# Training tactile sensors to learn force sensing from each other

**Authors:** Zhuo Chen, Ni Ou, Xuyang Zhang, Zhiyuan Wu, Yongqiang Zhao, Yupeng Wang, Emmanouil Spyrakos Papastavridis, Nathan Lepora, Lorenzo Jamone, Jiankang Deng, Shan Luo

PMC · DOI: 10.1038/s41467-026-68753-1 · Nature Communications · 2026-01-28

## TL;DR

GenForce is a framework that allows robots to transfer tactile sensing across different sensors, improving object manipulation and adaptability.

## Contribution

GenForce introduces a unified tactile representation for transferable force sensing across diverse tactile sensors in robotic hands.

## Key findings

- GenForce generalizes across both homogeneous and heterogeneous tactile sensors.
- The framework enables multi-sensor force coordination for tasks like grasping and slip detection.
- It offers a scalable paradigm for tactile sensing in unstructured environments.

## Abstract

Humans achieve stable and dexterous object manipulation by coordinating grasp forces across multiple fingers and palms, facilitated by a unified tactile memory system in the somatosensory cortex. This system encodes and stores tactile experiences across skin regions, enabling the flexible reuse and transfer of touch information. Inspired by this biological capability, we present GenForce, the first framework that enables transferable force sensing across diverse tactile sensors in robotic hands. GenForce unifies tactile signals into shared marker representations, analogous to cortical sensory encoding, allowing force prediction models trained on one sensor to be transferred to others without the need for exhaustive force data collection. We demonstrate that GenForce generalizes across both homogeneous sensors with varying configurations and heterogeneous sensors with distinct sensing modalities and material properties. This transferable force sensing capability is also demonstrated in robot manipulation tasks including daily-object grasping, slip detection and compensation with multi-sensor force coordination. Our results highlight a scalable paradigm for cross-sensor robotic tactile sensing, offering new pathways toward adaptable and tactile memory-driven robot manipulation in unstructured environments.

Biological system for stable object manipulation is facilitated by a unified tactile memory system. Here, GenForce enables transferable force sensing across diverse tactile sensors using a unified representation, enhancing robot manipulation through cross-sensor transfer and multi-sensor coordination.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12953886/full.md

## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC12953886/full.md

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Source: https://tomesphere.com/paper/PMC12953886