摘要
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.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Proceedings of the 38th Chinese Control Conference, CCC 2019 |
| 编辑 | Minyue Fu, Jian Sun |
| 出版商 | IEEE Computer Society |
| 页 | 4101-4106 |
| 页数 | 6 |
| ISBN（电子版） | 9789881563972 |
| DOI | |
| 出版状态 | 已出版 - 7月 2019 |
| 活动 | 38th Chinese Control Conference, CCC 2019 - Guangzhou, 中国 期限: 27 7月 2019 → 30 7月 2019 |
出版系列
| 姓名 | Chinese Control Conference, CCC |
|---|---|
| 卷 | 2019-July |
| ISSN（印刷版） | 1934-1768 |
| ISSN（电子版） | 2161-2927 |
会议
| 会议 | 38th Chinese Control Conference, CCC 2019 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Guangzhou |
| 时期 | 27/07/19 → 30/07/19 |
指纹
探究 'UAV online path planning based on improved genetic algorithm' 的科研主题。它们共同构成独一无二的指纹。引用此
Wang, X., & Meng, X. (2019). UAV online path planning based on improved genetic algorithm. 在 M. Fu, & J. Sun (编辑), Proceedings of the 38th Chinese Control Conference, CCC 2019 (页码 4101-4106). 文章 8866205 (Chinese Control Conference, CCC; 卷 2019-July). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2019.8866205