A Novel Humanoid Soft Hand with Variable Stiffness and Multi-modal Perception *

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2021-07-03 DOI:10.1109/ICARM52023.2021.9536073

Bin Fang, Qingchao Wang, Shixin Zhang, Ziwei Xia, F. Sun, Xiao Lu, Yiyong Yang, Licheng Wu

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引用次数: 5

Abstract

The human hand can adjust stiffness freely to realize different grasp modes, which is beneficial to adapting to different weights of objects. Therefore, humans have been trying different strategies to simulate hand, such as various rigid hand or soft hand, using different structure designs and materials. In this paper, we propose a novel five-finger soft hand. The layer jamming structure is used to increase stiffness and the vision-based tactile sensor is used to provide perception in the soft hand. Through the grasping experiment, the results show that the soft hand can effectively transmit into different grasping modes and adaptively grasp objects of different shapes. Besides, the tactile data is collected by the sensor and a recognition model is built. Through the test, the accuracy is up to 98.75%. In summary, the grasping ability of the soft hand is satisfied, and the combination of tactile sensor and variable stiffness improves performance further.

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一种具有变刚度和多模态感知的新型仿人软手

人手可以自由调节刚度，实现不同的抓取方式，有利于适应不同重量的物体。因此，人类一直在尝试不同的策略来模拟手，例如使用不同的结构设计和材料来模拟各种刚性手或柔软手。在本文中，我们提出了一种新的五指软手。采用层卡结构增加软性手的刚度，采用视觉触觉传感器提供软性手的感知。通过抓取实验，结果表明，软手可以有效地转换为不同的抓取模式，并自适应抓取不同形状的物体。此外，传感器采集触觉数据并建立识别模型。经测试，准确率可达98.75%。综上所述，软手的抓取能力得到了满足，触觉传感器与变刚度的结合进一步提高了性能。

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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来源期刊

2021 6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

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