Abstract: To solve the problems of long time consuming and large space occupation in the route planning process of Unmanned Underwater Vehicle (UUV) under complex environments and multi-constraint conditions, a new route planning method based on Charged System Search (CSS) was proposed. Firstly, the UUV route planning problem model was established, and the cost function was designed. Then, a route planning method based on CSS was presented, and the charged particle was affected by the electric field force of other charged particles in the search space to achieve the purpose of iterative optimization. In addition, a method of nonlinear adjustment of speed and acceleration parameters was proposed, which could effectively balance global search and local search processes, and avoid premature convergence of algorithm. Finally, the proposed method was compared with the route planning methods based on A^* algorithm, ant colony optimization algorithm and particle swarm optimization from two respects of the quality of planning route and the time consuming of algorithm. The experimental results show that, the proposed method has faster convergence speed and lower time complexity while ensuring the quality of planned route.

Key words: Unmanned Underwater Vehicle (UUV), Charged System Search (CSS), route planning, cost function, multi-objective optimization

摘要： 针对无人潜航器（UUV）在复杂环境、多约束条件下航路规划过程耗时长、占用空间大等问题，提出了基于带电粒子搜索（CSS）的航路规划方法。首先，建立UUV航路规划问题模型，设计代价函数；然后，给出了基于CSS的航路规划方法，带电粒子在搜索空间中会受到其他带电粒子电场力的作用进而迭代寻优；另外，提出了一种非线性调整速度与加速度参数的方法，通过该方法有效地平衡全局搜索与局部搜索过程，避免算法的早熟收敛。最后，通过对比实验从规划航路的质量和算法耗时两个角度将所提方法与A^*算法、蚁群算法、粒子群航路规划方法进行对比。实验结果表明该方法在保证规划出的航路质量的同时，具有更快的收敛速度、更低的时间复杂度。

关键词: 无人潜航器, 带电粒子搜索, 航路规划, 代价函数, 多目标优化