| 引用本文: | 赵苗,高永琪,吴笛霄,等.复杂海战场环境下AUV全局路径规划方法.[J].国防科技大学学报,2021,43(1):41-48.[点击复制] |
| ZHAO Miao,GAO Yongqi,WU Dixiao,et al.AUV global path planning method in complex sea battle field environment[J].Journal of National University of Defense Technology,2021,43(1):41-48[点击复制] |
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| 复杂海战场环境下AUV全局路径规划方法 |
| 赵苗1,2,高永琪1,吴笛霄1,王鹏1,张洪刚1 |
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(1. 海军工程大学 兵器工程学院, 湖北 武汉 430033;2. 火箭军工程大学 导弹工程学院, 陕西 西安 710025)
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| 摘要: |
| 针对无人自主水下航行器(Autonomous Underwater Vehicle, AUV)在复杂海战场环境中路径规划时环境模型复杂、约束条件多的情况,建立了包括战场地形、敌方威胁、障碍物和海流场等在内的比较完善的海战场环境模型。以AUV航行时间、威胁时间最短为优化目标,给出了一种基于振荡型入侵野草优化(Invasive Weeds Optimization, IWO)算法的AUV全局路径规划方法,并分别与标准IWO算法、全振荡型IWO算法以及粒子群算法等三种路径规划算法比较。仿真结果表明,所提方法具有较强的寻优能力和鲁棒性,可在复杂海战场环境下为AUV高效地规划出满足性能要求的航行路径。 |
| 关键词: 无人自主水下航行器 海战场 全局路径规划 振荡型入侵野草优化算法 |
| DOI：10.11887/j.cn.202101006 |
| 投稿日期：2019-07-26 |
| 基金项目:国家部委基金资助项目(3020605010201) |
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| AUV global path planning method in complex sea battle field environment |
| ZHAO Miao1,2, GAO Yongqi1, WU Dixiao1, WANG Peng1, ZHANG Honggang1 |
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(1. College of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China;2. College of Missile Engineering, Rocket Force University of Engineering, Xi′an 710025, China)
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| Abstract: |
| In view of the path planning of the unmanned AUV (autonomous underwater vehicle) in the complex sea battlefield environment, the environment model is complex and there are many constraints. A relatively perfect sea battlefield environment model including battlefield shape, enemy threats, obstacles, and sea current field was established. The AUV navigation time and threat time were the shortest as the optimization goal, and an oscillation-based type was given. The AUV global path planning method of the oscillation IWO(invasive weeds optimization) algorithm was compared with other three path planning algorithms, such as the standard IWO algorithm, the full-oscillation IWO algorithm and the PSO (particle swarm optimization) algorithm respectively. Simulation results show that the proposed method which has strong searching ability and excellent robustness, can effectively plan the navigation path which meets the performance requirements for the AUV in the complex sea battlefield environment. |
| Keywords: unmanned autonomous underwater vehicle sea battlefield global path planning oscillation invasive weed optimization algorithm |
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