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Unmanned Aerial Systems and Sensor Networks
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Unmanned Aerial Systems and Sensor Networks

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

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 14290

Special Issue Editor

Dr. José Ramiro Martínez-De-Dios

E-Mail Website
Guest Editor
School of Engineering, University of Seville, Avda. Camino de los Descubrimientos, 41092 Seville, Spain
Interests: robot perception; cooperative perception; multi-robot systems; robot–sensor network cooperation; localization/mapping; SLAM; aerial robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last years, different technological fields have been integrated into the broad context of the Internet-of-Things (IoT). The miniaturization and advances in sensors, computing and wireless intercommunication have boosted the development of sensor networks (SNs) with a very important impact on many applications and sectors. Also, the development of unmanned aerial systems (UAS) has revolutionized many sectors and originated new applications in many fields with a very high impact on society.

UAS and SN technologies can be combined with very interesting synergies for many problems providing unprecedented capabilities for many problems and applications. The cooperation between UAS and static and/or mobile SNs, the combined perception between local measurements from SNs and long-range measurements from UAS, the mobility of UAS for transporting and deploying SN nodes or for collecting measurements gathered by SNs are only a few examples. However, the cooperation between UAS and static and mobile SNs is far from being solved and poses unanswered questions not only in UAS–SN integration, cooperation schemes, communication, algorithms, protocols, perception techniques, planning of UAS and static and/or mobile SN or security issues, but also in devices and hardware design, implementation, real-world deployments and new applications.

This Special Issue will publish innovative works that explore new trends, frontiers and challenges in the field of UAS–SN cooperation, including new architectures, techniques and protocols, as well as implementation issues, devices, real-world deployments and new applications.

Topics of interest include, but are not limited to:

  • Architectures and UAS–SN integration
  • Cooperation between UAS and static SNs
  • Cooperation between UAS and networked ground robots
  • UAS–SN communication models
  • UAS–SN modeling, simulation and performance
  • SN algorithms for integration with UAS
  • UAS control and planning for integration with SN
  • UAS–SN perception
  • Security issues and protocols
  • Devices and hardware design
  • Testbeds
  • Implementation issues
  • Real-world deployments and lessons learnt
  • Applications: data collection, wireless aerial networks, target detection, smart cities, structural monitoring, earth/crop monitoring, animal monitoring, among many others

Dr. José Ramiro Martínez-De-Dios
Guest Editor

Manuscript Submission Information

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

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. 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 2600 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

  • Internet of Things
  • Sensor Networks
  • Unmanned Aerial Systems
  • Ubiquitous Systems

Published Papers (4 papers)

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Research

25 pages, 3432 KiB  
Article
Distributed Multi-Robot Information Gathering under Spatio-Temporal Inter-Robot Constraints
by Alberto Viseras, Zhe Xu and Luis Merino
Sensors 2020, 20(2), 484; https://doi.org/10.3390/s20020484 - 15 Jan 2020
Cited by 11 | Viewed by 3010
Abstract
Information gathering (IG) algorithms aim to intelligently select the mobile robotic sensor actions required to efficiently obtain an accurate reconstruction of a physical process, such as an occupancy map, a wind field, or a magnetic field. Recently, multiple IG algorithms that benefit from [...] Read more.
Information gathering (IG) algorithms aim to intelligently select the mobile robotic sensor actions required to efficiently obtain an accurate reconstruction of a physical process, such as an occupancy map, a wind field, or a magnetic field. Recently, multiple IG algorithms that benefit from multi-robot cooperation have been proposed in the literature. Most of these algorithms employ discretization of the state and action spaces, which makes them computationally intractable for robotic systems with complex dynamics. Moreover, they cannot deal with inter-robot restrictions such as collision avoidance or communication constraints. This paper presents a novel approach for multi-robot information gathering (MR-IG) that tackles the two aforementioned restrictions: (i) discretization of robot’s state space, and (ii) dealing with inter-robot constraints. Here we propose an algorithm that employs: (i) an underlying model of the physical process of interest, (ii) sampling-based planners to plan paths in a continuous domain, and (iii) a distributed decision-making algorithm to enable multi-robot coordination. In particular, we use the max-sum algorithm for distributed decision-making by defining an information-theoretic utility function. This function maximizes IG, while fulfilling inter-robot communication and collision avoidance constraints. We validate our proposed approach in simulations, and in a field experiment where three quadcopters explore a simulated wind field. Results demonstrate the effectiveness and scalability with respect to the number of robots of our approach. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Sensor Networks)
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32 pages, 2222 KiB  
Article
Data Collection Schemes for Animal Monitoring Using WSNs-Assisted by UAVs: WSNs-Oriented or UAV-Oriented
by Rodolfo Vera-Amaro, Mario Eduardo Rivero-Ángeles and Alberto Luviano-Juárez
Sensors 2020, 20(1), 262; https://doi.org/10.3390/s20010262 - 02 Jan 2020
Cited by 22 | Viewed by 3655
Abstract
Wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) have been used for monitoring animals but when their habitats have difficult access and are areas of a large expanse, remote monitoring by classic techniques becomes a difficult task. The use of traditional WSNs [...] Read more.
Wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) have been used for monitoring animals but when their habitats have difficult access and are areas of a large expanse, remote monitoring by classic techniques becomes a difficult task. The use of traditional WSNs requires a restrictive number of hops in a multi-hoping routing scheme, traveling long distances to the sink node where data is stored by nodes and UAVs are used to collect data by visiting each node. However, the use of UAVs is not straightforward since the energy balance between the WSN and UAV has to be carefully calibrated. Building on this, we propose two data collection schemes in clustered based WSNs: (1) WSN oriented and (2) UAV oriented. In the former, nodes within each cluster member (CM), send information to their cluster head (CH) and for recollection, the UAV visits all CHs. As the UAV visits many CHs the flight time is increased. In the latter, all CHs send data from their CMs to a sink node, hence, the UAV only visits this node, reducing the flying time but with a higher system energy cost. To find the most suitable scheme for different monitoring conditions in terms of the average energy consumption and the buffer capacity of the system, we develop a mathematical model that considers both the dynamics of the WSN along with the UAV. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Sensor Networks)
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29 pages, 2940 KiB  
Article
Performance Evaluation of Multi-UAV Network Applied to Scanning Rocket Impact Area
by Maurício R. Silva, Elitelma S. Souza, Pablo J. Alsina, Deyvid L. Leite, Mateus R. Morais, Diego S. Pereira, Luís B. P. Nascimento, Adelardo A. D. Medeiros, Francisco H. Cunha Junior, Marcelo B. Nogueira, Glauberto L. A. Albuquerque and João B. D. Dantas
Sensors 2019, 19(22), 4895; https://doi.org/10.3390/s19224895 - 09 Nov 2019
Cited by 15 | Viewed by 4170
Abstract
This paper presents a communication network for a squadron of unmanned aerial vehicles (UAVs) to be used in the scanning rocket impact area for Barreira do Inferno Launch Center—CLBI (Rio Grande do Norte, Brazil), aiming at detecting intruder boats. The main features of [...] Read more.
This paper presents a communication network for a squadron of unmanned aerial vehicles (UAVs) to be used in the scanning rocket impact area for Barreira do Inferno Launch Center—CLBI (Rio Grande do Norte, Brazil), aiming at detecting intruder boats. The main features of communication networks associated with multi-UAV systems are presented. This system sends information through Wireless Sensor Networks (WSN). After comparing and analyzing area scanning strategies, it presents the specification of a data communication network architecture for a squadron of UAVs within a sensor network using XBee Pro 900HP S3B modules. A brief description is made about the initial information from the construction of the system. The embedded hardware and the design procedure of a dedicated communication antenna to the XBee modules are presented. In order to evaluate the performance of the proposed architecture in terms of robustness and reliability, a set of experimental tests in different communication scenarios is carried out. Network management software is employed to measure the throughput, packet loss and other performance indicators in the communication links between the different network nodes. Experimental results allow verifying the quality and performance of the network nodes, as well as the reliability of the communication links, assessing signal received quality, range and latency. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Sensor Networks)
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16 pages, 1895 KiB  
Article
Profit-Driven Adaptive Moving Targets Search with UAV Swarms
by Xianfeng Li, Jie Chen, Fan Deng and Hui Li
Sensors 2019, 19(7), 1545; https://doi.org/10.3390/s19071545 - 30 Mar 2019
Cited by 15 | Viewed by 2982
Abstract
This paper presents a novel distributed algorithm for a moving targets search with a team of cooperative unmanned aerial vehicles (UAVs). UAVs sense targets using on-board sensors and the information can be shared with teammates within a communication range. Based on local and [...] Read more.
This paper presents a novel distributed algorithm for a moving targets search with a team of cooperative unmanned aerial vehicles (UAVs). UAVs sense targets using on-board sensors and the information can be shared with teammates within a communication range. Based on local and shared information, the UAV swarm tries to maximize its average observation rate on targets. Unlike traditional approaches that treat the impact from different sources separately, our framework characterizes the impact of moving targets and collaborating UAVs on the moving decision for each UAV with a unified metric called observation profit. Based on this metric, we develop a profit-driven adaptive moving targets search algorithm for a swarm of UAVs. The simulation results validate the effectiveness of our framework in terms of both observation rate and its adaptiveness. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Sensor Networks)
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