Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning

Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key direc...

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Main Authors: Yang Wang, Tianze Hao, Yibo Liu, Huaping Xiao, Shuhai Liu, Hongwu Zhu
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Actuators
Subjects:
Online Access:https://www.mdpi.com/2076-0825/13/3/84
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author Yang Wang
Tianze Hao
Yibo Liu
Huaping Xiao
Shuhai Liu
Hongwu Zhu
author_facet Yang Wang
Tianze Hao
Yibo Liu
Huaping Xiao
Shuhai Liu
Hongwu Zhu
author_sort Yang Wang
collection DOAJ
description Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.
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spelling doaj.art-2291ce9269454858a3332fdd523c3a082024-03-27T13:15:22ZengMDPI AGActuators2076-08252024-02-011338410.3390/act13030084Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine LearningYang Wang0Tianze Hao1Yibo Liu2Huaping Xiao3Shuhai Liu4Hongwu Zhu5College of Mechanical and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, ChinaTianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384, ChinaCollege of Mechanical and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, ChinaCollege of Mechanical and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, ChinaCollege of Mechanical and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, ChinaCollege of Mechanical and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, ChinaHumans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.https://www.mdpi.com/2076-0825/13/3/84anthropomorphic soft handsoft roboticstactile sensordexterous
spellingShingle Yang Wang
Tianze Hao
Yibo Liu
Huaping Xiao
Shuhai Liu
Hongwu Zhu
Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
Actuators
anthropomorphic soft hand
soft robotics
tactile sensor
dexterous
title Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
title_full Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
title_fullStr Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
title_full_unstemmed Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
title_short Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning
title_sort anthropomorphic soft hand dexterity sensing and machine learning
topic anthropomorphic soft hand
soft robotics
tactile sensor
dexterous
url https://www.mdpi.com/2076-0825/13/3/84
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AT huapingxiao anthropomorphicsofthanddexteritysensingandmachinelearning
AT shuhailiu anthropomorphicsofthanddexteritysensingandmachinelearning
AT hongwuzhu anthropomorphicsofthanddexteritysensingandmachinelearning