IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-51261-5.html
   My bibliography  Save this article

Multimodal tactile sensing fused with vision for dexterous robotic housekeeping

Author

Listed:
  • Qian Mao

    (Tsinghua University)

  • Zijian Liao

    (Tsinghua University)

  • Jinfeng Yuan

    (Tsinghua University)

  • Rong Zhu

    (Tsinghua University)

Abstract

As robots are increasingly participating in our daily lives, the quests to mimic human abilities have driven the advancements of robotic multimodal senses. However, current perceptual technologies still unsatisfied robotic needs for home tasks/environments, particularly facing great challenges in multisensory integration and fusion, rapid response capability, and highly sensitive perception. Here, we report a flexible tactile sensor utilizing thin-film thermistors to implement multimodal perceptions of pressure, temperature, matter thermal property, texture, and slippage. Notably, the tactile sensor is endowed with an ultrasensitive (0.05 mm/s) and ultrafast (4 ms) slip sensing that is indispensable for dexterous and reliable grasping control to avoid crushing fragile objects or dropping slippery objects. We further propose and develop a robotic tactile-visual fusion architecture that seamlessly encompasses multimodal sensations from the bottom level to robotic decision-making at the top level. A series of intelligent grasping strategies with rapid slip feedback control and a tactile-visual fusion recognition strategy ensure dexterous robotic grasping and accurate recognition of daily objects, handling various challenging tasks, for instance grabbing a paper cup containing liquid. Furthermore, we showcase a robotic desktop-cleaning task, the robot autonomously accomplishes multi-item sorting and cleaning desktop, demonstrating its promising potential for smart housekeeping.

Suggested Citation

  • Qian Mao & Zijian Liao & Jinfeng Yuan & Rong Zhu, 2024. "Multimodal tactile sensing fused with vision for dexterous robotic housekeeping," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51261-5
    DOI: 10.1038/s41467-024-51261-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-51261-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-51261-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jinhui Zhang & Haimin Yao & Jiaying Mo & Songyue Chen & Yu Xie & Shenglin Ma & Rui Chen & Tao Luo & Weisong Ling & Lifeng Qin & Zuankai Wang & Wei Zhou, 2022. "Finger-inspired rigid-soft hybrid tactile sensor with superior sensitivity at high frequency," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ningning Bai & Yiheng Xue & Shuiqing Chen & Lin Shi & Junli Shi & Yuan Zhang & Xingyu Hou & Yu Cheng & Kaixi Huang & Weidong Wang & Jin Zhang & Yuan Liu & Chuan Fei Guo, 2023. "A robotic sensory system with high spatiotemporal resolution for texture recognition," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Nan Li & Yingxin Zhou & Yuqing Li & Chunwei Li & Wentao Xiang & Xueqing Chen & Pan Zhang & Qi Zhang & Jun Su & Bohao Jin & Huize Song & Cai Cheng & Minghui Guo & Lei Wang & Jing Liu, 2024. "Transformable 3D curved high-density liquid metal coils – an integrated unit for general soft actuation, sensing and communication," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Rui Chen & Tao Luo & Jincheng Wang & Renpeng Wang & Chen Zhang & Yu Xie & Lifeng Qin & Haimin Yao & Wei Zhou, 2023. "Nonlinearity synergy: An elegant strategy for realizing high-sensitivity and wide-linear-range pressure sensing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Liuting Shan & Qizhen Chen & Rengjian Yu & Changsong Gao & Lujian Liu & Tailiang Guo & Huipeng Chen, 2023. "A sensory memory processing system with multi-wavelength synaptic-polychromatic light emission for multi-modal information recognition," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51261-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.