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DiagGen: Agentic Generation of Deformable Assets with Sim-based Diagnostics for Robotic Simulation

arXiv · AI, language, vision and robotics · article · Sep 19, 2026 · UTC

While simulation-ready deformable assets are essential for in-silico robotic manipulation tasks, existing generation frameworks typically assess physical plausibility after generation, leaving an object's simulated response unused as feedback for repairing upstream errors. We present DiagGen, an agentic framework that turns a single in-the-wild image into a simulation-ready deformable asset through a generate--simulate--diagnose--refine loop. DiagGen constructs part-aware geometry and material parameters, then uses a VLM (vision-language model)-based agent to select semantically informative re

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