@inproceedings{c820a3e7bfc74b7693d210642a9ff243,
title = "UAV online path planning based on improved genetic algorithm",
abstract = "When the traditional Genetic Algorithm(GA) is used for unmanned aerial vehicle(UAV) path planning, the shortcomings of local search ability are reflected when the planning time is more urgent. To address this shortcoming, this paper proposes an improved genetic algorithm that limits the new gene's generating region. The generating region of the evolution operator is dynamically adjusted. The algorithm is applied to UAV online path planning for tracking moving target. The simulation results show that the method enhances the local search ability of the algorithm and improves the searching efficiency. UAV online path planning can be completed well with the improved genetic algorithm.",
keywords = "Improved Genetic Algorithm, Local search ability, Moving Target, Online Path Planning, Searching Efficiency",
author = "Xiaohai Wang and Xiuyun Meng",
note = "Publisher Copyright: {\textcopyright} 2019 Technical Committee on Control Theory, Chinese Association of Automation.; 38th Chinese Control Conference, CCC 2019 ; Conference date: 27-07-2019 Through 30-07-2019",
year = "2019",
month = jul,
doi = "10.23919/ChiCC.2019.8866205",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4101--4106",
editor = "Minyue Fu and Jian Sun",
booktitle = "Proceedings of the 38th Chinese Control Conference, CCC 2019",
address = "United States",
}