三维无人机飞行器路径规划利用人工大猩猩部队优化器结合组合突变和二次插值运算符
Chen Ye1, Peng Shao1, Shaoping Zhang1
1School of Computer and Information Engineering, Jiangxi Agricultural University, 330045, China.
ISA transactions
|April 26, 2024
概括
一个增强的人工大猩猩部队优化器 (OQMGTO) 增强了复杂地形中的3D无人机路径规划. 这种方法改善了避开障碍的方法,并找到安全可靠的飞行路径,优于现有的算法.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 优化算法 优化算法
背景情况:
- 3D无人机 (UAV) 路径规划在现实地形和动态障碍环境中是复杂的.
- 现有的算法在具有挑战性的场景中与局部最佳和融合作斗争.
研究的目的:
- 提出一个增强的人工大猩猩部队优化器 (OQMGTO),以实现最佳的3D无人机路径规划.
- 增强无人机在复杂环境中逃避局部最佳并汇聚到全球最佳路径的能力.
主要方法:
- OQMGTO结合了组合突变,二次插值和基于随机对立的学习.
- 一个路径规划模型是构建的飞行距离,平滑度和地形碰撞的约束.
- OQMGTO算法优化了这个模型,以解决复杂的路径规划问题.
主要成果:
- 在模拟的多障碍和动态障碍地形场景中,OQMGTO表现出卓越的性能.
- 对CEC2017测试套件的验证证实了OQMGTO是一个强大的优化工具.
- 现实世界飞行任务显示,OQMGTO在复杂的地形上规划平滑,无碰撞的轨迹.
结论:
- OQMGTO算法有效地解决了复杂的现实场景中的3D无人机路径规划.
- 与其他方法相比,OQMGTO提供安全,可靠和优越的飞行路径解决方案.
- 拟议的战略显著提高了融合和避免障碍的能力.
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