scholarly journals Autonomous Mission of Multi-UAV for Optimal Area Coverage

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2482
Author(s):  
Youkyung Hong ◽  
Sunggoo Jung ◽  
Suseong Kim ◽  
Jihun Cha
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Motor Command ◽  
Area Coverage ◽  
Minimal Amount ◽  
Whole Process ◽  
Aerial Vehicles ◽  
Outdoor Experiment ◽  
Real Hardware ◽  
Optimal Area ◽  
The Given

This study proposes an entire hardware and software architecture from operator input to motor command for the autonomous area coverage mission using multiple unmanned aerial vehicles. Despite the rapid growth of commercial drone services, there are many limitations on operations, such as a low decision-making autonomy and the need for experienced operators to intervene in the whole process. For performing the area coverage mission more efficiently and autonomously, this study newly designs an optimization problem that allocates waypoints created to cover that area to unmanned aerial vehicles. With an optimized list of waypoints, unmanned aerial vehicles can fill the given areas with their footprints in a minimal amount of time and do not overlap each other during the mission. In addition, this study performs both various simulations for quantitative analysis and an outdoor experiment through real hardware implementation in order to verify the performance sufficiently. The methodologies developed in this study could be applied to endless applications using unmanned aerial vehicles equipped with mission-specific sensors.

Coordinate Transformation of the Quadrotor Unmanned Aerial Vehicles’s Flight Path

2014 ◽  
Vol 568-570 ◽  
pp. 1073-1077
Author(s):  
Ming Yao ◽  
Qu Sun
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Coordinate Transformation ◽  
Flight Path ◽  
Experimental Results ◽  
Geometric Algorithms ◽  
Calculation Error ◽  
Simulation Platform ◽  
Whole Process ◽  
Aerial Vehicles ◽  
Quadrotor Unmanned Aerial Vehicles

Because of the quadrotor unmanned aerial vehicles (named as QUAV-X4) has numerous advantages, it attract more and more researchers to study it. The paper use QUAV-X4 as a object of studying, adopting Matlab as a simulation platform. According to QUAV-X4’s practical flight track, this method modularized QUAV-X4’s the whole process. Using geometric algorithms to describe QUAV-X4’s flight path to avoid calculation error when we adopt difference algorithm, realizing free combination of QUAV-X4’s flight path. Experimental results show that, this method can reflect the true QUAV-X4’s flight path.

scholarly journals Setting optimal closed flight route of lightweight unmanned aerial vehicles with consideration of wind in flight area

2014 ◽  
Vol 17 (2) ◽  
pp. 99-108
Author(s):  
Quyen Xuan Pham ◽  
Моисеев Дмитрий Викторович ◽  
Minh Van Trinh
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Flight Time ◽  
Optimum Time ◽  
Aerial Vehicles ◽  
Flight Route ◽  
The Given

This article presents a method of planning closed routes by optimum time of unmanned light aerial vehicles passing through the given points, taking into account the effect of wind in the air and analyzing the effects of wind to route and flight time.

scholarly journals Methods of teaching control systems for unmanned aerial vehicles by immersing them in virtual reality

2019 ◽  
pp. 17-22
Author(s):  
Aleksandr Ivanovich Efimov ◽  
Nikita Andreevich Balily
Keyword(s):  
Virtual Reality ◽  
Unmanned Aerial Vehicles ◽  
Control Systems ◽  
Training System ◽  
Aircraft Control ◽  
Advantages And Disadvantages ◽  
Aerial Vehicles ◽  
The One ◽  
Equipment Configuration ◽  
The Given

The subject of study is the implementation of control systems for unmanned aerial vehicles. As their solution, a method of teaching and testing of these systems by immersing the entire system and its individual components into a virtual reality as close as possible to real conditions is proposed. The advantages and difficulties of implementation in relation to each of the system modules involved are considered. For each of the difficulties the authors propose solutions. The most successful scopes of application are revealed, and also possibility of application of the given method to land and surface vehicles is allocated. In the framework of this work, the existing aircraft control systems and the use of virtual reality within the framework of training their individual parts are investigated and the option of extending the use of such methods to the entire control system with an analysis of the advantages and disadvantages of this approach is proposed. The novelty of this article lies in the training of control systems for unmanned aerial vehicles by immersing it in virtual reality. The completeness and flexibility of such a training system is able, on the one hand, to adapt to any equipment configuration, on the other hand, to provide the highest quality training. The most important aspect is ensuring that you can use a larger proportion of the learning algorithms than is possible in other cases. In addition, this approach to the crane is useful in the framework of video navigation in connection with the possibility of better implementation of computer vision. The article shows the relevance of the research and the effectiveness of this method in the framework of aircraft control systems and proposed its application to other vehicles.

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.

Simple Area Coverage by a Dynamic Set of Unmanned Aerial Vehicles

2020 ◽  
Author(s):  
Grazieno Pellegrino ◽  
Gustavo Mota ◽  
Flavio Assis ◽  
Sergio Gorender ◽  
Alirio Sa
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Area Coverage ◽  
Aerial Vehicles

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.

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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