以无人艇 (unmanned surface vessel, USV) 为对象, 对其全局路径规划问题展开研究.针对传统 A∗ 算法进行规划时存在算法效率低、求解路径长度仅仅是栅格最优而非实际最优,且转折点多、路径不平滑等缺点, 提出了双向并行化处理和精英扩展搜索策略来提高算法的搜索性能. 同时, 采用路径剪枝优化和三次 B 样条曲线优化方式打破了栅格环境的限制, 对路径进一步优化. Matlab 仿真实验结果证明, 改进后的 A∗ 算法为无人艇提供了一种更加合适有效的全局路径规划算法.

This study took unmanned surface vessels (USVs) as the research objects to conduct a research on their global path planning. The traditional A∗ algorithm in global path planning for USVs has many shortcomings, such as the low efficiency of the algorithm, the length of the solution path being only grid optimal rather than actual optimal, and there being many turning points and uneven paths. Bidirectional parallelization and an elite extended search strategy were proposed to improve the search performance of the algorithm, and path pruning optimization and cubic B-spline curve optimization were used to break the constraints of the grid environment to further optimize the path. Matlab simulation experiments proved that the improved A∗ algorithm provided a more suitable and effective global path planning algorithm for USVs.