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基于模型的3D形状重建软机器人通过分布式应变传感
Liangshu Liu1,2, Xinghao Huang1,2, Xiaoci Zhang2
1Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, California, USA.
Soft robotics
|May 23, 2025
概括
本研究介绍了一种使用分布式软应变传感器和基于模型的框架来进行软机器人自身感应的新方法. 这种方法可以准确地重建形状,以便在复杂的环境中进行更安全的导航和交互.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 材料科学 材料科学 材料科学
- 机械工程 机械工程
背景情况:
- 对于软机器人在非结构化环境中的自主性至关重要.
- 目前用于形状重建的传感和机器学习方法的适用性有限.
- 软机器人需要先进的传感器来进行安全的交互和导航.
研究的目的:
- 为软机器人开发一种广泛适用的形状重建方案.
- 为了增强软机器人的自身感应,使用软应变传感器.
- 克服当前基于机器学习的重建方法的局限性.
主要方法:
- 在机器人表面上使用稀疏分布的软应变传感器 (可拉伸电容).
- 将传感器数据集成到具有机械约束的基于模型的重建框架中.
- 采用了优化算法,用于准确的局部应变测量和形状预测.
主要成果:
- 在软条变形中达到不到4%的最大位移误差.
- 精确重建了软气动抓手在抓取过程中的形状.
- 在复杂的场景中表现出多功能性,具有生物灵感的手臂.
结论:
- 拟议的分布式应变传感器方案为软机器人自身感知提供了一个方便和多功能解决方案.
- 这种方法增强了软机器人的感知自身形状和变形的能力.
- 该方法在不同的软机器人系统和环境中广泛适用.
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