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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >A Global Path Planning Algorithm for Fixed-wing UAVs
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A Global Path Planning Algorithm for Fixed-wing UAVs

机译:固定翼UAV的全局路径规划算法

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摘要

A new approach for solving the global optimal path planning problem to fixed-wing UAVs in multi-threat environments is proposed in this paper, which is mainly based on a natural combination of Genetic Algorithm (GA), Dijkstra searching algorithm, and Artificial Potential Field (APF) approach. First, a Delaunay partition of the flight space is introduced to map the continuous searching space on the Delaunay diagram, and the trajectory encoding methods for GA are designed based on the Delaunay network. Then, a shortest path is established by Dijkstra searching algorithm and the corresponding code is taken as the first population such that a GA could be conducted. Especially by considering flight turning constraints of fixedwing UAVs, artificial potential field approach is utilized to make the path smooth after each evolution in GA. Finally, a global optimal path is obtained through the suggested algorithm and simulation results validate the effectiveness in both Two-Dimensional (2-D) and Three-Dimensional (3-D) flight environments.
机译:本文提出了一种解决全球最佳路径规划问题的新方法,以多威胁环境中的固定翼UAV,这主要基于遗传算法(GA),Dijkstra搜索算法和人工潜在场的自然组合(apf)方法。首先,引入了飞行空间的Delaunay分区以映射Delaunay图上的连续搜索空间,并且基于Delaunay网络设计了GA的轨迹编码方法。然后,通过Dijkstra搜索算法建立最短路径,并且相应的代码被视为第一群体,使得可以进行GA。特别是考虑到固定窗体无人机的飞行匝数限制,利用人工潜在场方法使得在GA的每次演进之后使路径平滑。最后,通过建议的算法获得全局最优路径,仿真结果验证了二维(2-D)和三维(3-D)飞行环境中的有效性。

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