scholarly journals Dynamic Routing and Coordination of Cluster for Unmanned Aerial Vehicle (UAV) Swarms

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ali Abbas ◽  
Bhawani Shankar Chowdhry ◽  
Muhammad Saqib ◽  
Vishal Dattana
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Efficient Solution ◽  
High Mobility ◽  
Combinatorial Problem ◽  
Communication Graph ◽  
Frequent Change ◽  
Swarm Optimization ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Simulation Results

The flying networks provide an efficient solution for a wide range of military and commercial purposes. The demand for portable and flexible communication is directed towards a quick growth in interaction among unmanned aerial vehicles (UAVs). Due to the frequent change in topology and high mobility of vehicles, routing and coordination becomes a challenging task. To maximize the throughput of the network, this study addresses the UAV swarm’s problems related to the coordination and routing and defines the proposed solution to solve these issues. For this, a network is assumed which contains an equal number of dynamic vehicles. It also presents the communication graph concept of UAVs and designs a fixed-wing UAV model to improve the efficiency of the network in terms of throughput. Furthermore, the proposed algorithm based on Cauchy particle swarm optimization (CPSO) aims towards the better performance of UAV swarms and aims to solve the combinatorial problem. The simulation results show and confirm the performance of the proposed algorithm.

scholarly journals Effect of the Inclusion of Photovoltaic Solar Panels in the Autonomy of UAV Time of Flight

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 876
Author(s):  
Joana Engana Carmo ◽  
João Paulo Neto Torres ◽  
Gonçalo Cruz ◽  
Ricardo A. Marques Lameirinhas
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Stokes Equations ◽  
Fluid Motion ◽  
Time Of Flight ◽  
Navier Stokes ◽  
Solar Panels ◽  
Navier Stokes Equations ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Aerial Vehicle

Photovoltaic technology and unmanned aerial vehicles are both alluring areas with a lot of potential to explore. Consequently, they have an ability to adapt and progress when faced with new challenges, hence their wide range of applications. An auspicious combination between the two is born from the Unmanned Aerial Vehicles’ (UAVs) inability to to overcome some of its problems, namely the autonomy one. This article springs from the need to vanquish the problem, finding a more permanent solution. Its aim consists in the installation of solar photovoltaic panels in the structure of a UAV, with the objective of studying being its influence on the vehicle’s time of flight. To accomplish this, a theoretical study will be made, encompassing all the potential variables together with its influence. In order to verify the credibility of these claims, a prototype, based on the original aerial vehicle structure form and material, is constructed, using a finite element tool. Later, the prototype is used to evaluate possible harsh circumambient air to structure interactions, modeled by the fluid motion describer Navier–Stokes equations. For a smooth approach involving lighter computational power, a RANS model is used to asses the equations. Based on its results the chosen solar technology credibility is evaluated. A simulation of solar cells will also be carried out, accepting as input previously studied parameters which will modify its performance. Bearing in mind the produced results, it is concluded that the solar panels can only significantly augment the time of flight in very specific conditions.

scholarly journals An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Drones ◽  
2018 ◽  
Vol 2 (3) ◽  
pp. 31 ◽  
Author(s):  
Mohd. Sayeed ◽  
Rajesh Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Data Transmission ◽  
Topological Structure ◽  
Mobility Model ◽  
Wireless Sensor ◽  
Coverage Problem ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Navigation Control ◽  
Simulation Results

Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations.

Smart Agriculture With Autonomous Unmanned Ground and Air Vehicles

2021 ◽  
pp. 151-174
Author(s):  
Alparslan Guzey ◽  
Mehmet Mutlu Akinci ◽  
Haci Mehmet Guzey
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Nearest Neighbor ◽  
Optimal Number ◽  
Machine Learning Algorithms ◽  
Swarm Optimization ◽  
Agricultural Robots ◽  
Air Vehicle ◽  
Time Minimization ◽  
Aerial Vehicle ◽  
Smart Agriculture

This study researches smart agriculture and its components, robotic systems and machine learning algorithms, development of agricultural robots, and their effects on the industry. In application, it is aimed to collect the harvest of autonomous unmanned aerial vehicles and UGVs in communication with each other by means of time minimization of the target. It wanted to be tested with different approaches for an optimal number of stops by using particle swarm optimization. Deterministic, binary mixed (0-1) integer modeling was used to determine the optimal picking time of the apples allocated to the stalls with the k-means method. With this modeling, it has been determined which unmanned aerial vehicle will be collected and how it is calculated whether the air vehicle has collected the apple or not using 0-1 binary modeling. The route of the unmanned UGV was made by using the nearest neighbor, nearest insertion, and 2-opt methods. This study has been extended and reviewed by the summary paper at International OECD Studies Conference March 2020, Ankara, Turkey.

scholarly journals Detection of unmanned aerial vehicle using radio wave scatter on acoustic disturbances of the environment created by aircraft

Radiotekhnika ◽  
2021 ◽  
pp. 122-130
Author(s):  
V.M. Kartashov ◽  
O.I. Kharchenko ◽  
V.A. Pososhenko ◽  
V.I. Kolesnik ◽  
A.B. Yegorov ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Technical Problem ◽  
Technical Problems ◽  
Acoustic Disturbances ◽  
Aerial Vehicles ◽  
Wide Range ◽  
Radio Signals ◽  
Range Of Functions ◽  
Aerial Vehicle

Unmanned aerial vehicles (UAVs) have recently become widespread, because they are capable of performing a wide range of functions useful for mankind. At the same time, UAVs are a source of potential threats in a number of areas of human activity, namely, military, economic, and everyday life. Therefore, an urgent scientific and technical problem of detecting and observing UAVs has been formed recently to prevent them from performing unauthorized actions. The main means of UAV surveillance are radar (both active and passive), optical, infrared, acoustic stations, as well as complex systems in which joint processing of information obtained using these information channels is carried out. However, in general, the scientific and technical problem of monitoring UAVs, especially small UAVs, remains unresolved: the efficiency of UAV detection using all these methods remains insufficient, and the needs of practice are far from being fully satisfied with the available means. This article is devoted to the analysis of currently known scientific and practical results aimed to assess the possibility of detecting UAVs by radio signals scattered by acoustic disturbances of the environment created by UAVs, and to formulate urgent scientific and technical problems in this aria of knowledge.

scholarly journals Recent Advances in Unmanned Aerial Vehicle Forest Remote Sensing—A Systematic Review. Part I: A General Framework

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Relevant Information ◽  
Forest Monitoring ◽  
Machine Learning Techniques ◽  
Planted Forests ◽  
Systematic Analysis ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Aerial Vehicle

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

scholarly journals Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

2021 ◽  
Vol 11 (8) ◽  
pp. 3623
Author(s):  
Omar Said ◽  
Amr Tolba
Keyword(s):  
Packet Loss ◽  
Large Scale ◽  
Performance Metrics ◽  
Medical System ◽  
Healthcare Data ◽  
High Altitude Platforms ◽  
Wide Range ◽  
Simulation Results ◽  
Healthcare Architecture ◽  
The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

scholarly journals A Flow Analysis Using a Water Tunnel of an Innovative Unmanned Aerial Vehicle

2021 ◽  
Vol 11 (13) ◽  
pp. 5772
Author(s):  
Dawid Lis ◽  
Adam Januszko ◽  
Tadeusz Dobrocinski
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Rapid Development ◽  
Lift Coefficient ◽  
Flow Analysis ◽  
Water Tunnel ◽  
Dual Use ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Technical Construction

The purpose of this article is to present and discuss the results of a non-standard unnamed aerial vehicle construction with a constant cross-section square-shaped avionic profile. Based on the model’s in-air observed maneuverability, the research of avionic construction behavior was carried out in a water tunnel. The results show the model’s specific lift capabilities in comparison to classical avionic constructions. The characteristic results of the lift coefficient showed that the unmanned aerial vehicle presents favorable features than classic avionic constructions. The model was created with the prospect of using it in the future for dual-use purposes, where unmanned aerial vehicles are currently experiencing very rapid development. When creating the prototype, the focus was on low production cost, as well as convenience in operation. The development of this type of breakthrough avionic solution, which shows extraordinary maneuverability, may contribute to increasing the popularity and, above all, the availability of unmanned aerial vehicles for the largest possible group of recipients because of high avionic properties in relation to the technical construction complexity.

Energy absorbed ability and damage analysis for honeycomb sandwich material of bio-inspired micro aerial vehicle under low velocity impact

2020 ◽  
pp. 095440622097542
Author(s):  
Jianxun Du ◽  
Peng Hao ◽  
Mabao Liu ◽  
Rui Xue ◽  
Lin’an Li
Keyword(s):  
Honeycomb Structure ◽  
Low Velocity Impact ◽  
Parameter Study ◽  
Low Velocity ◽  
Micro Aerial Vehicle ◽  
Thin Walled Structures ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Thin Walled ◽  
The Impact

Because of the advantages of light weight, small size, and good maneuverability, the bio-inspired micro aerial vehicle has a wide range of application prospects and development potential in military and civil areas, and has become one of the research hotspots in the future aviation field. The beetle’s elytra possess high strength and provide the protection of the abdomen while being functional to guarantee its flight performance. In this study, the internal microstructure of beetle’s elytra was observed by scanning electron microscope (SEM), and a variety of bionic thin-walled structures were proposed and modelled. The energy absorption characteristics and protective performance of different configurations of thin-walled structures with hollow columns under impact loading was analyzed by finite element method. The parameter study was carried out to show the influence of the velocity of impactor, the impact angle of the impactor and the wall thickness of honeycomb structure. This study provides an important inspiration for the design of the protective structure of the micro aerial vehicle.

A novel identification approach for shearer running status through integration of rough sets and improved wavelet neural network

2016 ◽  
Vol 230 (16) ◽  
pp. 2792-2805 ◽  
Author(s):  
Lei Si ◽  
Zhongbin Wang ◽  
Xinhua Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Rough Sets ◽  
Particle Swarm Optimization Algorithm ◽  
Wavelet Neural Network ◽  
Decision Table ◽  
Swarm Optimization ◽  
Novel Approach ◽  
Identification Approach ◽  
Simulation Results

In order to accurately and conveniently identify the shearer running status, a novel approach based on the integration of rough sets (RS) and improved wavelet neural network (WNN) was proposed. The decision table of RS was discretized through genetic algorithm and the attribution reduction was realized by MIBARK algorithm to simply the samples of WNN. Furthermore, an improved particle swarm optimization algorithm was proposed to optimize the parameters of WNN and the flowchart of proposed approach was designed. Then, a simulation example was provided and some comparisons with other methods were carried out. The simulation results indicated that the proposed approach was feasible and outperforming others. Finally, an industrial application example of mining automation production was demonstrated to verify the effect of proposed system.

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