基于蚁群融合D*Lite的动态改航路径规划
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国家自然科学基金面上项目(42075007); 灾害天气国家重点实验室开放项目(2021LASW-B19); 苏州大学计算机信息处理技术省重点实验室开放项目(KJS2275)


Dynamic Diversion Path Planning Based on Combination of Ant Colony Optimization and D*Lite
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    摘要:

    危险天气下的改航与受限区划设和路径规划算法密切相关, 本文针对改航环境构建中Graham扫描结果存在较大无效区域, 提出分块后并行扫描. 针对危险天气的突发性, 为了适用于复杂环境, 提出在增量式的D*Lite全局规划路径基础上智能分割、蚁群算法局部搜索的复合结构动态规划方法. 通过改进信息素更新策略解决收敛速度慢、耗时长且易陷入局部最优的缺点. 实验结果表明, 分块并行Graham扫描划设的飞行受限区形状更接近实际, 面积缩至原先的48.1%. 改进蚁群融合D*Lite的复合结构动态路径规划算法D*Lite-ACO兼顾全局与局部, 将重规划范围控制到当前位置与目标点间, 在路径长度、规划时间和迭代范围上的评价指标分别提升1.2%、40.7%、66.7%.

    Abstract:

    Diversion in severe weather is closely related to the designation of forbidden areas and path planning algorithms. Given the large invalid area in the Graham scanning results in the construction of the diversion environment, this study proposes a delineation method of Graham parallel scanning after the area is divided into blocks. For the sudden occurrence of severe weather and complex environments, the study proposes a dynamic programming method of composite structure conducting intelligent segmentation and ant colony algorithm local search based on incremental D*Lite global planning path. The pheromone updating strategy is improved to solve the shortcomings of slow convergence speed, long time consumed, and tendency to fall into local optimum. The experimental results show that the shape of the flight forbidden areas designated by Graham parallel scanning based on the divided blocks is closer to reality, and the area is reduced to 48.1% of the original one. D*Lite-ACO, an improved ant colony fusion D*Lite dynamic path planning algorithm for composite structures, takes both the global and local area into account and controls the replanning range between the current position and the targeted point. The evaluation metrics in path length, planning time, and iteration range are improved by 1.2%, 40.7%, and 66.7%, respectively.

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张文,方巍.基于蚁群融合D*Lite的动态改航路径规划.计算机系统应用,2023,32(8):250-258

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  • 收稿日期:2023-02-08
  • 最后修改日期:2023-03-08
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  • 在线发布日期: 2023-05-19
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