Collision-free swarm take-off based on trajectory analysis and UAV grouping

Carles Sastre, J. Wubben, C. Calafate, Juan-Carlos Cano, P. Manzoni
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引用次数: 1

Abstract

In recent years, the adoption of unmanned aerial vehicles (UAVs) has widely spread to different sectors worldwide. Technological advances in this field have made it possible to coordinate the flight of these aircraft so as to conform a swarm. A UAV swarm is defined as a group of UAVs working collaboratively to carry out more complex missions or perform tasks more efficiently. Common applications of these swarms include rescue missions, precision agriculture, and border control, among others. However, there are still certain problems that prevent us from ensuring the success of their mission, especially as the number of drones in a swarm increases. In this paper, we specifically address the problem of a swarm take-off by optimizing the total time involved, while guaranteeing the safety of the UAVs during the take-off stage. To this end, we propose a new approach that combines a collision detection algorithm based on trajectory analysis with a batch generation mechanism that we use in order to determine the take-off sequence. Experiments show that our algorithm offers an efficient solution, managing to improve the performance of existing take-off techniques.
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基于轨迹分析和无人机分组的无碰撞群起飞
近年来,无人驾驶飞行器(uav)在世界范围内广泛应用于不同领域。这一领域的技术进步使得协调这些飞机的飞行从而形成一个集群成为可能。无人机群被定义为一组协同工作的无人机,以执行更复杂的任务或更有效地执行任务。这些蜂群的常见应用包括救援任务、精准农业和边境控制等。然而,仍然有一些问题阻碍我们确保他们的任务的成功,特别是随着无人机数量的增加。本文在保证无人机起飞阶段安全的前提下,通过优化总时间,具体解决了蜂群起飞问题。为此,我们提出了一种新的方法,该方法将基于轨迹分析的碰撞检测算法与我们用于确定起飞顺序的批生成机制相结合。实验表明,该算法提供了一种有效的解决方案,能够提高现有起飞技术的性能。
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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