Data-driven electrical resistance tomography for robotic large-area tactile sensing

被引:2
作者
Zheng, Wendong [1 ,2 ]
Liu, Huaping [2 ]
Liu, Xiaofeng [3 ]
Sun, Fuchun [2 ]
机构
[1] Tianjin Univ Technol, Sch Elect Engn & Automat, Tianjin 300382, Peoples R China
[2] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
[3] Hohai Univ, Key Lab Maritime Intelligent Cyberspace Technol, Minist Educ, Changzhou 213022, Peoples R China
基金
中国国家自然科学基金;
关键词
Microrobots; -; Nanorobots;
D O I
10.1007/s11432-023-4130-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
ConclusionIn this article, a novel DDERT sensing method is proposed for large-area tactile sensing. In particular, the method utilizes a generative model to reconstruct the boundary measurement voltage of the ERT sensor into a tactile image. To improve the quality of tactile imaging, a spatial attention mechanism is incorporated into the model. Additionally, a mask constraint is introduced as prior information to ensure that the generated images contain more accurate tactile information in areas of contact with objects. Experimental results validate the proposed method is effective for the large-area robotic tactile sensing. Furthermore, the prototype of the ERT-based tactile sensor is fabricated and the sensing performance is evaluated in real robotic applications.
引用
收藏
页数:2
相关论文
共 3 条
  • [1] Liu Huaping., 2020, Brain Science Advances, V6, P132
  • [2] Deep Neural Network Based Electrical Impedance Tomographic Sensing Methodology for Large-Area Robotic Tactile Sensing
    Park, Hyunkyu
    Park, Kyungseo
    Mo, Sangwoo
    Kim, Jung
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2021, 37 (05) : 1570 - 1583
  • [3] Adaptive Optimal Electrical Resistance Tomography for Large-Area Tactile Sensing
    Zheng, Wendong
    Liu, Huaping
    Guo, Di
    Yang, Wuqiang
    [J]. 2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2023), 2023, : 10338 - 10344