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

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

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.

Original languageEnglish
Article number106773
JournalComputers and Electrical Engineering
Volume87
DOIs
StatePublished - Oct 2020

Keywords

  • Ant colony algorithm
  • Fireworks algorithm
  • Ocean current environment
  • Path planning
  • Unmanned underwater vehicle

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