【摘要】 当波浪滑翔器(wave glider, WG)在实际海洋环境中编队作业时，为了满足多种复杂的时空协同约束，调整编队构型至关重要，然而，WG依靠波浪能推进，这导致其运动控制具有非线性和不可预测性。因此针对这一问题，提出了一种基于约束分割多目标粒子群算法(constraint-segmented multi-objective particle swarm optimization, CS-MOPSO)的柔性编队路径规划方法，采用分治策略将预规划路径使用多个航路点分割，使用CS-MOPSO算法优化每个航路点处的编队构型，CS-MOPSO算法根据约束违反程度分割粒子种群，并引导粒子向可行解空间移动。使用Dubins曲线连接编队构型，构建具有柔性队形约束的协同路径。此外，提出了编队构型评价体系，用于定量地评估编队构型和编队路径。使用逼近理想解排序法来确定最优解。仿真结果表明，与其他算法相比，所提出算法在复杂约束条件下实现了更短的航行时间和更低的编队构型失真度。更多还原

【Abstract】 To meet complex space-time coordination constraints, it is crucial to adjust the formation configuration when the wave gliders(WG) formation performs cooperative tasks in challenging marine environments. The propulsion of the WG relying on wave energy leads to nonlinear and unpredictable motion control, to address this challenge, a flexible formation path planning method based on the constraint-segmentation and multi-objective particle swarm optimization(CS-MOPSO) algorithm was proposed. A divide and conquer strategy was used to segment a pre-planned path into multiple waypoints, and the formation configuration of each waypoint were optimized by the CS-MOPSO. The CS-MOPSO algorithm segments the particle population according to constraint violation level and guides particles toward feasible region. Dubins curves were employed to construct collaborative paths with flexible formation constraint. A formation configuration evaluation system was proposed for quantitative assessment of the formation configuration and cooperative path, and the technique for order preference by similarity to the ideal solution was used to identify the optimal solution. Simulation results show that compared to other algorithms, the proposed method achieves shorter navigation time and lower formation distortion under complex constraint.更多还原