# Learning In-Hand Translation Using Tactile Skin With Shear and Normal Force Sensing

arXiv: https://arxiv.org/abs/2407.07885 · HTML: https://mlsanity.com/paper/2407.07885/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 56 references that are in the map.
- First posted on arXiv 10 Jul 2024.

## Builds on (most cited first, 30 of 32)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [Solving Rubik's Cube with a Robot Hand](https://mlsanity.com/paper/1910.07113/) (2019)
- [Learning Dexterous In-Hand Manipulation](https://mlsanity.com/paper/1808.00177/) (2018)
- [DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation](https://mlsanity.com/paper/2005.14679/) (2020)
- [DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation](https://mlsanity.com/paper/2403.07788/) (2024)
- [DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality](https://mlsanity.com/paper/2210.13702/) (2022)
- [In-Hand Object Rotation via Rapid Motor Adaptation](https://mlsanity.com/paper/2210.04887/) (2022)
- [Visual Dexterity: In-Hand Reorientation of Novel and Complex Object Shapes](https://mlsanity.com/paper/2211.11744/) (2022)
- [General In-Hand Object Rotation with Vision and Touch](https://mlsanity.com/paper/2309.09979/) (2023)
- [Rotating without Seeing: Towards In-hand Dexterity through Touch](https://mlsanity.com/paper/2303.10880/) (2023)
- [From One Hand to Multiple Hands: Imitation Learning for Dexterous Manipulation from Single-Camera Teleoperation](https://mlsanity.com/paper/2204.12490/) (2022)
- [Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation](https://mlsanity.com/paper/2203.13251/) (2022)
- [Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations](https://mlsanity.com/paper/2303.01497/) (2023)
- [TACTO: A Fast, Flexible, and Open-source Simulator for High-Resolution Vision-based Tactile Sensors](https://mlsanity.com/paper/2012.08456/) (2020)
- [Holo-Dex: Teaching Dexterity with Immersive Mixed Reality](https://mlsanity.com/paper/2210.06463/) (2022)
- [Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing](https://mlsanity.com/paper/2312.01853/) (2023)
- [Differentiable Physics Simulation of Dynamics-Augmented Neural Objects](https://mlsanity.com/paper/2210.09420/) (2022)
- [Taxim: An Example-based Simulation Model for GelSight Tactile Sensors](https://mlsanity.com/paper/2109.04027/) (2021)
- [Twisting Lids Off with Two Hands](https://mlsanity.com/paper/2403.02338/) (2024)
- [ReSkin: versatile, replaceable, lasting tactile skins](https://mlsanity.com/paper/2111.00071/) (2021)
- [Sim-to-Real for Robotic Tactile Sensing via Physics-Based Simulation and Learned Latent Projections](https://mlsanity.com/paper/2103.16747/) (2021)
- [Complex In-Hand Manipulation via Compliance-Enabled Finger Gaiting and Multi-Modal Planning](https://mlsanity.com/paper/2201.07928/) (2022)
- [DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation](https://mlsanity.com/paper/2403.08716/) (2024)
- [Sampling-based Exploration for Reinforcement Learning of Dexterous Manipulation](https://mlsanity.com/paper/2303.03486/) (2023)
- [AnyRotate: Gravity-Invariant In-Hand Object Rotation with Sim-to-Real Touch](https://mlsanity.com/paper/2405.07391/) (2024)
- [Dense Tactile Force Distribution Estimation using GelSlim and inverse FEM](https://mlsanity.com/paper/1810.04621/) (2018)
- [Tactile Gym 2.0: Sim-to-real Deep Reinforcement Learning for Comparing Low-cost High-Resolution Robot Touch](https://mlsanity.com/paper/2207.10763/) (2022)
- [Ground truth force distribution for learning-based tactile sensing: a finite element approach](https://mlsanity.com/paper/1909.04000/) (2019)
- [Tacchi: A Pluggable and Low Computational Cost Elastomer Deformation Simulator for Optical Tactile Sensors](https://mlsanity.com/paper/2301.08343/) (2023)

## Built on by (most cited first, 15 of 15)

- [AnySkin: Plug-and-play Skin Sensing for Robotic Touch](https://mlsanity.com/paper/2409.08276/) (2024)
- [What Matters for Batch Online Reinforcement Learning in Robotics?](https://mlsanity.com/paper/2505.08078/) (2025)
- [VT-Refine: Learning Bimanual Assembly with Visuo-Tactile Feedback via Simulation Fine-Tuning](https://mlsanity.com/paper/2510.14930/) (2025)
- [Learning Dexterous Manipulation Skills from Imperfect Simulations](https://mlsanity.com/paper/2512.02011/) (2025)
- [From Simple to Complex Skills: The Case of In-Hand Object Reorientation](https://mlsanity.com/paper/2501.05439/) (2025)
- [Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulation](https://mlsanity.com/paper/2512.09851/) (2025)
- [eFlesh: Highly customizable Magnetic Touch Sensing using Cut-Cell Microstructures](https://mlsanity.com/paper/2506.09994/) (2025)
- [TwinTac: A Wide-Range, Highly Sensitive Tactile Sensor with Real-to-Sim Digital Twin Sensor Model](https://mlsanity.com/paper/2509.10063/) (2025)
- [HydroShear: Hydroelastic Shear Simulation for Tactile Sim-to-Real Reinforcement Learning](https://mlsanity.com/paper/2603.00446/) (2026)
- [UniCross: Unified Cross-Skill Dexterous Manipulation Synthesis](https://mlsanity.com/paper/2607.28198/) (2026)
- [Tac2Motion: Contact-Aware Reinforcement Learning with Tactile Feedback for Robotic Hand Manipulation](https://mlsanity.com/paper/2509.17812/) (2025)
- [Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation](https://mlsanity.com/paper/2605.28812/) (2026)
- [Mana: Dexterous Manipulation of Articulated Tools](https://mlsanity.com/paper/2606.13677/) (2026)
- [NoContactNoWorries: Estimating Contact through Vision and Proprioception for In-Hand Dexterous Manipulation](https://mlsanity.com/paper/2606.24450/) (2026)
- [WM-Craftnet: World Synesthesia Model for Generalizable and Robust Dexterous In-Hand Manipulation](https://mlsanity.com/paper/2609.07002/) (2026)

## Abstract (arXiv)

Recent progress in reinforcement learning (RL) and tactile sensing has significantly advanced dexterous manipulation. However, these methods often utilize simplified tactile signals due to the gap between tactile simulation and the real world. We introduce a sensor model for tactile skin that enables zero-shot sim-to-real transfer of ternary shear and binary normal forces. Using this model, we develop an RL policy that leverages sliding contact for dexterous in-hand translation. We conduct extensive real-world experiments to assess how tactile sensing facilitates policy adaptation to various unseen object properties and robot hand orientations. We demonstrate that our 3-axis tactile policies consistently outperform baselines that use only shear forces, only normal forces, or only proprioception. Website: https://jessicayin.github.io/tactile-skin-rl/