Deep-Learning-Assisted Underwater 3D Tactile Tensegrity
The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data an...
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| Published in | Research (Washington) Vol. 6; p. 0062 |
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| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
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United States
AAAS
2023
American Association for the Advancement of Science (AAAS) |
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| Abstract | The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals’ musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback. |
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| AbstractList | The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals’ musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback. The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals' musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals' musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback. |
| Author | Xu, Peng Guan, Tangzhen Liu, Jianhua Liu, Xiangyu Wang, Xinyu Zheng, Jiaxi Fu, Xianping Xu, Minyi Xie, Guangming Wang, Siyuan Wang, Zhong Lin |
| AuthorAffiliation | 5 School of Materials Science and Engineering , Georgia Institute of Technology , Atlanta, GA 30332-0245 , USA 2 School of Information Science and Technology , Dalian Maritime University , Dalian 116026 , China 4 Beijing Institute of Nanoenergy and Nanosystems , Chinese Academy of Sciences , Beijing 100871 , China 1 Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College , Dalian Maritime University , Dalian 116026 , China 3 Intelligent Biomimetic Design Lab, College of Engineering , Peking University , Beijing 100871 , China |
| AuthorAffiliation_xml | – name: 1 Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College , Dalian Maritime University , Dalian 116026 , China – name: 2 School of Information Science and Technology , Dalian Maritime University , Dalian 116026 , China – name: 4 Beijing Institute of Nanoenergy and Nanosystems , Chinese Academy of Sciences , Beijing 100871 , China – name: 5 School of Materials Science and Engineering , Georgia Institute of Technology , Atlanta, GA 30332-0245 , USA – name: 3 Intelligent Biomimetic Design Lab, College of Engineering , Peking University , Beijing 100871 , China |
| Author_xml | – sequence: 1 givenname: Peng surname: Xu fullname: Xu, Peng organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 2 givenname: Jiaxi surname: Zheng fullname: Zheng, Jiaxi organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 3 givenname: Jianhua surname: Liu fullname: Liu, Jianhua organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 4 givenname: Xiangyu surname: Liu fullname: Liu, Xiangyu organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 5 givenname: Xinyu surname: Wang fullname: Wang, Xinyu organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 6 givenname: Siyuan surname: Wang fullname: Wang, Siyuan organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 7 givenname: Tangzhen surname: Guan fullname: Guan, Tangzhen organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 8 givenname: Xianping surname: Fu fullname: Fu, Xianping organization: School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China – sequence: 9 givenname: Minyi surname: Xu fullname: Xu, Minyi organization: Dalian Key Laboratory of Marine Micro/Nano Energy and Self-powered Systems, Marine Engineering College, Dalian Maritime University, Dalian 116026, China – sequence: 10 givenname: Guangming surname: Xie fullname: Xie, Guangming organization: Intelligent Biomimetic Design Lab, College of Engineering, Peking University, Beijing 100871, China – sequence: 11 givenname: Zhong Lin surname: Wang fullname: Wang, Zhong Lin organization: Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100871, China., School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0245, USA |
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| Copyright | Copyright © 2023 Peng Xu et al. Copyright © 2023 Peng Xu et al. 2023 Peng Xu et al. |
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| Snippet | The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an... |
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| Title | Deep-Learning-Assisted Underwater 3D Tactile Tensegrity |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/36930813 https://www.proquest.com/docview/2788797742 https://pubmed.ncbi.nlm.nih.gov/PMC10013964 https://doaj.org/article/9eba1c874a5f430c9570138d8faedacf |
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