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arXiv · 2510.09817

Cross-Sensor Touch Generation

Samanta Rodriguez·Yiming Dou·Miquel Oller·Andrew Owens·Nima Fazeli
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Abstract

Today's visuo-tactile sensors come in many shapes and sizes, making it challenging to develop general-purpose tactile representations. This is because most models are tied to a specific sensor design. To address this challenge, we propose two approaches to cross-sensor image generation. The first is an end-to-end method that leverages paired data (Touch2Touch). The second method builds an intermediate depth representation and does not require paired data (T2D2: Touch-to-Depth-to-Touch). Both methods enable the use of sensor-specific models across multiple sensors via the cross-sensor touch generation process. Together, these models offer flexible solutions for sensor translation, depending on data availability and application needs. We demonstrate their effectiveness on downstream tasks such as in-hand pose estimation and behavior cloning, successfully transferring models trained on one sensor to another. Project page: https://samantabelen.github.io/cross_sensor_touch_generation.

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Samanta Rodriguez, Yiming Dou, Miquel Oller, Andrew Owens, Nima Fazeli. 2025-10-10. Cross-Sensor Touch Generation. https://arxiv.org/abs/2510.09817

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