基于考虑航向切换压力的改进蚁群优化算法的自主水下航行器三维平滑路径规划

3D smooth path planning of AUV based on improved ant colony optimization considering heading switching pressure.

作者信息

Meng Ronghua, Sun Aiwen, Wu Zhengjia, Du Xuan, Meng Yongdong

机构信息

Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang, 443002, Hubei, China.

Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance, China Three Gorges University, Yichang, 443002, Hubei, China.

出版信息

Sci Rep. 2023 Jul 31;13(1):12348. doi: 10.1038/s41598-023-39346-5.

DOI:10.1038/s41598-023-39346-5

PMID:37524812

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10390500/

Abstract

A smooth and secure spatial path planning algorithm that integrates the improved ant colony optimization with the corrective connected spatial search strategy is proposed, aiming at heavy heading switching pressure of autonomous underwater vehicles sailing in complex marine environment. On the one hand, to overcome the low-dimensional search domain and inaccurate spatial communication information in traditional spatial path planning, the spatial connectivity adjacency domain search strategy is designed based on grid environment model. On the other hand, to alleviate heading switching pressure due to large path steering angles and redundant path turning points, the heuristic functions and pheromone update criterion based on ant colony optimization are introduced to improve the solution quality of smooth paths. The simulation results show that the space search strategy can improve the success probability of safe path planning without reducing the scope of explorable free space. Additionally, the simulations demonstrate that the improved ant colony optimization using the spatial search strategy can guarantee the shortest path with lowest tortuous degree and fewest turning times in the same grid environment.

摘要

针对自主水下航行器在复杂海洋环境中航行时航向切换压力大的问题，提出了一种将改进蚁群优化算法与修正连接空间搜索策略相结合的平滑安全空间路径规划算法。一方面，为克服传统空间路径规划中搜索域维度低和空间通信信息不准确的问题，基于网格环境模型设计了空间连通邻域搜索策略。另一方面，为缓解因路径转向角大及路径冗余转折点导致的航向切换压力，引入基于蚁群优化的启发式函数和信息素更新准则，以提高平滑路径的求解质量。仿真结果表明，该空间搜索策略可在不减小可探索自由空间范围的情况下提高安全路径规划的成功率。此外，仿真还表明，在相同网格环境下，采用空间搜索策略的改进蚁群优化算法能够保证路径最短、曲折度最低且转弯次数最少。