mlsanityData to 7 Oct 2026

Crossing The Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics

arXiv 2008.06686 ↗First posted 15 Aug 2020cs.RO cs.LGcited by 20

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Abstract (arXiv)

Zero-shot sim-to-real transfer of tasks with complex dynamics is a highly challenging and unsolved problem. A number of solutions have been proposed in recent years, but we have found that many works do not present a thorough evaluation in the real world, or underplay the significant engineering effort and task-specific fine tuning that is required to achieve the published results. In this paper, we dive deeper into the sim-to-real transfer challenge, investigate why this is such a difficult problem, and present objective evaluations of a number of transfer methods across a range of real-world tasks. Surprisingly, we found that a method which simply injects random forces into the simulation performs just as well as more complex methods, such as those which randomise the simulator's dynamics parameters, or adapt a policy online using recurrent network architectures.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Aug 2020.

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Citing papers per year: 2021: 5; 2022: 2; 2023: 3; 2024: 1; 2025: 6; 2026: 3.

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  1. 2021Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detectioncited by 84
  2. 2025A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Modelscited by 36
  3. 2022DROPO: Sim-to-Real Transfer with Offline Domain Randomizationcited by 16
  4. 2022Learning and Deploying Robust Locomotion Policies with Minimal Dynamics Randomizationcited by 15
  5. 2023Domain Randomization via Entropy Maximizationcited by 15
  6. 2021Dual Online Stein Variational Inference for Control and Dynamicscited by 10
  7. 2021Coarse-to-Fine for Sim-to-Real: Sub-Millimetre Precision Across Wide Task Spacescited by 9
  8. 2021Learning Eye-in-Hand Camera Calibration from a Single Imagecited by 8
  9. 2023Robust Visual Sim-to-Real Transfer for Robotic Manipulationcited by 5
  10. 2025Flow-based Domain Randomization for Learning and Sequencing Robotic Skillscited by 4
  11. 2021Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptationcited by 1
  12. 2023Roll-Drop: accounting for observation noise with a single parametercited by 1
8 more
  1. 2024Intervention-Assisted Policy Gradient Methods for Online Stochastic Queuing Network Optimization: Technical Reportcited by 1
  2. 2025Shaping Laser Pulses with Reinforcement Learningcited by 1
  3. 2025Safe Continual Domain Adaptation after Sim2Real Transfer of Reinforcement Learning Policies in Roboticscited by 1
  4. 2026The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspectivecited by 1
  5. 2025Variable-Friction In-Hand Manipulation for Arbitrary Objects via Diffusion-Based Imitation Learningcited by 0
  6. 2025Direct transfer of optimized controllers to similar systems using dimensionless MPCcited by 0
  7. 2026Sim-to-Real of Humanoid Locomotion Policies via Joint Torque Space Perturbation Injectioncited by 0
  8. 2026How Should a Simulation-to-Reality Transfer Budget Be Spent?cited by 0