| 引用本文: | 耿正霖,程兴华,包长春.面向真实地形的水下航行器三维航路规划方法.[J].国防科技大学学报,2024,46(6):88-95.[点击复制] |
| GENG Zhenglin,CHENG Xinghua,BAO Changchun.3D path planning method for underwater vehicles based on real terrain[J].Journal of National University of Defense Technology,2024,46(6):88-95[点击复制] |
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| 面向真实地形的水下航行器三维航路规划方法 |
| 耿正霖1,程兴华2,包长春2 |
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(1. 国防科技大学 电子科学学院, 湖南 长沙 410073;2. 国防科技大学 气象海洋学院, 湖南 长沙 410073)
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| 摘要: |
| 针对目前水下航行器航路规划结果适用性不强的问题,提出一种基于改进粒子群算法的水下航行器三维航路规划算法。基于海区真实地形数据构建维诺图,利用Dijkstra算法生成满足航行安全要求的初始航路集,作为粒子群算法的初始粒子,提高了初始粒子生成效率,同时改进粒子位置更新方法,根据航路上节点的毗邻节点的位置引导粒子位置变化,使得规划航路更加平滑,更适于水下航行器的航行。仿真结果表明,该算法较传统粒子群算法,规划航路适用性更好,且优化结果更稳健。 |
| 关键词: 水下航行器 航路规划 平滑 粒子群优化算法 |
| DOI：10.11887/j.cn.202406009 |
| 投稿日期：2023-01-04 |
| 基金项目:国家自然科学基金资助项目(61702531) |
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| 3D path planning method for underwater vehicles based on real terrain |
| GENG Zhenglin1, CHENG Xinghua2, BAO Changchun2 |
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(1. College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China;2. College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China)
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| Abstract: |
| Aiming at the problem of poor applicability of current path planning results for underwater vehicles, a three-dimensional path planning algorithm for underwater vehicles based on improved particle swarm optimization algorithm was proposed. A Voronoi map based on the real terrain data of sea area was built, and the Dijkstra algorithm was used to generate the initial path set that meets the requirements of navigation safety as the initial particles of particle swarm optimization algorithm, so the generation efficiency of initial particles was improved. At the same time, the particles′ position update method was improved to guide the particle position change according to the position of adjacent nodes on the route, which makes the planned route smoother and more suitable for the navigation of underwater vehicles. Simulation results show that the proposed algorithm is more robust and has better applicability than the traditional particle swarm optimization algorithm in path planning. |
| Keywords: underwater vehicle path planning smooth particle swarm optimization algorithm |
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