Autonomous Path Planning Method of UUV in Complex Environment Based on Improved Ant Colony Optimization Algorithm
Linlin Wang, Yang Li, Huawei Xie, Yi‐Min Wang, Xuefeng Xu · 2021 China Automation Congress (CAC) · 2021
This paper uses a modified ant colony optimization (ACO) algorithm based on heuristic to simulate the three-dimensional (3D) underwater route planning of unmanned underwater vehicles (UUV). In view of the complex marine environment such as "favorable zone" and "unfavorable zone" caused by underwater ridge and marine environmental factors, this paper has carried out research on the improvement of ant colony algorithm for 3D route planning considering safety, concealment, rapidity and smoothness as multiple optimization objectives. The simulation results show that the improved ACO algorithm can well satisfy the requirements of fixed depth direct navigation, which can reduce the course change frequency of UUV. Furthermore, it can make better use of the attraction area and avoid the exclusion area, which provides technical support for the route planning of UUV in complex underwater combat environment, and has good engineering feasibility.