A Pneumatic Soft Gripper with Configurable Workspace and Self-sensing

Qiwen Shao, Ningbin Zhang, Zequn Shen, Guoying Gu
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引用次数: 3

Abstract

In this paper, we present a novel pneumatic soft gripper with a configurable workspace and perception to grasp various objects and recognize their sizes. The soft gripper consists of three pneu-net soft fingers embedded with resistive strain sensors and cascaded by a stretchable palm. The pneu-net soft fingers are fabricated through a lost-wax casting process. Each strain sensor is designed with an ionic hydrogel-elastomer hybrid structure and embedded into a soft finger to recognize its deformation. The stretchable palm is designed with an opening-closing parallel mechanism driven by a pneumatic fiber-reinforced soft actuator to modify the grasping workspace of the gripper. The characterization experiments are conducted to demonstrate the excellent performance of soft gripper. Based on the measurement of the strain sensors, we propose two kinds of grasping strategies for the soft gripper: a traditional finger-bending identification strategy (FBI strategy) without the active palm and a new palm-closing identification strategy (PCI strategy) with the active palm. Experimental results with an industrial robot demonstrate that our soft gripper with the PCI strategy can perform more robust picking tasks and more accurate identification tasks than with the FBI strategy.
具有可配置工作空间和自感知的气动软夹持器
在本文中,我们提出了一种新颖的气动软爪,具有可配置的工作空间和感知,可以抓取各种物体并识别它们的大小。柔软的抓手由三个装有电阻应变传感器的软手指组成,并由一个可拉伸的手掌串联起来。软指是通过失蜡铸造工艺制造的。每个应变传感器都采用离子水凝胶-弹性体混合结构设计,并嵌入柔软的手指中以识别其变形。可伸缩手掌设计了由气动纤维增强软驱动器驱动的开合并联机构,以改变夹持器的抓取工作空间。通过表征实验验证了软夹持器的优良性能。基于应变传感器的测量结果,提出了两种软爪抓取策略:传统的无活动手掌的手指弯曲识别策略(FBI策略)和新的有活动手掌的手掌闭合识别策略(PCI策略)。在工业机器人上的实验结果表明,与FBI策略相比,PCI策略的软抓取器可以执行更稳健的抓取任务和更准确的识别任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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