基于改进ACO的带续航约束无人机全覆盖作业路径规划

doi:10.7527/S1000-6893.2022.27856

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基于改进ACO的带续航约束无人机全覆盖作业路径规划

于全友,徐止政,段纳,徐蜜觅,程义

江苏师范大学

收稿日期:2022-07-26 修回日期:2023-02-04 出版日期:2023-02-06 发布日期:2023-02-06
通讯作者: 徐止政
基金资助:
江苏省研究生科研与实践创新计划项目;国家自然科学基金项目;江苏省高等学校自然科学研究面上项目

Coverage operation path planning of UAV with endurance constraints based on improved ACO

Received:2022-07-26 Revised:2023-02-04 Online:2023-02-06 Published:2023-02-06

摘要/Abstract

摘要： 本文研究带续航约束的电动多旋翼无人机全覆盖作业路径规划问题。首先，基于扫描线路径生成方法建立了带续航约束的无人机全覆盖作业路径规划的数学模型，然后，针对该路径规划模型中路径节点拓扑结构动态变化的特点，提出了改进的蚁群算法。该蚁群算法给出了无人机返航时机判断机制和返航点计算方法，设计了动态局部距离矩阵，提出了滚动权值加权和的信息素更新机制，在寻优过程中兼顾全局启发性信息和局部启发性信息。最后，采用规则地形和复杂地形多田块作业算例进行仿真实验验证，算例结果验证了本文算法的有效性和优越性。

关键词: 无人机, 全覆盖作业, 路径规划, 续航约束, 蚁群算法

Abstract: This paper studies the path planning problem of full coverage operation of electric multi-rotor UAV with endurance con-straint. Firstly, a mathematical model of path planning for UAV full coverage operation with endurance constraints was established based on the scanline path generation method. Then, an improved ant colony optimization(ACO) was pro-posed for the dynamic change of path node topology in the path planning model. The ACO provides the judgment mecha-nism of UAV return time and calculation method of return point, designs the dynamic local distance matrix, and proposes the pheromone updating mechanism of rolling weight weighted sum, which takes into account both global and local heu-ristic information in the optimization process. Finally, an example of multi-field operation on regular terrain and complex terrain is used to verify the effectiveness and superiority of the proposed algorithm

Key words: UAV, full coverage operation, path planning, endurance constraint, ACO

于全友徐止政段纳徐蜜觅程义. 基于改进ACO的带续航约束无人机全覆盖作业路径规划[J]. 航空学报, doi: 10.7527/S1000-6893.2022.27856.

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于改进ACO的带续航约束无人机全覆盖作业路径规划

Coverage operation path planning of UAV with endurance constraints based on improved ACO

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