实时物体检测用于通过无人机自动检查太阳能电站的实时物体检测
Javier Rodriguez-Vazquez1,2,3, Inés Prieto-Centeno1,2,3, Miguel Fernandez-Cortizas1,2
1Computer Vision and Aerial Robotics Group, Universidad Politécnica de Madrid (CVAR-UPM), 28040 Madrid, Spain.
Sensors (Basel, Switzerland)
|February 10, 2024
概括
本研究介绍了一种基于关键点的对象检测框架,用于使用无人机 (UAV) 进行实时太阳能发电场检查. 该方法提高了机器人任务的检测精度和操作效率.
科学领域:
- 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
- 人工智能的人工智能
背景情况:
- 太阳能发电场检查需要敏捷而精确的对象检测.
- 传统的方法,如边界框或细分,缺乏细节检查的细节性.
- 无人驾驶飞行器 (UAV) 越来越多地用于工业资产检查.
研究的目的:
- 为实时太阳能发电场检查引入基于关键点的创新物体检测框架.
- 通过专注于太阳能电池板顶部来提高对象检测的颗粒度.
- 优化嵌入式平台的框架,以实现高效的机器人操作.
主要方法:
- 开发了一个基于关键点的对象检测框架,灵感来自CenterNet.
- 为嵌入式平台 (例如,NVIDIA AGX Jetson Orin) 优化了架构.
- 集成的积极学习策略,以减少注释工作.
主要成果:
- 在1024 × 1376分辨率下达到60FPS左右,超过了相机的操作频率.
- 证明了对时间关键的工业检查至关重要的实时能力.
- 模型设计强调减少实际部署的计算需求.
结论:
- 基于关键点的物体检测为基于无人机的太阳能发电场检查提供了实用和有效的方法.
- 与传统方法相比,拟议的框架提供了更丰富的细节性.
- 该系统被优化为实时性能和减少计算负载.
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