通过速度/合规性操纵性优化解决重心管机器人的冗余性
Jia Shen1, Yifan Wang1, Milad Azizkhani1
1Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta 30332 USA.
概括
这项研究引入了一种新的方法,用于集中管机器人 (CTR) 改进使用操作性优化进行手术路径跟踪. 该框架提高了微创手术执行执行器命令的安全性和可行性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 最少侵入性的手术
- 控制系统 控制系统
背景情况:
- 集中管机器人 (CTR) 显示出对最小侵入性手术的承诺.
- 现有的CTR研究侧重于建模和控制,对路径跟踪的可操作性给予有限的关注.
- 操作性对于安全的运动和在CTR中可行的执行器命令至关重要.
研究的目的:
- 为CTRs提出一个基于梯度的冗余解决框架.
- 在路径跟踪过程中优化速度/合规性操纵性指数.
- 为了提高路径跟踪性能,并确保安全,可行的机器人运动.
主要方法:
- 开发了一个基于梯度的框架,用于在CTR中解决冗余问题.
- 使用Cosserat棒模型衍生品,用于高效的操纵度梯度计算.
- 采用零空间投影来优化特定任务的性能指数.
主要成果:
- 与有限差异方法相比,在梯度计算时间中实现了68%的减少.
- 通过提出的方法证明了成功完成任务.
- 与常用的冗余解决方案技术相比,展示了优越的性能.
结论:
- 拟议的框架有效地优化了CTR路径跟踪的操作性.
- 这种方法提高了手术运动的安全性和可行性.
- 与CTR控制的现有方法相比,提供了显著的改进.
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