芬贝斯:软机器人手指的多目标贝叶斯优化框架
Xing Wang1, Bing Wang2, Joshua Pinskier1
1Robotics and Autonomous Systems, Data61, CSIRO, Brisbane, Australia.
Soft robotics
|March 18, 2024
概括
这项研究使用先进的计算方法增强软机器人设计. 它优化了Fin Ray抓手,以更好地遵守和强度,从而改善了现实世界的机器人应用.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算设计的计算设计.
- 材料科学 材料科学 材料科学
背景情况:
- 软机器人提供了高性能,灵活性和安全的互动.
- 计算设计是关键,但在评估准确性,代数和单一目标优化方面面临限制.
- 贝叶斯式方法对于设计太空探索中昂贵的分析系统是有效的.
研究的目的:
- 为了解决软机器人计算设计中的缺陷.
- 开发一个快速,准确的特征和广泛的设计空间探索的框架.
- 为了优化Fin Ray抓手用于多个目标,如合规性和接触力.
主要方法:
- 使用非线性有限元素建模套件进行准确的表征.
- 通过自动化设备和3D打印机器人手指进行了广泛的物理测试.
- 采用多目标贝叶斯优化器来探索合规与接触力之间的权衡.
主要成果:
- 实现了机器人设计的快速和准确的表征.
- 探索了更大的设计空间,发现了新的高性能设计.
- 确定了有前途的Fin Ray抓手设计,平衡了合规性和接触力.
结论:
- 开发的计算框架增强了软机器人设计优化.
- 经过3D打印和实际应用,优化的Fin Ray抓柄得到了验证.
- 这种方法可以发现具有更好的性能特征的优异机器人设计.
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