LingBot-Touch has landed: an open-source tactile foundation model for transferring touch-based skills across robot hands, sensors, and manipulation tasks. 📜 Apache-2.0 License.
🤖 https://modelscope.ai/collections/Robbyant/LingBot-Touch
🖐️ Pretrained on touch at scale: Learns from 4,983 hours of tactile recordings, 1.33B frames, and 464K interaction episodes across piezoresistive, magnetic, and visuotactile sensors.
📊 Built for dexterous manipulation: Evaluated across 26 real-world tasks and 12 simulated RL tasks, including fragile-object handling, deformable objects, and bimanual coordination.
🔄 Transfer across sensors and hands: A shared Haptic Transformer maps heterogeneous tactile signals into one reusable representation, enabling transfer to unseen tactile sensors and real-world dexterous hands.
⚡ High-frequency and lightweight: The HaT-Tiny encoder uses just 5.46M parameters while supporting responsive downstream tactile inference.
🛠️ Ready to build with: Tiny and Small checkpoints, inference code, sensor interfaces, and sample data are released for three tactile modalities.