mlsanityData to 7 Oct 2026

QuasiSim: Parameterized Quasi-Physical Simulators for Dexterous Manipulations Transfer

arXiv 2404.07988 ↗First posted 11 Apr 2024cs.RO cs.CV cs.GRcited by 10

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Abstract (arXiv)

We explore the dexterous manipulation transfer problem by designing simulators. The task wishes to transfer human manipulations to dexterous robot hand simulations and is inherently difficult due to its intricate, highly-constrained, and discontinuous dynamics and the need to control a dexterous hand with a DoF to accurately replicate human manipulations. Previous approaches that optimize in high-fidelity black-box simulators or a modified one with relaxed constraints only demonstrate limited capabilities or are restricted by insufficient simulation fidelity. We introduce parameterized quasi-physical simulators and a physics curriculum to overcome these limitations. The key ideas are 1) balancing between fidelity and optimizability of the simulation via a curriculum of parameterized simulators, and 2) solving the problem in each of the simulators from the curriculum, with properties ranging from high task optimizability to high fidelity. We successfully enable a dexterous hand to track complex and diverse manipulations in high-fidelity simulated environments, boosting the success rate by 11%+ from the best-performed baseline. The project website is available at https://meowuu7.github.io/QuasiSim/.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 49 of its 80 references that are in the map. First posted on arXiv 11 Apr 2024.

Builds on

49 of 80 references.

References · 49

  1. 2019A Comprehensive Survey on Transfer Learningcited by 1,154
  2. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 882
  3. 2020Learning Mesh-Based Simulation with Graph Networkscited by 840
  4. 2019Solving Rubik's Cube with a Robot Handcited by 699
  5. 2017Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrationscited by 685
  6. 2018Learning Dexterous In-Hand Manipulationcited by 643
  7. 2015Policy Distillationcited by 414
  8. 2020GRAB: A Dataset of Whole-Body Human Grasping of Objectscited by 397
  9. 2020Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Surveycited by 388
  10. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  11. 2022ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulationcited by 306
  12. 2023Affordances from Human Videos as a Versatile Representation for Roboticscited by 221
37 more
  1. 2021DexMV: Imitation Learning for Dexterous Manipulation from Human Videoscited by 194
  2. 2021A System for General In-Hand Object Re-Orientationcited by 155
  3. 2023AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation Systemcited by 136
  4. 2019TossingBot: Learning to Throw Arbitrary Objects with Residual Physicscited by 131
  5. 2021D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactionscited by 109
  6. 2022VideoDex: Learning Dexterity from Internet Videoscited by 101
  7. 2022Visual Dexterity: In-Hand Reorientation of Novel and Complex Object Shapescited by 92
  8. 2020State-Only Imitation Learning for Dexterous Manipulationcited by 90
  9. 2024TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understandingcited by 85
  10. 2022DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Videocited by 83
  11. 2020Reinforcement Learning with Videos: Combining Offline Observations with Interactioncited by 80
  12. 2022From One Hand to Multiple Hands: Imitation Learning for Dexterous Manipulation from Single-Camera Teleoperationcited by 79
  13. 2022DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulationcited by 78
  14. 2020NeuralSim: Augmenting Differentiable Simulators with Neural Networkscited by 77
  15. 2022Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulationcited by 75
  16. 2023PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interactioncited by 72
  17. 2021An End-to-End Differentiable Framework for Contact-Aware Robot Designcited by 53
  18. 2023ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulationcited by 53
  19. 2023Towards Generalizable Zero-Shot Manipulation via Translating Human Interaction Planscited by 51
  20. 2022Learning Generalizable Dexterous Manipulation from Human Grasp Affordancecited by 46
  21. 2022Global Planning for Contact-Rich Manipulation via Local Smoothing of Quasi-dynamic Contact Modelscited by 46
  22. 2020ContactNets: Learning Discontinuous Contact Dynamics with Smooth, Implicit Representationscited by 38
  23. 2018Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncingcited by 36
  24. 2016Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstrationcited by 35
  25. 2019Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfercited by 24
  26. 2021Bundled Gradients through Contact via Randomized Smoothingcited by 23
  27. 2023Learning Vortex Dynamics for Fluid Inference and Predictioncited by 17
  28. 2024Sim-to-Real of Soft Robots with Learned Residual Physicscited by 14
  29. 2023Continuation Path Learning for Homotopy Optimizationcited by 12
  30. 2022HERD: Continuous Human-to-Robot Evolution for Learning from Human Demonstrationcited by 8
  31. 2023Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithmscited by 7
  32. 2020Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamicscited by 6
  33. 2023Human Demonstrations are Generalizable Knowledge for Robotscited by 6
  34. 2021Trajectory Optimization with Optimization-Based Dynamicscited by 5
  35. 2023Learning to Transfer In-Hand Manipulations Using a Greedy Shape Curriculumcited by 5
  36. 2023Learning Multi-Step Manipulation Tasks from A Single Human Demonstrationcited by 4
  37. 2019Neural network augmented wave-equation simulationcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 7; 2026: 3.

10 papers.

  1. 2025ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learningcited by 56
  2. 2025SPIDER: Scalable Physics-Informed Dexterous Retargetingcited by 25
  3. 2025DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policycited by 16
  4. 2025DexTrack: Towards Generalizable Neural Tracking Control for Dexterous Manipulation from Human Referencescited by 13
  5. 2025Learning to Transfer Human Hand Skills for Robot Manipulationscited by 10
  6. 2025DyTact: Capturing Dynamic Contacts in Hand-Object Manipulationcited by 8
  7. 2025DexMan: Learning Bimanual Dexterous Manipulation from Human and Generated Videoscited by 7
  8. 2026ContactGaussian-WM: Learning Physics-Grounded World Model from Videoscited by 7
  9. 2026Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstrationcited by 6
  10. 2026LUCID: Learning Embodiment-Agnostic Intent Models from Unstructured Human Videos for Scalable Dexterous Robot Skill Acquisitioncited by 2