Accurate recognition of object contour based on flexible piezoelectric and piezoresistive dual mode strain sensors

被引:42
作者
Gao, Zhiqiang [1 ]
Ren, Bing [1 ]
Fang, Zhaozhou [2 ]
Kang, Huiqiang [1 ]
Han, Jing [1 ]
Li, Jie [2 ]
机构
[1] North Univ China, Coll Mechatron Engn, Taiyuan 030051, Peoples R China
[2] North Univ China, Sch Mat Sci & Engn, Taiyuan 030051, Peoples R China
基金
中国国家自然科学基金;
关键词
Robot hand; Contour recognition; Combination of piezoelectric and; piezoresistive sensor; Conductive hydrogel; PVDF-TrFE; ZnO film; TACTILE SENSOR; COMPOSITES; SKIN;
D O I
10.1016/j.sna.2021.113121
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The application of flexible wearable sensors in the grasping process of robot hand can recognize the contour, soft and hard, material, surface temperature and other information of the grasping object, which can effectively improve the intelligent level of the robot. In this work, a method of object contour recognition is proposed by combining the flexible PVDF polymer piezoelectric sensor and high conductivity hydrogel piezoresistive sensor aiming at the problem of profile recognition for objects of the same or similar material. The response of flexible piezoresistive sensor to the static strain is used to sense the angular displacement of robot fingers, and then the shape and size of the object is recognized indirectly. At the same time, the flexible piezoelectric sensor is used as the fingertip tactile sensor to reflect the surface morphology of the object through the dynamic strain information when touching the object. In the whole process of grasping the object, the dual-mode strain information is fully used to realize the recognition of the shape, size and surface morphology of the object. Combining these information, the accurate recognition of the object contour can be further realized. In the experiments, six objects with different shape and four objects with different surface morphology are recognized to verify the feasibility of piezoresistive sensors and piezoelectric sensors respectively. In a comprehensive experiment, eight objects made of the same rubber material with different shape, size and surface morphology are recognized, and the average recognition rate is about 84%, which shows good classification advantages for the objects with similar shape, size and material. (c) 2021 Elsevier B.V. All rights reserved.
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页数:14
相关论文
共 39 条
  • [1] Piezoresistive flexible composite for robotic tactile applications
    Canavese, Giancarlo
    Stassi, Stefano
    Fallauto, Carmelo
    Corbellini, Simone
    Cauda, Valentina
    Camarchia, Vittorio
    Pirola, Marco
    Pirri, Candido Fabrizio
    [J]. SENSORS AND ACTUATORS A-PHYSICAL, 2014, 208 : 1 - 9
  • [2] Dahiya RS, 2009, 2009 2ND INTERNATIONAL WORKSHOP ON ELECTRON DEVICES AND SEMICONDUCTOR TECHNOLOGY, P101
  • [3] Recent progress on flexible and stretchable piezoresistive strain sensors: From design to application
    Duan, Lingyan
    D'hooge, Dagmar R.
    Cardon, Ludwig
    [J]. PROGRESS IN MATERIALS SCIENCE, 2020, 114 (114)
  • [4] Designing formulation variables of extrusion-based manufacturing of carbon black conductive polymer composites for piezoresistive sensing
    Duan, Lingyan
    Spoerk, Martin
    Wieme, Tom
    Cornillie, Pieter
    Xia, Hesheng
    Zhang, Jie
    Cardon, Ludwig
    D'hooge, Dagmar R.
    [J]. COMPOSITES SCIENCE AND TECHNOLOGY, 2019, 171 : 78 - 85
  • [5] Fang B, 2018, IEEE INT CONF ROBOT, P4740
  • [6] Highly Sensitive Impact Sensor Based on PVDF-TrFE/Nano-ZnO Composite Thin Film
    Han, Jing
    Li, Dong
    Zhao, Chunmao
    Wang, Xiaoyan
    Li, Jie
    Wu, Xinzhe
    [J]. SENSORS, 2019, 19 (04)
  • [7] Ho VA, 2009, IEEE INT CONF ROBOT, P1757, DOI 10.1109/ROBOT.2009.5152458
  • [8] Anthropomorphic robotic soft fingertip with randomly distributed receptors
    Hosoda, K
    Tada, Y
    Asada, M
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2006, 54 (02) : 104 - 109
  • [9] Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications
    Jin, Tao
    Sun, Zhongda
    Li, Long
    Zhang, Quan
    Zhu, Minglu
    Zhang, Zixuan
    Yuan, Guangjie
    Chen, Tao
    Tian, Yingzhong
    Hou, Xuyan
    Lee, Chengkuo
    [J]. NATURE COMMUNICATIONS, 2020, 11 (01)
  • [10] Robust Tactile Descriptors for Discriminating Objects From Textural Properties via Artificial Robotic Skin
    Kaboli, Mohsen
    Cheng, Gordon
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2018, 34 (04) : 985 - 1003