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路径规划和障碍回避的应用,用于河岸检查
Jhong-Wei Jhang1, Jih-Gau Juang1
1Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung 202301, Taiwan.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
一个无人驾驶飞行器 (UAV) 系统有效地检查河岸的垃圾,防止海洋污染. 这项技术使用先进的路径规划和避开障碍物,以实现高效的清理操作.
科学领域:
- 环境科学 环境科学
- 机器人和自动化 机器人和自动化
背景情况:
- 沿海污染主要来自陆地来源.
- 有效地管理河流废物对于保持海洋生态健康至关重要.
- 当前的检查方法可能缺乏对复杂的河流环境所需的效率和适应性.
研究的目的:
- 开发和评估用于河岸检查和垃圾识别的无人机 (UAV) 系统.
- 通过先进的算法,提高无人机在复杂的河流环境中的效率和适应性.
- 通过在污染物到达海洋之前识别污染物,促进积极的废物管理.
主要方法:
- 使用无人机 (UAV) 进行自主河岸检查.
- 实施了改进的粒子群集优化 (IPSO),采用模糊系统来优化路径规划.
- 集成了一个人工潜力场 (APF) 算法,用于实时动态避障.
主要成果:
- 无人机系统在复杂的环境中成功执行了河岸检查.
- 优化路径规划减少了能源消耗和检查时间.
- 避障系统有效应对突出的树枝等环境挑战.
结论:
- 拟议的无人机系统为监测和识别河岸废物提供了可行的解决方案.
- 这项技术可以通过及时清理,为防止海洋污染做出重大贡献.
- 集成先进的路径规划和避开障碍的整合提高了环境监测的运营效率.
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