DEVELOPMENT OF CONTROL LAWS OF UNMANNED AERIAL VEHICLES FOR PERFORMING GROUP FLIGHT AT THE STRAIGHT-LINE HORIZONTAL FLIGHT STAGE

Oleg Barabash, A. Kyrianov
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Abstract

The article proposes an improved approach to controlling groups of unmanned aerial vehicles (UAVs) aimed at increasing the overall efficiency and flexibility of the control process. The use of a heterogeneous external field, which varies both in magnitude and direction, allows achieving greater adaptability and accuracy in controlling a group of UAVs. A vector field for unmanned aerial vehicles determines the direction and intensity of the vehicles' movement in space. Such vector fields can be used to develop UAV control laws, including determining optimal flight paths, controlling speed, avoiding obstacles, and ensuring coordination of a group of UAVs. The subject of the study is the methods of controlling groups of autonomous UAVs, where each vehicle may have different speeds and flight directions. To solve this problem, various methods of using a heterogeneous field have been developed and proposed. Instead of using a homogeneous field that provides a constant flight speed, a vector field is used that adapts to different conditions and characteristics of the vehicles in the group. This method allows for effective group management, ensuring the necessary coordination and interaction between the vehicles. An analysis of recent research and publications in the field of autonomous system control indicates the feasibility of using machine learning, vector fields, and a large amount of data to successfully coordinate the movement of autonomous systems. These approaches make it possible to create efficient and reliable control systems. The aim of the study is to develop laws for controlling the movement of a group of autonomous unmanned aerial vehicles at the stage of straight-line horizontal flight based on natural analogues to improve the efficiency and reliability of their coordinated movement in different conditions. The main conclusions of the research are that the proposed method of controlling groups of UAVs based on a heterogeneous field can be implemented. It takes into account a variety of vehicle characteristics and environmental conditions that are typical for real-world use scenarios. This work opens up prospects for further improving the management of UAV groups and their use in various fields of activity. The article emphasises the relevance of technology development for autonomous unmanned systems, especially in the context of autonomous transport systems.
制定无人驾驶飞行器在直线水平飞行阶段进行群体飞行的控制法则
本文提出了一种改进的无人机群控制方法,旨在提高控制过程的整体效率和灵活性。使用大小和方向都不同的异质外场,可以在控制一组无人机时实现更大的适应性和准确性。飞行器的矢量场决定了飞行器在空间中的运动方向和强度。这些矢量场可用于制定无人机控制规律,包括确定最优飞行路径、控制速度、避开障碍物和确保一组无人机的协调。研究的主题是自主无人机群的控制方法,其中每个飞行器可能具有不同的速度和飞行方向。为了解决这个问题,人们开发并提出了各种利用非均质场的方法。代替使用提供恒定飞行速度的均匀场,使用矢量场来适应组中飞行器的不同条件和特性。这种方法允许有效的群体管理,确保车辆之间必要的协调和互动。对自主系统控制领域的最新研究和出版物的分析表明,使用机器学习、向量场和大量数据来成功协调自主系统的运动是可行的。这些方法使创建有效和可靠的控制系统成为可能。研究的目的是基于自然类似物,发展一组自主无人机在直线水平飞行阶段的运动控制规律,以提高其在不同条件下协调运动的效率和可靠性。研究结果表明,本文提出的基于异质场的无人机群控制方法是可行的。它考虑了各种车辆特性和环境条件,这些都是现实世界中典型的使用场景。这项工作为进一步改善无人机群的管理及其在各种活动领域的使用开辟了前景。文章强调了自主无人系统技术发展的相关性,特别是在自主运输系统的背景下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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