# Visuotactile Affordances for Cloth Manipulation with Local Control

arXiv: https://arxiv.org/abs/2212.05108 · HTML: https://mlsanity.com/paper/2212.05108/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 36 references that are in the map.
- First posted on arXiv 9 Dec 2022.

## Builds on (most cited first, 22 of 22)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Playing Atari with Deep Reinforcement Learning](https://mlsanity.com/paper/1312.5602/) (2013)
- [Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics](https://mlsanity.com/paper/1703.09312/) (2017)
- [TossingBot: Learning to Throw Arbitrary Objects with Residual Physics](https://mlsanity.com/paper/1903.11239/) (2019)
- [PLAS: Latent Action Space for Offline Reinforcement Learning](https://mlsanity.com/paper/2011.07213/) (2020)
- [Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning](https://mlsanity.com/paper/1803.09956/) (2018)
- [Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching](https://mlsanity.com/paper/1710.01330/) (2017)
- [FlingBot: The Unreasonable Effectiveness of Dynamic Manipulation for Cloth Unfolding](https://mlsanity.com/paper/2105.03655/) (2021)
- [Learning to Manipulate Deformable Objects without Demonstrations](https://mlsanity.com/paper/1910.13439/) (2019)
- [Learning Predictive Representations for Deformable Objects Using Contrastive Estimation](https://mlsanity.com/paper/2003.05436/) (2020)
- [Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data](https://mlsanity.com/paper/2003.01835/) (2020)
- [Cable Manipulation with a Tactile-Reactive Gripper](https://mlsanity.com/paper/1910.02860/) (2019)
- [GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion](https://mlsanity.com/paper/2104.05177/) (2021)
- [VisuoSpatial Foresight for Multi-Step, Multi-Task Fabric Manipulation](https://mlsanity.com/paper/2003.09044/) (2020)
- [GelSight Wedge: Measuring High-Resolution 3D Contact Geometry with a Compact Robot Finger](https://mlsanity.com/paper/2106.08851/) (2021)
- [Cloth Region Segmentation for Robust Grasp Selection](https://mlsanity.com/paper/2008.05626/) (2020)
- [Occlusion-robust Deformable Object Tracking without Physics Simulation](https://mlsanity.com/paper/2101.00733/) (2021)
- [Tactile Regrasp: Grasp Adjustments via Simulated Tactile Transformations](https://mlsanity.com/paper/1803.01940/) (2018)
- [Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics](https://mlsanity.com/paper/2003.12698/) (2020)
- [Semi-supervised 3D Object Detection via Temporal Graph Neural Networks](https://mlsanity.com/paper/2202.00182/) (2022)
- [Learning to Fold Real Garments with One Arm: A Case Study in Cloud-Based Robotics Research](https://mlsanity.com/paper/2204.10297/) (2022)

## Built on by (most cited first, 21 of 21)

- [General In-Hand Object Rotation with Vision and Touch](https://mlsanity.com/paper/2309.09979/) (2023)
- [Learning Visuotactile Skills with Two Multifingered Hands](https://mlsanity.com/paper/2404.16823/) (2024)
- [3D-ViTac: Learning Fine-Grained Manipulation with Visuo-Tactile Sensing](https://mlsanity.com/paper/2410.24091/) (2024)
- [Transferable Tactile Transformers for Representation Learning Across Diverse Sensors and Tasks](https://mlsanity.com/paper/2406.13640/) (2024)
- [UniGarmentManip: A Unified Framework for Category-Level Garment Manipulation via Dense Visual Correspondence](https://mlsanity.com/paper/2405.06903/) (2024)
- [GelSight Svelte: A Human Finger-shaped Single-camera Tactile Robot Finger with Large Sensing Coverage and Proprioceptive Sensing](https://mlsanity.com/paper/2309.10885/) (2023)
- [Sim2Real Manipulation on Unknown Objects with Tactile-based Reinforcement Learning](https://mlsanity.com/paper/2403.12170/) (2024)
- [FeelAnyForce: Estimating Contact Force Feedback from Tactile Sensation for Vision-Based Tactile Sensors](https://mlsanity.com/paper/2410.02048/) (2024)
- [VT-Refine: Learning Bimanual Assembly with Visuo-Tactile Feedback via Simulation Fine-Tuning](https://mlsanity.com/paper/2510.14930/) (2025)
- [SculptBot: Pre-Trained Models for 3D Deformable Object Manipulation](https://mlsanity.com/paper/2309.08728/) (2023)
- [Universal Visuo-Tactile Video Understanding for Embodied Interaction](https://mlsanity.com/paper/2505.22566/) (2025)
- [FlexiTac: A Low-Cost, Open-Source, Scalable Tactile Sensing Solution for Robotic Systems](https://mlsanity.com/paper/2604.28156/) (2026)
- [UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models](https://mlsanity.com/paper/2606.31723/) (2026)
- [LeTac-MPC: Learning Model Predictive Control for Tactile-reactive Grasping](https://mlsanity.com/paper/2403.04934/) (2024)
- [Reactive In-Air Clothing Manipulation with Confidence-Aware Dense Correspondence and Visuotactile Affordance](https://mlsanity.com/paper/2509.03889/) (2025)
- [TouchFormer: A Robust Transformer-based Framework for Multimodal Material Perception](https://mlsanity.com/paper/2511.19509/) (2025)
- [VTAO-BiManip: Masked Visual-Tactile-Action Pre-training with Object Understanding for Bimanual Dexterous Manipulation](https://mlsanity.com/paper/2501.03606/) (2025)
- [Force-Modulated Visual Policy for Robot-Assisted Dressing with Arm Motions](https://mlsanity.com/paper/2509.12741/) (2025)
- [ViTac-Tracing: Visual-Tactile Imitation Learning of Deformable Object Tracing](https://mlsanity.com/paper/2603.18784/) (2026)
- [VQ-Touch: A Data-Efficient Tactile Generation Framework Across Sensors and Scenarios](https://mlsanity.com/paper/2607.14728/) (2026)
- [Vision-Based 6-DoF Grasp Pose Estimation for Robot Cloth Unfolding](https://mlsanity.com/paper/2609.31452/) (2026)

## Abstract (arXiv)

Cloth in the real world is often crumpled, self-occluded, or folded in on itself such that key regions, such as corners, are not directly graspable, making manipulation difficult. We propose a system that leverages visual and tactile perception to unfold the cloth via grasping and sliding on edges. By doing so, the robot is able to grasp two adjacent corners, enabling subsequent manipulation tasks like folding or hanging. As components of this system, we develop tactile perception networks that classify whether an edge is grasped and estimate the pose of the edge. We use the edge classification network to supervise a visuotactile edge grasp affordance network that can grasp edges with a 90% success rate. Once an edge is grasped, we demonstrate that the robot can slide along the cloth to the adjacent corner using tactile pose estimation/control in real time. See http://nehasunil.com/visuotactile/visuotactile.html for videos.