基于蚁群算法的无人机最短航路规划
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Shortest Route Planning of UAV Based on Ant Colony Algorithm
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    摘要:

    为解决无人机在执行多航点任务过程中,由于航点数量较多而导致的多种飞行轨迹问题,提出一种仿生 蚁群觅食路径选择的无人机航点任务轨迹规划方法。介绍算法原理,计算信息点的信息素浓度,通过工蚁航点转换 规则和信息素浓度修改规则进行算法实现,并对其进行计算仿真和结果分析。仿真结果表明:该算法能够保证飞行 器以最短路径飞行完成所有航点任务,提高了无人机的任务执行效率,减少了控制系统的时间损耗,便于无人机编 队飞行系统的实现。

    Abstract:

    In order to solve the problem of multiple flight routes caused by the large number of waypoints in the process of executing multi-way missions, a method of selection for UAV waypoint-mission based on ant colony route planning algorithm is proposed. Introduce the principle of the algorithm, calculate the pheromone concentration of the information point, realize the algorithm by the conversion rule of the worker-ant’s waypoint and the modification rule of the pheromone concentration, and carry out the simulation and result analysis. The result shows that it can ensure the aircraft complete all missions in the shortest path. This improves the efficiency of UAV’s task execution, reduces the time loss of the control system, and facilitates the realization of the UAV formation flight system.

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邵长旭,王茂森,戴劲松,陈 斌.基于蚁群算法的无人机最短航路规划[J].,2018,37(09).

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  • 收稿日期:2018-06-17
  • 最后修改日期:2018-07-21
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  • 在线发布日期: 2018-11-05
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