一个光伏面板清洁机器人,有一个轻量级的YOLO v8清洁机器人
Jidong Luo1,2,3, Guoyi Wang1,2,3, Yanjiao Lei1,2,3
1College of Mechanical and Electrical Engineering, Tarim University, Alar, China.
Frontiers in robotics and AI
|November 17, 2025
概括
这项研究引入了一个自主机器人来清洁光伏电池板,提高了23%的效率. 机器人利用先进的AI进行检测和导航,克服了手动清洁的局限性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 可再生能源系统可再生能源系统
背景情况:
- 光伏 (PV) 面板上的污垢和灰尘显著降低了太阳能转换效率.
- 太阳能发电站的手动清洗方法往往不一致,效率低下,并且由于高电压和高电流而带来安全风险.
研究的目的:
- 开发一台用于光伏电池板的自动清洁机器人.
- 为了改善光伏清洁机器人的检测,路径规划和动作控制.
- 提高光伏电站维护的整体效率和安全性.
主要方法:
- 将轻量级的移动视觉变压器 (Mobile-VIT) 与自我注意机制集成,以增强YOLOv8 (You Only Look Once v8) 对象检测模型.
- 改进A*和动态窗口方法 (DWA) 路径规划算法,以实现高效的机器人导航.
- 开发用于自主清洁光伏电池板的动作控制系统.
主要成果:
- 改进后的YOLOv8模型实现了91.08%的精度和每秒215的处理速度.
- 路线规划模拟显示,时间消耗从1.19秒减少到0.66秒,转从23秒减少到10秒.
- 机器人成功地自主清洁光伏阵列,导致清洁率增加23%.
结论:
- 开发的清洁机器人有效地解决了手动维护光伏电池板的挑战.
- 该研究证明了深度学习,计算机视觉和机器人导航在可再生能源维护中的成功应用.
- 这些发现为未来在自主光伏电站维护方面的技术应用提供了宝贵的参考.
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