# Challenges and Outlook in Robotic Manipulation of Deformable Objects

arXiv: https://arxiv.org/abs/2105.01767 · HTML: https://mlsanity.com/paper/2105.01767/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 May 2021.

## Built on by (most cited first, 30 of 43)

- [SpeedFolding: Learning Efficient Bimanual Folding of Garments](https://mlsanity.com/paper/2208.10552/) (2022)
- [A Survey of Embodied Learning for Object-Centric Robotic Manipulation](https://mlsanity.com/paper/2408.11537/) (2024)
- [ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation](https://mlsanity.com/paper/2505.09698/) (2025)
- [ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment](https://mlsanity.com/paper/2308.09987/) (2023)
- [Learning Keypoints for Robotic Cloth Manipulation using Synthetic Data](https://mlsanity.com/paper/2401.01734/) (2024)
- [EDO-Net: Learning Elastic Properties of Deformable Objects from Graph Dynamics](https://mlsanity.com/paper/2209.08996/) (2022)
- [Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision](https://mlsanity.com/paper/2501.01715/) (2025)
- [RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning](https://mlsanity.com/paper/2602.18742/) (2026)
- [Neural Autoencoder-Based Structure-Preserving Model Order Reduction and Control Design for High-Dimensional Physical Systems](https://mlsanity.com/paper/2312.06256/) (2023)
- [From Reaction to Anticipation: Proactive Failure Recovery through Agentic Task Graph for Robotic Manipulation](https://mlsanity.com/paper/2605.11951/) (2026)
- [InstructionBench: An Instructional Video Understanding Benchmark](https://mlsanity.com/paper/2504.05040/) (2025)
- [DeformerNet: Learning Bimanual Manipulation of 3D Deformable Objects](https://mlsanity.com/paper/2305.04449/) (2023)
- [DexDLO: Learning Goal-Conditioned Dexterous Policy for Dynamic Manipulation of Deformable Linear Objects](https://mlsanity.com/paper/2312.15204/) (2023)
- [A Systematic Literature Review of Computer Vision Applications in Robotized Wire Harness Assembly](https://mlsanity.com/paper/2309.13744/) (2023)
- [DefGoalNet: Contextual Goal Learning from Demonstrations For Deformable Object Manipulation](https://mlsanity.com/paper/2309.14463/) (2023)
- [Robot Deformable Object Manipulation via NMPC-generated Demonstrations in Deep Reinforcement Learning](https://mlsanity.com/paper/2502.11375/) (2025)
- [GraphGarment: Learning Garment Dynamics for Bimanual Cloth Manipulation Tasks](https://mlsanity.com/paper/2503.05817/) (2025)
- [Offline Goal-Conditioned Reinforcement Learning for Shape Control of Deformable Linear Objects](https://mlsanity.com/paper/2403.10290/) (2024)
- [Implicit Neural-Representation Learning for Elastic Deformable-Object Manipulations](https://mlsanity.com/paper/2505.00500/) (2025)
- [Preference Aligned Visuomotor Diffusion Policies for Deformable Object Manipulation](https://mlsanity.com/paper/2602.09583/) (2026)
- [SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects (Early Version)](https://mlsanity.com/paper/2607.04234/) (2026)
- [Learning visual-based deformable object rearrangement with local graph neural networks](https://mlsanity.com/paper/2310.10307/) (2023)
- [Learning to bag with a simulation-free reinforcement learning framework for robots](https://mlsanity.com/paper/2310.14398/) (2023)
- [Make a Donut: Hierarchical EMD-Space Planning for Zero-Shot Deformable Manipulation with Tools](https://mlsanity.com/paper/2311.02787/) (2023)
- [Conditional Variational Auto Encoder Based Dynamic Motion for Multi-task Imitation Learning](https://mlsanity.com/paper/2405.15266/) (2024)
- [RaggeDi: Diffusion-based State Estimation of Disordered Rags, Sheets, Towels and Blankets](https://mlsanity.com/paper/2409.11831/) (2024)
- [SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation](https://mlsanity.com/paper/2409.18082/) (2024)
- [DEFT: Differentiable Branched Discrete Elastic Rods for Modeling Furcated DLOs in Real-Time](https://mlsanity.com/paper/2502.15037/) (2025)
- [Sim2Real Transfer for Vision-Based Grasp Verification](https://mlsanity.com/paper/2505.03046/) (2025)
- [SCOOP'D: Learning Mixed-Liquid-Solid Scooping via Sim2Real Generative Policy](https://mlsanity.com/paper/2510.11566/) (2025)

## Abstract (arXiv)

Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new applications in the industrial, services, and healthcare sectors. However, compared to rigid object manipulation, the manipulation of deformable objects is considerably more complex, and is still an open research problem. Addressing DOM challenges demand breakthroughs in almost all aspects of robotics, namely hardware design, sensing, (deformation) modeling, planning, and control. In this article, we review recent advances and highlight the main challenges when considering deformation in each sub-field. A particular focus of our paper lies in the discussions of these challenges and proposing future directions of research.