@inproceedings{76cca3841d184b5bb55c75a8534d942d,
title = "Path Planning for Unmanned Surface Vehicle based on genetic algorithm and sequential quadratic programming",
abstract = "Path planning and obstacle avoidance of Unmanned Surface Vehicle (USV) is one of the hottest research topics in modem national defense and ocean engineering. Considering the issue of obstacle-free path planning of USV, this paper focuses on a 3-DoF USV and develops an algorithm design. We adopt Gauss pseudo-spectral method to discretize control model and make use of a hybrid algorithm to optimize which combines the advantage of genetic algorithm and sequential quadratic programming algorithm. Simulation results show that this method can quickly explore a high-precision route in an unknown environment which meets the mobility requirement of USV without setting the initial value artificially.",
keywords = "Unmanned Surface Vehicle (USV), genetic algorithm, path planning, sequential quadratic programming",
author = "Yufei Zhuang and Cheng Wang and Haibin Huang",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Chinese Automation Congress, CAC 2020 ; Conference date: 06-11-2020 Through 08-11-2020",
year = "2020",
month = nov,
day = "6",
doi = "10.1109/CAC51589.2020.9327234",
language = "英语",
series = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3513--3518",
booktitle = "Proceedings - 2020 Chinese Automation Congress, CAC 2020",
address = "美国",
}