SPLIT: Separating Physical-Contact via Latent Arithmetic in Image-Based Tactile Sensors
Training machine learning models for robotic tactile sensing requires vast amounts of data, yet obtaining realistic interaction data remains a challenge due to physical complexity and variability. Simulating tactile sensors is thus a crucial step in accelerating progress. This paper presents SPLIT, a novel method for simulating image-based tactile sensors, with a primary focus on the DIGIT sensor. Central to our approach is a latent space arithmetic strategy that explicitly disentangles contact geometry from sensor-specific optical properties. Unlike methods that require recalibration for every new unit, this disentanglement allows SPLIT to adapt to diverse DIGIT backgrounds and even tran...
| Authors | Wadhah Zai El Amri, Nicolás Navarro-Guerrero |
|---|---|
| Primary category | cs.RO |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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