Robotic stiffness control and calibration as applied to human grasping tasks
Robotic stiffness control and calibration as applied to human grasping tasks
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DOI：
10.1109/70.611319
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发表时间：
1997-08-01
期刊：
影响因子：
--
通讯作者：
Johansson, RS
中科院分区：
文献类型：
--
作者：
Kao, I;Cutkosky, MR;Johansson, RS
本文研究了刚度分析在人类抓取中的应用，抓取刚度已被证明对机器人的建模和控制是有用的，抓取的一般线性R-3×3刚度矩阵的计算可以分解为对称(保守)和反对称(非保守)分量，为机器人和人类抓取的刚度控制提供了物理上的见解，提出了利用最小二乘最优拟合的方法，并将其应用于从抓取任务中获得的力和位移数据，以研究人类的抓取行为，这项研究的结果表明，力和位移之间的线性关系能够捕捉到位移较小(约1-7 mm)的人类抓取实验数据的特征，机器人文献中提出和发展的不同方法被用来预测人类抓取在外部载荷作用下的行为。
In this paper, we study stiffness analysis as applied to human grasping, Grasp stiffness has been demonstrated to be useful for modeling and controlling robotic manipulators, The computation of general linear R-3 x 3 stiffness matrices for grasping, which can be decomposed into symmetric (conservative) and antisymmetric (nonconservative) components, offers physical insights for stiffness control in robotics as well as human grasping, Methods of stiffness calibration, using least-squares best fits with and without symmetry constraints, are presented and applied to the force and displacement data obtained from grasping tasks to study human grasping behaviors, The results of this study show that a linear relationship between force and displacement is capable of capturing the characteristics of the experimental data of human grasps for which displacements are small (on the order of one to seven mm), Different measures, proposed and developed in the robotics literature, are employed to predict the behavior of human grasps in reacting to externally applied loads.