尹逢川, 梁晓龙, 陶浩, 等. 海上无人系统时间协同航迹规划[J]. 中国舰船研究, 2022, 17(4): 57–70. doi: 10.19693/j.issn.1673-3185.02302
引用本文: 尹逢川, 梁晓龙, 陶浩, 等. 海上无人系统时间协同航迹规划[J]. 中国舰船研究, 2022, 17(4): 57–70. doi: 10.19693/j.issn.1673-3185.02302
YIN F C, LIANG X L, TAO H, et al. Time cooperative path planning for unmanned marine system[J]. Chinese Journal of Ship Research, 2022, 17(4): 57–70. doi: 10.19693/j.issn.1673-3185.02302
Citation: YIN F C, LIANG X L, TAO H, et al. Time cooperative path planning for unmanned marine system[J]. Chinese Journal of Ship Research, 2022, 17(4): 57–70. doi: 10.19693/j.issn.1673-3185.02302

海上无人系统时间协同航迹规划

Time cooperative path planning for unmanned marine system

  • 摘要:
      目的  为解决复杂环境下海上无人系统(UMS)时间协同航迹规划问题,提出一种基于差分进化(DE)算法的时间协同航迹规划方法。
      方法  首先,建立空中、海上和水下的自然环境与敌方威胁模型,构建多约束条件下的航迹规划目标函数,提出一种时间协同策略,解决在约束条件下异构平台出发时间和地点不同而同时同地到达的时间协同问题;然后,采用DE算法进行优化求解,研究航迹点数量对规划成功率的影响。
      结果  结果显示,在合理选择航迹点数量的基础上,DE算法可在威胁及障碍多的复杂环境下为海上无人系统规划出满足时间协同约束的航迹,使其到达目标的时间最短;航迹点数量过多或过少都会降低航迹规划的成功率。
      结论  研究表明所构建的模型和约束条件合理,使用的算法能够解决海上无人系统离线航迹规划的时间协同问题,具有一定的实用价值。

     

    Abstract:
      Objective  In order to solve the problem of time cooperative path planning for unmanned marine system (UMS) in complex environments, we propose a cooperative path planning method based on a differential evolution (DE) algorithm.
      Methods  First, natural environment and enemy threat models in the air, sea and underwater are established. The objective function of path planning with multiple constraints is constructed and a strategy proposed to solve the time coordination problem under the constraints of heterogeneous platforms starting at different times and places, but arriving at the same time and place. Next, a DE algorithm is used to optimize the solution, and the influence of the number of waypoints on the success rate of the planning is studied.
      Results  Based on the reasonable selection of the number of waypoints, the DE algorithm can respectively plan the path that satisfies the time cooperative constraint for the UMS and find the shortest time to reaching the target in complex environments with multiple threats and obstacles. The results also show that either excessive or inadequate numbers of waypoints will result in success rate reduction of the path planning.
      Conclusions  The results of this study show that the model and constraint conditions are reasonable, and the proposed algorithm can solve the problem of time coordination in the path planning of UMS, which has great practical application value.

     

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