A Hybrid Algorithm Based on Ant Colony and Genetic Algorithm for AUV Path Planning

被引：4

作者：

Hu, Jihong ^{[1
]}

Er, Meng Joo ^{[1
]}

Liu, Tianhe ^{[1
]}

Wang, Siqi ^{[1
]}

机构：

[1] Dalian Maritime Univ, Inst Artificial Intelligence & Marine Robot, Coll Marine Elect Engn, Dalian 116026, Peoples R China

来源：

2023 2ND CONFERENCE ON FULLY ACTUATED SYSTEM THEORY AND APPLICATIONS, CFASTA | 2023年

关键词：

autonomous underwater vehicle; ant colony optimization; genetic algorithm; path planning;

D O I：

10.1109/CFASTA57821.2023.10243252

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a hybrid algorithm based on ant colony optimization (ACO) and genetic algorithm(GA) is proposed for path planning of an autonomous underwater vehicle. The novel algorithm, which combines ACO and GA has the following features: (1) It plans path through ACO; (2) GA is used to find the optimal path; (3) A new evaluation function is proposed and is adjusted to select a relatively smooth path; (4) The number of search points is reduced to reduce computation

引用

页码：888 / 893

页数：6

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