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ACROSS: A Deformation-Based Cross-Modal Representation for Robotic Tactile Perception

Wadhah Zai El Amri, Malte Kuhlmann, Nicolás Navarro-Guerrero

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Abstract

Tactile perception is essential for human interaction with the environment and is becoming increasingly crucial in robotics. Tactile sensors like the BioTac mimic human fingertips and provide detailed interaction data. Despite its utility in applications like slip detection and object identification, this sensor is now deprecated, making many valuable datasets obsolete. However, recreating similar datasets with newer sensor technologies is both tedious and time-consuming. Therefore, adapting these existing datasets for use with new setups and modalities is crucial. In response, we introduce ACROSS, a novel framework for translating data between tactile sensors by exploiting sensor deformation information. We demonstrate the approach by translating BioTac signals into the DIGIT sensor. Our framework consists of first converting the input signals into 3D deformation meshes. We then transition from the 3D deformation mesh of one sensor to the mesh of another, and finally convert the generated 3D deformation mesh into the corresponding output space. We demonstrate our approach to the most challenging problem of going from a low-dimensional tactile representation to a high-dimensional one. In particular, we transfer the tactile signals of a BioTac sensor to DIGIT tactile images. Our approach enables the continued use of valuable datasets and data exchange between groups with different setups.

OriginalspracheEnglisch
Titel des Sammelwerks2025 IEEE International Conference on Robotics and Automation, ICRA 2025
Herausgeber/-innenChristian Ott, Henny Admoni, Sven Behnke, Stjepan Bogdan, Aude Bolopion, Youngjin Choi, Fanny Ficuciello, Nicholas Gans, Clement Gosselin, Kensuke Harada, Erdal Kayacan, H. Jin Kim, Stefan Leutenegger, Zhe Liu, Perla Maiolino, Lino Marques, Takamitsu Matsubara, Anastasia Mavromatti, Mark Minor, Jason O'Kane, Hae Won Park, Hae-Won Park, Ioannis Rekleitis, Federico Renda, Elisa Ricci, Laurel D. Riek, Lorenzo Sabattini, Shaojie Shen, Yu Sun, Pierre-Brice Wieber, Katsu Yamane, Jingjin Yu
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten5836-5842
Seitenumfang7
ISBN (elektronisch)9798331541392
ISBN (Print)979-8-3315-4140-8
DOIs
PublikationsstatusVeröffentlicht - 13 Mai 2025
Veranstaltung2025 IEEE International Conference on Robotics and Automation, ICRA 2025 - Atlanta, USA / Vereinigte Staaten
Dauer: 19 Mai 202523 Mai 2025

Publikationsreihe

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Konferenz

Konferenz2025 IEEE International Conference on Robotics and Automation, ICRA 2025
KurztitelICRA 2025
Land/GebietUSA / Vereinigte Staaten
OrtAtlanta
Zeitraum19 Mai 202523 Mai 2025

ASJC Scopus Sachgebiete

  • Software
  • Steuerungs- und Systemtechnik
  • Artificial intelligence
  • Elektrotechnik und Elektronik

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