A Novel Soft Robotic Hand Design With Human-Inspired Soft Palm
A Novel Soft Robotic Hand Design With Human-Inspired Soft Palm
复制标题
一种新颖的软机器人手设计，具有仿人类软手掌
DOI：
10.1109/mra.2021.3065870
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发表时间：
2021
影响因子：
5.7
通讯作者：
Xu He
中科院分区：
文献类型：
--
作者：
Wang Haihang;Abu-Dakka Fares J.;Le Tran Nguyen;Kyrki Ville;Xu He
软机器人手和抓取器作为机器人末端执行器越来越受到关注。与刚性机械手相比，柔性机械手在人与机器人、环境与机器人的交互中更安全、更易于控制、更柔顺、成本更低、重量更轻。然而，手掌也是抓握的重要组成部分。在这项工作中，我们提出了一种新颖的设计，一个廉价的软人形手气动软手指和软手掌。软手掌的配置基于模块化设计，其可应用于致动不同种类的现有软手指。手指的张开，整个手掌的弯曲，拇指的外展和内收都是由手掌来实现的。此外，我们提出了一种新的软手指设计，称为混合弯曲软手指（HBSF），它可以在抓握轴上弯曲，并在左右轴上偏转，实现类似人类的运动（图1）。HBSF和软手掌的功能进行评估，在模拟，使用模拟开放框架架构（SOFA）的框架，和实验。分析了具有1-11个纵向段的六个手指设计。软手的多功能性的评估和实验证明，其根据Feix的分类的物体的把握。结果表明，掌握了很大的多样性，与31的33个把握类型的分类成功地执行与建议的设计，显示了把握各种各样的不同形状和重量的物体的承诺。
Soft robotic hands and grippers are increasingly attracting attention as robotic end effectors. Compared with their rigid counterparts, they are safer for human-robot and environment-robot interactions, easier to control, and more compliant, and they cost and weigh less. Design studies of soft robotic hands have focused mostly on the soft fingers and bending actuators. However, the palm is also an essential part in grasping. In this work, we propose a novel design for an inexpensive soft humanoid hand with pneumatic soft fingers and a soft palm. The configuration of the soft palm is based on a modular design that can be applied to actuate different kinds of existing soft fingers. The splaying of the fingers, bending of the whole palm, and abduction and adduction of the thumb are implemented by the palm. Moreover, we present a new design of soft finger, called the hybrid-bending soft finger (HBSF), that can both bend in the grasping axis and deflect in the side-to-side axis, achieving human-like motion (Figure 1). The functions of the HBSF and soft palm are evaluated both in simulation, using the Simulation Open Framework Architecture (SOFA) framework, and experimentally. Six finger designs with 1-11 longitudinal segments are analyzed. The versatility of the soft hand is evaluated and demonstrated experimentally by its grasping of objects according to Feix's taxonomy. The results demonstrate a great diversity of grasps, with 31 of the 33 grasp types of the taxonomy performed successfully with the proposed design, showing promise for grasping a large variety of objects with different shapes and weights.