Development of a software simulator for small satellite swarm control

Moldamurat, Kh.; Utegen, A.S.; Бримжанова, С. С.; Kalmanova, D. M.; Yryskeldi, N. G.

doi:10.1109/icecco53203.2021.9663828

Cited by 3 publications

(2 citation statements)

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“…Webots R2023b has been chosen as the 3-dimensional robot simulator [23,24] to develop an automated flight algorithm for UAV, as it has a wide scope of applications, allows programming the controller, contains a large library of robots and tools for their design, maintains a large number of widely used programming languages, and it is a cross-platform software.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, the travel routes optimisation [6] and minimisation of the data refreshment rate [7] are quite critical issues in UAV reconnaissance. The former could be solved by applying the ant colony algorithm [8] and the latter by adding a few drones with a genetic algorithm to observe a point of interest [9,10]. Nevertheless, the human factor is a key parameter when performing a reconnaissance operation using UAVs [11].…”

Section: Introductionmentioning

confidence: 99%

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Digital model of automated unmanned aerial vehicle with edge computing application for railway reconnaissance

Tulembayeva,

Ashirov,

Makarov

et al. 2024

Acta Polytech

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In the last decade, unmanned aerial vehicles have been widely used in various civil and military field operations. Most modern drones are manually controlled by an operator and require decision making, which requires experience gained through training, which is time consuming and expensive, and even with experienced operators, the human factor can never be excluded. In this paper, an algorithm for an automatic flight mode of unmanned aerial vehicles without an operator’s participation has been developed. The proposed algorithm has been considered in the military reconnaissance of railways using edge computing and computer vision approaches to recognise railroads and moving trains for simulated and real cases as well as send report data to the web platform. As a result, the head of the operation received information about the number of carriages and Global Positioning System coordinates of the recognised train to make the necessary decisions.

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Section: Methodsmentioning

confidence: 99%