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GUIDING UNMANNED AERIAL VEHICLE PATH PLANNING DESIGN BASED ON IMPROVED ANT COLONY ALGORITHM

机译:基于改进的蚁群算法指导无人驾驶飞行器路径规划设计

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摘要

This paper is specific to the requirements of guiding flight and navigation control of an unmanned aerial vehicle (UAV) and the problems such as slow convergence rate and unreasonable path planning occurred in the path planning of a traditional ant colony algorithm. In this paper, the ant colony algorithm combined with the manual correction algorithm added with angle calculation operators is adopted, and systematic angle calculation operators are introduced as a part of the heuristic information so that the combined algorithm has higher global searching ability and reasonable guiding ability, and local optimum caused by misleading of heuristic information in the traditional ant colony algorithm can be avoided. To verify the validity of this algorithm, a simulation experiment based on MATLAB simulation is conducted, and meanwhile, experiments are conducted at a practical guiding ground station. The experimental results indicate that the motion path of the UAV is smooth, which is close to the optimal path.
机译:本文特定于传统蚁群算法路径规划中的非人空中车辆(UAV)的指导飞行和导航控制的要求和诸如缓慢收敛速度和不合理的路径规划等问题。本文采用了与角度计算运算符的手动校正算法结合的蚁群算法,并将系统角度计算运算符作为启发式信息的一部分引入,以便组合算法具有更高的全球搜索能力和合理的指导能力并且可以避免通过传统蚁群算法中的引发信息误导引起的局部最佳。为了验证该算法的有效性,对基于MATLAB模拟的仿真实验进行了进行,同时,在实际的引导地面站进行实验。实验结果表明,UAV的运动路径平滑,靠近最佳路径。

著录项

  • 来源
    《Control and Intelligent Systems》 |2021年第1期|48-54|共7页
  • 作者

    Wenzhi Wu; Ying Wei;

  • 作者单位

    Network Information Center Xiamen University of Technol-ogy Xiamen China Engineering Research Center for Software Testing and Evalua-tion of Fujian Province China;

    Department of Computer and Science Xiamen University Tan KahKee College Xiamen China;

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

    Path planning; ant colony algorithm; UAV; MATLAB; simulation;

    机译:路径规划;蚁群算法;无人机;matlab;模拟;

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