一个新的算法用于视觉导航在无人机空中飞行器水面检查水面检查
Jianfeng Han1,2, Xiongwei Gao1,2, Lili Song1,2
1School of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Sensors (Basel, Switzerland)
|April 26, 2025
概括
本研究介绍了WaterSegLite,这是一个高效的算法,用于在水面检查期间无人驾驶飞行器 (UAV) 的视觉导航. 它可以实时对水体进行细分,改善水生环境监测.
科学领域:
- 环境科学 环境科学
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
背景情况:
- 水面检查对于水生环境保护至关重要.
- 无人驾驶飞行器 (UAV) 为大面积水域检查提供了高效的移动解决方案.
研究的目的:
- 为河流和湖泊引入新的无人机检查方法.
- 为无人机视觉导航开发一个高效的语义细分算法,WaterSegLite.
- 为了实现实时水体细分,并为无人机提供位置数据.
主要方法:
- 开发了两种针对河流和湖泊环境的无人机检查方法.
- 设计了WaterSegLite,一种轻量级的语义细分算法,利用空中视角和精简的神经网络.
- 集成的WaterSegLite用于实时细分和无人机视觉导航.
主要成果:
- WaterSegLite实现了93.81%的细分精度 (mIoU) 和95.44%的F1得分.
- 性能超过了基线模型的2.7% (mIoU) 和2.23% (F1得分).
- 算法在机载设备上达到28.27fps的处理率,满足实时要求.
结论:
- WaterSegLite有效地支持无人机实时检查水面.
- 该算法为水生环境中的无人机检查技术提供技术援助.
- 介绍了用于推进智能水面检查系统的创新概念.
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