Improved Genetic Algorithm Based on Oscillation Factor to Solve the AUV Path Planning Problem

Abstract

In this paper, the bi-objective AUV path planning problem considering the shortest path and the minimum path smoothness is studied. Firstly, a mathematical model of the problem is established and a two-dimensional Cartesian coordinate system model is used to model the AUV working environment. Then the dual objective is normalized and transformed into an adaptation function by dimensionality reduction. An improved Genetic Algorithm is proposed to solve the problem according to its characteristics. An initial solution generation strategy for the n-1 equipartition method based on the improved oscillation factor is designed, and an elite retention strategy with simulated annealing operation is introduced to improve the genetic strategy. To verify the effectiveness of the improved algorithm in this paper, simulation experiments were conducted by the Microsoft Visual Studio platform. After the comparison and analysis of the three algorithms, the algorithm proposed in this paper has shorter and smoother paths, faster convergence speed, and more obvious advantages in the quality of the solution.