@inproceedings{9ec0aafc95684228b3477f1c728eca99,
title = "Unmanned Surface Vehicle Cooperative Task Assignment Based on Genetic Algorithm",
abstract = "Task allocation modeling plays an important role in unmanned surface vehicles (USV) collaborative systems. In order to adapt to the complex environment, a cooperative multi-task assignment problem (CMTAP) model suitable for multi-USV, multi-target, and multi-task is designed. The article first clarifies the advantages of collaboration, then based on the traditional genetic algorithm (GA), the crossover and mutation operators are optimized to be more suitable for the current environment. This method utilizes the strong global search ability of GA to optimize the result of cooperative task assignment of USV. Simulation experiments demonstrate the effectiveness of the method.",
keywords = "collaboration, cooperative multi-task assignment problem, genetic algorithm, task assignment, unmanned surface vehicles",
author = "Qinghua Luo and Xiaozhen Yan and Di Wu and Ruochen Ding",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022 ; Conference date: 13-10-2022 Through 16-10-2022",
year = "2022",
doi = "10.1109/PHM-Yantai55411.2022.9941917",
language = "英语",
series = "2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Wei Guo and Steven Li",
booktitle = "2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022",
address = "美国",
}