| 面向复杂山地地形的多无人机测绘任务分配 / 航迹规划一体化求解方法研究 |
| Research on the integrated solution method of multi⁃UAV surveying and mapping task allocation and flight track planning for complex mountainous terrain |
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| 中文摘要: |
| 为了解决复杂山地地形环境下的无人机测绘任务分配问题，提出了一种面向复杂山地地形的多无人机测绘任务分配 / 航迹规划一体化求解方法。首先，基于山区不同地形的复杂程度，建立每个测绘区的无人机航迹规划模型；其次，以任务区的测绘时间及无人机各个任务点之间的飞行时间最短为优化目标，以无人机的航速、最大任务时长等为约束条件，建立多无人机测绘任务分配 / 航迹规划一体化模型；最后，基于分布式遗传算法对多无人机测绘任务分配一体化模型进行求解。开展实验验证算法的有效性，结果表明分布式遗传算法显著减少了测绘时间，提高了测绘效率。研究成果为无人机测绘任务分配提供了新的技术思路，为推动无人机测绘领域的发展起到了积极作用。 |
| 英文摘要: |
| To solve the problem of task allocation for drone mapping in complex mountainous terrain, a unified solution for multi?drone mapping task allocation / flight path planning was proposed. Firstly, a flight path planning model was established for each mapping area based on the complexity of different terrain in mountainous areas. Then, a unified model for multi?drone mapping task allocation / flight path planning was established with the optimization objective of minimizing the mapping time and flight time between various task points of the drone, and the constraints of the drone's cruising speed and maximum task duration, etc. Finally, the multi?drone mapping task allocation unified model was solved using a distributed genetic algorithm. An experimental verification was conducted to verify the effectiveness of the algorithm, and the results showed that the distributed genetic algorithm significantly reduced the mapping time and improved the mapping efficiency. The research findings provide a new technical approach for drone mapping task allocation and play a positive role in promoting the development of drone mapping. |
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| 中文关键词: 无人机测绘 山脉地貌 分布式遗传算法 航迹规划 |
| 英文关键词:UAV survey mountainous terrain distributed genetic algorithm flight path planning |
| 基金项目: |
| DOI：10.11823/j.issn.1674-5795.2024.04.06 |
| 引用本文：白艳, 宋崎, 胡为, 王继虎.面向复杂山地地形的多无人机测绘任务分配 / 航迹规划一体化求解方法研究[J].计测技术,2024,(4):. |
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