使用带有2DoF操纵器和立体视觉传感器的移动机器人进行自主混凝土裂监测
Seola Yang1, Daeik Jang2, Jonghyeok Kim3
1Department of Civil and Environmental Engineering, Hanbat National University, Daejeon 34158, Republic of Korea.
Sensors (Basel, Switzerland)
|October 16, 2025
概括
本研究介绍了一种用于混凝土裂监测和绘制地图的自主机器人. 机器人使用深度学习和立体视觉来检测,细分和高精度测量裂.
科学领域:
- 机器人和自动化机器人与自动化
- 结构健康监测 结构健康监测
- 计算机视觉 计算机视觉
背景情况:
- 保持混凝土结构的结构完整性需要有效的裂监测.
- 现有的方法可能缺乏效率或在大面积上缺乏全面的绘图能力.
研究的目的:
- 提出和验证一个移动地面机器人系统,用于在混凝土结构中进行自主裂监测和绘制地图.
- 通过使用先进的机器人技术和深度学习来提高裂纹检测和测量准确性.
主要方法:
- 使用了一台移动机器人,配备了2度自由度 (2-DoF) 操纵器,立体视觉传感器和手动旋转板.
- 他们使用了深度学习算法,包括YOLO (You Only Look Once) v6-s用于检测和SFNet (语义流网络) 进行细分.
- 合成图像生成,预处理和点云的中位数绝对偏差过用于增强裂纹分析.
主要成果:
- 该系统实现了自主裂检测,细分和维度计算.
- 预测了裂传播方向,从而实现了精确的机器人操纵.
- 来自多个的组合3D点云允许总裂纹长度和宽度的计算,最大相对误差为1%.
结论:
- 拟议的机器人系统证明了自主裂监测和绘制的可行和准确的解决方案.
- 机器人,深度学习和立体视觉的整合显著提高了结构性健康监测的效率和精度.
- 该方法显示了在基础设施维护和安全评估中实际应用的潜力.
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