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 existing valuable datasets obsolete. However, recreating similar datasets with newer sensor technologies is both tedious and time-consuming. Therefore, it is crucial to adapt these existing datasets for use with new setups and modalities. 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 the exchange of data between groups with different setups.

翻译：触觉感知对于人类与环境的交互至关重要，在机器人领域也日益重要。BioTac等触觉传感器模仿人类指尖，能提供详细的交互数据。尽管该传感器在滑移检测和物体识别等应用中具有实用价值，但其现已停产，导致许多现有宝贵数据集失效。然而，使用更新的传感器技术重建类似数据集既繁琐又耗时。因此，如何调整这些现有数据集以适用于新设备和新模态至关重要。为此，我们提出了ACROSS，一种通过利用传感器形变信息在不同触觉传感器间转换数据的新型框架。我们通过将BioTac信号转换为DIGIT传感器信号来演示该方法。我们的框架首先将输入信号转换为3D形变网格，然后将一个传感器的3D形变网格转换为另一个传感器的网格，最后将生成的3D形变网格转换到相应的输出空间。我们展示了该方法应对最具挑战性的问题——从低维触觉表征转换到高维表征。具体而言，我们将BioTac传感器的触觉信号转换为DIGIT触觉图像。我们的方法使得宝贵数据集得以继续使用，并促进了不同配置团队间的数据交换。