Obstacle avoidance path planning of unmanned submarine vehicle in ocean current environment based on improved firework-ant colony algorithm

Yan Ma, Zhaoyong Mao, Tao Wang, Jian Qin, Wenjun Ding, Xiangyao Meng

科研成果: 期刊稿件文章同行评审

54 引用 (Scopus)

摘要

In order to solve the unmanned underwater vehicle two-dimensional autonomous path planning problem in the environment affected by ocean current and obstacles, this paper applies the improved Fireworks-Ant Colony Hybrid Algorithm to solve it. Firstly, a two-dimensional Lamb vortex ocean current environment model with randomly distributed obstacles is established, and the circular obstacle is equivalent to a square grid. Then, the mathematical model of path planning is established considering the energy consumption cost, navigation time cost and navigation distance cost. Finally, the improved fireworks-ant colony hybrid algorithm is applied to solve the nonlinear optimization problem, and this algorithm is compared with the basic ant colony algorithm for simulation experiments in the four different marine environments. The experimental results show that this algorithm can quickly find the global optimal solution, and the more complex the environment, the more obvious its advantages. The algorithm proposed in this paper provides a new way for autonomous path planning of underwater vehicles.

源语言英语
文章编号106773
期刊Computers and Electrical Engineering
87
DOI
出版状态已出版 - 10月 2020

指纹

探究 'Obstacle avoidance path planning of unmanned submarine vehicle in ocean current environment based on improved firework-ant colony algorithm' 的科研主题。它们共同构成独一无二的指纹。

引用此