# Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing

arXiv: https://arxiv.org/abs/2312.01853 · HTML: https://mlsanity.com/paper/2312.01853/

## Key facts

- Cited by 56 papers in the map (data through 14 Oct 2026).
- Builds on 40 of its 68 references that are in the map.
- First posted on arXiv 4 Dec 2023.

## Builds on (most cited first, 30 of 40)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016)
- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations](https://mlsanity.com/paper/1709.10087/) (2017)
- [Learning Dexterous In-Hand Manipulation](https://mlsanity.com/paper/1808.00177/) (2018)
- [Deep Dynamics Models for Learning Dexterous Manipulation](https://mlsanity.com/paper/1909.11652/) (2019)
- [DexMV: Imitation Learning for Dexterous Manipulation from Human Videos](https://mlsanity.com/paper/2108.05877/) (2021)
- [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)
- [A System for General In-Hand Object Re-Orientation](https://mlsanity.com/paper/2111.03043/) (2021)
- [Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks](https://mlsanity.com/paper/1810.10191/) (2018)
- [AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System](https://mlsanity.com/paper/2307.04577/) (2023)
- [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)
- [More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch](https://mlsanity.com/paper/1805.11085/) (2018)
- [General In-Hand Object Rotation with Vision and Touch](https://mlsanity.com/paper/2309.09979/) (2023)
- [DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation](https://mlsanity.com/paper/2211.09423/) (2022)
- [Rotating without Seeing: Towards In-hand Dexterity through Touch](https://mlsanity.com/paper/2303.10880/) (2023)
- [Robotic Telekinesis: Learning a Robotic Hand Imitator by Watching Humans on Youtube](https://mlsanity.com/paper/2202.10448/) (2022)
- [From One Hand to Multiple Hands: Imitation Learning for Dexterous Manipulation from Single-Camera Teleoperation](https://mlsanity.com/paper/2204.12490/) (2022)
- [LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning](https://mlsanity.com/paper/2309.06440/) (2023)
- [Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation](https://mlsanity.com/paper/2203.13251/) (2022)
- [DexArt: Benchmarking Generalizable Dexterous Manipulation with Articulated Objects](https://mlsanity.com/paper/2305.05706/) (2023)
- [Dexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play](https://mlsanity.com/paper/2303.12076/) (2023)
- [Holo-Dex: Teaching Dexterity with Immersive Mixed Reality](https://mlsanity.com/paper/2210.06463/) (2022)
- [Learning Generalizable Dexterous Manipulation from Human Grasp Affordance](https://mlsanity.com/paper/2204.02320/) (2022)
- [Visuo-Tactile Transformers for Manipulation](https://mlsanity.com/paper/2210.00121/) (2022)
- [Dynamic Handover: Throw and Catch with Bimanual Hands](https://mlsanity.com/paper/2309.05655/) (2023)
- [See to Touch: Learning Tactile Dexterity through Visual Incentives](https://mlsanity.com/paper/2309.12300/) (2023)
- [Learning Continuous Grasping Function with a Dexterous Hand from Human Demonstrations](https://mlsanity.com/paper/2207.05053/) (2022)
- [Learning to Imitate Object Interactions from Internet Videos](https://mlsanity.com/paper/2211.13225/) (2022)

## Built on by (most cited first, 30 of 56)

- [3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations](https://mlsanity.com/paper/2403.03954/) (2024)
- [HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulation](https://mlsanity.com/paper/2403.10506/) (2024)
- [Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation](https://mlsanity.com/paper/2503.02881/) (2025)
- [3D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensing](https://mlsanity.com/paper/2410.24091/) (2024)
- [SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splatting](https://mlsanity.com/paper/2409.10161/) (2024)
- [Twisting Lids Off with Two Hands](https://mlsanity.com/paper/2403.02338/) (2024)
- [Beyond Sight: Finetuning Generalist Robot Policies with Heterogeneous Sensors via Language Grounding](https://mlsanity.com/paper/2501.04693/) (2025)
- [ViViDex: Learning Vision-based Dexterous Manipulation from Human Videos](https://mlsanity.com/paper/2404.15709/) (2024)
- [Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations](https://mlsanity.com/paper/2408.04380/) (2024)
- [BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects](https://mlsanity.com/paper/2412.05066/) (2024)
- [Touch in the Wild: Learning Fine-Grained Manipulation with a Portable Visuo-Tactile Gripper](https://mlsanity.com/paper/2507.15062/) (2025)
- [CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation](https://mlsanity.com/paper/2402.14795/) (2024)
- [Lessons from Learning to Spin "Pens"](https://mlsanity.com/paper/2407.18902/) (2024)
- [GenDP: 3D Semantic Fields for Category-Level Generalizable Diffusion Policy](https://mlsanity.com/paper/2410.17488/) (2024)
- [AnySkin: Plug-and-play Skin Sensing for Robotic Touch](https://mlsanity.com/paper/2409.08276/) (2024)
- [AnyRotate: Gravity-Invariant In-Hand Object Rotation with Sim-to-Real Touch](https://mlsanity.com/paper/2405.07391/) (2024)
- [RoboPack: Learning Tactile-Informed Dynamics Models for Dense Packing](https://mlsanity.com/paper/2407.01418/) (2024)
- [Learning In-Hand Translation Using Tactile Skin With Shear and Normal Force Sensing](https://mlsanity.com/paper/2407.07885/) (2024)
- [Multi-Modal Manipulation via Multi-Modal Policy Consensus](https://mlsanity.com/paper/2509.23468/) (2025)
- [Learning Precise, Contact-Rich Manipulation through Uncalibrated Tactile Skins](https://mlsanity.com/paper/2410.17246/) (2024)
- [Sim2Real Manipulation on Unknown Objects with Tactile-based Reinforcement Learning](https://mlsanity.com/paper/2403.12170/) (2024)
- [VT-Refine: Learning Bimanual Assembly with Visuo-Tactile Feedback via Simulation Fine-Tuning](https://mlsanity.com/paper/2510.14930/) (2025)
- [Subtask-Aware Visual Reward Learning from Segmented Demonstrations](https://mlsanity.com/paper/2502.20630/) (2025)
- [DexNDM: Closing the Reality Gap for Dexterous In-Hand Rotation via Joint-Wise Neural Dynamics Model](https://mlsanity.com/paper/2510.08556/) (2025)
- [From Simple to Complex Skills: The Case of In-Hand Object Reorientation](https://mlsanity.com/paper/2501.05439/) (2025)
- [RUKA: Rethinking the Design of Humanoid Hands with Learning](https://mlsanity.com/paper/2504.13165/) (2025)
- [FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems](https://mlsanity.com/paper/2604.28156/) (2026)
- [eFlesh: Highly customizable Magnetic Touch Sensing using Cut-Cell Microstructures](https://mlsanity.com/paper/2506.09994/) (2025)
- [Enhancing Tactile-based Reinforcement Learning for Robotic Control](https://mlsanity.com/paper/2510.21609/) (2025)
- [DexSkin: High-Coverage Conformable Robotic Skin for Learning Contact-Rich Manipulation](https://mlsanity.com/paper/2509.18830/) (2025)

## Abstract (arXiv)

Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual feedback. However, the distinct nature of these modalities poses significant challenges. In this paper, we introduce a system that leverages visual and tactile sensory inputs to enable dexterous in-hand manipulation. Specifically, we propose Robot Synesthesia, a novel point cloud-based tactile representation inspired by human tactile-visual synesthesia. This approach allows for the simultaneous and seamless integration of both sensory inputs, offering richer spatial information and facilitating better reasoning about robot actions. The method, trained in a simulated environment and then deployed to a real robot, is applicable to various in-hand object rotation tasks. Comprehensive ablations are performed on how the integration of vision and touch can improve reinforcement learning and Sim2Real performance. Our project page is available at https://yingyuan0414.github.io/visuotactile/ .