SoftMimicGen: A Data Generation System for Scalable Robot Learning in Deformable Object Manipulation

Description

Large-scale robot datasets have facilitated the learning of a wide range of robot manipulation skills, but these datasets remain difficult to collect and scale further, owing to the intractable amount of human time, effort, and cost required. Simulation and synthetic data generation have proven to be an effective alternative to fuel this need for data, especially with the advent of recent work showing that such synthetic datasets can dramatically reduce real-world data requirements and facilitat

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