# A Grasping-centered Analysis for Cloth Manipulation

arXiv: https://arxiv.org/abs/1906.08202 · HTML: https://mlsanity.com/paper/1906.08202/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2019.

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

- [FabricFlowNet: Bimanual Cloth Manipulation with a Flow-based Policy](https://mlsanity.com/paper/2111.05623/) (2021)
- [Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor](https://mlsanity.com/paper/1910.04854/) (2019)
- [ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation](https://mlsanity.com/paper/2505.09698/) (2025)
- [VisuoSpatial Foresight for Physical Sequential Fabric Manipulation](https://mlsanity.com/paper/2102.09754/) (2021)
- [Benchmarking the Sim-to-Real Gap in Cloth Manipulation](https://mlsanity.com/paper/2310.09543/) (2023)
- [SculptBot: Pre-Trained Models for 3D Deformable Object Manipulation](https://mlsanity.com/paper/2309.08728/) (2023)
- [TraKDis: A Transformer-based Knowledge Distillation Approach for Visual Reinforcement Learning with Application to Cloth Manipulation](https://mlsanity.com/paper/2401.13362/) (2024)
- [Semantic State Estimation in Cloth Manipulation Tasks](https://mlsanity.com/paper/2203.11647/) (2022)
- [Learning Keypoints from Synthetic Data for Robotic Cloth Folding](https://mlsanity.com/paper/2205.06714/) (2022)
- [GraphGarment: Learning Garment Dynamics for Bimanual Cloth Manipulation Tasks](https://mlsanity.com/paper/2503.05817/) (2025)
- [Controlled Gaussian Process Dynamical Models with Application to Robotic Cloth Manipulation](https://mlsanity.com/paper/2103.06615/) (2021)
- [An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning](https://mlsanity.com/paper/2205.14457/) (2022)
- [Learning to bag with a simulation-free reinforcement learning framework for robots](https://mlsanity.com/paper/2310.14398/) (2023)
- [Autonomous Quilt Spreading for Caregiving Robots](https://mlsanity.com/paper/2405.15373/) (2024)
- [TRACER: Texture-Robust Affordance Chain-of-Thought for Deformable-Object Refinement](https://mlsanity.com/paper/2601.20208/) (2026)

## Abstract (arXiv)

Compliant and soft hands have gained a lot of attention in the past decade because of their ability to adapt to the shape of the objects, increasing their effectiveness for grasping. However, when it comes to grasping highly flexible objects such as textiles, we face the dual problem: it is the object that will adapt to the shape of the hand or gripper. In this context, the classic grasp analysis or grasping taxonomies are not suitable for describing textile objects grasps. This work proposes a novel definition of textile object grasps that abstracts from the robotic embodiment or hand shape and recovers concepts from the early neuroscience literature on hand prehension skills. This framework enables us to identify what grasps have been used in literature until now to perform robotic cloth manipulation, and allows for a precise definition of all the tasks that have been tackled in terms of manipulation primitives based on regrasps. In addition, we also review what grippers have been used. Our analysis shows how the vast majority of cloth manipulations have relied only on one type of grasp, and at the same time we identify several tasks that need more variety of grasp types to be executed successfully. Our framework is generic, provides a classification of cloth manipulation primitives and can inspire gripper design and benchmark construction for cloth manipulation.