Fuel Cells for Unmanned Aerial Vehicles

This study empirically evaluated the effects of unmanned aerial vehicles (UAVs) applications and acceptable cost on intention to use UAVs in maritime shipping contexts. Factor analysis was employed to identify key UAVs applications (i.e. pollution forensics, supervision and service, search and rescue, humanitarian and emergency delivery, and safety and security), acceptable UAV cost, and intention to use UAVs. Survey data were collected from 201 respondents working for a maritime port corporation, shipping company, agency, and stevedoring company, and then hierarchical regression analysis was conducted to test research hypotheses and examine the effects of UAVs applications and acceptable cost dimensions on intention to use UAVs. The results suggested that the pollution forensics, supervision and service, search and rescue, humanitarian and emergency delivery, and safety and security dimensions positively affected intention to use UAVs. The study findings also revealed negative associations among seniority, turnover, and intention to use UAVs. Theoretical contributions and managerial implications are proposed to assist maritime port bureaus, corporations, and operating practice design in remaining competitive and efficient.

<p>In this paper, the performance of a 5-level cascaded H-bridge inverter in unmanned aerial vehicle (UAV) applications is analized to identify, at the converter design stage, the better device choice depending on different UAV operation scenarios. Considering that regardless of the specific application there are some typical operations, such as take-off, climb, land, cruise, and potential recurring climbs and descents, the results can support the choice by considering the typical working conditions of the specific application where the UAV would be used. The results have been obtained by simulating the H-bridge inverter considering the circuit models of insulated-gate bipolar transistors (IGBTs), GaN high-electron-mobility transistors (HEMTs), and Si and SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) provided by manufacturers. The study has highlighted that the choice of the device depends on the UAV usage, switching frequency, and load conditions. More specifically, considering the typical devices and systems costs in the case of a selective harmonic elimination procedure operating at the fundamental switching frequency, the Si devices should be used. Moreover, the preference for using IGBTs or Si MOSFETs depends on the typical working conditions of the UAV application. In the case of phase-shift carrier modulation technique, at 4 kHz the MOSFET is the best device and the choice between Si and SiC devices depends on the UAV application's main operation scenarios. At 20 kHz the SiC MOSFET is the best device, while at higher frequencies the GaN HEMT cost should be faced to take advantage of its best performance.</p>

As part of our recent research to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicle (UAV) applications, we investigated the potential of carrier-phase Global Navigation Satellite System (GNSS) for attitude determination and control of small size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro- Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD)sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.

This study presents an experimental investigation of blade-shaped riblets for drag reduction in unmanned aerial vehicle (UAV) applications. UAVs have gained significant attention since they can perform various missions, including surveillance, reconnaissance, and package delivery. However, their aerodynamic performance, specifically the high drag associated with their exposed surfaces, remains a key challenge for enhancing their efficiency and extending their flight endurance. To address this issue, riblet geometries are proposed as a potential solution, which can reduce the turbulent skin friction drag by up to 8%. The experimental investigation involves wind tunnel testing of blade-shaped riblets, with various spacing-to-height (s/h) ratios and constant groove cross-sectional area (Ag). The riblets are designed for application on the wing, empennage, and fuselage surfaces of a UAV. The investigations are performed on a flat plate for various flow conditions, including different freestream velocities, to evaluate the drag reduction effectiveness of the riblet configuration. The drag force is measured using a force balance system and flow visualization techniques are employed to assess the position where the boundary layer has transitioned to fully turbulent. The results demonstrate the drag-reducing effect of blade-shaped and trapezoidal riblets and the different performances observed for the various s/h ratios. The cases with s/h=1 result in the smallest drag coefficients, while the cases with s/h=2 have significantly increased drag values, compared to the smooth flat plate, due to the increased wetted surface area. These findings highlight the potential of riblets as an effective drag-reduction technique for UAV applications, enabling increased endurance and/or enhanced payload capacity.

Abstract. Commercial pesticide applications using small-scale Unmanned Aerial Vehicles (UAVs) is now well established as a crop protection method in China and East Asia. The brief but intense evolution and adoption of drone technology has been disruptive in the China crop protection industry. Users are unprepared on how to choose quality drones from such a wide array of models and configurations with unstandardized spray systems and lack of guidance on best spray practices to achieve effective crop protection. This presents challenges to correct and safe application of pesticides with drone applications, particularly at low or ultra-low water volumes. Most concerning is how to maximize spray accuracy and distribution while minimizing drift under dynamic environmental, crop growth, and pest biology conditions. Pesticides containing the active ingredient of chlorantraniliprole (Coragen®, Prevathon®, Altacor®) are among the most commonly used crop protection products sprayed via drones in China to control insect pests of rice. Drone end users are challenged with the lack of applicator experience that is far beyond basic drone operations but involves comprehensive understanding of the multiple variables affecting drone spray quality and pesticide efficacy. Hence, FMC Corporation developed an initial draft of Best Management Practices (BMPs) for proper drone application. The objective was to optimize the insecticidal attributes of FMC‘s chlorantraniliprole-based insecticides by maximizing spray quality, however, these BMP‘s will apply to most other pesticides including fungicides and herbicides. A holistic approach was employed with cross-disciplinary considerations from biological, chemical, and engineering perspectives along with complex environmental variables. These BMP‘s begin to mitigate the many variables that affect a quality spray by UAV application, but numerous knowledge gaps still exist that require further research to continually improve future best management guidance.

With the maturation of remote sensing, the applications of small unmanned aerial vehicles are rapidly expanding. Efficient image object detection algorithms have become crucial for information extraction in unmanned aerial vehicles. To meet this demand, an improved YOLOv5s algorithm was developed and deployed within a multi-processor system to optimize the performance of object detection in high-resolution remote sensing images captured by small unmanned aerial vehicles. Through adjustments to the structure and parameters of YOLOv5s, the algorithm was enhanced to improve object recognition capabilities in high-resolution remote sensing imagery. Experimental results demonstrated that the improved YOLOv5s (I-YOLOv5s) algorithm effectively mitigates interference from shadows and other external factors, enabling precise identification of objects. During training, I-YOLOv5s exhibited faster convergence, reaching optimal status after approximately 176 iterations. In performance evaluation, the algorithm achieved F1 and Recall values of 0.92 and 0.94, respectively, significantly outperforming single-shot multibox detectors. I-YOLOv5s attained a maximum average precision of 0.96, markedly higher than comparative algorithms, with its Loss value reduced to a mere 0.06. The introduction of this enhanced algorithm not only enhances the accuracy and efficiency of object detection but also profoundly advances the further application of unmanned aerial vehicles in fields such as environmental monitoring, traffic management, and disaster assessment.

A growing number of designs of future unmanned aerial vehicle (UAV) applications utilise DC for the primary power distribution method. Such systems typically employ large numbers of power electronic converters as interfaces for novel loads and generators. The characteristic behaviour of these systems under electrical fault conditions, and in particular their natural response, can produce particularly demanding protection requirements. Although a number of protection methods for multi-terminal DC networks have been proposed in the literature, these are not universally applicable and will not meet the specific protection challenges associated with the aerospace domain. Through extensive analysis, this study seeks to determine the operating requirements of protection systems for compact DC networks proposed for future UAV applications, with particular emphasis on dealing with the issues of capacitive discharge in these compact networks. The capability of existing multi-terminal DC network protection methods and technologies are then assessed against these criteria in order to determine their suitability for UAV applications. Recommendations for best protection practice are proposed and key inhibiting research challenges are discussed.

Unmanned Aerial Vehicles (UAVs) are used in various applications, including crowd management, crime prevention, accident detection, and rescue operations. However, since UAVs perform their tasks independently, some UAV applications are dynamic and geographically distributed, which may require extensive real-time processing capabilities. Thus, processing UAV data locally can be challenging due to their limited computing capabilities. To overcome such limitations, fog and cloud computing can facilitate UAV application development by providing additional resource capacities when needed. Despite this, designing sophisticated and efficient UAV task offloading strategies that collaborate with fog and cloud technologies considering their service latency and energy consumption, is rarely addressed in the literature. Therefore, a collaborative offloading strategy for UAV applications is presented in this work, leveraging fog and cloud computing advantages and capabilities. This approach aims to minimize UAVs’ service latency and energy consumption, as well as provide the required resources and services in real time. In addition, task offloading decisions are formulated using the Mixed-Integer Linear Programming (MILP) model to reduce the energy consumption of the entire UAV-fog-cloud system by optimizing the allocation of computation resources and communication requested by each UAV. The simulation results demonstrate that the proposed strategy can significantly reduce UAV service latency by 15.38%, 35.29%, and 59.26%, as well as decrease overall energy consumption (including processing and networking) by 3.3%, 7.37%, and 12% when compared to alternative standalone strategies (namely UAV, fog, and cloud).

Unmanned aerial vehicles for logistics are attracting increasing attention in recent years because of their important contribution and cost effective application in many tasks. In this paper, the logistics applications of unmanned aerial vehicles is investigated, which shows the problems in the development of our country's unmanned aerial vehicles. A research design decision method for the applications of unmanned aerial vehicles in logistics is given, which can be used to determine the feasibility of unmanned aerial vehicles for logistics applications. At last, key technology in the development of logistical unmanned aerial vehicles is summarized, which should be paid more attention in the future.

In the chapter, the authors present the results of unmanned aerial vehicle (UAV) applications for military geoinformation system (GIS) task solutions. The results of the visual modelling of the revealing process of invisible military objects from one of point of observation on the mountainous terrain of the Azerbaijan Republic by using UAV are presented. The observation conditions between two points of the selected mountain terrain during battle operation have been investigated using GIS technology. The quantitative method of the invisible area assessment and military objects in mountainous terrain are developed and offered by using UAVs. The numerical estimation method of a task support success of UAV reconnaissance flight in mountainous battle conditions has been offered and considered. Using UAVs for the purpose of orthophotomap making of the terrain and combat control the detailed 3D-model has been constructed.

Предметом вивчення в статті є розгляд особливостей використання безпілотних літальних апаратів (БПЛА) при проведенні екологічного моніторингу для оптимізації проведення спостережень техногенних об’єктів та виконання екологічних завдань в системі екологічного моніторингу. Це можливо здійснити за допомогою висвітлення позитивних та врахування негативних властивостей при застосуванні БПЛА в системі екологічного моніторингу. Метою є розкриття особливостей використання БПЛА в екологічному моніторингу та визначення напрямків їх застосування для проведення контролю за параметрами стану навколишнього природного середовища заданих територій. Завдання: провести аналіз можливості використання БПЛА в системі екологічного моніторингу; висвітлити особливі властивості застосування БПЛА в системі спостереження; визначити можливості БПЛА для формування процедури проведення екологічного моніторингу та визначити коло екологічних завдань для їх вирішення за допомогою БПЛА; розглянути можливості застосування БПЛА в системі спостереження та знімання параметрів навколишнього середовища, що є підґрунтям для проведення робіт, що пов’язані з проведенням екологічного моніторингу. Використовуваними методами є: системний підхід до розробки складних систем, проведення порівняльного аналізу параметрів та властивостей БПЛА, математичні моделі оптимізації для побудови складних систем. Отримані такі результати. Проведено порівняльний аналіз властивостей БПЛА, висвітлення процесу обробки інформації в системі екологічного моніторингу при здійсненні вибору оптимальної структури системи екологічного моніторингу за допомогою використання БПЛА. На основі системного аналізу різних технічних показників та властивостей БПЛА можливо здійснити вивчення структурно-параметричних характеристик та дослідити режими роботи літальних апаратів в різних умовах при побудові системи екологічного моніторингу. Висновки. Наукова новизна отриманих результатів полягає в наступному: проведено аналіз властивостей БПЛА, визначено характеристики та параметри, що впливають на спостереження в системі екологічного моніторингу, також висвітлено коло питань, які необхідно враховувати при побудові системи екологічного моніторингу з використанням дистанційно керованих літальних апаратів.

Distributed decision making for unmanned aerial vehicle inspection with limited energy constraint

The availability, cost, and applicability of Unmanned Aerial Vehicles (UAVs) are rapidly altering the way we perceive the landscape, can access sites, and model the landscape as it unfolds through remote sensing technologies. It falls to present and future researchers to take advantage of this and use the technology to improve our understanding of our surroundings. One way that geomorphologists would be able to take advantage of the improvements in technology is to use the UAV to map soil processes, in particular erosion. The current methods and technology for mapping gully erosion do not look at the smaller features but rather the landscape as a whole. The purpose of this research was to assess the prospects of UAV technology mapping gully erosion. Specifically, the study investigates the application of the UAV imagery to other technologies or methods in mapping gully erosion activities. This was achieved by testing the multiple available modelling software, by mapping objects of known shapes and volumes to determine which software produced results comparable to that of the known shapes. Tests were conducted to determine if this software and UAV combination would have the ability to map and 3D render soil erosion, thus allowing researchers to verify if this technique could be implemented into mapping gully systems. From these tests, it was found the UAV was able to improve the resolution to that of the available methods. Obtaining a resolution of 0.03m would allow geomorphologists to map and situate the soil erosional landscapes and map the test objects. The software package AgiSoft MetaShape had the highest accuracy and reliability in mapping various objects making it ideal in the mapping of smaller erosional features. Multiple erosional landscapes were mapped using a UAV and the attached RGB sensor and a second UAV with a multi-spectral sensor and AgiSoft MetaShape software. Both sensors mapped plant health, capturing plant health with band widths related to each sensor. Ideally the multi-spectral sensors were seen to be more versatile, however the RGB sensor can be useful. The combination of both UAVs created a 3D-rendered model, and the resulting data was useful in determining the potential future areas of erosion and existing areas of high erosion risk. The multi-sensor camera allowed the user to determine micro-features that could potentially become erosional areas in the future as it identified areas with a concentration in water flow. In conclusion, the UAV is a useful spatial tool to monitor, measure and manage soil erosion and gully mapping. Iqoqa. Ukusetshenziswa kweUAV kwenza izinguquko ngokushesha endleleni okubukwa ngayo izwe (landscape) kanti kukubacwaningi ukuthi sithathe ithuba lokusebenzisa lensizakusebenza ngendlela ezoba wusizo ukuze sibe nokuqonda okungcono kolwazi olukhona. Lobuchwepheshe bungasetshenziswa ukubona ukuqopha ukunyakaza komhlabathi ngoguguleka kwemihosha . Inhloso kube wukuhlola ukusetshenziswa kwe UAV ukubona ukuthi iyakwazi yini ukukhiqiza izithombe ezithathwe ngobuchwepheshe basemoyeni obusezingeni eliphezulu. Inhloso yenzekie ngokuthi kwenziwe ukuhlola okunhlobonhlobo kwimodelling software. Lokhu kwenziwe ngezimpawu zebalazwe zomumo owaziwayo kanye nezinga lomsindo, ukuqonda ukuthi ilona luphi uhlelokusebenza olusebenzayo ngezinga lomsindo oseduze . Ukuhlolwa kwenziwe ukubona ukuthi lenhlanganisela yohlelokusebenza ne UAV ingakwazi yini ukuveza ukuguguleka kwenhlabathi igugulwa ngebalalazwe nemodli ye3D kanye nokuqinisekisa ukuthi lobu buchwepheshe bungasetshenziswa ebalazweni lwemihosha kanye nemodeli yekhompyutha eyaziwa nge 3D computer models of gullies. Kulokhu kuhlola kutholakale ukuthi iUAV iyakwazi ukuthuthukisa ukuhleleka kohlelo okukhona. Ukuthola ukuhleleka okungango 0.03 m okungavumela igeomorphologist ukungena ebalazweni kuphinde kuveze ukuguguleka komhlabathi. Izinjongo eziwusayizi owaziwayo zifakwe ebalazweni, okuzale iAgiSoft MetaShape okube sezingeni eliphezulu lokuqagula kanye nokwethembeka ekufakeni ebalazweni izinto ezahlukahlukene . Imiphumela yemininingo ibe wusizo ukuqonda izindawo ezingaguguleka ngengomuso kanye nezindawo ezikhona ezisethubeni lobungozi bokuguguleka .Ikhamera eyimulti sensor yenze umcwaningi ukuthi abone izimpawu ezaziwa ngemicro features ezingaba sethubeni lokuba sendaweni engaguguleka ngengomuso njengoba zikhombisa ukuba nenkinga yobuningi kwamanzi agelezayo. Ukuphetha, i-UAV okwamanje iyinsizakusebenza ewusizo engasetshenziswa ocwaningweni lwegeomorphologists futhi ishibhile kunezinye izinsizakusebenza ezifana nemanned vehicle noma isatellite.

There are many applications of Unmanned Aerial Vehicle (UAV) networks where all UAVs belong to one organization or a person. In such applications, the number of UAVs that can be employed is limited due to the cost factor. Local Area Networks of Drones (LoDs) have been introduced recently for such purposes. This paper presents methods of determining the minimum number of UAVs to perform tasks in four basic categories of LoD applications: completing a single task at a time, completing multiple tasks simultaneously, monitoring the entire area using a single UAV branch and monitoring the entire area simultaneously using multiple branches of UAVs. Completing one task at a time always requires a minimum number of UAVs and increasing the number of simultaneous tasks performed always increases the number of UAVs required for any application.

Trajectory planning in airborne networks is a primary application of Unmanned Aerial Vehicle (UAV) communication. The literature contains algorithms focusing on collision avoidance, intelligent task assignment and path planning among UAVs. Cooperative schemes exist in which the UAVs communicate with each other to reach a consensus on how each vehicle will take up one trajectory at a time efficiently based on its capability. In the last decade, much research is being done to use UAVs to track contamination in the environment, detect fires and even volcanic eruptions. As the plumes are constantly varying in space and time, there have to be efficient guidance algorithms for the UAVs in order to keep track of the shape of the plume. In this paper, we survey the literature to explore the currently available trajectory planning algorithms and also the few available plume tracking algorithms. We then formulate the Plume wrapping problem and propose a cooperative trajectory planning approach for a group of UAVs, through which the UAVs communicate their position estimates and planned trajectories to update each others trajectory to efficiently wrap around a plume region so that the contamination in the region can be studied.