由锥形介电弹性体致动器驱动的软抓手,可实现位移放大和顺应性抓取

IF 2.3 4区 计算机科学 Q3 ROBOTICS
Ning Li, Yanwen Xue, Yajiao Li, Changhao Liu, Qingyuan Du, Yao Huang, Yingjie Jiang, Jingyao Sun
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引用次数: 0

摘要

柔性介电弹性致动器(DEA)在具有智能系统的软体机器人中具有重要意义。它们克服了传统刚性系统的缺点,从而扩大了在可穿戴设备中的应用。然而,现有的软机器人末端执行器的抓取适应性有限,通常需要传感器和控制算法的复杂耦合,才能实现应用数据驱动的智能抓取。这种复杂性大大增加了制造成本和设计难度。在这种情况下,我们提出了一种由锥形 DEA 驱动的简单、自适应和多功能双指软抓手(DFSG),以实现顺应性抓取。DFSG 由三个主要部分组成:锥形致动器、夹具和力传输机构。最初,我们通过调整锥形致动器的几何结构、预紧力和偏置电压来优化其输出性能。DFSG 利用了锥形致动器垂直位移大(即输入力大)的特点,利用了所设计的力传输机构的高效位移放大功能(最多 9 倍)。它将垂直方向的输入力转换为水平方向的抓取力。因此,所开发的 DFSG 不仅能轻松抓取规则和坚硬的物体,还能抓取具有挑战性的物体,如小的、不规则的、软的或易挤压的物体。值得注意的是,只需一层 DEA,它就能夹住自身重量的 14.5 倍。这项研究为设计具有自适应能力和高可靠性的软抓手提供了指导,为软机器人系统的发展提供了一条前景广阔的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A soft gripper driven by conical dielectric elastomer actuator to achieve displacement amplification and compliant grips

A soft gripper driven by conical dielectric elastomer actuator to achieve displacement amplification and compliant grips

Flexible dielectric elastomeric actuators (DEAs) have become significant in soft robots with intelligent systems. They overcome the shortcomings of traditional rigid systems, thereby expanding their applications in wearable devices. However, existing soft robot end-effectors have limited grasping adaptability and often require a complex coupling of sensors and control algorithms to achieve application data-driven smart grasping. This complexity significantly increases manufacturing costs and design difficulties. In this context, we present a simple, adaptive, and versatile double-finger soft gripper (DFSG) driven by a conical DEA to achieve compliant grips. The DFSG consists of three main parts: a conical actuator, clamp, and force transmission mechanism. Initially, we optimize the output performance of the conical actuator by tailoring its geometric structure, preload force, and bias voltage. The DFSG exploits the tapered actuator's characteristic of large vertical displacement (i.e., large input force) by utilizing the efficient displacement amplification function (up to 9 times) of the designed force transmission mechanism. It converts the input force in the vertical direction into a gripping force in the horizontal direction. As a result, the developed DFSG can easily grasp not only regular and stiff objects but also challenging objects such as small, irregular, soft, or squeezable items. Notably, it can clamp up to 14.5 times its own weight with just one layer of DEA. This work provides guidance for designing soft grippers with adaptive and high reliability, offering a promising avenue for the advancement of soft robotic systems.

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来源期刊
CiteScore
5.70
自引率
4.00%
发文量
46
期刊介绍: The journal directs special attention to the emerging significance of integrating robotics with information technology and cognitive science (such as ubiquitous and adaptive computing,information integration in a distributed environment, and cognitive modelling for human-robot interaction), which spurs innovation toward a new multi-dimensional robotic service to humans. The journal intends to capture and archive this emerging yet significant advancement in the field of intelligent service robotics. The journal will publish original papers of innovative ideas and concepts, new discoveries and improvements, as well as novel applications and business models which are related to the field of intelligent service robotics described above and are proven to be of high quality. The areas that the Journal will cover include, but are not limited to: Intelligent robots serving humans in daily life or in a hazardous environment, such as home or personal service robots, entertainment robots, education robots, medical robots, healthcare and rehabilitation robots, and rescue robots (Service Robotics); Intelligent robotic functions in the form of embedded systems for applications to, for example, intelligent space, intelligent vehicles and transportation systems, intelligent manufacturing systems, and intelligent medical facilities (Embedded Robotics); The integration of robotics with network technologies, generating such services and solutions as distributed robots, distance robotic education-aides, and virtual laboratories or museums (Networked Robotics).
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