E-Mail Alert

Add your e-mail address to receive forthcoming issues of this journal:

Journal Browser

Journal Browser

Special Issue "UAV Sensors for Environmental Monitoring"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (15 September 2015)

Special Issue Editors

Guest Editor
Assoc. Prof. Dr. Felipe Gonzalez Toro

School of Electrical Engineering and Computer Science, Australian Research Center for Aerospace Automation (ARCAA), Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4000, Australia
Website | E-Mail
Interests: UAV, gas sensors, imaging sensors; image processing; pattern recognition; 3D image reconstruction, spatio-temporal image change detection, sense and avoid
Co-Guest Editor
Prof. Dr. Antonios Tsourdos

Institute of Aerospace Sciences, School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, MK43 0AL, UK
Website | E-Mail
Interests: UAV; sensor and data fusion; network decision systems; information management; sense and avoid; guidance and navigation; target tracking and estimation

Special Issue Information

Dear Colleagues,

The rapid development and growth of UAVs as a remote sensing platform as well as advances in the miniaturization of instrumentation and data systems are catalyzing a renaissance in remote sensing in a variety of fields and disciplines from precision agriculture to ecology, atmospheric research, and disaster response.

This Special Issue is seeking submissions that highlight advances in the development and use of sensors deployed on UAVs. Topics include, but are not limited, to:

  • Optical, multi-spectral, hyperspectral, laser, and optical SAR technologies
  • Gas analyzers and sensors
  • Artificial intelligence and data mining based strategies from UAVs
  • UAV onboard data storage, transmission, and retrieval
  • Collaborative strategies and mechanisms to control multiple UAVs and sensor networks
  • UAV sensor applications: precision agriculture; pest detection, forestry, mammal species tracking search and rescue; target tracking, the monitoring of the atmosphere; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring, pollution monitoring, micro-climates and land use

Dr. Felipe Gonzalez Toro
Guest Editor
Prof. Dr. Antonios Tsourdos
Co-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 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 monthly 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 1800 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.

Published Papers (31 papers)

View options order results:
result details:
Displaying articles 1-31
Export citation of selected articles as:

Research

Jump to: Review, Other

Open AccessArticle Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments
Sensors 2016, 16(5), 666; doi:10.3390/s16050666
Received: 21 December 2015 / Revised: 3 May 2016 / Accepted: 5 May 2016 / Published: 10 May 2016
PDF Full-text (3190 KB) | HTML Full-text | XML Full-text
Abstract
Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is
[...] Read more.
Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes—A Case Study from the CarboZALF Experimental Area
Sensors 2016, 16(2), 255; doi:10.3390/s16020255
Received: 15 December 2015 / Revised: 12 February 2016 / Accepted: 15 February 2016 / Published: 19 February 2016
Cited by 4 | PDF Full-text (9670 KB) | HTML Full-text | XML Full-text
Abstract
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural
[...] Read more.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation
Sensors 2016, 16(1), 97; doi:10.3390/s16010097
Received: 15 September 2015 / Revised: 5 January 2016 / Accepted: 5 January 2016 / Published: 14 January 2016
Cited by 14 | PDF Full-text (3905 KB) | HTML Full-text | XML Full-text
Abstract
Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to
[...] Read more.
Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers
Sensors 2015, 15(12), 31362-31391; doi:10.3390/s151229861
Received: 28 September 2015 / Revised: 30 November 2015 / Accepted: 2 December 2015 / Published: 12 December 2015
Cited by 8 | PDF Full-text (6411 KB) | HTML Full-text | XML Full-text
Abstract
Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is
[...] Read more.
Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Adaptive Environmental Source Localization and Tracking with Unknown Permittivity and Path Loss Coefficients
Sensors 2015, 15(12), 31125-31141; doi:10.3390/s151229852
Received: 16 August 2015 / Revised: 22 November 2015 / Accepted: 3 December 2015 / Published: 10 December 2015
Cited by 4 | PDF Full-text (820 KB) | HTML Full-text | XML Full-text
Abstract
Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for
[...] Read more.
Accurate signal-source and signal-reflector target localization tasks via mobile sensory units and wireless sensor networks (WSNs), including those for environmental monitoring via sensory UAVs, require precise knowledge of specific signal propagation properties of the environment, which are permittivity and path loss coefficients for the electromagnetic signal case. Thus, accurate estimation of these coefficients has significant importance for the accuracy of location estimates. In this paper, we propose a geometric cooperative technique to instantaneously estimate such coefficients, with details provided for received signal strength (RSS) and time-of-flight (TOF)-based range sensors. The proposed technique is integrated to a recursive least squares (RLS)-based adaptive localization scheme and an adaptive motion control law, to construct adaptive target localization and adaptive target tracking algorithms, respectively, that are robust to uncertainties in aforementioned environmental signal propagation coefficients. The efficiency of the proposed adaptive localization and tracking techniques are both mathematically analysed and verified via simulation experiments. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle UAV Control on the Basis of 3D Landmark Bearing-Only Observations
Sensors 2015, 15(12), 29802-29820; doi:10.3390/s151229768
Received: 15 August 2015 / Revised: 20 October 2015 / Accepted: 10 November 2015 / Published: 27 November 2015
Cited by 8 | PDF Full-text (1029 KB) | HTML Full-text | XML Full-text
Abstract
The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid
[...] Read more.
The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle UAVs Task and Motion Planning in the Presence of Obstacles and Prioritized Targets
Sensors 2015, 15(11), 29734-29764; doi:10.3390/s151129734
Received: 25 June 2015 / Revised: 5 November 2015 / Accepted: 12 November 2015 / Published: 24 November 2015
Cited by 2 | PDF Full-text (902 KB) | HTML Full-text | XML Full-text
Abstract
The intertwined task assignment and motion planning problem of assigning a team of fixed-winged unmanned aerial vehicles to a set of prioritized targets in an environment with obstacles is addressed. It is assumed that the targets’ locations and initial priorities are determined using
[...] Read more.
The intertwined task assignment and motion planning problem of assigning a team of fixed-winged unmanned aerial vehicles to a set of prioritized targets in an environment with obstacles is addressed. It is assumed that the targets’ locations and initial priorities are determined using a network of unattended ground sensors used to detect potential threats at restricted zones. The targets are characterized by a time-varying level of importance, and timing constraints must be fulfilled before a vehicle is allowed to visit a specific target. It is assumed that the vehicles are carrying body-fixed sensors and, thus, are required to approach a designated target while flying straight and level. The fixed-winged aerial vehicles are modeled as Dubins vehicles, i.e., having a constant speed and a minimum turning radius constraint. The investigated integrated problem of task assignment and motion planning is posed in the form of a decision tree, and two search algorithms are proposed: an exhaustive algorithm that improves over run time and provides the minimum cost solution, encoded in the tree, and a greedy algorithm that provides a quick feasible solution. To satisfy the target’s visitation timing constraint, a path elongation motion planning algorithm amidst obstacles is provided. Using simulations, the performance of the algorithms is compared, evaluated and exemplified. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle
Sensors 2015, 15(11), 28472-28489; doi:10.3390/s151128472
Received: 16 September 2015 / Revised: 26 October 2015 / Accepted: 2 November 2015 / Published: 11 November 2015
Cited by 1 | PDF Full-text (2412 KB) | HTML Full-text | XML Full-text
Abstract
The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study,
[...] Read more.
The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (i.e., Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands
Sensors 2015, 15(11), 28287-28313; doi:10.3390/s151128287
Received: 10 July 2015 / Revised: 30 October 2015 / Accepted: 2 November 2015 / Published: 10 November 2015
Cited by 3 | PDF Full-text (6415 KB) | HTML Full-text | XML Full-text
Abstract
Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back
[...] Read more.
Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Open AccessArticle Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery
Sensors 2015, 15(11), 27969-27989; doi:10.3390/s151127969
Received: 29 July 2015 / Revised: 24 October 2015 / Accepted: 28 October 2015 / Published: 4 November 2015
Cited by 10 | PDF Full-text (8992 KB) | HTML Full-text | XML Full-text
Abstract
European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern
[...] Read more.
European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Open AccessArticle Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time
Sensors 2015, 15(11), 27783-27803; doi:10.3390/s151127783
Received: 27 June 2015 / Revised: 17 September 2015 / Accepted: 27 October 2015 / Published: 2 November 2015
Cited by 9 | PDF Full-text (879 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices
[...] Read more.
This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling
Sensors 2015, 15(11), 27493-27524; doi:10.3390/s151127493
Received: 15 September 2015 / Revised: 19 October 2015 / Accepted: 20 October 2015 / Published: 30 October 2015
Cited by 11 | PDF Full-text (9294 KB) | HTML Full-text | XML Full-text
Abstract
The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system
[...] Read more.
The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system consists of an electric-powered helicopter, a high-resolution digital camera and an inertial navigation system. The software of the system includes the in-house programs specifically designed for camera calibration, platform calibration, system integration, on-board data acquisition, flight planning and on-the-job self-calibration. The detailed features of the system are discussed, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The developed system is extensively tested for precise modeling of the challenging environment of an open-pit gravel mine. The accuracy of the results is evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy are assessed. The experiments demonstrated that 1.55 m horizontal and 3.16 m vertical absolute modeling accuracy could be achieved via direct geo-referencing, which was improved to 0.4 cm and 1.7 cm after indirect geo-referencing. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles
Sensors 2015, 15(9), 23805-23846; doi:10.3390/s150923805
Received: 3 June 2015 / Revised: 20 August 2015 / Accepted: 31 August 2015 / Published: 18 September 2015
Cited by 2 | PDF Full-text (4896 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring,
[...] Read more.
Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032 × 778 resolution) and 150 ms outdoors (1280 × 720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Open AccessArticle Dual-Stack Single-Radio Communication Architecture for UAV Acting As a Mobile Node to Collect Data in WSNs
Sensors 2015, 15(9), 23376-23401; doi:10.3390/s150923376
Received: 16 July 2015 / Revised: 3 September 2015 / Accepted: 7 September 2015 / Published: 16 September 2015
Cited by 3 | PDF Full-text (3121 KB) | HTML Full-text | XML Full-text
Abstract
The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzing these works, it
[...] Read more.
The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzing these works, it is apparent that mobile nodes used in such scenarios are typically equipped with at least two different radio interfaces. The present work presents a Dual-Stack Single-Radio Communication Architecture (DSSRCA), which allows a UAV to communicate in a bidirectional manner with a WSN and a Sink node. The proposed architecture was specifically designed to support different network QoS requirements, such as best-effort and more reliable communications, attending both UAV-to-WSN and UAV-to-Sink communications needs. DSSRCA was implemented and tested on a real UAV, as detailed in this paper. This paper also includes a simulation analysis that addresses bandwidth consumption in an environmental monitoring application scenario. It includes an analysis of the data gathering rate that can be achieved considering different UAV flight speeds. Obtained results show the viability of using a single radio transmitter for collecting data from the WSN and forwarding such data to the Sink node. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Open AccessArticle Inspection of Pole-Like Structures Using a Visual-Inertial Aided VTOL Platform with Shared Autonomy
Sensors 2015, 15(9), 22003-22048; doi:10.3390/s150922003
Received: 14 July 2015 / Revised: 24 August 2015 / Accepted: 26 August 2015 / Published: 2 September 2015
Cited by 3 | PDF Full-text (8988 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an algorithm and a system for vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures such as light and power distribution poles is a difficult task that is time-consuming, dangerous
[...] Read more.
This paper presents an algorithm and a system for vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures such as light and power distribution poles is a difficult task that is time-consuming, dangerous and expensive. Recently, micro VTOL platforms (i.e., quad-, hexa- and octa-rotors) have been rapidly gaining interest in research, military and even public domains. The unmanned, low-cost and VTOL properties of these platforms make them ideal for situations where inspection would otherwise be time-consuming and/or hazardous to humans. There are, however, challenges involved with developing such an inspection system, for example flying in close proximity to a target while maintaining a fixed stand-off distance from it, being immune to wind gusts and exchanging useful information with the remote user. To overcome these challenges, we require accurate and high-update rate state estimation and high performance controllers to be implemented onboard the vehicle. Ease of control and a live video feed are required for the human operator. We demonstrate a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. Two approaches are presented: Position-Based Visual Servoing (PBVS) using an Extended Kalman Filter (EKF) and estimator-free Image-Based Visual Servoing (IBVS). Both use monocular visual, inertia, and sonar data, allowing the approaches to be applied for indoor or GPS-impaired environments. We extensively compare the performances of PBVS and IBVS in terms of accuracy, robustness and computational costs. Results from simulations Sensors 2015, 15 22004 and indoor/outdoor (day and night) flight experiments demonstrate the system is able to successfully inspect and circumnavigate a vertical pole. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Towards the Development of a Low Cost Airborne Sensing System to Monitor Dust Particles after Blasting at Open-Pit Mine Sites
Sensors 2015, 15(8), 19667-19687; doi:10.3390/s150819667
Received: 26 May 2015 / Revised: 31 July 2015 / Accepted: 6 August 2015 / Published: 12 August 2015
Cited by 7 | PDF Full-text (11403 KB) | HTML Full-text | XML Full-text | Correction
Abstract
Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers
[...] Read more.
Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation
Sensors 2015, 15(8), 18334-18359; doi:10.3390/s150818334
Received: 4 May 2015 / Revised: 15 July 2015 / Accepted: 17 July 2015 / Published: 28 July 2015
Cited by 1 | PDF Full-text (1800 KB) | HTML Full-text | XML Full-text
Abstract
This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class,
[...] Read more.
This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle A Multispectral Image Creating Method for a New Airborne Four-Camera System with Different Bandpass Filters
Sensors 2015, 15(7), 17453-17469; doi:10.3390/s150717453
Received: 28 April 2015 / Revised: 5 July 2015 / Accepted: 6 July 2015 / Published: 20 July 2015
Cited by 1 | PDF Full-text (4560 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and
[...] Read more.
This paper describes an airborne high resolution four-camera multispectral system which mainly consists of four identical monochrome cameras equipped with four interchangeable bandpass filters. For this multispectral system, an automatic multispectral data composing method was proposed. The homography registration model was chosen, and the scale-invariant feature transform (SIFT) and random sample consensus (RANSAC) were used to generate matching points. For the difficult registration problem between visible band images and near-infrared band images in cases lacking manmade objects, we presented an effective method based on the structural characteristics of the system. Experiments show that our method can acquire high quality multispectral images and the band-to-band alignment error of the composed multiple spectral images is less than 2.5 pixels. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing
Sensors 2015, 15(7), 17397-17419; doi:10.3390/s150717397
Received: 5 June 2015 / Revised: 13 July 2015 / Accepted: 14 July 2015 / Published: 17 July 2015
Cited by 3 | PDF Full-text (7494 KB) | HTML Full-text | XML Full-text
Abstract
To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the
[...] Read more.
To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture
Sensors 2015, 15(7), 16688-16709; doi:10.3390/s150716688
Received: 15 May 2015 / Revised: 25 June 2015 / Accepted: 3 July 2015 / Published: 10 July 2015
Cited by 6 | PDF Full-text (3240 KB) | HTML Full-text | XML Full-text
Abstract
Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying
[...] Read more.
Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications
Sensors 2015, 15(7), 15717-15737; doi:10.3390/s150715717
Received: 14 May 2015 / Revised: 11 June 2015 / Accepted: 23 June 2015 / Published: 2 July 2015
Cited by 11 | PDF Full-text (5481 KB) | HTML Full-text | XML Full-text
Abstract
Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation
[...] Read more.
Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author’s group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle UAV-Based Photogrammetry and Integrated Technologies for Architectural Applications—Methodological Strategies for the After-Quake Survey of Vertical Structures in Mantua (Italy)
Sensors 2015, 15(7), 15520-15539; doi:10.3390/s150715520
Received: 31 March 2015 / Revised: 23 June 2015 / Accepted: 24 June 2015 / Published: 30 June 2015
Cited by 10 | PDF Full-text (3065 KB) | HTML Full-text | XML Full-text
Abstract
This paper examines the survey of tall buildings in an emergency context like in the case of post-seismic events. The after-earthquake survey has to guarantee time-savings, high precision and security during the operational stages. The main goal is to optimize the application of
[...] Read more.
This paper examines the survey of tall buildings in an emergency context like in the case of post-seismic events. The after-earthquake survey has to guarantee time-savings, high precision and security during the operational stages. The main goal is to optimize the application of methodologies based on acquisition and automatic elaborations of photogrammetric data even with the use of Unmanned Aerial Vehicle (UAV) systems in order to provide fast and low cost operations. The suggested methods integrate new technologies with commonly used technologies like TLS and topographic acquisition. The value of the photogrammetric application is demonstrated by a test case, based on the comparison of acquisition, calibration and 3D modeling results in case of use of a laser scanner, metric camera and amateur reflex camera. The test would help us to demonstrate the efficiency of image based methods in the acquisition of complex architecture. The case study is Santa Barbara Bell tower in Mantua. The applied survey solution allows a complete 3D database of the complex architectural structure to be obtained for the extraction of all the information needed for significant intervention. This demonstrates the applicability of the photogrammetry using UAV for the survey of vertical structures, complex buildings and difficult accessible architectural parts, providing high precision results. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications
Sensors 2015, 15(6), 13874-13898; doi:10.3390/s150613874
Received: 18 April 2015 / Revised: 1 June 2015 / Accepted: 4 June 2015 / Published: 12 June 2015
Cited by 3 | PDF Full-text (1349 KB) | HTML Full-text | XML Full-text
Abstract
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging
[...] Read more.
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images
Sensors 2015, 15(5), 12053-12079; doi:10.3390/s150512053
Received: 27 March 2015 / Accepted: 20 May 2015 / Published: 22 May 2015
Cited by 2 | PDF Full-text (2019 KB) | HTML Full-text | XML Full-text
Abstract
In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the
[...] Read more.
In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method
Sensors 2015, 15(5), 10948-10972; doi:10.3390/s150510948
Received: 15 October 2014 / Revised: 30 April 2015 / Accepted: 4 May 2015 / Published: 11 May 2015
Cited by 2 | PDF Full-text (3193 KB) | HTML Full-text | XML Full-text
Abstract
An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by
[...] Read more.
An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle New Calibration Method Using Low Cost MEM IMUs to Verify the Performance of UAV-Borne MMS Payloads
Sensors 2015, 15(3), 6560-6585; doi:10.3390/s150306560
Received: 9 January 2015 / Revised: 9 January 2015 / Accepted: 6 March 2015 / Published: 19 March 2015
Cited by 3 | PDF Full-text (8337 KB) | HTML Full-text | XML Full-text
Abstract
Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV)-borne mobile mapping system (MMS) can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility
[...] Read more.
Spatial information plays a critical role in remote sensing and mapping applications such as environment surveying and disaster monitoring. An Unmanned Aerial Vehicle (UAV)-borne mobile mapping system (MMS) can accomplish rapid spatial information acquisition under limited sky conditions with better mobility and flexibility than other means. This study proposes a long endurance Direct Geo-referencing (DG)-based fixed-wing UAV photogrammetric platform and two DG modules that each use different commercial Micro-Electro Mechanical Systems’ (MEMS) tactical grade Inertial Measurement Units (IMUs). Furthermore, this study develops a novel kinematic calibration method which includes lever arms, boresight angles and camera shutter delay to improve positioning accuracy. The new calibration method is then compared with the traditional calibration approach. The results show that the accuracy of the DG can be significantly improved by flying at a lower altitude using the new higher specification hardware. The new proposed method improves the accuracy of DG by about 20%. The preliminary results show that two-dimensional (2D) horizontal DG positioning accuracy is around 5.8 m at a flight height of 300 m using the newly designed tactical grade integrated Positioning and Orientation System (POS). The positioning accuracy in three-dimensions (3D) is less than 8 m. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images
Sensors 2015, 15(3), 6633-6651; doi:10.3390/s150306633
Received: 9 December 2014 / Revised: 13 February 2015 / Accepted: 10 March 2015 / Published: 19 March 2015
Cited by 1 | PDF Full-text (21391 KB) | HTML Full-text | XML Full-text
Abstract
Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the
[...] Read more.
Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses
Sensors 2015, 15(2), 3334-3350; doi:10.3390/s150203334
Received: 26 September 2014 / Revised: 19 January 2015 / Accepted: 26 January 2015 / Published: 2 February 2015
Cited by 17 | PDF Full-text (3902 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking
[...] Read more.
This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Open AccessArticle Cooperative Surveillance and Pursuit Using Unmanned Aerial Vehicles and Unattended Ground Sensors
Sensors 2015, 15(1), 1365-1388; doi:10.3390/s150101365
Received: 17 October 2014 / Accepted: 4 January 2015 / Published: 13 January 2015
Cited by 10 | PDF Full-text (810 KB) | HTML Full-text | XML Full-text
Abstract
This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors
[...] Read more.
This paper considers the problem of path planning for a team of unmanned aerial vehicles performing surveillance near a friendly base. The unmanned aerial vehicles do not possess sensors with automated target recognition capability and, thus, rely on communicating with unattended ground sensors placed on roads to detect and image potential intruders. The problem is motivated by persistent intelligence, surveillance, reconnaissance and base defense missions. The problem is formulated and shown to be intractable. A heuristic algorithm to coordinate the unmanned aerial vehicles during surveillance and pursuit is presented. Revisit deadlines are used to schedule the vehicles’ paths nominally. The algorithm uses detections from the sensors to predict intruders’ locations and selects the vehicles’ paths by minimizing a linear combination of missed deadlines and the probability of not intercepting intruders. An analysis of the algorithm’s completeness and complexity is then provided. The effectiveness of the heuristic is illustrated through simulations in a variety of scenarios. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Figures

Review

Jump to: Research, Other

Open AccessReview Vision and Control for UAVs: A Survey of General Methods and of Inexpensive Platforms for Infrastructure Inspection
Sensors 2015, 15(7), 14887-14916; doi:10.3390/s150714887
Received: 27 December 2014 / Revised: 20 May 2015 / Accepted: 26 May 2015 / Published: 25 June 2015
Cited by 9 | PDF Full-text (928 KB) | HTML Full-text | XML Full-text
Abstract
Unmanned aerial vehicles (UAVs) have gained significant attention in recent years. Low-cost platforms using inexpensive sensor payloads have been shown to provide satisfactory flight and navigation capabilities. In this report, we survey vision and control methods that can be applied to low-cost UAVs,
[...] Read more.
Unmanned aerial vehicles (UAVs) have gained significant attention in recent years. Low-cost platforms using inexpensive sensor payloads have been shown to provide satisfactory flight and navigation capabilities. In this report, we survey vision and control methods that can be applied to low-cost UAVs, and we list some popular inexpensive platforms and application fields where they are useful. We also highlight the sensor suites used where this information is available. We overview, among others, feature detection and tracking, optical flow and visual servoing, low-level stabilization and high-level planning methods. We then list popular low-cost UAVs, selecting mainly quadrotors. We discuss applications, restricting our focus to the field of infrastructure inspection. Finally, as an example, we formulate two use-cases for railway inspection, a less explored application field, and illustrate the usage of the vision and control techniques reviewed by selecting appropriate ones to tackle these use-cases. To select vision methods, we run a thorough set of experimental evaluations. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)

Other

Jump to: Research, Review

Open AccessCorrection Correction: Alvarado, M., et al. Towards the Development of a Low Cost Airborne Sensing System to Monitor Dust Particles after Blasting at Open-Pit Mine Sites. Sensors 2015, 15, 19667–19687
Sensors 2016, 16(7), 1028; doi:10.3390/s16071028
Received: 13 June 2016 / Accepted: 14 June 2016 / Published: 5 July 2016
PDF Full-text (854 KB) | HTML Full-text | XML Full-text
Abstract The author wishes to change Figure 1 and Figure 3 from his paper published in Sensors [1], doi:10.3390/s150819667, website: http://www.mdpi.com/1424-8220/15/8/19667 for Figures 1 and 2 presented in this ‘Correction’.[...] Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Type of Paper: Article
Title: A Real-Time Multi-Camera Vision System for Small UAV Sense and Avoid
Authors: Akos Zarandy, Mate Nemeth, Tamás Zsedrovits, Istvan Gozse, Peter Bauer, Balint Vanek
Affiliations: MTA SZTAKI, Budapest, Hungary
Abstract: A real-time vision system with multiple cameras are developed for UAV sense and avoid and visual navigation for fixed-wing small or medium sized aircrafts. The embedded vision system simultaneously acquires images by using five cameras, stores, and evaluates the visual data with an FPGA based multi-core processor system. The system was designed to fulfill the strict size, power, and weight requirements arising from UAV on-board restrictions. The hardware components are coupled with an intelligent autopilot system which guides the UAV respecting the image system field-of-view limitations. The image system intruder information are passed to a collision avoidance algorithm hosted on-board the autopilot to automatically execute avoidance maneuvers. The overall system is demonstrated with in-field tests.

Type of Paper: Article
Title: UAVs Task and Motion Planning in the Presence of Obstacles and Prioritized Targets
Authors: Yoav Gottlieb and Tal Shima
Affiliation: Israel Institute of Technology, Haifa, Israel; E-Mail: tal.shima@technion.ac.il
Abstract: This paper addresses the intertwined task assignment and motion planning problem of assigning a heterogeneous team of unmanned aerial vehicles to perform multiple tasks on heterogeneous prioritized targets in an environment with obstacles. In the problem of interest we assume that the targets location and initial priority are determined using a network of unattended ground sensors used to detect potential threats at restricted zones. The targets are characterized by a time varying level of importance and priority, and by different tasks required to be performed at each target in a specific order. In order to generate feasible vehicles’ trajectories, the obstacles scattered in the environment are taken into account and since the vehicles have a minimum turn radius constraints they are modeled as a Dubins vehicle. The time varying priority issue is addressed by incorporating the vehicles’ feasible path length which represents the vehicles’ response time and the targets’ properties as part of the problem formulation. The investigated (integrated) problem is posed in the form of a decision tree and two algorithms are proposed. An exhaustive search algorithm which improves over run time and provides the best solution encoded in the decision tree, and a greedy algorithm that provides a quick feasible solution. Using sample runs and Monte Carlo simulations, the performance of the algorithms is compared and evaluated, and the problem parameters are investigated.

Type of Paper: Article
Title: Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images.
Authors: Inhye Yoon, Jaehoen Jeong, Doochun Seo, and Joonki Paik
Affiliations: Chung-Ang University and Korea Aerospace Research Insitute, Korea
Abstract: Since incoming light to a remote sensing platform is scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Restoration of the original clear image from its hazy version is an important task in recovering visual information from various remote sensing platforms including aircrafts and satellites. This paper presents a spatially adaptive dehazing algorithm that merges color histograms based on the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed algorithm consists of three steps: i) image segmentation based on geometric classes, ii) generation of the context-adaptive transmission map, and iii) intensity transformation for restoring a hazy remote sensing image. Major contribution of the research is a novel hazy remote sensing image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

Type of Paper: Article
Title: Free Space Laser Communications Based On Orthogonal Frequency Shift Keying (OFSK)
Authors: Saleh Faruque and Mohammad Rakibul Alam
Affiliations: Department of Electrical Engineering, University of North Dakota, Grand Forks, ND 58202-7165, USA; Phone: (701) 777 – 4428; Fax: (701) 777 – 5253; E-Mail: saleh.faruque@engr.und.edu
Abstract: Orthogonal Frequency Shift Keying (OFSK) is proposed for free space laser communication. OFSK is a coded modulation technique where the carrier Frequency changes in discrete levels, in accordance with the input orthogonal signal. In the proposed technique, the input digital signal is mapped into a block of bi-orthogonal code. When a block of data needs to be transmitted, the corresponding block of bi-orthogonal code is transmitted by means of Frequency Shift Keying (OFSK). Upon receiving, the receiver synchronizes, detects and corrects errors by means of code correlation. The proposed coded modulation technique offers synchronization and error control coding in the same platform. The detailed design and bit error performance will be presented in the final manuscript.

Type of Paper: Article
Title:
Formation Flight of Multiple UAVs Using onboard Information Sharing
Authors: Chulwoo Park, Namhoon Cho, Kyunghyun Lee and Youdan Kim
Affiliations: Department of Mechanical & Aerospace Engineering, Seoul National University, Daehak-dong, Gwanak-gu, Seoul, Korea
Abstract: To perform surveillance and monitoring multiple targets, formation flight of multiple UAVs is required. Various studies have been performed for the development of formation flight guidance and control system of multiple UAVs using a numerical simulation or ground robots. However, a numerical simulation does not consider many practical problems such as intercommunication among UAVs, and ground robot experiment does not reflect the dynamics of UAV. Therefore, the results of these studies have the limitation for the implementation of the formation flight algorithms.
In this study, the onboard information sharing scheme and the formation flight algorithm of the multiple UAVs are proposed. Communication delay of RF telemetry is analyzed for the implementation of onboard information sharing scheme. Utilizing the information sharing scheme, formation flight algorithms of multiple UAVs including loitering and triangular formation are designed. Hardware system including avionics and airframe is constructed for the multi-UAV platform. Numerical simulation of multiple UAVs is performed to demonstrate the reconfiguration function of the multiple UAVs. Finally, flight test is conducted to verify the performance of the multiple UAVs formation flight system.

Journal Contact

MDPI AG
Sensors Editorial Office
St. Alban-Anlage 66, 4052 Basel, Switzerland
E-Mail: 
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18
Editorial Board
Contact Details Submit to Sensors Edit a special issue Review for Sensors
loading...
Back to Top