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Multiple UAVs path planning algorithms: a comparative study

机译:多种无人机路径规划算法:比较研究

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摘要

Unmanned aerial vehicles (UAVs) are used in team for detecting targets and keeping them in its sensor range. There are various algorithms available for searching and monitoring targets. The complexity of the search algorithm increases if the number of nodes is increased. This paper focuses on multi UAVs path planning and Path Finding algorithms. Number of Path Finding and Search algorithms was applied to various environments, and their performance compared. The number of searches and also the computation time increases as the number of nodes increases. The various algorithms studied are Dijkstra’s algorithm, Bellman Ford’s algorithm, Floyd-Warshall’s algorithm and the AStar algorithm. These search algorithms were compared. The results show that the AStar algorithm performed better than the other search algorithms. These path finding algorithms were compared so that a path for communication can be established and monitored.
机译:团队使用无人飞行器(UAV)检测目标并将其保持在其传感器范围内。有多种算法可用于搜索和监视目标。如果节点数量增加,则搜索算法的复杂性也会增加。本文着重于多无人机的路径规划和路径查找算法。将“路径查找和搜索”算法的数量应用于各种环境,并对它们的性能进行了比较。搜索的数量以及计算时间随着节点数量的增加而增加。研究的各种算法是Dijkstra算法,Bellman Ford算法,Floyd-Warshall算法和AStar算法。比较了这些搜索算法。结果表明,AStar算法的性能优于其他搜索算法。比较了这些路径查找算法,以便可以建立和监视通信路径。

著录项

  • 来源
    《Fuzzy Optimization and Decision Making》 |2008年第3期|257-267|共11页
  • 作者单位

    Knowledge Based Intelligent Engineering Systems Center University of South Australia Adelaide Australia;

    Knowledge Based Intelligent Engineering Systems Center University of South Australia Adelaide Australia;

    Defence Science ampamp Technology Organisation P. O. Box 1500 Edinburgh SA 5115 Australia;

    Defence Science ampamp Technology Organisation P. O. Box 1500 Edinburgh SA 5115 Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Pathfinding; AStar; Dijkstra; Distance vector algorithms;

    机译:寻路;AStar;Dijkstra;距离矢量算法;

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