedo on an unmanned aircraft system (UAS). This spectral albedometer uses two Hamamatsu micro-spectrometers (range: 340–780 nm) for measuring incident and reflected solar radiation at the surface. The instrument was deployed on 5 October 2017 in Nevada’s Black Rock Desert (BRD) to investigate a region of known high surface reflectance for comparison with albedo products from satellites. It was found that satellite retrievals underestimate surface reflectance compared to the UAS mounted albedometer. To highlight the importance of surface reflectance on the AOD from satellite retrieval algorithms, a 1-D radiative transfer model was used. The simple model was used to determine the sensitivity of AOD with respect to the change in albedo and indicates a large sensitivity of AOD retrievals to surface reflectance for certain combinations of surface albedo and aerosol optical properties. This demonstrates the need to increase the number of surface albedo measurements and an intensive evaluation of albedo satellite retrievals to improve satellite-derived AOD. The portable instrument is suitable for other applications as well. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Complex Network Theory-Based Modeling Framework for Unmanned Aerial Vehicle Swarms
Sensors 2018, 18(10), 3434; https://doi.org/10.3390/s18103434 - 12 Oct 2018
Cited by 5
Abstract
Unmanned aerial vehicle (UAV) swarms is an emerging technology that will significantly expand the application areas and open up new possibilities for UAVs, while also presenting new requirements for the robustness and reliability of the UAV swarming system. However, its complex and dynamic [...] Read more.
Unmanned aerial vehicle (UAV) swarms is an emerging technology that will significantly expand the application areas and open up new possibilities for UAVs, while also presenting new requirements for the robustness and reliability of the UAV swarming system. However, its complex and dynamic characteristics make it extremely challenging and uncertain to model such a system. In this study, to reach a full understanding of the swarming system, a modeling framework based on complex network theory is presented. First, the scope of work is identified from the point of view of control algorithms considering the dynamics and research novelty of the development of UAV swarming control strategy and three control structures consisting of three interdependent network layers are proposed. Second, three algorithms that systematically build the modeling framework considering all characteristics of the system are also developed. Finally, some network measurements are introduced by adjusting the fundamental ones into the UAV swarming system. The proposed framework is applied to a case study to illustrate the visualization models and estimate the statistical characteristics of the proposed networks with static and dynamic topology analysis. Furthermore, a simple demonstration of the robustness evaluation of the network is also presented. The networks obtained from this framework can be used to further analyze the robustness or reliability of a UAV swarming system in a high-confrontation battlefield environment the effect of cascading failure in ad-hoc network on system. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Enabling Multi-Mission Interoperable UAS Using Data-Centric Communications
Sensors 2018, 18(10), 3421; https://doi.org/10.3390/s18103421 - 12 Oct 2018
Cited by 4
Abstract
We claim the strong potential of data-centric communications in Unmanned Aircraft Systems (UAS), as a suitable paradigm to enhance collaborative operations via efficient information sharing, as well as to build systems supporting flexible mission objectives. In particular, this paper analyzes the primary contributions [...] Read more.
We claim the strong potential of data-centric communications in Unmanned Aircraft Systems (UAS), as a suitable paradigm to enhance collaborative operations via efficient information sharing, as well as to build systems supporting flexible mission objectives. In particular, this paper analyzes the primary contributions to data dissemination in UAS that can be given by the Data Distribution Service (DDS) open standard, as a solid and industry-mature data-centric technology. Our study is not restricted to traditional UAS where a set of Unmanned Aerial Vehicles (UAVs) transmit data to the ground station that controls them. Instead, we contemplate flexible UAS deployments with multiple UAV units of different sizes and capacities, which are interconnected to form an aerial communication network, enabling the provision of value-added services over a delimited geographical area. In addition, the paper outlines an approach to address the issues inherent to the utilization of network-level multicast, a baseline technology in DDS, in the considered UAS deployments. We complete our analysis with a practical experience aiming at validating the feasibility and the advantages of using DDS in a multi-UAV deployment scenario. For this purpose, we use a UAS testbed built up by heterogeneous hardware equipment, including a number of interconnected micro aerial vehicles, carrying single board computers as payload, as well as real equipment from a tactical UAS from the Spanish Ministry of Defense. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations
Sensors 2018, 18(10), 3411; https://doi.org/10.3390/s18103411 - 11 Oct 2018
Abstract
This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous [...] Read more.
This paper proposes a positioning strategy for a fleet of unmanned aerial vehicles (UAVs) airlifting wireless base stations driven by communication constraints. First, two schedulers that model the distribution of resources among users within a single cell are analyzed. Then, an UAV autonomous positioning strategy is developed, based on a fair distribution of the radio resources among all the users of all the cells in a given scenario, in such a way that the user bitrate is the same regardless the users’ distribution and spatial density. Moreover, two realistic constraints are added related to capacity of the backhaul link among the UAVs and the ground station: the bitrate delivered per UAV and the total backhaul bandwidth shared among all the UAVs. Additionally, an energy consumption model is considered to evaluate the efficiency and viability of the proposed strategy. Finally, numerical results in different scenarios are provided to assess both the schedulers performance and the proposed coordinated positioning strategy for the UAVs. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications
Sensors 2018, 18(10), 3391; https://doi.org/10.3390/s18103391 - 10 Oct 2018
Cited by 23
Abstract
This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a [...] Read more.
This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational efficiency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting flight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Design of Amphibious Vehicle for Unmanned Mission in Water Quality Monitoring Using Internet of Things
Sensors 2018, 18(10), 3318; https://doi.org/10.3390/s18103318 - 03 Oct 2018
Cited by 11
Abstract
Unmanned aerial vehicles (UAVs) have gained significant attention in recent times due to their suitability for a wide variety of civil, military, and societal missions. Development of an unmanned amphibious vehicle integrating the features of a multi-rotor UAV and a hovercraft is the [...] Read more.
Unmanned aerial vehicles (UAVs) have gained significant attention in recent times due to their suitability for a wide variety of civil, military, and societal missions. Development of an unmanned amphibious vehicle integrating the features of a multi-rotor UAV and a hovercraft is the focus of the present study. Components and subsystems of the amphibious vehicle are developed with due consideration for aerodynamic, structural, and environmental aspects. Finite element analysis (FEA) on static thrust conditions and skirt pressure are performed to evaluate the strength of the structure. For diverse wind conditions and angles of attack (AOA), computational fluid dynamic (CFD) analysis is carried out to assess the effect of drag and suitable design modification is suggested. A prototype is built with a 7 kg payload capacity and successfully tested for stable operations in flight and water-borne modes. Internet of things (IoT) based water quality measurement is performed in a typical lake and water quality is measured using pH, dissolved oxygen (DO), turbidity, and electrical conductivity (EC) sensors. The developed vehicle is expected to meet functional requirements of disaster missions catering to the water quality monitoring of large water bodies. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Dynamic Computation Offloading Scheme for Drone-Based Surveillance Systems
Sensors 2018, 18(9), 2982; https://doi.org/10.3390/s18092982 - 06 Sep 2018
Cited by 8
Abstract
Recently, various technologies for utilizing unmanned aerial vehicles have been studied. Drones are a kind of unmanned aerial vehicle. Drone-based mobile surveillance systems can be applied for various purposes such as object recognition or object tracking. In this paper, we propose a mobility-aware [...] Read more.
Recently, various technologies for utilizing unmanned aerial vehicles have been studied. Drones are a kind of unmanned aerial vehicle. Drone-based mobile surveillance systems can be applied for various purposes such as object recognition or object tracking. In this paper, we propose a mobility-aware dynamic computation offloading scheme, which can be used for tracking and recognizing a moving object on the drone. The purpose of the proposed scheme is to reduce the time required for recognizing and tracking a moving target object. Reducing recognition and tracking time is a very important issue because it is a very time critical job. Our dynamic computation offloading scheme considers both the dwell time of the moving target object and the network failure rate to estimate the response time accurately. Based on the simulation results, our dynamic computation offloading scheme can reduce the response time required for tracking the moving target object efficiently. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Development of Model Predictive Controller for a Tail-Sitter VTOL UAV in Hover Flight
Sensors 2018, 18(9), 2859; https://doi.org/10.3390/s18092859 - 30 Aug 2018
Cited by 11
Abstract
This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency [...] Read more.
This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Trusted Lightweight Communication Strategy for Flying Named Data Networking
Sensors 2018, 18(8), 2683; https://doi.org/10.3390/s18082683 - 15 Aug 2018
Cited by 12
Abstract
Flying Ad hoc Network (FANET) is a new resource-constrained breed and instantiation of Mobile Ad hoc Network (MANET) employing Unmanned Aerial Vehicles (UAVs) as communicating nodes. These latter follow a predefined path called ’mission’ to provide a wide range of applications/services. Without loss [...] Read more.
Flying Ad hoc Network (FANET) is a new resource-constrained breed and instantiation of Mobile Ad hoc Network (MANET) employing Unmanned Aerial Vehicles (UAVs) as communicating nodes. These latter follow a predefined path called ’mission’ to provide a wide range of applications/services. Without loss of generality, the services and applications offered by the FANET are based on data/content delivery in various forms such as, but not limited to, pictures, video, status, warnings, and so on. Therefore, a content-centric communication mechanism such as Information Centric Networking (ICN) is essential for FANET. ICN addresses the problems of classical TCP/IP-based Internet. To this end, Content-centric networking (CCN), and Named Data Networking (NDN) are two of the most famous and widely-adapted implementations of ICN due to their intrinsic security mechanism and Interest/Data-based communication. To ensure data security, a signature on the contents is appended to each response/data packet in transit. However, trusted communication is of paramount importance and currently lacks in NDN-driven communication. To fill the gaps, in this paper, we propose a novel trust-aware Monitor-based communication architecture for Flying Named Data Networking (FNDN). We first select the monitors based on their trust and stability, which then become responsible for the interest packets dissemination to avoid broadcast storm problem. Once the interest reaches data producer, the data comes back to the requester through the shortest and most trusted path (which is also the same path through which the interest packet arrived at the producer). Simultaneously, the intermediate UAVs choose whether to check the data authenticity or not, following their subjective belief on its producer’s behavior and thus-forth reducing the computation complexity and delay. Simulation results show that our proposal can sustain the vanilla NDN security levels exceeding the 80% dishonesty detection ratio while reducing the generated end-to-end delay to less than 1 s in the worst case and reducing the average consumed energy by more than two times. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
An Efficient Sampling-Based Algorithms Using Active Learning and Manifold Learning for Multiple Unmanned Aerial Vehicle Task Allocation under Uncertainty
Sensors 2018, 18(8), 2645; https://doi.org/10.3390/s18082645 - 12 Aug 2018
Cited by 2
Abstract
This paper presents a sampling-based approximation for multiple unmanned aerial vehicle (UAV) task allocation under uncertainty. Our goal is to reduce the amount of calculations and improve the accuracy of the algorithm. For this purpose, Gaussian process regression models are constructed from an [...] Read more.
This paper presents a sampling-based approximation for multiple unmanned aerial vehicle (UAV) task allocation under uncertainty. Our goal is to reduce the amount of calculations and improve the accuracy of the algorithm. For this purpose, Gaussian process regression models are constructed from an uncertainty parameter and task reward sample set, and this training set is iteratively refined by active learning and manifold learning. Firstly, a manifold learning method is used to screen samples, and a sparse graph is constructed to represent the distribution of all samples through a small number of samples. Then, multi-points sampling is introduced into the active learning method to obtain the training set from the sparse graph quickly and efficiently. This proposed hybrid sampling strategy could select a limited number of representative samples to construct the training set. Simulation analyses demonstrate that our sampling-based algorithm can effectively get a high-precision evaluation model of the impact of uncertain parameters on task reward. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Probabilistic Target Search Algorithm Based on Hierarchical Collaboration for Improving Rapidity of Drones
Sensors 2018, 18(8), 2535; https://doi.org/10.3390/s18082535 - 02 Aug 2018
Cited by 8
Abstract
Finding a target quickly is one of the most important tasks in drone operations. In particular, rapid target detection is a critical issue for tasks such as finding rescue victims during the golden period, environmental monitoring, locating military facilities, and monitoring natural disasters. [...] Read more.
Finding a target quickly is one of the most important tasks in drone operations. In particular, rapid target detection is a critical issue for tasks such as finding rescue victims during the golden period, environmental monitoring, locating military facilities, and monitoring natural disasters. Therefore, in this study, an improved hierarchical probabilistic target search algorithm based on the collaboration of drones at different altitudes is proposed. This is a method for reducing the search time and search distance by improving the information transfer methods between high-altitude and low-altitude drones. Specifically, to improve the speed of target detection, a high-altitude drone first performs a search of a wide area. Then, when the probability of existence of the target is higher than a certain threshold, the search information is transmitted to a low-altitude drone which then performs a more detailed search in the identified area. This method takes full advantage of fast searching capabilities at high altitudes. In other words, it reduces the total time and travel distance required for searching by quickly searching a wide search area. Several drone collaboration scenarios that can be performed by two drones at different altitudes are described and compared to the proposed algorithm. Through simulations, the performances of the proposed algorithm and the cooperation scenarios are analyzed. It is demonstrated that methods utilizing hierarchical searches with drones are comparatively excellent and that the proposed algorithm is approximately 13% more effective than a previous method and much better compared to other scenarios. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Multi-Camera Imaging System for UAV Photogrammetry
Sensors 2018, 18(8), 2433; https://doi.org/10.3390/s18082433 - 26 Jul 2018
Cited by 14
Abstract
In the last few years, it has been possible to observe a considerable increase in the use of unmanned aerial vehicles (UAV) equipped with compact digital cameras for environment mapping. The next stage in the development of photogrammetry from low altitudes was the [...] Read more.
In the last few years, it has been possible to observe a considerable increase in the use of unmanned aerial vehicles (UAV) equipped with compact digital cameras for environment mapping. The next stage in the development of photogrammetry from low altitudes was the development of the imagery data from UAV oblique images. Imagery data was obtained from side-facing directions. As in professional photogrammetric systems, it is possible to record footprints of tree crowns and other forms of the natural environment. The use of a multi-camera system will significantly reduce one of the main UAV photogrammetry limitations (especially in the case of multirotor UAV) which is a reduction of the ground coverage area, while increasing the number of images, increasing the number of flight lines, and reducing the surface imaged during one flight. The approach proposed in this paper is based on using several head cameras to enhance the imaging geometry during one flight of UAV for mapping. As part of the research work, a multi-camera system consisting of several cameras was designed to increase the total Field of View (FOV). Thanks to this, it will be possible to increase the ground coverage area and to acquire image data effectively. The acquired images will be mosaicked in order to limit the total number of images for the mapped area. As part of the research, a set of cameras was calibrated to determine the interior orientation parameters (IOPs). Next, the method of image alignment using the feature image matching algorithms was presented. In the proposed approach, the images are combined in such a way that the final image has a joint centre of projections of component images. The experimental results showed that the proposed solution was reliable and accurate for the mapping purpose. The paper also presents the effectiveness of existing transformation models for images with a large coverage subjected to initial geometric correction due to the influence of distortion. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Internet-Of-Things in Motion: A UAV Coalition Model for Remote Sensing in Smart Cities
Sensors 2018, 18(7), 2184; https://doi.org/10.3390/s18072184 - 06 Jul 2018
Cited by 11
Abstract
Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently [...] Read more.
Unmanned aerial vehicles (UAVs) or drones are increasingly used in cities to provide service tasks that are too dangerous, expensive or difficult for human beings. Drones are also used in cases where a task can be performed more economically and or more efficiently than if done by humans. These include remote sensing tasks where drones can be required to form coalitions by pooling their resources to meet the service requirements at different locations of interest in a city. During such coalition formation, finding the shortest path from a source to a location of interest is key to efficient service delivery. For fixed-wing UAVs, Dubins curves can be applied to find the shortest flight path. When a UAV flies to a location of interest, the angle or orientation of the UAV upon its arrival is often not important. In such a case, a simplified version of the Dubins curve consisting of two instead of three parts can be used. This paper proposes a novel model for UAV coalition and an algorithm derived from basic geometry that generates a path derived from the original Dubins curve for application in remote sensing missions of fixed-wing UAVs. The algorithm is tested by incorporating it into three cooperative coalition formation algorithms. The performance of the model is evaluated by varying the number of types of resources and the sensor ranges of the UAVs to reveal the relevance and practicality of the proposed model. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
AVSS: Airborne Video Surveillance System
Sensors 2018, 18(6), 1939; https://doi.org/10.3390/s18061939 - 14 Jun 2018
Cited by 10
Abstract
Most surveillance systems only contain CCTVs. CCTVs, however, provide only limited maneuverability against dynamic targets and are inefficient for short term surveillance. Such limitations do not raise much concern in some cases, but for the scenario in which traditional surveillance systems do not [...] Read more.
Most surveillance systems only contain CCTVs. CCTVs, however, provide only limited maneuverability against dynamic targets and are inefficient for short term surveillance. Such limitations do not raise much concern in some cases, but for the scenario in which traditional surveillance systems do not suffice, adopting a fleet of UAVs can help overcoming the limitations. In this paper, we present a surveillance system implemented with a fleet of unmanned aerial vehicles (UAVs). A surveillance system implemented with a fleet of UAVs is easy to deploy and maintain. A UAV fleet requires little time to deploy and set up, and removing the surveillance is also virtually instant. The system we propose deploys UAVs to the target area for installation and perform surveillance operations. The camera mounted UAVs act as surveillance probes, the server provides overall control of the surveillance system, and the fleet platform provides fleet-wise control of the UAVs. In the proposed system, the UAVs establish a network and enable multi-hop communication, which allows the system to widen its coverage area. The operator of the system can control the fleet of UAVs via the fleet platform and receive surveillance information gathered by the UAVs. The proposed system is described in detail along with the algorithm for effective placement of the UAVs. The prototype of the system is presented, and the experiment carried out shows that the system can successfully perform surveillance over an area set by the system. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
A Self-Organized Reciprocal Decision Approach for Sensing Coverage with Multi-UAV Swarms
Sensors 2018, 18(6), 1864; https://doi.org/10.3390/s18061864 - 07 Jun 2018
Cited by 3
Abstract
This paper tackles the problem of sensing coverage for multiple Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the reciprocal between neighboring UAVs to reduce the oscillation of their trajectories. The proposed reciprocal decision approach, which is performed in three [...] Read more.
This paper tackles the problem of sensing coverage for multiple Unmanned Aerial Vehicles (UAVs) with an approach that takes into account the reciprocal between neighboring UAVs to reduce the oscillation of their trajectories. The proposed reciprocal decision approach, which is performed in three steps, is self-organized, distributed and autonomous. First, in contrast to the traditional method modeled and optimized in configuration space, the sensing coverage problem is directly presented as an optimal reciprocal coverage velocity (ORCV) in velocity space that is concise and effective. Second, the ORCV is determined by adjusting the action velocity out of weak coverage velocity relative to neighboring UAVs to demonstrate that the ORCV supports a collision-avoiding assembly. Third, a corresponding random probability method is proposed for determining the optimal velocity in the ORCV. The results from the simulation indicate that the proposed method has a high coverage rate, rapid convergence rate and low deadweight loss. In addition, for up to 103-size UAVs, the proposed method has excellent scalability and collision-avoiding ability. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Open AccessArticle
Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT
Sensors 2018, 18(5), 1519; https://doi.org/10.3390/s18051519 - 11 May 2018
Cited by 10
Abstract
Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an [...] Read more.
Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1) low-battery first scheme; (2) high-battery first scheme; and (3) random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF) signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicle Networks, Systems and Applications)
Show Figures

Figure 1

Back to TopTop