在电力线路场景中,用于无人机返回任务的规模不变的临近探测器
Jiannan Zhao1, Qidong Zhao1, Chenggen Wu2
1Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, School of Electrical Engineering, Guangxi University, Nanning 530004, China.
Biomimetics (Basel, Switzerland)
|February 25, 2025
概括
这项研究引入了用于无人机 (UAV) 的尺度不变垂直探测器 (SILD),以防止电线碰撞. SILD 增强了对迫在眉的威胁的实时检测,改善了在电网维护期间的无人机安全.
科学领域:
- 机器人和自动化机器人与自动化
- 计算机视觉 计算机视觉
- 航空航天工程 航空航天工程
背景情况:
- 无人驾驶飞行器 (UAV) 对于电网维护至关重要,但面临与电力线的碰撞风险.
- 传统的视觉系统和现有的深度学习方法在动态场景中难以实时检测薄电线.
研究的目的:
- 为在电力线附近运行的无人机开发一种新的实时防撞系统.
- 解决目前检测复杂电力线和动态威胁的方法的局限性.
主要方法:
- 提出了一个以生物运动探测 (Lobula巨型运动探测器) 为灵感的尺度不变垂直探测器 (SILD).
- 实现了预处理,注意力面具以增强运动,并模拟生物唤醒以识别威胁.
- 将SILD与Hough转换和D-LinkNet进行比较,用于静态电力线路检测.
主要成果:
- SILD在检测精度和实时处理效率之间取得了平衡.
- 该系统有效地检测到迫在眉的威胁,并预测高速飞行期间即将发生的碰撞.
- 在不同尺度上对迫在眉的物体实现了一致的灵敏度,克服了运动视觉的限制.
结论:
- SILD非常适合基于无人机的电力线路检测,提供高精度和低延迟性能.
- 该模型成功地部署在无人机嵌入式板上,用于现实世界避免碰撞的测试.
- 这种方法为无人机在电力线环境中避开障碍提供了一个新的解决方案.
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