| 多约束条件下无人机航迹规划 |
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| 引用本文： | 李昱奇,刘志乾,程凝怡,王莹莹,朱春丽.多约束条件下无人机航迹规划[J].计算机工程与应用,2021,57(4):225-230. |
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| 作者姓名： | 李昱奇 刘志乾 程凝怡 王莹莹 朱春丽 |
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| 作者单位： | 1.中国石油大学（北京） 安全与海洋工程学院，北京 102249
2.中国石油大学（北京） 机械与储运工程学院，北京 102249
3.中海油研究总院有限责任公司，北京 100027 |
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| 基金项目： | 国家高技术船舶科研项目;国家重点研发计划项目 |
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| 摘 要： | 针对多约束条件下的无人机航迹快速规划问题，建立了导航精度约束下无人机航迹规划模型，并设计了“基于Dijkstra算法的航迹规划法”求解模型。通过校正策略优选、校正方案优选和O-D邻接矩阵处理方式，简化搜索路径，降低计算量，提高执行效率，从而实现对传统Dijkstra算法的改进。在满足导航精度约束条件的前提下，以航迹长度最短和经过校正点数量最少为研究目标进行仿真实验，并将所得结果与传统Dijkstra算法和遗传算法所得结果分别进行对比，发现此算法在精度与复杂度方面均优于传统算法和遗传算法。此结果表明，导航精度约束下无人机航迹规划模型和“基于Dijkstra算法的航迹规划法”在解决多约束下无人机航迹规划问题方面具有一定的正确性、有效性和先进性。
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| 关 键 词： | 航迹规划 导航精度约束 Dijkstra算法 遗传算法 误差校正 |
Path Planning of UAV Under Multi-constraint Conditions |
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| LI Yuqi,LIU Zhiqian,CHENG Ningyi,WANG Yingying,ZHU Chunli.Path Planning of UAV Under Multi-constraint Conditions[J].Computer Engineering and Applications,2021,57(4):225-230. |
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| Authors: | LI Yuqi LIU Zhiqian CHENG Ningyi WANG Yingying ZHU Chunli |
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| Affiliation: | 1.College of Safety and Ocean Engineering, China University of Petroleum, Beijing 102249, China
2.College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
3.China National Offshore Oil Corporation Research Institute, Beijing 100027, China |
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| Abstract: | To solve the quick path planning problem of UAVs（Unmanned Aerial Vehicles） under multiple constraints, a UAVs path planning model under the navigation accuracy constraint is established and a method of path planning based on Dijkstra algorithm is proposed. Through the optimization of the correction strategies and schemes with the O-D adjacency matrix, the traditional Dijkstra algorithm is improved by simplifying the search path, reducing the computational complexity and enhancing the execution efficiency. On the premise of satisfying the constraint condition of navigation accuracy, the simulation experiment is carried out with the shortest path length and the least number of correction points as the research target. By comparing the results with the traditional Dijkstra algorithm and genetic algorithm, it is found that the algorithm is better than the other two in accuracy and complexity. The experiment shows that the UAVs path planning model under the navigation accuracy constraint and the method of path planning based on Dijkstra algorithm are correct, effective and advanced in solving the problem of UAVs path planning under the multi-constraint conditions. |
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| Keywords: | path planning navigation accuracy constraint Dijkstra algorithm genetic algorithm error correction |
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