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Drones
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Drones in the Wild
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Drones in the Wild

A special issue of Drones (ISSN 2504-446X). This special issue belongs to the section "Drones in Ecology".

Deadline for manuscript submissions: 13 July 2024 | Viewed by 15469

Special Issue Editors

Prof. Dr. Sophie F. Armanini

E-Mail Website
Guest Editor
Department of Aerospace and Geodesy, TUM School of Engineering and Design, Technical University of Munich, 85748 Munich, Germany
Interests: unmanned aerial vehicles; system identification; flight dynamics; flight control; bioinspired aerial vehicles; VTOL configurations
Special Issues, Collections and Topics in MDPI journals
Dr. Raphael Zufferey

E-Mail Website
Guest Editor
LIS-IMT-STI, Room MED1 1126, Station 9, EPFL, 1015 Lausanne, Switzerland
Interests: aerial-aquatic vehicles with flapping-wing technology

Special Issue Information

Dear Colleagues,

Thanks to rapid technological developments in wide-ranging fields spanning from instrumentation and sensing, through control and navigation algorithms, all the way to new materials and manufacturing methods, unmanned aerial vehicle (UAV) research is progressing swiftly. At present, UAVs can be highly sophisticated and are already being used in numerous different sectors. Next to traditional photography and delivery applications, UAVs are increasingly being deployed for tasks such as search and rescue operations, disaster response, damage assessment, etc. Additionally, such vehicles also play an increasingly important role in supporting research efforts in fields such as surveying, mapping, marine biology, climate research or wildlife monitoring.

Many of the applications mentioned require UAVs to operate successfully “in the wild”, that is, in challenging outdoor environments. Environments such as dense forests, mountainous or maritime regions, arctic regions, areas exposed to extreme atmospheric conditions, etc., require a high degree of robustness, safety and versatility. UAVs may need to react reliably to rapidly changing circumstances, navigate with minimal sensing, withstand strong perturbations, maneuver in severely restricted spaces, or operate safely in the vicinity of critical human-built infrastructure or delicate flora and fauna. This Special Issue focuses on the development, evaluation and testing of UAVs capable of operating in challenging, realistic outdoor environments, with a particular emphasis on natural environments. Key research focuses will include the following:

  • Operations in cluttered spaces;
  • Rapid navigation in unknown spaces;
  • Novel, unconventional designs allowing new applications;
  • Hybrid and multi-modal drones;
  • Energy-efficient design, mission planning and control;
  • Swarming and collaborative tasks;
  • Highly autonomous mission execution;
  • Planning and navigation in complex dynamic environments;
  • Vision-based control, minimal sensing;
  • Navigation in dim or unlit environments;
  • Safe/soft drones that cause no damage;
  • Demonstration of new applications.

Prof. Dr. Sophie F. Armanini
Dr. Raphael Zufferey
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. Drones 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 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

  • operations in cluttered spaces
  • rapid navigation in unknown spaces
  • novel, unconventional designs allowing new applications
  • hybrid and multi-modal drones
  • energy-efficient design, mission planning and control
  • swarming and collaborative tasks
  • highly autonomous mission execution
  • planning and navigation in complex dynamic environments
  • vision-based control, minimal sensing
  • navigation in dim or unlit environments
  • safe/soft drones that cause no damage
  • demonstration of new applications

Published Papers (7 papers)

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Research

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20 pages, 6913 KiB  
Article
The Mamba: A Suspended Manipulator to Sample Plants in Cliff Environments
by Hughes La Vigne, Guillaume Charron, David Rancourt and Alexis Lussier Desbiens
Drones 2024, 8(4), 139; https://doi.org/10.3390/drones8040139 - 03 Apr 2024
Viewed by 688
Abstract
Conservation efforts in cliff habitats pose unique challenges due to their inaccessibility, limiting the study and protection of rare endemic species. This project introduces a novel approach utilizing aerial manipulation through a suspended manipulator attached with a cable under a drone to address [...] Read more.
Conservation efforts in cliff habitats pose unique challenges due to their inaccessibility, limiting the study and protection of rare endemic species. This project introduces a novel approach utilizing aerial manipulation through a suspended manipulator attached with a cable under a drone to address these challenges. Unlike existing solutions, the Mamba provides a horizontal reach up to 8 m to approach cliffs while keeping the drone at a safe distance. The system includes a model-based control system relying solely on an inertial measurement unit (IMU), reducing sensor requirements and computing power to minimize overall system mass. This article presents novel contributions such as a double pendulum dynamic modeling approach and the development and evaluation of a precise control system for sampling operations. Indoor and outdoor tests demonstrate the effectiveness of the suspended aerial manipulator in real-world environments allowing the collection of 55 samples from 28 different species. This research signifies a significant step toward enhancing the efficiency and safety of conservation efforts in challenging cliff habitats. Full article
(This article belongs to the Special Issue Drones in the Wild)
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23 pages, 569 KiB  
Article
Firefighting Drone Configuration and Scheduling for Wildfire Based on Loss Estimation and Minimization
by Rong-Yu Wu, Xi-Cheng Xie and Yu-Jun Zheng
Drones 2024, 8(1), 17; https://doi.org/10.3390/drones8010017 - 10 Jan 2024
Viewed by 1690
Abstract
Drones have been increasingly used in firefighting to improve the response speed and reduce the dangers to human firefighters. However, few studies simultaneously consider fire spread prediction, drone scheduling, and the configuration of supporting staff and supplies. This paper presents a mathematical model [...] Read more.
Drones have been increasingly used in firefighting to improve the response speed and reduce the dangers to human firefighters. However, few studies simultaneously consider fire spread prediction, drone scheduling, and the configuration of supporting staff and supplies. This paper presents a mathematical model that estimates wildfire spread and economic losses simultaneously. The model can also help us to determine the minimum number of firefighting drones in preparation for wildfire in a given wild area. Next, given a limited number of firefighting drones, we propose a method for scheduling the drones in response to wildfire occurrence to minimize the expected loss using metaheuristic optimization. We demonstrate the performance advantages of water wave optimization over a set of other metaheuristic optimization algorithms on 72 test instances simulated on selected suburb areas of Hangzhou, China. Based on the optimization results, we can pre-define a comprehensive plan of scheduling firefighting drone and configuring support staff in response to a set of scenarios of wildfire occurrences, significantly improving the emergency response efficiency and reducing the potential losses. Full article
(This article belongs to the Special Issue Drones in the Wild)
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23 pages, 4503 KiB  
Article
Evaluation of an Innovative Rosette Flight Plan Design for Wildlife Aerial Surveys with UAS
by Julie Linchant, Philippe Lejeune, Samuel Quevauvillers, Cédric Vermeulen, Yves Brostaux, Simon Lhoest and Adrien Michez
Drones 2023, 7(3), 208; https://doi.org/10.3390/drones7030208 - 17 Mar 2023
Cited by 1 | Viewed by 1315
Abstract
(1) Regular wildlife abundance surveys are a key conservation tool. Manned aircraft flying transects often remain the best alternative for counting large ungulates. Drones have cheaper and safer logistics, however their range is generally too short for large-scale application of the traditional method. [...] Read more.
(1) Regular wildlife abundance surveys are a key conservation tool. Manned aircraft flying transects often remain the best alternative for counting large ungulates. Drones have cheaper and safer logistics, however their range is generally too short for large-scale application of the traditional method. Our paper investigates an innovative rosette flight plan for wildlife census, and evaluates relevance of this sampling protocol by comparing its statistical performance with transects, based on numerical simulations. (2) The UAS flight plan consisted in two rosettes of 6 triangular “petals” spread across the survey area, for a theoretical sampling rate of 2.95%, as opposed to a 20.04% classic sampling protocol with systematic transects. We tested the logistics of our survey design in Garamba National Park. We then modeled theoretical population distributions for both antelopes and buffaloes. We calculated animal densities in the simulated footprints of the theoretical rosette and transect flight plans. We also tested aggregating results for 2, 3 and 4 repetitions of the same rosette flight plan to increase the sampling rate. (3) Simulation results showed that the coefficient of variation associated with density estimates decreases with the number of repetitions of the rosette flight plan, and aggregating four repetitions is enough to give antelope densities with acceptable accuracy and precision while staying at a lower sampling rate. Buffalo densities displayed much higher variability and it shows the significant impact of gregariousness on density estimate accuracy and precision. (4) The method was found to be inappropriate for highly aggregative species but efficient for species that disperse widely and more randomly in their environment. Logistics required to perform a full survey in the field remain time- and resources-intensive. Therefore, we recommend it for remote parks facing difficulties to organize manned aerial counts. Lower costs and developments such as solar UASs offer interesting future perspectives. Full article
(This article belongs to the Special Issue Drones in the Wild)
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26 pages, 16651 KiB  
Article
Oxpecker: A Tethered UAV for Inspection of Stone-Mine Pillars
by Bernardo Martinez Rocamora, Jr., Rogério R. Lima, Kieren Samarakoon, Jeremy Rathjen, Jason N. Gross and Guilherme A. S. Pereira
Drones 2023, 7(2), 73; https://doi.org/10.3390/drones7020073 - 19 Jan 2023
Cited by 11 | Viewed by 3924
Abstract
This paper presents a state-of-the-art tethered unmanned aerial vehicle (TUAV) for structural integrity assessment of underground stone mine pillars. The TUAV, powered by its tether, works in tandem with an unmanned ground vehicle (UGV) that hosts the TUAV batteries, a self-leveled landing platform, [...] Read more.
This paper presents a state-of-the-art tethered unmanned aerial vehicle (TUAV) for structural integrity assessment of underground stone mine pillars. The TUAV, powered by its tether, works in tandem with an unmanned ground vehicle (UGV) that hosts the TUAV batteries, a self-leveled landing platform, and the tether management system. The UGV and the TUAV were named Rhino and Oxpecker, respectively, given that the TUAV stays landed on the UGV while the ensemble moves inside a mine. The mission of Oxpecker is to create, using a LiDAR sensor, 3D maps of the mine pillars to support time-lapse hazard mapping and time-dependent pillar degradation analysis. Given the height of the pillars (7–12 m), this task cannot be executed by Rhino alone. This paper describes the drone’s hardware and software. The hardware includes the tether management system, designed to control the tension of the tether, and the tether perception system, which provides information that can be used for localization and landing in global navigation satellite systems (GNSS)-denied environments. The vehicle’s software is based on a state machine that controls the several phases of a mission (i.e., takeoff, inspection, and landing) by coordinating drone motion with the tethering system. The paper also describes and evaluates our approach for tether-based landing and autonomous 3D mapping of pillars. We show experiments that illustrate and validate our system in laboratories and underground mines. Full article
(This article belongs to the Special Issue Drones in the Wild)
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34 pages, 4955 KiB  
Article
Parallel Multiobjective Multiverse Optimizer for Path Planning of Unmanned Aerial Vehicles in a Dynamic Environment with Moving Obstacles
by Raja Jarray, Soufiene Bouallègue, Hegazy Rezk and Mujahed Al-Dhaifallah
Drones 2022, 6(12), 385; https://doi.org/10.3390/drones6120385 - 28 Nov 2022
Cited by 9 | Viewed by 2100
Abstract
Path planning with collision avoidance for unmanned aerial vehicles (UAVs) in environments with moving obstacles is a complex process of navigation, often considered a hard optimization problem. Ordinary resolution algorithms may fail to provide flyable and collision-free paths under the time-consumption constraints required [...] Read more.
Path planning with collision avoidance for unmanned aerial vehicles (UAVs) in environments with moving obstacles is a complex process of navigation, often considered a hard optimization problem. Ordinary resolution algorithms may fail to provide flyable and collision-free paths under the time-consumption constraints required by the dynamic 3D environment. In this paper, a new parallel multiobjective multiverse optimizer (PMOMVO) is proposed and successfully applied to deal with the increased computation time of the UAV path planning problem in dynamic 3D environments. Collision constraints with moving obstacles and narrow pass zones were established based on a mathematical characterization of any intersection with lines connecting two consecutive drones’ positions. For the implementation, a multicore central processing unit (CPU) architecture was proposed according to the concept of master–slave processing parallelization. Each subswarm of the entire PMOMVO population was granted to a corresponding slave, and representative solutions were selected and shared with the master core. Slaves sent their local Pareto fronts to the CPU core representing the master that merged the received set of nondominated solutions and built a global Pareto front. Demonstrative results and nonparametric ANOVA statistical analyses were carried out to show the effectiveness and superiority of the proposed PMOMVO algorithm compared to other homologous, multiobjective metaheuristics. Full article
(This article belongs to the Special Issue Drones in the Wild)
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15 pages, 72577 KiB  
Article
Lightweight Multipurpose Three-Arm Aerial Manipulator Systems for UAV Adaptive Leveling after Landing and Overhead Docking
by Hannibal Paul, Ricardo Rosales Martinez, Robert Ladig and Kazuhiro Shimonomura
Drones 2022, 6(12), 380; https://doi.org/10.3390/drones6120380 - 27 Nov 2022
Cited by 6 | Viewed by 3414
Abstract
In aerial manipulation, the position and size of a manipulator attached to an aerial robot defines its workspace relative to the robot. However, the working region of a multipurpose robot is determined by its task and is not always predictable prior to deployment. [...] Read more.
In aerial manipulation, the position and size of a manipulator attached to an aerial robot defines its workspace relative to the robot. However, the working region of a multipurpose robot is determined by its task and is not always predictable prior to deployment. In this paper, the development of a multipurpose manipulator design for a three-armed UAV with a large workspace around its airframe is proposed. The manipulator is designed to be lightweight and slim in order to not disrupt the UAV during in-flight manipulator movements. In the experiments, we demonstrate various advanced and critical tasks required of an aerial robot when deployed in a remote environment, focusing on the landing and docking tasks, which is accomplished using a single manipulator system. Full article
(This article belongs to the Special Issue Drones in the Wild)
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14 pages, 1556 KiB  
Project Report
Efficacy of Mapping Grassland Vegetation for Land Managers and Wildlife Researchers Using sUAS
by John R. O’Connell, Alex Glass, Caleb S. Crawford and Michael W. Eichholz
Drones 2022, 6(11), 318; https://doi.org/10.3390/drones6110318 - 26 Oct 2022
Viewed by 1313
Abstract
The proliferation of small unmanned aerial systems (sUAS) is making very high-resolution imagery attainable for vegetation classifications, potentially allowing land managers to monitor vegetation in response to management or wildlife activities and offering researchers opportunities to further examine relationships among wildlife species and [...] Read more.
The proliferation of small unmanned aerial systems (sUAS) is making very high-resolution imagery attainable for vegetation classifications, potentially allowing land managers to monitor vegetation in response to management or wildlife activities and offering researchers opportunities to further examine relationships among wildlife species and their habitats. The broad adoption of sUAS for remote sensing among these groups may be hampered by complex coding, expensive equipment, and time-consuming protocols. We used a consumer sUAS, semiautomated flight planning software, and graphical user interface GIS software to classify grassland vegetation with the aim of providing a user-friendly framework for managers and ecological researchers. We compared the overall accuracy from classifications using this sUAS imagery (89.22%) to classifications using freely available National Agriculture Imagery Program imagery (76.25%) to inform decisions about cost and accuracy. We also compared overall accuracy between manual classification (89.22%) and random forest classification (69.26%) to aid with similar decisions. Finally, we examined the impact of resolution and the addition of a canopy height model on classification accuracy, obtaining mixed results. Our findings can help new users make informed choices about imagery sources and methodologies, and our protocols can serve as a template for those groups wanting to perform similar vegetation classifications on grassland sites without the need for survey-grade equipment or coding. These should help more land managers and researchers obtain appropriate grassland vegetation classifications for their projects within their budgetary and logistical constraints. Full article
(This article belongs to the Special Issue Drones in the Wild)
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