基于粒子群算法的多无人机航路规划

Guoshi Wang, Qiang Li, Lejiang Guo
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引用次数: 27

摘要

针对多无人机协同航路规划不理想、航路规划次优、航路实时规划不理想、航路规划不理想等问题,在对影响多无人机航路规划的主要因素建模的基础上,提出了多无人机航路规划的成本函数。然后,基于粒子群优化(PSO)算法,提出了多无人机协同的静态三维航路规划和动态三维航路规划方法。该方法也可用于规划单个无人机路线。利用这些方法设计了仿真器并进行了实验,结果表明,这些方法能够满足多无人机航路规划的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple UAVs Routes Planning Based on Particle Swarm Optimization Algorithm
Aiming at solving the problems of unsatisfactory routes planning that are suboptimal to optimal routes planning and dissatisfactory real time routes planning and routes planning of multiple unmanned aerial vehicles (UAVs) cooperation, a cost function of multiple UAVs routes planning is presented after modeling the primary factors influencing on multiple UAVs route planning. Then, Based on particle swarm optimization (PSO) algorithm, this paper presents the approaches of static three-dimensional routes planning and dynamic three-dimensional routes planning for multiple UAVs cooperation. The approaches can also be used to plan a single UAV route. Using these approaches, an emluator is designed and some experiments are made, and the results demonstrate that the approaches can satisfy the requests of the multiple UAVs routes planning.
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