无人驾驶Ariel车辆 (UAV) 路径规划用于智能地雷检测系统中的区域细分
Ahmed Barnawi1, Krishan Kumar2, Neeraj Kumar1
1Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
本研究介绍了使用无人机 (UAV) 探测地雷的自动化框架. 该系统优化无人机飞行路径,以便在受污染地区进行高效和安全的空中调查.
科学领域:
- 机器人技术和自主系统
- 环境工程 环境工程
- 地理空间分析的研究.
背景情况:
- 地雷污染构成全球威胁,需要有效和安全的检测方法.
- 目前的地雷检测是昂贵的,耗时的,潜在的危险,特别是在未知的地区.
- 无人驾驶飞行器 (UAV) 为探测地雷的空中传感提供了一个有前途的平台.
研究的目的:
- 开发一个基于无人机的地雷检测的自主框架.
- 优化无人机覆盖路线,以有效扫描受污染地区.
- 提高地雷检测过程的安全性和有效性.
主要方法:
- 使用深度学习通过图像细分来提取感兴趣的区域.
- 开发一个自动化系统来规划最佳的无人机覆盖路线.
- 评估多个覆盖路径模式,以实现理想的空中勘测设计.
主要成果:
- 成功开发了一种基于无人机的自主地雷检测的新型框架.
- 该框架展示了全面的空中调查的有效路线规划.
- 在不同复杂度的不同目标领域验证了有效性.
结论:
- 拟议的框架提高了使用无人机探测地雷的自动化和效率.
- 优化覆盖路径规划对于基于无人机的调查中的资源管理至关重要.
- 这种方法显著提高了识别地雷威胁的安全性和有效性.
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