从点云中提取,细分和3D重建线束,用于机器人运动规划
Saki Komoriya1, Hiroshi Masuda1
1Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-8585, Japan.
Sensors (Basel, Switzerland)
|December 31, 2025
概括
本研究介绍了一种自动化框架,可以从激光扫描中创建精确的3D电线束模型,从而提高机器人模拟安全性和数字双胞胎准确性.
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
- 几何建模 几何建模
背景情况:
- 精确的机器人模拟需要模拟像电缆带这样的灵活组件.
- 现有的方法缺乏精确的3D模型,导致模拟现实差异.
- 在CAD模型中,电线束经常被遗漏,阻碍了碰撞检测和安全.
研究的目的:
- 开发一个用于提取,细分和重建3D线束模型的自动化框架.
- 通过区分静态和动态带部件来实现现实的运动模拟.
- 改进机器人模拟中的碰撞检测和数字双胞胎准确性.
主要方法:
- 使用地面激光扫描点云的自动化框架.
- 运动感知细分,将带分为静态和动态组件.
- 双重构造:无分支电缆的OBB树和分支结构的Reeb图.
主要成果:
- 高准确度的3D电线束模型是从密集的,封闭的点云中生成的.
- 即使有严重的数据封闭,重建也成功.
- 已证明适用于工业机器人的碰撞检测和数字双胞胎模拟.
结论:
- 拟议的框架有效地解决了在机器人模拟中模拟柔性电缆束的挑战.
- 这项工作弥合了几何传感和基于物理的机器人模拟之间的差距.
- 在制造环境中实现更可靠,更安全的机器人操作.
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