Tactile-based Object Recognition

Tactile-Based Object Recognition is a methodological framework within robotic感知 systems that enables the identification of object properties and categories through the analysis of tactile sensory data obtained during physical interaction, distinguishing itself from other perception modalities by relying exclusively on somatosensory feedback from contact.

210

Publications

11.3K

Citations

626

Authors

254

Institutions

Publications per year

2017–2026

85

Authors

626

  1. FS
    Fuchun Sun

    Tsinghua University, China

    11 publications · 574 citations

    11

    h-index

  2. HL
    Huaping Liu

    Tsinghua University, China

    10 publications · 545 citations

    10

    h-index

  3. MK
    Mohsen Kaboli

    Technical University of Munich, Germany

    10 publications · 478 citations

    10

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  4. GC
    Gordon Cheng

    Technical University of Munich, Germany

    9 publications · 454 citations

    9

    h-index

  5. DG
    Di Guo

    Tsinghua University, China

    7 publications · 492 citations

    7

    h-index

1–5 of 626

Venues

  1. IEEE Robotics and Automation Letters

    8 publications · 313 citations

    8

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  2. Sensors

    8 publications · 279 citations

    8

    h-index

  3. 5

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  4. IEEE Transactions on Robotics

    5 publications · 414 citations

    5

    h-index

  5. 5

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1–5