基于弹性力传输的可控制增长连续机器人 (GCCR) 的自刚性调整研究
Mingyuan Wang1,2, Jianjun Yuan1,2, Sheng Bao1,2
1Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.
Biomimetics (Basel, Switzerland)
|September 27, 2023
概括
研究人员为可增长控制连续机器人 (GCCR) 开发了一种新的刚性调整机制 (SAM). 这项创新提高了运动精度和机器人的刚性,没有额外的执行器,提高了复杂环境中的性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 机械工程 机械工程
- 材料科学 材料科学 材料科学
背景情况:
- 连续机器人在复杂的环境中具有很高的适应性,但由于其灵活的结构,在精确的运动和负载能力方面面临挑战.
- 刚度调整对于提高连续机器人的性能和适用性至关重要.
研究的目的:
- 在可增长控制连续机器人 (GCCR) 中提出和实施度调整机制 (SAM).
- 通过可变刚度控制来提高连续机器人的运动精度和承载能力.
- 通过静态建模和实验测试来验证SAM的有效性.
主要方法:
- 一种新的刚性调整机制 (SAM) 被设计并集成到可控制生长的连续机器人 (GCCR) 中.
- 在机器人长度变化过程中,通过对抗性电缆力传输实现了自我刚性调整.
- 开发了一个理论静态模型来预测机器人形状在重力和端负荷下变形.
主要成果:
- 集成的SAM显示有效增强了近79.6%的度.
- 实验验证证证实了静态模型的准确性,最大误差率在5.65%.
- SAM具有简单的结构,对机器人重量和质量分布的影响最小,不需要独立的执行器.
结论:
- 拟议的SAM显著提高了GCCR的刚性和运动精度.
- 开发的静态模型准确地预测机器人的变形,有助于设计和控制.
- 这种方法提供了一种实际的解决方案,用于在苛刻的应用中提高连续机器人的性能.
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