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Sensors for Aerial Unmanned Systems
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Sensors for Aerial Unmanned Systems

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

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 20451

Special Issue Editors

Prof. Dr. Carlo Bettanini

E-Mail Website
Guest Editor
Department of Industrial Engineering, Via Venezia 1, 35131 Padova, Italy Center for Studies and Activities for Space, Via Venezia 15, 35131 Padova, Italy
Interests: Design, realization, and qualification of instruments and mechanisms for space applications; Design and qualification of Earth low- and high-altitude autonomous flight systems; Methods for prediction and reconstruction of trajectory and attitude of both space and atmospheric flying systems
Special Issues, Collections and Topics in MDPI journals
Dr. Giacomo Colombatti

E-Mail Website
Guest Editor
Center for Studies and Activities for Space, Via Venezia 15, 35131 Padova, Italy
Interests: planetary probes; instrumentation for space applications; instrumentation for drones; air pollution monitoring; drones for archeology
Dr. Alessio Aboudan

E-Mail Website
Guest Editor
Center for Studies and Activities for Space, Via Venezia 15, 35131 Padova, Italy
Interests: instrumentation for space and airborne applications; autonomous navigation systems and SLAM methods; data analysis and data fusion techniques; image processing and machine learning
Dr. Sebastiano Chiodini

E-Mail Website
Guest Editor
1. Department of Industrial Engineering, Università Degli Studi di Padova, Via Venezia 1, 35131 Padova, Italy
2. Center for Studies and Activities for Space, Via Venezia 15, 35131 Padova, Italy
Interests: design, realization, and qualification of instruments and mechanisms for space applications; machine-vision-based localization methods for rovers; pose estimation; simultaneous localization and mapping (SLAM); active vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

On behalf of the Editorial Board of Sensors, it is my honor to inform you about our upcoming Special Issue on Sensors for Aerial Unmanned System. Join us in our efforts to extend and share the latest advancements in sensors for UAVs and acknowledge us if you can submit a manuscript by the end of July or let us know about your feasible time to make the submission. I look forward to your favorable response.

Potential topics include but are not limited to the following:

  • Sensors for drones and balloons navigation
  • Sensors and control for UAV formation flight
  • Vision systems and RGB-D sensors for navigation
  • Optical sensors for remote sensing including aerial-based measurement for cultural heritage, aerial-based measurement for precision farming, aerial-based measurement for geology
  • Aerial systems and sensors for light pollution measurement
  • Aerial systems and sensors for air pollution measurement
  • UAV application in civil engineering and oil and gas industry
  • UAV application for planetary exploration
  • Sensors for human–UAV interaction
  • Machine learning in UAV sensing
  • Sensors and algorithms for a safe landing
  • Active safety devices for UAVs ( parachutes and commanded wings)
Prof. Dr. Carlo Bettanini
Dr. Giacomo Colombatti
Dr. Alessio Aboudan
Dr. Sebastiano Chiodini
Guest Editors

Manuscript Submission Information

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

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

  • UAV trajectory and attitude control
  • Navigation sensors
  • Light pollution measurement
  • Air pollution measurement
  • Optical sensors for remote sensing
  • Sensors miniaturization

Published Papers (5 papers)

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Research

20 pages, 1308 KiB  
Article
A BCI Based Alerting System for Attention Recovery of UAV Operators
by Jonghyuk Park, Jonghun Park, Dongmin Shin and Yerim Choi
Sensors 2021, 21(7), 2447; https://doi.org/10.3390/s21072447 - 2 Apr 2021
Cited by 10 | Viewed by 2631
Abstract
As unmanned aerial vehicles have become popular, the number of accidents caused by an operator’s inattention have increased. To prevent such accidents, the operator should maintain an attention status. However, limited research has been conducted on the brain-computer interface (BCI)-based system with an [...] Read more.
As unmanned aerial vehicles have become popular, the number of accidents caused by an operator’s inattention have increased. To prevent such accidents, the operator should maintain an attention status. However, limited research has been conducted on the brain-computer interface (BCI)-based system with an alerting module for the operator’s attention recovery of unmanned aerial vehicles. Therefore, we introduce a detection and alerting system that prevents an unmanned aerial vehicle operator from falling into inattention status by using the operator’s electroencephalogram signal. The proposed system consists of the following three components: a signal processing module, which collects and preprocesses an electroencephalogram signal of an operator, an inattention detection module, which determines whether an inattention status occurred based on the preprocessed signal, and, lastly, an alert providing module that presents stimulus to an operator when inattention is detected. As a result of evaluating the performance with a real-world dataset, it was shown that the proposed system successfully contributed to the recovery of operator attention in the evaluating dataset, although statistical significance could not be established due to the small number of subjects. Full article
(This article belongs to the Special Issue Sensors for Aerial Unmanned Systems)
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24 pages, 11883 KiB  
Article
A Multispectral Camera Development: From the Prototype Assembly until Its Use in a UAV System
by Alejandro Morales, Raul Guerra, Pablo Horstrand, Maria Diaz, Adan Jimenez, Jose Melian, Sebastian Lopez and Jose F. Lopez
Sensors 2020, 20(21), 6129; https://doi.org/10.3390/s20216129 - 28 Oct 2020
Cited by 19 | Viewed by 6019
Abstract
Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name [...] Read more.
Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name some. Different implementations are commercially available from the industry and yet there is quite an interest from the scientific community to spread its use to the majority of society by means of cost effectiveness and ease of use for solutions. These devices make the most sense when combined with unmanned aerial vehicles (UAVs), going a step further and alleviating repetitive routines which could be strenuous if traditional methods were adopted. In this work, a low cost and modular solution for a multispectral camera is presented, based on the use of a single panchromatic complementary metal oxide semiconductor (CMOS) sensor combined with a rotating wheel of interchangeable band pass optic filters. The system is compatible with open source hardware permitting one to capture, process, store and/or transmit data if needed. In addition, a calibration and characterization methodology has been developed for the camera, allowing not only for quantifying its performance, but also able to characterize other CMOS sensors in the market in order to select the one that best suits the budget and application. The process was experimentally validated by mounting the camera in a Dji Matrice 600 UAV to uncover vegetation indices in a reduced area of palm trees plantation. Results are presented for the normalized difference vegetation index (NDVI) showing a generated colored map with the captured information. Full article
(This article belongs to the Special Issue Sensors for Aerial Unmanned Systems)
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20 pages, 1803 KiB  
Article
Sensor Fusion Algorithm Using a Model-Based Kalman Filter for the Position and Attitude Estimation of Precision Aerial Delivery Systems
by Raul A. Garcia-Huerta, Luis E. González-Jiménez and Ivan E. Villalon-Turrubiates
Sensors 2020, 20(18), 5227; https://doi.org/10.3390/s20185227 - 13 Sep 2020
Cited by 5 | Viewed by 5049
Abstract
In this research, we focus on the use of Unmanned Aerial Vehicles (UAVs) for the delivery of payloads and navigation towards safe-landing zones, specifically on the modeling of flight dynamics of lightweight vehicles denoted Precision Aerial Delivery Systems (PADSs). While a wide range [...] Read more.
In this research, we focus on the use of Unmanned Aerial Vehicles (UAVs) for the delivery of payloads and navigation towards safe-landing zones, specifically on the modeling of flight dynamics of lightweight vehicles denoted Precision Aerial Delivery Systems (PADSs). While a wide range of nonlinear models has been developed and tested on high-end applications considering various degrees of freedom (DOF), linear models suitable for low-cost applications have not been explored thoroughly. In this study, we propose and compare two linear models, a linearized version of a 6-DOF model specifically developed for micro-lightweight systems, and an alternative model based on a double integrator. Both linear models are implemented with a sensor fusion algorithm using a Kalman filter to estimate the position and attitude of PADSs, and their performance is compared to a nonlinear 6-DOF model. Simulation results demonstrate that both models, when incorporated into a Kalman filter estimation scheme, can determine the flight dynamics of PADSs during smooth flights. While it is validated that the double integrator model can adequately operate under the proposed estimation scheme for up to small acceleration changes, the linearized model proves to be capable of reproducing the nonlinear model characteristics even during moderately steep turns. Full article
(This article belongs to the Special Issue Sensors for Aerial Unmanned Systems)
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32 pages, 4280 KiB  
Article
Decentralized Mesh-Based Model Predictive Control for Swarms of UAVs
by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro, Luciano Blasi and Massimiliano Mattei
Sensors 2020, 20(15), 4324; https://doi.org/10.3390/s20154324 - 3 Aug 2020
Cited by 22 | Viewed by 3628
Abstract
This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence [...] Read more.
This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles. A custom numerical simulator was developed in a Matlab/Simulink environment to prove the effectiveness of the proposed guidance and control scheme in several 2D operational scenarios with obstacles of different sizes and increasing number of aircraft. Full article
(This article belongs to the Special Issue Sensors for Aerial Unmanned Systems)
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19 pages, 2118 KiB  
Article
Velocity Sensor for Real-Time Backstepping Control of a Multirotor Considering Actuator Dynamics
by Walter Alejandro Mayorga-Macías, Luis Enrique González-Jiménez, Marco Antonio Meza-Aguilar and Luis Fernando Luque-Vega
Sensors 2020, 20(15), 4229; https://doi.org/10.3390/s20154229 - 29 Jul 2020
Viewed by 2424
Abstract
A real-time implementation of a control scheme for a multirotor, based on angular velocity sensors for the actuators, is presented. The control scheme is composed of two loops: an inner loop for the actuators and an outer loop for the unmanned aerial vehicle [...] Read more.
A real-time implementation of a control scheme for a multirotor, based on angular velocity sensors for the actuators, is presented. The control scheme is composed of two loops: an inner loop for the actuators and an outer loop for the unmanned aerial vehicle (UAV). The UAV control algorithm is designed by means of the backstepping technique and a robust sliding mode differentiator, and the actuator control strategy is based on a standard proportional-integral-derivative (PID) controller. A robust exact differentiator, based on high order sliding modes, is used to estimate the complex derivatives present in the proposed control law. As the measurements of the propeller’s angular velocities are required for the control law, velocity sensors are mounted in the axles of the rotors to retrieve them and a signal conditioning stage is implemented. In addition, dynamical models for the actuators of the aircraft were calculated by means of transfer functions obtained via experimental measurements in a test bench developed for this purpose. This test bench permits to characterize the parameters of the transfer functions by comparing the forces computed using the nominal parameter to the measured forces. To this end, it is assumed that the loads in the actuators of the vehicle are insignificant during flight. The effectiveness of the proposed sensor, its signal conditioning, and the overall control scheme are validated by means of simulation results and real-time experiments. Full article
(This article belongs to the Special Issue Sensors for Aerial Unmanned Systems)
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