mlsanityData to 7 Oct 2026

DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations

arXiv 2209.14284 ↗First posted 28 Sep 2022cs.CVcited by 19

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Abstract (arXiv)

Teaching a multi-fingered dexterous robot to grasp objects in the real world has been a challenging problem due to its high dimensional state and action space. We propose a robot-learning system that can take a small number of human demonstrations and learn to grasp unseen object poses given partially occluded observations. Our system leverages a small motion capture dataset and generates a large dataset with diverse and successful trajectories for a multi-fingered robot gripper. By adding domain randomization, we show that our dataset provides robust grasping trajectories that can be transferred to a policy learner. We train a dexterous grasping policy that takes the point clouds of the object as input and predicts continuous actions to grasp objects from different initial robot states. We evaluate the effectiveness of our system on a 22-DoF floating Allegro Hand in simulation and a 23-DoF Allegro robot hand with a KUKA arm in real world. The policy learned from our dataset can generalize well on unseen object poses in both simulation and the real world

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 31 of its 46 references that are in the map. First posted on arXiv 28 Sep 2022.

Builds on

31 of 46 references.

References · 31

  1. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  2. 2019Solving Rubik's Cube with a Robot Handcited by 699
  3. 2017Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrationscited by 685
  4. 2018Learning Dexterous In-Hand Manipulationcited by 643
  5. 2020GRAB: A Dataset of Whole-Body Human Grasping of Objectscited by 397
  6. 2019Learning joint reconstruction of hands and manipulated objectscited by 377
  7. 2016The CMA Evolution Strategy: A Tutorialcited by 364
  8. 2021DexYCB: A Benchmark for Capturing Hand Grasping of Objectscited by 320
  9. 2017Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metricscited by 259
  10. 20196-DOF GraspNet: Variational Grasp Generation for Object Manipulationcited by 237
  11. 2017First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotationscited by 229
  12. 2021Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenescited by 213
19 more
  1. 2019Deep Dynamics Models for Learning Dexterous Manipulationcited by 200
  2. 2021DexMV: Imitation Learning for Dexterous Manipulation from Human Videoscited by 194
  3. 2020Grasping Field: Learning Implicit Representations for Human Graspscited by 178
  4. 2021A System for General In-Hand Object Re-Orientationcited by 155
  5. 2020Visual Imitation Made Easycited by 111
  6. 2021D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactionscited by 109
  7. 2019DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm Systemcited by 105
  8. 2019Grasping in the Wild:Learning 6DoF Closed-Loop Grasping from Low-Cost Demonstrationscited by 104
  9. 2020State-Only Imitation Learning for Dexterous Manipulationcited by 90
  10. 2019ContactGrasp: Functional Multi-finger Grasp Synthesis from Contactcited by 87
  11. 2022DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Videocited by 83
  12. 2020Learning Dexterous Grasping with Object-Centric Visual Affordancescited by 80
  13. 2018Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Costcited by 79
  14. 2020Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentationcited by 64
  15. 2020Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learningcited by 37
  16. 2016Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstrationcited by 35
  17. 2019Learning Task-Oriented Grasping from Human Activity Datasetscited by 32
  18. 2020Learning Dexterous Manipulation from Suboptimal Expertscited by 23
  19. 2021Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behaviorcited by 17

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 5; 2025: 7; 2026: 4.

19 papers.

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  1. 2024DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulationcited by 149
  2. 2025DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Graspingcited by 87
  3. 2023DexArt: Benchmarking Generalizable Dexterous Manipulation with Articulated Objectscited by 64
  4. 2025Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videoscited by 63
  5. 2024GraspXL: Generating Grasping Motions for Diverse Objects at Scalecited by 59
  6. 2025ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learningcited by 56
  7. 2023ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulationcited by 53
  8. 2024Hand-Object Interaction Pretraining from Videoscited by 38
  9. 2023GraspGF: Learning Score-based Grasping Primitive for Human-assisting Dexterous Graspingcited by 23
  10. 2025Dex1B: Learning with 1B Demonstrations for Dexterous Manipulationcited by 23
  11. 2024DexHandDiff: Interaction-aware Diffusion Planning for Adaptive Dexterous Manipulationcited by 15
  12. 2025Dexplore: Scalable Neural Control for Dexterous Manipulation from Reference-Scoped Explorationcited by 9
7 more
  1. 2025DexMan: Learning Bimanual Dexterous Manipulation from Human and Generated Videoscited by 7
  2. 2026AoE: Always-on Egocentric Human Video Collection for Embodied AIcited by 3
  3. 2025Traj2Action: A Co-Denoising Framework for Trajectory-Guided Human-to-Robot Skill Transfercited by 2
  4. 2026Imitating What Works: Simulation-Filtered Modular Policy Learning from Human Videoscited by 1
  5. 2026AutoDex: An Automated Real-World System for Dexterous Grasping Data Collectioncited by 1
  6. 2024FunGrasp: Functional Grasping for Diverse Dexterous Handscited by 0
  7. 2026Learning Dexterous Grasping from Sparse Taxonomy Guidancecited by 0