Machine Learning Assisted Electronic/Ionic Skin Recognition of Thermal Stimuli and Mechanical Deformation for Soft Robots

作者全名："Shi, Xuewei; Lee, Alamusi; Yang, Bo; Ning, Huiming; Liu, Haowen; An, Kexu; Liao, Hansheng; Huang, Kaiyan; Wen, Jie; Luo, Xiaolin; Zhang, Lidan; Gu, Bin; Hu, Ning"

作者地址："[Shi, Xuewei; Lee, Alamusi; Yang, Bo; Liu, Haowen; An, Kexu; Liao, Hansheng; Wen, Jie; Hu, Ning] Hebei Univ Technol, Sch Mech Engn, Tianjin 300401, Peoples R China; [Ning, Huiming] Chongqing Univ, Coll Aerosp Engn, Chongqing 400044, Peoples R China; [Huang, Kaiyan; Gu, Bin] Southwest Univ Sci & Technol, Sch Mfg Sci & Engn, 59 Qinglong Rd, Mianyang 621010, Sichuan, Peoples R China; [Luo, Xiaolin] Tianjin Univ Tradit Chinese Med, Teaching Hosp 1, Natl Clin Res Ctr Chinese Med Acupuncture & Moxib, Tianjin 300381, Peoples R China; [Zhang, Lidan] Chongqing Med Univ, Sch Basic Med, Chongqing 400042, Peoples R China; [Hu, Ning] Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China; [Hu, Ning] Hebei Univ Technol, Minist Educ, Key Lab Adv Intelligent Protect Equipment Technol, Tianjin 300401, Peoples R China"

通信作者："Lee, A; Yang, B; Hu, N (通讯作者)，Hebei Univ Technol, Sch Mech Engn, Tianjin 300401, Peoples R China.; Hu, N (通讯作者)，Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China.; Hu, N (通讯作者)，Hebei Univ Technol, Minist Educ, Key Lab Adv Intelligent Protect Equipment Technol, Tianjin 300401, Peoples R China."

来源：ADVANCED SCIENCE

ESI学科分类：PHYSICS

WOS号：WOS:001244000300001

JCR分区：Q1

影响因子：15.1

年份：2024

卷号：11

期号：30

开始页：　

结束页：　

文献类型：Article

关键词：electronic/ionic conductive hydrogel; machine learning; mechanical deformation; thermal stimuli

摘要："Soft robots have the advantage of adaptability and flexibility in various scenarios and tasks due to their inherent flexibility and mouldability, which makes them highly promising for real-world applications. The development of electronic skin (E-skin) perception systems is crucial for the advancement of soft robots. However, achieving both exteroceptive and proprioceptive capabilities in E-skins, particularly in terms of decoupling and classifying sensing signals, remains a challenge. This study presents an E-skin with mixed electronic and ionic conductivity that can simultaneously achieve exteroceptive and proprioceptive, based on the resistance response of conductive hydrogels. It is integrated with soft robots to enable state perception, with the sensed signals further decoded using the machine learning model of decision trees and random forest algorithms. The results demonstrate that the newly developed hydrogel sensing system can accurately predict attitude changes in soft robots when subjected to varying degrees of pressing, hot pressing, bending, twisting, and stretching. These findings that multifunctional hydrogels combine with machine learning to decode signals may serve as a basis for improving the sensing capabilities of intelligent soft robots in future advancements."

基金机构："Chinese National Natural Science Fund [12227801, 32300666, 52305602]; Fund for Innovative Research Groups of Natural Science Foundation of Hebei Province [A2020202002]; Natural Science Foundation of Chongqing [cstc2021jcyj-msxmX0241, cstb2023nscq-msx0303]; Post-graduate's Innovation Fund Project of Hebei Province [CXZZBS2023035]; Key Technologies and Demonstration Application Research Project for Large-scale Lithium-ion Hybrid Energy Storage Equipment [HC23118]; Hebei Province Military-civilian Integration Science and Technology Innovation Project [SJMYF2022X15]"

基金资助正文："This work was supported by the Chinese National Natural Science Fund (Grant Nos.: 12227801, 32300666, 52305602), the Fund for Innovative Research Groups of Natural Science Foundation of Hebei Province (A2020202002), Natural Science Foundation of Chongqing (cstc2021jcyj-msxmX0241, cstb2023nscq-msx0303), Hebei Province Military-civilian Integration Science and Technology Innovation Project (SJMYF2022X15), Post-graduate's Innovation Fund Project of Hebei Province (CXZZBS2023035) and Key Technologies and Demonstration Application Research Project for Large-scale Lithium-ion Hybrid Energy Storage Equipment (HC23118)."