# Vegetable Peeling: A Case Study in Constrained Dexterous Manipulation

arXiv: https://arxiv.org/abs/2407.07884 · HTML: https://mlsanity.com/paper/2407.07884/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 53 references that are in the map.
- First posted on arXiv 10 Jul 2024.

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

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Generative Adversarial Imitation Learning](https://mlsanity.com/paper/1606.03476/) (2016)
- [Objaverse: A Universe of Annotated 3D Objects](https://mlsanity.com/paper/2212.08051/) (2022)
- [Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://mlsanity.com/paper/2108.10470/) (2021)
- [Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks](https://mlsanity.com/paper/2401.14159/) (2024)
- [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)
- [Learning Quadrupedal Locomotion over Challenging Terrain](https://mlsanity.com/paper/2010.11251/) (2020)
- [RMA: Rapid Motor Adaptation for Legged Robots](https://mlsanity.com/paper/2107.04034/) (2021)
- [Learning by Cheating](https://mlsanity.com/paper/1912.12294/) (2019)
- [Sim-to-Real: Learning Agile Locomotion For Quadruped Robots](https://mlsanity.com/paper/1804.10332/) (2018)
- [Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects](https://mlsanity.com/paper/1809.10790/) (2018)
- [Asymmetric Actor Critic for Image-Based Robot Learning](https://mlsanity.com/paper/1710.06542/) (2017)
- [Deep Dynamics Models for Learning Dexterous Manipulation](https://mlsanity.com/paper/1909.11652/) (2019)
- [Rapid Locomotion via Reinforcement Learning](https://mlsanity.com/paper/2205.02824/) (2022)
- [A System for General In-Hand Object Re-Orientation](https://mlsanity.com/paper/2111.03043/) (2021)
- [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)
- [Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots](https://mlsanity.com/paper/2103.14295/) (2021)
- [Rotating without Seeing: Towards In-hand Dexterity through Touch](https://mlsanity.com/paper/2303.10880/) (2023)
- [LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning](https://mlsanity.com/paper/2309.06440/) (2023)
- [Global Planning for Contact-Rich Manipulation via Local Smoothing of Quasi-dynamic Contact Models](https://mlsanity.com/paper/2206.10787/) (2022)
- [Learning to Jump from Pixels](https://mlsanity.com/paper/2110.15344/) (2021)
- [Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger](https://mlsanity.com/paper/2108.09779/) (2021)
- [Learning Dexterous Manipulation Policies from Experience and Imitation](https://mlsanity.com/paper/1611.05095/) (2016)
- [Complex In-Hand Manipulation via Compliance-Enabled Finger Gaiting and Multi-Modal Planning](https://mlsanity.com/paper/2201.07928/) (2022)
- [Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion](https://mlsanity.com/paper/2009.10019/) (2020)
- [Goal-conditioned dual-action imitation learning for dexterous dual-arm robot manipulation](https://mlsanity.com/paper/2203.09749/) (2022)
- [Dextrous Tactile In-Hand Manipulation Using a Modular Reinforcement Learning Architecture](https://mlsanity.com/paper/2303.04705/) (2023)
- [Surprisingly Robust In-Hand Manipulation: An Empirical Study](https://mlsanity.com/paper/2201.11503/) (2022)

## Built on by (most cited first, 9 of 9)

- [ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learning](https://mlsanity.com/paper/2503.21860/) (2025)
- [FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model](https://mlsanity.com/paper/2412.08261/) (2024)
- [SimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation](https://mlsanity.com/paper/2602.16863/) (2026)
- [VLMgineer: Vision Language Models as Robotic Toolsmiths](https://mlsanity.com/paper/2507.12644/) (2025)
- [Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation](https://mlsanity.com/paper/2505.05287/) (2025)
- [Mash, Spread, Slice! Learning to Manipulate Object States via Visual Spatial Progress](https://mlsanity.com/paper/2509.24129/) (2025)
- [How to Peel with a Knife: Aligning Fine-Grained Manipulation with Human Preference](https://mlsanity.com/paper/2603.03280/) (2026)
- [AsymDex: Asymmetry and Relative Coordinates for RL-based Bimanual Dexterity](https://mlsanity.com/paper/2411.13020/) (2024)
- [Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation](https://mlsanity.com/paper/2606.22471/) (2026)

## Abstract (arXiv)

Recent studies have made significant progress in addressing dexterous manipulation problems, particularly in in-hand object reorientation. However, there are few existing works that explore the potential utilization of developed dexterous manipulation controllers for downstream tasks. In this study, we focus on constrained dexterous manipulation for food peeling. Food peeling presents various constraints on the reorientation controller, such as the requirement for the hand to securely hold the object after reorientation for peeling. We propose a simple system for learning a reorientation controller that facilitates the subsequent peeling task. Videos are available at: https://taochenshh.github.io/projects/veg-peeling.