中文版 | English
Title

Soft Robot Proprioception Using Unified Soft Body Encoding and Recurrent Neural Network

Author
Corresponding AuthorWang, Zheng
Publication Years
2023-03-01
DOI
Source Title
ISSN
2169-5172
EISSN
2169-5180
Abstract
Compared with rigid robots, soft robots are inherently compliant and have advantages in the tasks requiring flexibility and safety. But sensing the high dimensional body deformation of soft robots is a challenge. Encasing soft strain sensors into the internal body of soft robots is the most popular solution to address this challenge. But most of them usually suffer from problems like nonlinearity, hysteresis, and fabrication complexity. To endow the soft robots with body movement awareness, this work presents a bioinspired architecture by taking cues from human proprioception system. Differing from the popular usage of smart material-based sensors embedded in soft actuators, we created a synthetic analog to the human muscle system, using paralleled soft pneumatic chambers to serve as receptors for sensing body deformation. We proposed to build the system with redundant receptors and explored deep learning tools for generating the kinematic model. Based on the proposed methodology, we demonstrated the design of three degrees of freedom continuum joint and how its kinematic model was learned from the unified pressure information of the actuators and receptors. In addition, we investigated the response of the soft system to receptor failures and presented both hardware and software level solutions for achieving graceful degradation. This approach offers an alternative to enable soft robots with proprioception capability, which will be useful for closed-loop control and interaction with environment.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
Funding Project
Science, Technology and Innovation Commission of Shenzhen Municipality[ZDSYS20200811143601004] ; NSFC[51975268]
WOS Research Area
Robotics
WOS Subject
Robotics
WOS Accession No
WOS:000961052800001
Publisher
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/527719
DepartmentDepartment of Mechanical and Energy Engineering
Affiliation
1.Univ Hong Kong, Dept Mech Engn, Hong Kong, Peoples R China
2.Southern Univ Sci & Technol, Dept Mech & Energy Engn, 605 Innovat Pk 7,1088 Xueyuan Ave, Shenzhen 518055, Peoples R China
Corresponding Author AffilicationDepartment of Mechanical and Energy Engineering
Recommended Citation
GB/T 7714
Wang, Liangliang,Lam, James,Chen, Xiaojiao,et al. Soft Robot Proprioception Using Unified Soft Body Encoding and Recurrent Neural Network[J]. SOFT ROBOTICS,2023.
APA
Wang, Liangliang.,Lam, James.,Chen, Xiaojiao.,Li, Jing.,Zhang, Runzhi.,...&Wang, Zheng.(2023).Soft Robot Proprioception Using Unified Soft Body Encoding and Recurrent Neural Network.SOFT ROBOTICS.
MLA
Wang, Liangliang,et al."Soft Robot Proprioception Using Unified Soft Body Encoding and Recurrent Neural Network".SOFT ROBOTICS (2023).
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