Simulation Tool for the Drone Trajectory Planning Based on Genetic Algorithm Approach

Andriy Dashkevich, Sergii Rosokha, D. Vorontsova
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引用次数: 4

Abstract

In recent years, unmanned aerial vehicles (UAVs) have been found in many applications, from farm monitoring to civil infrastructure, from military to fire safety services. Drones are being actively introduced and are already being put into practice in emergency response services. The value of their use is primarily in saving time and resources. At minimal cost, the device covers a large area of the surveyed area. One of the main problems is estimation the optimal path of the UAV to cover the target area. In the present paper, we consider the problem of the estimation of the optimal parameters of trajectory planning algorithms. The main focus of the paper is the development of software utility to conduct the simulations of the drone trajectory generation, evaluation and optimization approaches, which is based on genetic algorithm approach. In particular, we explore the influence of the parameters genetic operators on the improvement of fitness values of the trajectory. A quantitative evaluation of the algorithm was conducted based on the results of experiments.
基于遗传算法的无人机轨迹规划仿真工具
近年来,从农场监控到民用基础设施,从军事到消防安全服务,无人驾驶飞行器(uav)已经在许多应用中被发现。目前正在积极引进无人机,并已在应急服务中投入使用。使用它们的价值主要在于节省时间和资源。以最小的成本,该设备覆盖了大面积的调查区域。其中一个主要问题是无人机覆盖目标区域的最优路径估计。本文研究了轨迹规划算法中最优参数的估计问题。本文的主要重点是开发基于遗传算法的无人机轨迹生成、评估和优化方法仿真软件。特别地,我们探讨了参数遗传算子对轨迹适应度值改进的影响。根据实验结果对算法进行了定量评价。
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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