免费的力量:基于视觉的接触力估计与合规的手
Yifan Zhu1, Mei Hao1, Xupeng Zhu2
1Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, USA.
Science robotics
|June 25, 2025
概括
这项研究引入了一种基于视觉的系统,用于估计使用符合机器人手的接触力. 这种具有成本效益的方法利用了手的变形,为机器人操纵提供了传统力传感器的替代方案.
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
- 机械工程 机械工程
背景情况:
- 传统的力/扭矩传感器是昂贵的,沉重的,脆弱的.
- 触觉传感器的范围有限,电路脆弱.
- 机器人操纵需要精确的力感应.
研究的目的:
- 开发一个经济高效的,基于视觉的接触力估计器,用于符合机器人手.
- 为了利用弹性变形进行力预测.
- 为昂贵和脆弱的传统传感器提供替代品.
主要方法:
- 利用基于视觉的估计器观察一个符合3D打印标准的机器人手.
- 使用弹性变形分析来估计力.
- 将内存集成到估计器中,以解决摩擦和歇斯底里.
- 使用视觉基础模型来进行强大的指纹细分,以防止分心和闭塞.
主要成果:
- 在力估计中达到0.2到0.4牛顿的误差范围.
- 证明了估计器对背景噪声和手指遮的稳定性.
- 在各种操作任务中使用符合规范的抓器验证了实用性.
结论:
- 基于视觉的力估计器是传统传感器的可行,具有成本效益的替代方案.
- 该方法显示了提高机器人操纵能力的前景.
- 与商业传感器相比,进一步开发可以提高准确性和速度.
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