RHC Method Based 2D-equal-step Path Generation for UAV Swarm Online Cooperative Path Planning in Dynamic Mission Environment

Yue Shen, Guoliang Fan
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Abstract

This paper first mathematically models the UAV swarm online cooperative path planning problem based on the prerequisite assumptions of transparent posture and dynamic mission environment. Then the receding horizon control (RHC) and 2D-equal-step path generation method are briefly introduced and combined with the improved firefly optimization algorithm to solve the UAV swarm online cooperative path planning problem modeled in the previous. Simulations show that the improved firefly algorithm combining the RHC and 2D-equal-step path generation methods can be used to optimally solve the UAV swarm online cooperative path planning problem for moving mission targets in dynamic environments, and the improved firefly algorithm is more powerful and more efficient than the original algorithm in this process of application.
基于RHC方法的动态任务环境下无人机群在线协同路径规划二维等步路径生成
本文首先基于透明姿态和动态任务环境的前提假设,对无人机群在线协同路径规划问题进行数学建模。然后简要介绍了后退地平线控制(RHC)和二维等步路径生成方法,并结合改进的萤火虫优化算法解决了前面建模的无人机群在线协同路径规划问题。仿真结果表明,结合RHC和2d等步路径生成方法的改进萤火虫算法可以最优地解决动态环境下移动任务目标的无人机群在线协同路径规划问题,改进萤火虫算法在应用过程中比原算法更强大、更高效。
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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