Maintaining the spatial stability of a swarm of autonomous unmanned aerial vehicles

2021 ◽  
Vol 9 (2) ◽  
pp. 85-90
Author(s):  
Andrey Boyko ◽  
Ruben Girgidov
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Practical Solution ◽  
Spatial Stability ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
Software And Hardware ◽  
Swarm Engineering ◽  
Simple Combination

This paper describes the application of a swarm engineering methodology that allows creating hexagonal UAV grids with predefined properties. It is achieved by imitation of physics processes that demonstrate conditions for stabilizing the above-mention hexagon grids of UAV swarm. We propose a simple combination of software and hardware applications that create a more efficient practical solution.

scholarly journals APPLICATION OF MODERN TECHNICAL AND SOFTWARE MEANS IN THE CONDITIONS OF FORMATION OF THE DIGITAL ECONOMY OF THE RUSSIAN FEDERATION

2020 ◽  
Vol 7 (2) ◽  
pp. 66-70
Author(s):  
Olga A. Opritova ◽  
Alexandr A. Antonov ◽  
Polina E. Ivanenko
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Russian Federation ◽  
Digital Economy ◽  
Aerial Vehicles ◽  
Photogrammetric Method ◽  
The Russian Federation ◽  
Software And Hardware

The article presents a method of using modern software and hardware in various fields and fields of activity. The definition and prospects of the development of the photogrammetric method in cadastral activities, as well as the possibility of using unmanned aerial vehicles and cloud platforms are given.

Development of hardware and software complex for monitoring fires by unmanned aerial vehicles

2021 ◽  
pp. 118-129
Author(s):  
Вера Васильевна Извозчикова ◽  
Владимир Михайлович Шардаков ◽  
Вероника Вячеславовна Запорожко
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Processing System ◽  
Fire Detection ◽  
Dynamic Monitoring ◽  
Fire Source ◽  
Aerial Vehicles ◽  
Hardware Complex ◽  
Aerial Vehicle ◽  
Software And Hardware

Рассматривается вопрос обнаружения пожара с помощью беспилотного летательного аппарата (БПЛА) и разработанного программного обеспечения. Для раннего обнаружения пожара в нефтяных и газовых скважинах предложен алгоритм, основанный на применении цветовой модели RGB к полученным видеоизображениям от квадрокоптера. Приведены требования к БПЛА, смоделирован прототип программно-аппаратного комплекса дистанционного динамического мониторинга, включающего бортовую систему обработки информации БПЛА и информационную систему. Результаты проведенных экспериментов показали способность предложенного алгоритма успешно обнаруживать пожары на местности. Созданный программно-аппаратный комплекс позволит оперативно разрабатывать и принимать наиболее оптимальные решения по направлению пожарных расчетов и пожарной техники к местам возгорания, что особо актуально для отдаленных районов The paper addresses the problem of fire detection that is based on information obtained by an unmanned aerial vehicle. The purpose of this work is the possibility of early detection of ignition in oil and gas wells. An algorithm for fire detection based on the application of the RGB color model to the obtained video images of the studied area is proposed. The algorithm is based on the methods of spatial image segmentation and color quantization. According to the presented algorithm, a quadcopter transmits the incoming image from the digital video camera to the terminal, scanning the monitoring zone and GPS coordinates set by the operator. The algorithm for detecting the fire source is divided into four stages: analysis of the color intensity on the frame; checking the color of the area specified by the operator for coincidence with the range of fire; determining the fire coverage area in a certain territory and analyzing the change in the shape of the fire center relative to the angle of the moving unmanned aerial vehicle; determining the direction of fire propagation. Accurate automated determination of coordinates is carried out using the GPS signal of the fire, which allows starting localization and eliminating the fire source in a timely manner, thereby preventing a negative impact on people, nature and wildlife, as well as reducing the damage caused by the fire. A prototype of a software and hardware complex for remote dynamic monitoring, including an on-board information processing system for an unmanned aerial vehicle (UAV) and an information system, has been modelled. The paper presents the requirements for unmanned aerial vehicles, as well as analysis for the cost of the quadcopter’s flight time. The results of the experiments have shown the ability of the algorithm proposed by the authors to successfully detect the source of a fire on the ground. The created software and hardware complex allows quickly developing and making the most optimal decisions on the direction of fire crews and fire equipment to the fire sites, which is especially important for remote areas

scholarly journals Data Transfer via UAV Swarm Behaviours

2018 ◽  
Vol 6 (2) ◽  
pp. 35-57
Author(s):  
Phillip Smith ◽  
Robert Hunjet ◽  
Aldeida Aleti ◽  
Jan Carlo Barca
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Data Transfer ◽  
Evolution Process ◽  
Heuristic Rule ◽  
Upper Limit ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
Robotic Swarm ◽  
The Given

This paper presents an adaptive robotic swarm of Unmanned Aerial Vehicles (UAVs) enabling communications between separated non-swarm devices. The swarm nodes utilise machine learning and hyper-heuristic rule evolution to enable each swarm member to act appropriately for the given environment. The contribution of the machine learning is verified with an exploration of swarms with and without this module. The exploration finds that in challenging environments the learning greatly improves the swarm’s ability to complete the task. The swarm evolution process of this study is found to successfully create different data transfer methods depending on the separation of non-swarm devices and the communication range of the swarm members. This paper also explores the resilience of the swarm to agent loss, and the scalability of the swarm in a range of environment sizes. In regard to resilience, the swarm is capable of recovering from agent loss and is found to have improved evolution. In regard to scalability, the swarm is observed to have no upper limit to the number of agents deployed in an environment. However, the size of the environment is seen to be a limit for optimal swarm performance.

Using an Intelligent UAV Swarm in Natural Disaster Environments

2018 ◽  
Author(s):  
Jamie Asbach ◽  
Souma Chowdhury ◽  
Kemper Lewis
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Natural Disaster ◽  
Decentralized Control ◽  
Efficient Method ◽  
Control Method ◽  
Sensor Technology ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
The Status

Due to their volatile behavior, natural disasters are challenging problems as they often cannot be accurately predicted. An efficient method to gather updated information of the status of a disaster, such as the location of any trapped survivors, is extremely important to properly conduct rescue operations. To accomplish this, an algorithm is presented to control a swarm of UAVs (Unmanned Aerial Vehicles) and optimize the value of the information gathered. For this application, the UAVs are autonomously navigated with a decentralized control method. With sensor technology embedded, this swarm collects information from the environment as it operates. By using the swarm’s location history, areas of the environment that have gone the longest without exploration can be prioritized, ensuring a thorough search. Measures are also developed to prevent redundant or inefficient exploration, which would reduce the value of the gathered information. A case study of a flood scenario is examined and simulated. Through this approach, the value of the proposed swarm algorithm can be tested by tracking the number of survivors found as well as the rate at which they are discovered.

scholarly journals Data Transfer via UAV Swarm Behaviours

2018 ◽  
Vol 6 (2) ◽  
pp. 35-57
Author(s):  
Phillip Smith ◽  
Robert Hunjet ◽  
Aldeida Aleti ◽  
Jan Carlo Barca
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Data Transfer ◽  
Evolution Process ◽  
Heuristic Rule ◽  
Upper Limit ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
Robotic Swarm ◽  
The Given

This paper presents an adaptive robotic swarm of Unmanned Aerial Vehicles (UAVs) enabling communications between separated non-swarm devices. The swarm nodes utilise machine learning and hyper-heuristic rule evolution to enable each swarm member to act appropriately for the given environment. The contribution of the machine learning is verified with an exploration of swarms with and without this module. The exploration finds that in challenging environments the learning greatly improves the swarm’s ability to complete the task. The swarm evolution process of this study is found to successfully create different data transfer methods depending on the separation of non-swarm devices and the communication range of the swarm members. This paper also explores the resilience of the swarm to agent loss, and the scalability of the swarm in a range of environment sizes. In regard to resilience, the swarm is capable of recovering from agent loss and is found to have improved evolution. In regard to scalability, the swarm is observed to have no upper limit to the number of agents deployed in an environment. However, the size of the environment is seen to be a limit for optimal swarm performance.

scholarly journals Modelling and Simulation of Distributed UAV Swarm Cooperative Planning and Perception

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haifeng Ling ◽  
Hongchuan Luo ◽  
Haisong Chen ◽  
Linyuan Bai ◽  
Tao Zhu ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Real World ◽  
Simulation Platform ◽  
Real World Application ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
Different Types ◽  
Simulation Results ◽  
Cooperative Planning

As an emerging topic, the swarm of autonomous unmanned aerial vehicles (UAVs) has been attracting great attention. Due to the indeterminacy of sensors, distributed cooperative swarms have been considered to be efficient and robust but challenging to design and test. To facilitate the development of distributed swarms, it has been proposed to utilise a simulation platform for cooperative UAVs using imperfect perception. However, the existing simulation platforms cannot satisfy this demand due to a few reasons. First, they are designed for a specific purpose, and their functionalities are difficult to extend. Second, the existing platforms lack compatibility to be applied to different types of scenarios. Third, the modelling of these platforms is too simplified to simulate flight motion dynamic and noisy communication accurately, which may cause a difference in performance between the simulation and real-world application. To address the mentioned issues, this paper models the problem and proposes a simulation platform for distributed swarm cooperative perception, which addresses software engineering concerns and provides a set of extendable functionalities of a cooperative swarm, including communication, estimation, perception fusion, and path planning. The applicability of the proposed platform is verified by simulations with the real-world application. The simulation results demonstrate that the proposed system is viable.

Development of thickened semi-synthetic engine oil M-5z / 20 AERO for four-stroke gasoline engines aircraft piston of unmanned aerial vehicles (UAVs)

2020 ◽  
Vol 06 ◽  
pp. 44-47
Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Engine Oil ◽  
Motor Oil ◽  
Gasoline Engines ◽  
State Research Institute ◽  
Technical Requirements ◽  
Aerial Vehicles ◽  
State Research ◽  
Industrial Batch ◽  
The Russian Federation

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.

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