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arXiv 2403.19293cs.ROcs.SYeess.SY
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面向搬运任务的绳驱并联机器人自适应预紧力控制

Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task

University of Stuttgart(斯图加特大学);ISW

Thomas Reichenbach, Johannes Clar, Andreas Pott, Alexander Verl

AI总结:

本文针对绳驱并联机器人搬运任务,提出基于驱动冗余性与扩展零空间公式的自适应预紧力控制方法,并通过仿真与实验验证了其在运动与操作过程中动态调节平台刚度的有效性。

摘要:

本文提出了一种基于绳驱并联机器人(CDPR)驱动冗余性的绳索预紧力动态调整方法,该方法可根据任务需求提高或降低平台刚度。通过使用运动学的扩展零空间公式计算预紧参数来实现这一目标。该方法便于操作者在操作空间内指定所需的预紧力。相关算法在实时环境中实现,从而能够在混合位置-力控制中使用优化方法。为验证该方法的有效性,进行了仿真研究,并将所得结果与现有方法进行了比较。此外,还在实验中对该方法进行了研究,并与绳驱机器人的传统位置控制运行方式进行了对比。结果表明,在平台运动及操作附加物体的过程中自适应调整绳索预紧力是可行的。

英文摘要:

This paper presents a method for dynamic adjustment of cable preloads based on the actuation redundancy of \acp{CDPR}, which allows increasing or decreasing the platform stiffness depending on task requirements. This is achieved by computing preload parameters with an extended nullspace formulation of the kinematics. The method facilitates the operator's ability to specify a defined preload within the operation space. The algorithms are implemented in a real-time environment, allowing for the use of optimization in hybrid position-force control. To validate the effectiveness of this approach, a simulation study is performed, and the obtained results are compared to existing methods. Furthermore, the method is investigated experimentally and compared with the conventional position-controlled operation of a cable robot. The results demonstrate the feasibility of adaptively adjusting cable preloads during platform motion and manipulation of additional objects.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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