An Improved Genetic Algorithm for Optimal Search Path of Unmanned Underwater Vehicles

Zhaoyong Mao, Peiliang Liu, Wenjun Ding, Guo Hui

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

To solve path planning problem of continuous space-time Markov moving targets for UUV search, an optimal path planning model is established. The search direction of the UUV is set as decision variables. An improved genetic algorithm is adopted to pursue an optimal path for underwater anti-submarine search. The algorithm utilizes an improved real number encoding method to describe the path. The target’s motion is assumed as uniform distribution in direction and normal distribution in velocity around an initial speed. The results show that the search path planning is more reasonable through a certain number of genetic and cross mutation operations. The proposed method has the advantages of high search efficiency, good stability and short reaction period, and is suitable for solving underwater path-searching problems.

源语言英语
主期刊名Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings
编辑Haibin Yu, Jinguo Liu, Lianqing Liu, Yuwang Liu, Zhaojie Ju, Dalin Zhou
出版商Springer Verlag
480-488
页数9
ISBN(印刷版)9783030275310
DOI
出版状态已出版 - 2019
活动12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 - Shenyang, 中国
期限: 8 8月 201911 8月 2019

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11741 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议12th International Conference on Intelligent Robotics and Applications, ICIRA 2019
国家/地区中国
Shenyang
时期8/08/1911/08/19

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