传输线维护无人机的生物模拟姿势估计和目标感知策略
Haoze Zhuo1,2, Zhong Yang1, Chi Zhang1
1College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Biomimetics (Basel, Switzerland)
|December 27, 2024
概括
本研究介绍了用于电力线路检查的生物无人机 (UAV) 战略. 它通过使用红外图像在输电线路上增强了目标检测和跟踪,提高了电网安全性和效率.
科学领域:
- 机器人和自动化 机器人和自动化
- 电气工程 电气工程
- 计算机视觉 计算机视觉
背景情况:
- 高压电力线对电网稳定性至关重要,需要及早检测异物.
- 智能机器人,特别是无人飞行器 (UAV),为复杂的电力线路检查挑战提供了解决方案.
- 传统的无人机缺乏强大的模式识别,自动跟踪和可靠的视觉测距,用于电力线环境.
研究的目的:
- 开发基于生物无人机的电力线检查姿势估计和目标感知策略.
- 克服现有的无人机检查方法在模式识别,自动跟踪和视觉测距方面的局限性.
- 通过先进的无人机能力提高电网运营的效率,经济性和安全性.
主要方法:
- 提出了一个基于无人机的生物技术策略,用于无人机的姿势估计和目标感知.
- 从红外图像中高效提取点和线特征的算法.
- 在电力线场景中为小型多旋转机无人机实施了目标检测和自动跟踪功能.
主要成果:
- 生物目标感知算法有效地从红外图像中提取关键特征.
- 在电力线环境中实现了无人机的目标检测和自动跟踪.
- 对于拟议的无人机感知策略来说,证明了低功耗.
结论:
- 基于生物无人机的无人机战略显著改善了对电力线路检查的环境感知.
- 开发的算法提供了增强的模式识别和自动跟踪功能.
- 这种方法有助于电网的安全,高效和经济运行.
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