Sim2Real2Sim: Bridging the Gap Between Simulation and Real-World in Flexible Object Manipulation
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Abstract (arXiv)
This paper addresses a new strategy called Simulation-to-Real-to-Simulation (Sim2Real2Sim) to bridge the gap between simulation and real-world, and automate a flexible object manipulation task. This strategy consists of three steps: (1) using the rough environment with the estimated models to develop the methods to complete the manipulation task in the simulation; (2) applying the methods from simulation to real-world and comparing their performance; (3) updating the models and methods in simulation based on the differences between the real world and the simulation. The Plug Task from the 2015 DARPA Robotics Challenge Finals is chosen to evaluate our Sim2Real2Sim strategy. A new identification approach for building the model of the linear flexible objects is derived from real-world to simulation. The automation of the DRC plug task in both simulation and real-world proves the success of the Sim2Real2Sim strategy. Numerical experiments are implemented to validate the simulated model.
Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Feb 2020.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 0; 2024: 3; 2025: 5; 2026: 1.
14 papers.
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- 2022AKB-48: A Real-World Articulated Object Knowledge Basecited by 82
- 2024TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correctioncited by 59
- 2021Auto-Tuned Sim-to-Real Transfercited by 49
- 2025NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidancecited by 49
- 2022DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objectscited by 31
- 2025X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Realcited by 28
- 2021A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulationcited by 11
- 2022Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomizationcited by 8
- 2024SliceIt! -- A Dual Simulator Framework for Learning Robot Food Slicingcited by 6
- 2025A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewardscited by 5
- 2024Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planningcited by 4
- 2025Learning to Play Piano in the Real Worldcited by 2
- 2026Enhancing Sim2Real Transfer for Torque-Controlled Robots through Real2Sim Dynamics Estimation and Reinforcement Learning23 Aug 2026
- 2025RoboPearls: Editable Video Simulation for Robot Manipulation28 Jun 2025
- 2025NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance13 May 2025
- 2025X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real11 May 2025
- 2025Learning to Play Piano in the Real World19 Mar 2025
- 2025A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards12 Feb 2025
- 2024TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction16 May 2024
- 2024SliceIt! -- A Dual Simulator Framework for Learning Robot Food Slicing3 Apr 2024
- 2024Multi-Fidelity Reinforcement Learning for Time-Optimal Quadrotor Re-planning13 Mar 2024
- 2022Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization29 Jul 2022
- 2022DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects7 Apr 2022
- 2022AKB-48: A Real-World Articulated Object Knowledge Base17 Feb 2022
2 more
- 2021A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation9 Dec 2021
- 2021Auto-Tuned Sim-to-Real Transfer15 Apr 2021
- 2025X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Realcited by 28
- 2025X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real11 May 2025
- 2022AKB-48: A Real-World Articulated Object Knowledge Basecited by 82
- 2024TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correctioncited by 59
- 2021Auto-Tuned Sim-to-Real Transfercited by 49
- 2022DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objectscited by 31
- 2021A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulationcited by 11
- 2022Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomizationcited by 8
- 2024SliceIt! -- A Dual Simulator Framework for Learning Robot Food Slicingcited by 6
- 2025A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewardscited by 5
- 2025Learning to Play Piano in the Real Worldcited by 2
- 2025RoboPearls: Editable Video Simulation for Robot Manipulationcited by 0
- 2025RoboPearls: Editable Video Simulation for Robot Manipulation28 Jun 2025
- 2025Learning to Play Piano in the Real World19 Mar 2025
- 2025A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards12 Feb 2025
- 2024TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction16 May 2024
- 2024SliceIt! -- A Dual Simulator Framework for Learning Robot Food Slicing3 Apr 2024
- 2022Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization29 Jul 2022
- 2022DiffCloud: Real-to-Sim from Point Clouds with Differentiable Simulation and Rendering of Deformable Objects7 Apr 2022
- 2022AKB-48: A Real-World Articulated Object Knowledge Base17 Feb 2022
- 2021A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation9 Dec 2021
- 2021Auto-Tuned Sim-to-Real Transfer15 Apr 2021