Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing | |
Cui, Shaowei1,2; Wang, Rui6; Hu, Jingyi1,2; Zhang, Chaofan1,3; Chen, Lipeng5; Wang, Shuo3,4,6 | |
刊名 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT |
2022 | |
卷号 | 71页码:9 |
关键词 | Geometry Sensors Three-dimensional displays Estimation Image reconstruction Tactile sensors Color Depth estimation robotic sensing systems self-supervised learning tactile sensors |
ISSN号 | 0018-9456 |
DOI | 10.1109/TIM.2021.3136181 |
英文摘要 | Vision-based tactile sensors have recently shown promising contact information sensing capabilities in various fields, especially for dexterous robotic manipulation. However, dense contact geometry measurement is still a challenging problem. In this article, we update the design of our previous GelStereo tactile sensor and present a self-supervised contact geometry learning pipeline. Specifically, a self-supervised stereo-based depth estimation neural network (GS-DepthNet) is proposed to achieve real-time disparity estimation, and two specifically designed loss functions are proposed to accelerate the convergence of the network during the training process and improve the inference accuracy. Furthermore, extensive qualitative and quantitative experiments of perceived contact shape were performed on our GelStereo sensor. The experimental results verify the accuracy and robustness of the proposed contact geometry sensing pipeline. This updated GelStereo tactile sensor with dense contact geometric sensing capability has predictable application potential in the field of industrial and service robots. |
资助项目 | National Key Research and Development Program of China[2018AAA0103003] ; National Natural Science Foundation of China[U1913201] ; Chinese Academy of Sciences (CAS)[XDB32050100] ; CIE-Tencent Robotics X Rhino-Bird Focused Research Program ; Youth Innovation Promotion Association CAS[2020137] |
WOS关键词 | TACTILE ; MANIPULATION ; SENSORS |
WOS研究方向 | Engineering ; Instruments & Instrumentation |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000766300200060 |
资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Chinese Academy of Sciences (CAS) ; CIE-Tencent Robotics X Rhino-Bird Focused Research Program ; Youth Innovation Promotion Association CAS |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48135] |
专题 | 智能机器人系统研究 |
通讯作者 | Wang, Shuo |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Future Technol, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 5.Tencent Robot X Lab, Shenzhen 518054, Peoples R China 6.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Cui, Shaowei,Wang, Rui,Hu, Jingyi,et al. Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,2022,71:9. |
APA | Cui, Shaowei,Wang, Rui,Hu, Jingyi,Zhang, Chaofan,Chen, Lipeng,&Wang, Shuo.(2022).Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing.IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT,71,9. |
MLA | Cui, Shaowei,et al."Self-Supervised Contact Geometry Learning by GelStereo Visuotactile Sensing".IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 71(2022):9. |
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