Paoletti P, Jones G W, Mahadevan L
School of Engineering, University of Liverpool, Liverpool L69 3GH, UK.
School of Mathematics, University of Manchester, Manchester M13 9PL, UK.
J R Soc Interface. 2017 Mar;14(128). doi: 10.1098/rsif.2016.0867.
The interaction of a robotic manipulator with unknown soft objects represents a significant challenge for traditional robotic platforms because of the difficulty in controlling the grasping force between a soft object and a stiff manipulator. Soft robotic actuators inspired by elephant trunks, octopus limbs and muscular hydrostats are suggestive of ways to overcome this fundamental difficulty. In particular, the large intrinsic compliance of soft manipulators such as 'pneu-nets'-pneumatically actuated elastomeric structures-makes them ideal for applications that require interactions with an uncertain mechanical and geometrical environment. Using a simple theoretical model, we show how the geometric and material nonlinearities inherent in the passive mechanical response of such devices can be used to grasp soft objects using force control, and stiff objects using position control, without any need for active sensing or feedback control. Our study is suggestive of a general principle for designing actuators with autonomous intrinsic impedance control.
由于难以控制软物体与刚性机械手之间的抓握力,机器人操纵器与未知软物体的相互作用对传统机器人平台来说是一项重大挑战。受象鼻、章鱼触手和肌肉流体静力学启发的软体机器人致动器为克服这一基本困难提供了思路。特别是,诸如“气动网络”(气动驱动的弹性体结构)这类软机械手具有很大的固有柔顺性,使其非常适合需要与不确定的机械和几何环境进行交互的应用。通过一个简单的理论模型,我们展示了此类装置被动机械响应中固有的几何和材料非线性如何可用于通过力控制抓取软物体,以及通过位置控制抓取刚性物体,而无需任何主动传感或反馈控制。我们的研究为设计具有自主固有阻抗控制的致动器提出了一个通用原则。